Update README.md

Co-Authored-By: Joe Moura <joao@crewai.com>

.gitignore

@@ -21,4 +21,3 @@ crew_tasks_output.json
 .mypy_cache
 .ruff_cache
 .venv
-agentops.log

docs/concepts/flows.mdx

@@ -138,7 +138,7 @@ print("---- Final Output ----")
 print(final_output)
 ````
 
-```text Output
+``` text Output
 ---- Final Output ----
 Second method received: Output from first_method
 ````

docs/concepts/knowledge.mdx

@@ -4,6 +4,8 @@ description: What is knowledge in CrewAI and how to use it.
 icon: book
 ---
 
+# Using Knowledge in CrewAI
+
 ## What is Knowledge?
 
 Knowledge in CrewAI is a powerful system that allows AI agents to access and utilize external information sources during their tasks.
@@ -34,20 +36,7 @@ CrewAI supports various types of knowledge sources out of the box:
   </Card>
 </CardGroup>
 
-## Supported Knowledge Parameters
-
-| Parameter                    | Type                                | Required | Description                                                                                                                                           |
-| :--------------------------- | :---------------------------------- | :------- | :---------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `sources`                  | **List[BaseKnowledgeSource]**        | Yes      | List of knowledge sources that provide content to be stored and queried. Can include PDF, CSV, Excel, JSON, text files, or string content.           |
-| `collection_name`          | **str**                              | No       | Name of the collection where the knowledge will be stored. Used to identify different sets of knowledge. Defaults to "knowledge" if not provided.     |
-| `storage`                  | **Optional[KnowledgeStorage]**       | No       | Custom storage configuration for managing how the knowledge is stored and retrieved. If not provided, a default storage will be created.              |
-
-## Quickstart Example
-
-<Tip>
-For file-Based Knowledge Sources, make sure to place your files in a `knowledge` directory at the root of your project. 
-Also, use relative paths from the `knowledge` directory when creating the source.
-</Tip>
+## Quick Start
 
 Here's an example using string-based knowledge:
 
@@ -91,8 +80,7 @@ result = crew.kickoff(inputs={"question": "What city does John live in and how o
 ```
 
 
-Here's another example with the `CrewDoclingSource`. The CrewDoclingSource is actually quite versatile and can handle multiple file formats including TXT, PDF, DOCX, HTML, and more. 
-
+Here's another example with the `CrewDoclingSource`
 ```python Code
 from crewai import LLM, Agent, Crew, Process, Task
 from crewai.knowledge.source.crew_docling_source import CrewDoclingSource
@@ -140,192 +128,39 @@ result = crew.kickoff(
 )
 ```
 
-## More Examples
-
-Here are examples of how to use different types of knowledge sources:
-
-### Text File Knowledge Source
-```python
-from crewai.knowledge.source import CrewDoclingSource
-
-# Create a text file knowledge source
-text_source = CrewDoclingSource(
-    file_paths=["document.txt", "another.txt"]
-)
-
-# Create knowledge with text file source
-knowledge = Knowledge(
-    collection_name="text_knowledge",
-    sources=[text_source]
-)
-```
-
-### PDF Knowledge Source
-```python
-from crewai.knowledge.source import PDFKnowledgeSource
-
-# Create a PDF knowledge source
-pdf_source = PDFKnowledgeSource(
-    file_paths=["document.pdf", "another.pdf"]
-)
-
-# Create knowledge with PDF source
-knowledge = Knowledge(
-    collection_name="pdf_knowledge",
-    sources=[pdf_source]
-)
-```
-
-### CSV Knowledge Source
-```python
-from crewai.knowledge.source import CSVKnowledgeSource
-
-# Create a CSV knowledge source
-csv_source = CSVKnowledgeSource(
-    file_paths=["data.csv"]
-)
-
-# Create knowledge with CSV source
-knowledge = Knowledge(
-    collection_name="csv_knowledge",
-    sources=[csv_source]
-)
-```
-
-### Excel Knowledge Source
-```python
-from crewai.knowledge.source import ExcelKnowledgeSource
-
-# Create an Excel knowledge source
-excel_source = ExcelKnowledgeSource(
-    file_paths=["spreadsheet.xlsx"]
-)
-
-# Create knowledge with Excel source
-knowledge = Knowledge(
-    collection_name="excel_knowledge",
-    sources=[excel_source]
-)
-```
-
-### JSON Knowledge Source
-```python
-from crewai.knowledge.source import JSONKnowledgeSource
-
-# Create a JSON knowledge source
-json_source = JSONKnowledgeSource(
-    file_paths=["data.json"]
-)
-
-# Create knowledge with JSON source
-knowledge = Knowledge(
-    collection_name="json_knowledge",
-    sources=[json_source]
-)
-```
-
 ## Knowledge Configuration
 
 ### Chunking Configuration
 
-Knowledge sources automatically chunk content for better processing. 
-You can configure chunking behavior in your knowledge sources:
+Control how content is split for processing by setting the chunk size and overlap.
 
-```python
-from crewai.knowledge.source import StringKnowledgeSource
-
-source = StringKnowledgeSource(
-    content="Your content here",
-    chunk_size=4000,      # Maximum size of each chunk (default: 4000)
-    chunk_overlap=200     # Overlap between chunks (default: 200)
+```python Code
+knowledge_source = StringKnowledgeSource(
+    content="Long content...",
+    chunk_size=4000,     # Characters per chunk (default)
+    chunk_overlap=200    # Overlap between chunks (default)
 )
 ```
 
-The chunking configuration helps in:
-- Breaking down large documents into manageable pieces
-- Maintaining context through chunk overlap
-- Optimizing retrieval accuracy
+## Embedder Configuration
 
-### Embeddings Configuration
+You can also configure the embedder for the knowledge store. This is useful if you want to use a different embedder for the knowledge store than the one used for the agents.
 
-You can also configure the embedder for the knowledge store. 
-This is useful if you want to use a different embedder for the knowledge store than the one used for the agents.
-The `embedder` parameter supports various embedding model providers that include:
-- `openai`: OpenAI's embedding models
-- `google`: Google's text embedding models
-- `azure`: Azure OpenAI embeddings
-- `ollama`: Local embeddings with Ollama
-- `vertexai`: Google Cloud VertexAI embeddings
-- `cohere`: Cohere's embedding models
-- `bedrock`: AWS Bedrock embeddings
-- `huggingface`: Hugging Face models
-- `watson`: IBM Watson embeddings
-
-Here's an example of how to configure the embedder for the knowledge store using Google's `text-embedding-004` model:
-<CodeGroup>
-```python Example
-from crewai import Agent, Task, Crew, Process, LLM
-from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
-import os
-
-# Get the GEMINI API key
-GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
-
-# Create a knowledge source
-content = "Users name is John. He is 30 years old and lives in San Francisco."
+```python Code
+...
 string_source = StringKnowledgeSource(
-    content=content,
+    content="Users name is John. He is 30 years old and lives in San Francisco.",
 )
-
-# Create an LLM with a temperature of 0 to ensure deterministic outputs
-gemini_llm = LLM(
-    model="gemini/gemini-1.5-pro-002",
-    api_key=GEMINI_API_KEY,
-    temperature=0,
-)
-
-# Create an agent with the knowledge store
-agent = Agent(
-    role="About User",
-    goal="You know everything about the user.",
-    backstory="""You are a master at understanding people and their preferences.""",
-    verbose=True,
-    allow_delegation=False,
-    llm=gemini_llm,
-)
-
-task = Task(
-    description="Answer the following questions about the user: {question}",
-    expected_output="An answer to the question.",
-    agent=agent,
-)
-
 crew = Crew(
-    agents=[agent],
-    tasks=[task],
-    verbose=True,
-    process=Process.sequential,
+    ...
     knowledge_sources=[string_source],
     embedder={
-        "provider": "google",
-        "config": {
-            "model": "models/text-embedding-004",
-            "api_key": GEMINI_API_KEY,
-        }
-    }
+        "provider": "openai",
+        "config": {"model": "text-embedding-3-small"},
+    },
 )
-
-result = crew.kickoff(inputs={"question": "What city does John live in and how old is he?"})
 ```
-```text Output
-# Agent: About User
-## Task: Answer the following questions about the user: What city does John live in and how old is he?
 
-# Agent: About User
-## Final Answer: 
-John is 30 years old and lives in San Francisco.
-```
-</CodeGroup>
 ## Clearing Knowledge
 
 If you need to clear the knowledge stored in CrewAI, you can use the `crewai reset-memories` command with the `--knowledge` option.

docs/how-to/portkey-observability.mdx

@@ -1,202 +0,0 @@
----
-title: Portkey Observability and Guardrails
-description: How to use Portkey with CrewAI
-icon: key
----
-
-<img src="https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/main/Portkey-CrewAI.png" alt="Portkey CrewAI Header Image" width="70%" />
-
-
-[Portkey](https://portkey.ai/?utm_source=crewai&utm_medium=crewai&utm_campaign=crewai) is a 2-line upgrade to make your CrewAI agents reliable, cost-efficient, and fast.
-
-Portkey adds 4 core production capabilities to any CrewAI agent:
-1. Routing to **200+ LLMs**
-2. Making each LLM call more robust
-3. Full-stack tracing & cost, performance analytics
-4. Real-time guardrails to enforce behavior
-
-## Getting Started
-
-<Steps>
-    <Step title="Install CrewAI and Portkey">
-    ```bash
-    pip install -qU crewai portkey-ai
-    ```
-    </Step>
-    <Step title="Configure the LLM Client">
-    To build CrewAI Agents with Portkey, you'll need two keys:
-    - **Portkey API Key**: Sign up on the [Portkey app](https://app.portkey.ai/?utm_source=crewai&utm_medium=crewai&utm_campaign=crewai) and copy your API key
-    - **Virtual Key**: Virtual Keys securely manage your LLM API keys in one place. Store your LLM provider API keys securely in Portkey's vault
-
-    ```python
-    from crewai import LLM
-    from portkey_ai import createHeaders, PORTKEY_GATEWAY_URL
-
-    gpt_llm = LLM(
-        model="gpt-4",
-        base_url=PORTKEY_GATEWAY_URL,
-        api_key="dummy", # We are using Virtual key
-        extra_headers=createHeaders(
-            api_key="YOUR_PORTKEY_API_KEY",
-            virtual_key="YOUR_VIRTUAL_KEY", # Enter your Virtual key from Portkey
-        )
-    )
-    ```
-    </Step>
-    <Step title="Create and Run Your First Agent">
-    ```python
-    from crewai import Agent, Task, Crew
-
-    # Define your agents with roles and goals
-    coder = Agent(
-        role='Software developer',
-        goal='Write clear, concise code on demand',
-        backstory='An expert coder with a keen eye for software trends.',
-        llm=gpt_llm
-    )
-
-    # Create tasks for your agents
-    task1 = Task(
-        description="Define the HTML for making a simple website with heading- Hello World! Portkey is working!",
-        expected_output="A clear and concise HTML code",
-        agent=coder
-    )
-
-    # Instantiate your crew
-    crew = Crew(
-        agents=[coder],
-        tasks=[task1],
-    )
-
-    result = crew.kickoff()
-    print(result)
-    ```
-    </Step>
-</Steps>
-
-## Key Features
-
-| Feature | Description |
-|:--------|:------------|
-| 🌐 Multi-LLM Support | Access OpenAI, Anthropic, Gemini, Azure, and 250+ providers through a unified interface |
-| 🛡️ Production Reliability | Implement retries, timeouts, load balancing, and fallbacks |
-| 📊 Advanced Observability | Track 40+ metrics including costs, tokens, latency, and custom metadata |
-| 🔍 Comprehensive Logging | Debug with detailed execution traces and function call logs |
-| 🚧 Security Controls | Set budget limits and implement role-based access control |
-| 🔄 Performance Analytics | Capture and analyze feedback for continuous improvement |
-| 💾 Intelligent Caching | Reduce costs and latency with semantic or simple caching |
-
-
-## Production Features with Portkey Configs
-
-All features mentioned below are through Portkey's Config system. Portkey's Config system allows you to define routing strategies using simple JSON objects in your LLM API calls. You can create and manage Configs directly in your code or through the Portkey Dashboard. Each Config has a unique ID for easy reference.
-
-<Frame>
-    <img src="https://raw.githubusercontent.com/Portkey-AI/docs-core/refs/heads/main/images/libraries/libraries-3.avif"/>
-</Frame>
-
-
-### 1. Use 250+ LLMs
-Access various LLMs like Anthropic, Gemini, Mistral, Azure OpenAI, and more with minimal code changes. Switch between providers or use them together seamlessly. [Learn more about Universal API](https://portkey.ai/docs/product/ai-gateway/universal-api)
-
-
-Easily switch between different LLM providers:
-
-```python
-# Anthropic Configuration
-anthropic_llm = LLM(
-    model="claude-3-5-sonnet-latest",
-    base_url=PORTKEY_GATEWAY_URL,
-    api_key="dummy",
-    extra_headers=createHeaders(
-        api_key="YOUR_PORTKEY_API_KEY",
-        virtual_key="YOUR_ANTHROPIC_VIRTUAL_KEY", #You don't need provider when using Virtual keys
-        trace_id="anthropic_agent"
-    )
-)
-
-# Azure OpenAI Configuration
-azure_llm = LLM(
-    model="gpt-4",
-    base_url=PORTKEY_GATEWAY_URL,
-    api_key="dummy",
-    extra_headers=createHeaders(
-        api_key="YOUR_PORTKEY_API_KEY",
-        virtual_key="YOUR_AZURE_VIRTUAL_KEY", #You don't need provider when using Virtual keys
-        trace_id="azure_agent"
-    )
-)
-```
-
-
-### 2. Caching
-Improve response times and reduce costs with two powerful caching modes:
-- **Simple Cache**: Perfect for exact matches
-- **Semantic Cache**: Matches responses for requests that are semantically similar
-[Learn more about Caching](https://portkey.ai/docs/product/ai-gateway/cache-simple-and-semantic)
-
-```py
-config = {
-    "cache": {
-        "mode": "semantic",  # or "simple" for exact matching
-    }
-}
-```
-
-### 3. Production Reliability
-Portkey provides comprehensive reliability features:
-- **Automatic Retries**: Handle temporary failures gracefully
-- **Request Timeouts**: Prevent hanging operations
-- **Conditional Routing**: Route requests based on specific conditions
-- **Fallbacks**: Set up automatic provider failovers
-- **Load Balancing**: Distribute requests efficiently
-
-[Learn more about Reliability Features](https://portkey.ai/docs/product/ai-gateway/)
-
-
-
-### 4. Metrics
-
-Agent runs are complex. Portkey automatically logs **40+ comprehensive metrics** for your AI agents, including cost, tokens used, latency, etc. Whether you need a broad overview or granular insights into your agent runs, Portkey's customizable filters provide the metrics you need.
-
-
-- Cost per agent interaction
-- Response times and latency
-- Token usage and efficiency
-- Success/failure rates
-- Cache hit rates
-
-<img src="https://github.com/siddharthsambharia-portkey/Portkey-Product-Images/blob/main/Portkey-Dashboard.png?raw=true" width="70%" alt="Portkey Dashboard" />
-
-### 5. Detailed Logging
-Logs are essential for understanding agent behavior, diagnosing issues, and improving performance. They provide a detailed record of agent activities and tool use, which is crucial for debugging and optimizing processes.
-
-
-Access a dedicated section to view records of agent executions, including parameters, outcomes, function calls, and errors. Filter logs based on multiple parameters such as trace ID, model, tokens used, and metadata.
-
-<details>
-  <summary><b>Traces</b></summary>
-  <img src="https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/main/Portkey-Traces.png" alt="Portkey Traces" width="70%" />
-</details>
-
-<details>
-  <summary><b>Logs</b></summary>
-  <img src="https://raw.githubusercontent.com/siddharthsambharia-portkey/Portkey-Product-Images/main/Portkey-Logs.png" alt="Portkey Logs" width="70%" />
-</details>
-
-### 6. Enterprise Security Features
-- Set budget limit and rate limts per Virtual Key (disposable API keys)
-- Implement role-based access control
-- Track system changes with audit logs
-- Configure data retention policies
-
-
-
-For detailed information on creating and managing Configs, visit the [Portkey documentation](https://docs.portkey.ai/product/ai-gateway/configs).
-
-## Resources
-
-- [📘 Portkey Documentation](https://docs.portkey.ai)
-- [📊 Portkey Dashboard](https://app.portkey.ai/?utm_source=crewai&utm_medium=crewai&utm_campaign=crewai)
-- [🐦 Twitter](https://twitter.com/portkeyai)
-- [💬 Discord Community](https://discord.gg/DD7vgKK299)

docs/mint.json

@@ -100,8 +100,7 @@
         "how-to/conditional-tasks",
         "how-to/agentops-observability",
         "how-to/langtrace-observability",
-        "how-to/openlit-observability",
-        "how-to/portkey-observability"
+        "how-to/openlit-observability"
       ]
     },
     {

pyproject.toml

@@ -13,25 +13,25 @@ dependencies = [
     "openai>=1.13.3",
     "litellm>=1.44.22",
     "instructor>=1.3.3",
-
+    
     # Text Processing
     "pdfplumber>=0.11.4",
     "regex>=2024.9.11",
-
+    
     # Telemetry and Monitoring
     "opentelemetry-api>=1.22.0",
     "opentelemetry-sdk>=1.22.0",
     "opentelemetry-exporter-otlp-proto-http>=1.22.0",
-
+    
     # Data Handling
     "chromadb>=0.5.23",
     "openpyxl>=3.1.5",
     "pyvis>=0.3.2",
-
+    
     # Authentication and Security
     "auth0-python>=4.7.1",
     "python-dotenv>=1.0.0",
-
+    
     # Configuration and Utils
     "click>=8.1.7",
     "appdirs>=1.4.4",
@@ -40,7 +40,7 @@ dependencies = [
     "uv>=0.4.25",
     "tomli-w>=1.1.0",
     "tomli>=2.0.2",
-    "blinker>=1.9.0"
+    "blinker>=1.9.0",
 ]
 
 [project.urls]
@@ -49,7 +49,7 @@ Documentation = "https://docs.crewai.com"
 Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
-tools = ["crewai-tools>=0.25.5"]
+tools = ["crewai-tools>=0.17.0"]
 embeddings = [
     "tiktoken~=0.7.0"
 ]

src/crewai/agent.py

@@ -21,7 +21,6 @@ from crewai.tools.base_tool import Tool
 from crewai.utilities import Converter, Prompts
 from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_FILE
 from crewai.utilities.converter import generate_model_description
-from crewai.utilities.llm_utils import create_llm
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 from crewai.utilities.training_handler import CrewTrainingHandler
 
@@ -140,9 +139,89 @@ class Agent(BaseAgent):
     def post_init_setup(self):
         self._set_knowledge()
         self.agent_ops_agent_name = self.role
+        unaccepted_attributes = [
+            "AWS_ACCESS_KEY_ID",
+            "AWS_SECRET_ACCESS_KEY",
+            "AWS_REGION_NAME",
+        ]
 
-        self.llm = create_llm(self.llm)
-        self.function_calling_llm = create_llm(self.function_calling_llm)
+        # Handle different cases for self.llm
+        if isinstance(self.llm, str):
+            # If it's a string, create an LLM instance
+            self.llm = LLM(model=self.llm)
+        elif isinstance(self.llm, LLM):
+            # If it's already an LLM instance, keep it as is
+            pass
+        elif self.llm is None:
+            # Determine the model name from environment variables or use default
+            model_name = (
+                os.environ.get("OPENAI_MODEL_NAME")
+                or os.environ.get("MODEL")
+                or "gpt-4o-mini"
+            )
+            llm_params = {"model": model_name}
+
+            api_base = os.environ.get("OPENAI_API_BASE") or os.environ.get(
+                "OPENAI_BASE_URL"
+            )
+            if api_base:
+                llm_params["base_url"] = api_base
+
+            set_provider = model_name.split("/")[0] if "/" in model_name else "openai"
+
+            # Iterate over all environment variables to find matching API keys or use defaults
+            for provider, env_vars in ENV_VARS.items():
+                if provider == set_provider:
+                    for env_var in env_vars:
+                        # Check if the environment variable is set
+                        key_name = env_var.get("key_name")
+                        if key_name and key_name not in unaccepted_attributes:
+                            env_value = os.environ.get(key_name)
+                            if env_value:
+                                key_name = key_name.lower()
+                                for pattern in LITELLM_PARAMS:
+                                    if pattern in key_name:
+                                        key_name = pattern
+                                        break
+                                llm_params[key_name] = env_value
+                        # Check for default values if the environment variable is not set
+                        elif env_var.get("default", False):
+                            for key, value in env_var.items():
+                                if key not in ["prompt", "key_name", "default"]:
+                                    # Only add default if the key is already set in os.environ
+                                    if key in os.environ:
+                                        llm_params[key] = value
+
+            self.llm = LLM(**llm_params)
+        else:
+            # For any other type, attempt to extract relevant attributes
+            llm_params = {
+                "model": getattr(self.llm, "model_name", None)
+                or getattr(self.llm, "deployment_name", None)
+                or str(self.llm),
+                "temperature": getattr(self.llm, "temperature", None),
+                "max_tokens": getattr(self.llm, "max_tokens", None),
+                "logprobs": getattr(self.llm, "logprobs", None),
+                "timeout": getattr(self.llm, "timeout", None),
+                "max_retries": getattr(self.llm, "max_retries", None),
+                "api_key": getattr(self.llm, "api_key", None),
+                "base_url": getattr(self.llm, "base_url", None),
+                "organization": getattr(self.llm, "organization", None),
+            }
+            # Remove None values to avoid passing unnecessary parameters
+            llm_params = {k: v for k, v in llm_params.items() if v is not None}
+            self.llm = LLM(**llm_params)
+
+        # Similar handling for function_calling_llm
+        if self.function_calling_llm:
+            if isinstance(self.function_calling_llm, str):
+                self.function_calling_llm = LLM(model=self.function_calling_llm)
+            elif not isinstance(self.function_calling_llm, LLM):
+                self.function_calling_llm = LLM(
+                    model=getattr(self.function_calling_llm, "model_name", None)
+                    or getattr(self.function_calling_llm, "deployment_name", None)
+                    or str(self.function_calling_llm)
+                )
 
         if not self.agent_executor:
             self._setup_agent_executor()
@@ -193,8 +272,6 @@ class Agent(BaseAgent):
 
         task_prompt = task.prompt()
 
-        print("task_prompt:", task_prompt)
-
         # If the task requires output in JSON or Pydantic format,
         # append specific instructions to the task prompt to ensure
         # that the final answer does not include any code block markers

src/crewai/cli/cli.py

@@ -1,14 +1,11 @@
-import os
 from importlib.metadata import version as get_version
-from typing import Optional, Tuple
+from typing import Optional
 
 import click
 
 from crewai.cli.add_crew_to_flow import add_crew_to_flow
 from crewai.cli.create_crew import create_crew
 from crewai.cli.create_flow import create_flow
-from crewai.cli.crew_chat import run_chat
-from crewai.cli.fetch_chat_llm import fetch_chat_llm
 from crewai.memory.storage.kickoff_task_outputs_storage import (
     KickoffTaskOutputsSQLiteStorage,
 )
@@ -345,15 +342,5 @@ def flow_add_crew(crew_name):
     add_crew_to_flow(crew_name)
 
 
-@crewai.command()
-def chat():
-    """
-    Start a conversation with the Crew, collecting user-supplied inputs,
-    and using the Chat LLM to generate responses.
-    """
-    click.echo("Starting a conversation with the Crew")
-    run_chat()
-
-
 if __name__ == "__main__":
     crewai()

src/crewai/cli/constants.py

@@ -158,8 +158,6 @@ MODELS = {
     ],
 }
 
-DEFAULT_LLM_MODEL = "gpt-4o-mini"
-
 JSON_URL = "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"
 
 

src/crewai/cli/crew_chat.py

@@ -1,386 +0,0 @@
-import json
-import re
-import sys
-from pathlib import Path
-from typing import Any, Dict, List, Set, Tuple
-
-import click
-import tomli
-
-from crewai.agents.agent_builder.base_agent import BaseAgent
-from crewai.cli.fetch_chat_llm import fetch_chat_llm
-from crewai.cli.fetch_crew_inputs import fetch_crew_inputs
-from crewai.crew import Crew
-from crewai.task import Task
-from crewai.types.crew_chat import ChatInputField, ChatInputs
-from crewai.utilities.llm_utils import create_llm
-
-
-def run_chat():
-    """
-    Runs an interactive chat loop using the Crew's chat LLM with function calling.
-    Incorporates crew_name, crew_description, and input fields to build a tool schema.
-    Exits if crew_name or crew_description are missing.
-    """
-    crew, crew_name = load_crew_and_name()
-    click.secho("\nFetching the Chat LLM...", fg="cyan")
-    try:
-        chat_llm = create_llm(crew.chat_llm)
-    except Exception as e:
-        click.secho(f"Failed to retrieve Chat LLM: {e}", fg="red")
-        return
-    if not chat_llm:
-        click.secho("No valid Chat LLM returned. Exiting.", fg="red")
-        return
-
-    # Generate crew chat inputs automatically
-    crew_chat_inputs = generate_crew_chat_inputs(crew, crew_name, chat_llm)
-    print("crew_inputs:", crew_chat_inputs)
-
-    # Generate a tool schema from the crew inputs
-    crew_tool_schema = generate_crew_tool_schema(crew_chat_inputs)
-    print("crew_tool_schema:", crew_tool_schema)
-
-    # Build initial system message
-    required_fields_str = (
-        ", ".join(
-            f"{field.name} (desc: {field.description or 'n/a'})"
-            for field in crew_chat_inputs.inputs
-        )
-        or "(No required fields detected)"
-    )
-
-    system_message = (
-        "You are a helpful AI assistant for the CrewAI platform. "
-        "Your primary purpose is to assist users with the crew's specific tasks. "
-        "You can answer general questions, but should guide users back to the crew's purpose afterward. "
-        "For example, after answering a general question, remind the user of your main purpose, such as generating a research report, and prompt them to specify a topic or task related to the crew's purpose. "
-        "You have a function (tool) you can call by name if you have all required inputs. "
-        f"Those required inputs are: {required_fields_str}. "
-        "Once you have them, call the function. "
-        "Please keep your responses concise and friendly. "
-        "If a user asks a question outside the crew's scope, provide a brief answer and remind them of the crew's purpose. "
-        "After calling the tool, be prepared to take user feedback and make adjustments as needed. "
-        "If you are ever unsure about a user's request or need clarification, ask the user for more information."
-        f"\nCrew Name: {crew_chat_inputs.crew_name}"
-        f"\nCrew Description: {crew_chat_inputs.crew_description}"
-    )
-
-    messages = [
-        {"role": "system", "content": system_message},
-    ]
-
-    # Create a wrapper function that captures 'crew' and 'messages' from the enclosing scope
-    def run_crew_tool_with_messages(**kwargs):
-        return run_crew_tool(crew, messages, **kwargs)
-
-    # Prepare available_functions with the wrapper function
-    available_functions = {
-        crew_chat_inputs.crew_name: run_crew_tool_with_messages,
-    }
-
-    click.secho(
-        "\nEntering an interactive chat loop with function-calling.\n"
-        "Type 'exit' or Ctrl+C to quit.\n",
-        fg="cyan",
-    )
-
-    # Main chat loop
-    while True:
-        try:
-            user_input = click.prompt("You", type=str)
-            if user_input.strip().lower() in ["exit", "quit"]:
-                click.echo("Exiting chat. Goodbye!")
-                break
-
-            # Append user message
-            messages.append({"role": "user", "content": user_input})
-
-            # Invoke the LLM, passing tools and available_functions
-            final_response = chat_llm.call(
-                messages=messages,
-                tools=[crew_tool_schema],
-                available_functions=available_functions,
-            )
-
-            # Append assistant's reply
-            messages.append({"role": "assistant", "content": final_response})
-
-            # Display assistant's reply
-            click.secho(f"\nAssistant: {final_response}\n", fg="green")
-
-        except KeyboardInterrupt:
-            click.echo("\nExiting chat. Goodbye!")
-            break
-        except Exception as e:
-            click.secho(f"An error occurred: {e}", fg="red")
-            break
-
-
-def generate_crew_tool_schema(crew_inputs: ChatInputs) -> dict:
-    """
-    Dynamically build a Littellm 'function' schema for the given crew.
-
-    crew_name: The name of the crew (used for the function 'name').
-    crew_inputs: A ChatInputs object containing crew_description
-                 and a list of input fields (each with a name & description).
-    """
-    properties = {}
-    for field in crew_inputs.inputs:
-        properties[field.name] = {
-            "type": "string",
-            "description": field.description or "No description provided",
-        }
-
-    required_fields = [field.name for field in crew_inputs.inputs]
-
-    return {
-        "type": "function",
-        "function": {
-            "name": crew_inputs.crew_name,
-            "description": crew_inputs.crew_description or "No crew description",
-            "parameters": {
-                "type": "object",
-                "properties": properties,
-                "required": required_fields,
-            },
-        },
-    }
-
-
-def run_crew_tool(crew: Crew, messages: List[Dict[str, str]], **kwargs):
-    """
-    Runs the crew using crew.kickoff(inputs=kwargs) and returns the output.
-
-    Args:
-        crew (Crew): The crew instance to run.
-        messages (List[Dict[str, str]]): The chat messages up to this point.
-        **kwargs: The inputs collected from the user.
-
-    Returns:
-        str: The output from the crew's execution.
-
-    Raises:
-        SystemExit: Exits the chat if an error occurs during crew execution.
-    """
-    try:
-        # Serialize 'messages' to JSON string before adding to kwargs
-        kwargs['crew_chat_messages'] = json.dumps(messages)
-
-        # Run the crew with the provided inputs
-        crew_output = crew.kickoff(inputs=kwargs)
-
-        # Convert CrewOutput to a string to send back to the user
-        result = str(crew_output)
-
-        return result
-    except Exception as e:
-        # Exit the chat and show the error message
-        click.secho("An error occurred while running the crew:", fg="red")
-        click.secho(str(e), fg="red")
-        sys.exit(1)
-
-
-def load_crew_and_name() -> Tuple[Crew, str]:
-    """
-    Loads the crew by importing the crew class from the user's project.
-    
-    Returns:
-        Tuple[Crew, str]: A tuple containing the Crew instance and the name of the crew.
-    """
-    # Get the current working directory
-    cwd = Path.cwd()
-
-    # Path to the pyproject.toml file
-    pyproject_path = cwd / "pyproject.toml"
-    if not pyproject_path.exists():
-        raise FileNotFoundError("pyproject.toml not found in the current directory.")
-
-    # Load the pyproject.toml file using 'tomli'
-    with pyproject_path.open("rb") as f:
-        pyproject_data = tomli.load(f)
-
-    # Get the project name from the 'project' section
-    project_name = pyproject_data["project"]["name"]
-    folder_name = project_name
-
-    # Derive the crew class name from the project name
-    # E.g., if project_name is 'my_project', crew_class_name is 'MyProject'
-    crew_class_name = project_name.replace("_", " ").title().replace(" ", "")
-
-    # Add the 'src' directory to sys.path
-    src_path = cwd / "src"
-    if str(src_path) not in sys.path:
-        sys.path.insert(0, str(src_path))
-
-    # Import the crew module
-    crew_module_name = f"{folder_name}.crew"
-    try:
-        crew_module = __import__(crew_module_name, fromlist=[crew_class_name])
-    except ImportError as e:
-        raise ImportError(f"Failed to import crew module {crew_module_name}: {e}")
-
-    # Get the crew class from the module
-    try:
-        crew_class = getattr(crew_module, crew_class_name)
-    except AttributeError:
-        raise AttributeError(
-            f"Crew class {crew_class_name} not found in module {crew_module_name}"
-        )
-
-    # Instantiate the crew
-    crew_instance = crew_class().crew()
-    return crew_instance, crew_class_name
-
-
-def generate_crew_chat_inputs(crew: Crew, crew_name: str, chat_llm) -> ChatInputs:
-    """
-    Generates the ChatInputs required for the crew by analyzing the tasks and agents.
-
-    Args:
-        crew (Crew): The crew object containing tasks and agents.
-        crew_name (str): The name of the crew.
-        chat_llm: The chat language model to use for AI calls.
-
-    Returns:
-        ChatInputs: An object containing the crew's name, description, and input fields.
-    """
-    # Extract placeholders from tasks and agents
-    required_inputs = fetch_required_inputs(crew)
-
-    # Generate descriptions for each input using AI
-    input_fields = []
-    for input_name in required_inputs:
-        description = generate_input_description_with_ai(input_name, crew, chat_llm)
-        input_fields.append(ChatInputField(name=input_name, description=description))
-
-    # Generate crew description using AI
-    crew_description = generate_crew_description_with_ai(crew, chat_llm)
-
-    return ChatInputs(
-        crew_name=crew_name,
-        crew_description=crew_description,
-        inputs=input_fields
-    )
-
-
-def fetch_required_inputs(crew: Crew) -> Set[str]:
-    """
-    Extracts placeholders from the crew's tasks and agents.
-
-    Args:
-        crew (Crew): The crew object.
-
-    Returns:
-        Set[str]: A set of placeholder names.
-    """
-    placeholder_pattern = re.compile(r"\{(.+?)\}")
-    required_inputs: Set[str] = set()
-
-    # Scan tasks
-    for task in crew.tasks:
-        text = f"{task.description or ''} {task.expected_output or ''}"
-        required_inputs.update(placeholder_pattern.findall(text))
-
-    # Scan agents
-    for agent in crew.agents:
-        text = f"{agent.role or ''} {agent.goal or ''} {agent.backstory or ''}"
-        required_inputs.update(placeholder_pattern.findall(text))
-
-    return required_inputs
-
-
-def generate_input_description_with_ai(input_name: str, crew: Crew, chat_llm) -> str:
-    """
-    Generates an input description using AI based on the context of the crew.
-
-    Args:
-        input_name (str): The name of the input placeholder.
-        crew (Crew): The crew object.
-        chat_llm: The chat language model to use for AI calls.
-
-    Returns:
-        str: A concise description of the input.
-    """
-    # Gather context from tasks and agents where the input is used
-    context_texts = []
-    placeholder_pattern = re.compile(r"\{(.+?)\}")
-
-    for task in crew.tasks:
-        if f"{{{input_name}}}" in task.description or f"{{{input_name}}}" in task.expected_output:
-            # Replace placeholders with input names
-            task_description = placeholder_pattern.sub(lambda m: m.group(1), task.description)
-            expected_output = placeholder_pattern.sub(lambda m: m.group(1), task.expected_output)
-            context_texts.append(f"Task Description: {task_description}")
-            context_texts.append(f"Expected Output: {expected_output}")
-    for agent in crew.agents:
-        if f"{{{input_name}}}" in agent.role or f"{{{input_name}}}" in agent.goal or f"{{{input_name}}}" in agent.backstory:
-            # Replace placeholders with input names
-            agent_role = placeholder_pattern.sub(lambda m: m.group(1), agent.role)
-            agent_goal = placeholder_pattern.sub(lambda m: m.group(1), agent.goal)
-            agent_backstory = placeholder_pattern.sub(lambda m: m.group(1), agent.backstory)
-            context_texts.append(f"Agent Role: {agent_role}")
-            context_texts.append(f"Agent Goal: {agent_goal}")
-            context_texts.append(f"Agent Backstory: {agent_backstory}")
-
-    context = "\n".join(context_texts)
-    if not context:
-        # If no context is found for the input, raise an exception as per instruction
-        raise ValueError(f"No context found for input '{input_name}'.")
-
-    prompt = (
-        f"Based on the following context, write a concise description (15 words or less) of the input '{input_name}'.\n"
-        "Provide only the description, without any extra text or labels. Do not include placeholders like '{topic}' in the description.\n"
-        "Context:\n"
-        f"{context}"
-    )
-    response = chat_llm.call(messages=[{"role": "user", "content": prompt}])
-    description = response.strip()
-
-    return description
-
-
-def generate_crew_description_with_ai(crew: Crew, chat_llm) -> str:
-    """
-    Generates a brief description of the crew using AI.
-
-    Args:
-        crew (Crew): The crew object.
-        chat_llm: The chat language model to use for AI calls.
-
-    Returns:
-        str: A concise description of the crew's purpose (15 words or less).
-    """
-    # Gather context from tasks and agents
-    context_texts = []
-    placeholder_pattern = re.compile(r"\{(.+?)\}")
-
-    for task in crew.tasks:
-        # Replace placeholders with input names
-        task_description = placeholder_pattern.sub(lambda m: m.group(1), task.description)
-        expected_output = placeholder_pattern.sub(lambda m: m.group(1), task.expected_output)
-        context_texts.append(f"Task Description: {task_description}")
-        context_texts.append(f"Expected Output: {expected_output}")
-    for agent in crew.agents:
-        # Replace placeholders with input names
-        agent_role = placeholder_pattern.sub(lambda m: m.group(1), agent.role)
-        agent_goal = placeholder_pattern.sub(lambda m: m.group(1), agent.goal)
-        agent_backstory = placeholder_pattern.sub(lambda m: m.group(1), agent.backstory)
-        context_texts.append(f"Agent Role: {agent_role}")
-        context_texts.append(f"Agent Goal: {agent_goal}")
-        context_texts.append(f"Agent Backstory: {agent_backstory}")
-
-    context = "\n".join(context_texts)
-    if not context:
-        raise ValueError("No context found for generating crew description.")
-
-    prompt = (
-        "Based on the following context, write a concise, action-oriented description (15 words or less) of the crew's purpose.\n"
-        "Provide only the description, without any extra text or labels. Do not include placeholders like '{topic}' in the description.\n"
-        "Context:\n"
-        f"{context}"
-    )
-    response = chat_llm.call(messages=[{"role": "user", "content": prompt}])
-    crew_description = response.strip()
-
-    return crew_description

src/crewai/cli/fetch_chat_llm.py

@@ -1,81 +0,0 @@
-import json
-import subprocess
-
-import click
-from packaging import version
-
-from crewai.cli.utils import read_toml
-from crewai.cli.version import get_crewai_version
-from crewai.llm import LLM
-
-
-def fetch_chat_llm() -> LLM:
-    """
-    Fetch the chat LLM by running "uv run fetch_chat_llm" (or your chosen script name),
-    parsing its JSON stdout, and returning an LLM instance.
-
-    This expects the script "fetch_chat_llm" to print out JSON that represents the
-    LLM parameters (e.g., by calling something like: print(json.dumps(llm.to_dict()))).
-
-    Any error, whether from the subprocess or JSON parsing, will raise a RuntimeError.
-    """
-
-    # You may change this command to match whatever's in your pyproject.toml [project.scripts].
-    command = ["uv", "run", "fetch_chat_llm"]
-
-    crewai_version = get_crewai_version()
-    min_required_version = "0.87.0"  # Adjust as needed
-
-    pyproject_data = read_toml()
-
-    # If old poetry-based setup is detected and version is below min_required_version
-    if pyproject_data.get("tool", {}).get("poetry") and (
-        version.parse(crewai_version) < version.parse(min_required_version)
-    ):
-        click.secho(
-            f"You are running an older version of crewAI ({crewai_version}) that uses poetry pyproject.toml.\n"
-            f"Please run `crewai update` to transition your pyproject.toml to use uv.",
-            fg="red",
-        )
-
-    # Initialize a reference to your LLM
-    llm_instance = None
-
-    try:
-        result = subprocess.run(command, capture_output=True, text=True, check=True)
-        stdout_lines = result.stdout.strip().splitlines()
-
-        # Find the line that contains the JSON data
-        json_line = next(
-            (
-                line
-                for line in stdout_lines
-                if line.startswith("{") and line.endswith("}")
-            ),
-            None,
-        )
-
-        if not json_line:
-            raise RuntimeError(
-                "No valid JSON output received from `fetch_chat_llm` command."
-            )
-
-        try:
-            llm_data = json.loads(json_line)
-            llm_instance = LLM.from_dict(llm_data)
-        except json.JSONDecodeError as e:
-            raise RuntimeError(
-                f"Unable to parse JSON from `fetch_chat_llm` output: {e}\nOutput: {repr(json_line)}"
-            ) from e
-
-    except subprocess.CalledProcessError as e:
-        raise RuntimeError(f"An error occurred while fetching chat LLM: {e}") from e
-    except Exception as e:
-        raise RuntimeError(
-            f"An unexpected error occurred while fetching chat LLM: {e}"
-        ) from e
-
-    if not llm_instance:
-        raise RuntimeError("Failed to create a valid LLM from `fetch_chat_llm` output.")
-
-    return llm_instance

src/crewai/cli/fetch_crew_inputs.py

@@ -1,86 +0,0 @@
-import json
-import subprocess
-from typing import Optional
-
-import click
-from packaging import version
-
-from crewai.cli.utils import read_toml
-from crewai.cli.version import get_crewai_version
-from crewai.types.crew_chat import ChatInputs
-
-
-def fetch_crew_inputs() -> Optional[ChatInputs]:
-    """
-    Fetch the crew's ChatInputs (a structure containing crew_description and input fields)
-    by running "uv run fetch_chat_inputs", which prints JSON representing a ChatInputs object.
-
-    This function will parse that JSON and return a ChatInputs instance.
-    If the output is empty or invalid, an empty ChatInputs object is returned.
-    """
-
-    command = ["uv", "run", "fetch_chat_inputs"]
-    crewai_version = get_crewai_version()
-    min_required_version = "0.87.0"
-
-    pyproject_data = read_toml()
-    crew_name = pyproject_data.get("project", {}).get("name", None)
-
-    # If you're on an older poetry-based setup and version < min_required_version
-    if pyproject_data.get("tool", {}).get("poetry") and (
-        version.parse(crewai_version) < version.parse(min_required_version)
-    ):
-        click.secho(
-            f"You are running an older version of crewAI ({crewai_version}) that uses poetry pyproject.toml.\n"
-            f"Please run `crewai update` to update your pyproject.toml to use uv.",
-            fg="red",
-        )
-
-    try:
-        result = subprocess.run(command, capture_output=True, text=True, check=True)
-        stdout_lines = result.stdout.strip().splitlines()
-
-        # Find the line that contains the JSON data
-        json_line = next(
-            (
-                line
-                for line in stdout_lines
-                if line.startswith("{") and line.endswith("}")
-            ),
-            None,
-        )
-
-        if not json_line:
-            click.echo(
-                "No valid JSON output received from `fetch_chat_inputs` command.",
-                err=True,
-            )
-            return None
-
-        try:
-            raw_data = json.loads(json_line)
-            chat_inputs = ChatInputs(**raw_data)
-            if crew_name:
-                chat_inputs.crew_name = crew_name
-            return chat_inputs
-        except json.JSONDecodeError as e:
-            click.echo(
-                f"Unable to parse JSON from `fetch_chat_inputs` output: {e}\nOutput: {repr(json_line)}",
-                err=True,
-            )
-            return None
-
-    except subprocess.CalledProcessError as e:
-        click.echo(f"An error occurred while fetching chat inputs: {e}", err=True)
-        click.echo(e.output, err=True, nl=True)
-
-        if pyproject_data.get("tool", {}).get("poetry"):
-            click.secho(
-                "It's possible that you are using an old version of crewAI that uses poetry.\n"
-                "Please run `crewai update` to update your pyproject.toml to use uv.",
-                fg="yellow",
-            )
-    except Exception as e:
-        click.echo(f"An unexpected error occurred: {e}", err=True)
-
-    return None

src/crewai/cli/templates/crew/main.py

@@ -1,10 +1,8 @@
 #!/usr/bin/env python
 import sys
-import json
 import warnings
 
 from {{folder_name}}.crew import {{crew_name}}
-from crewai.utilities.llm_utils import create_llm
 
 warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
 
@@ -15,30 +13,12 @@ warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
 
 def run():
     """
-    Run the crew, allowing CLI overrides for required inputs.
-    Usage example:
-        uv run run_crew -- --topic="New Topic" --some_other_field="Value"
+    Run the crew.
     """
-    # Default inputs
     inputs = {
         'topic': 'AI LLMs'
-        # Add any other default fields here
     }
-
-    # 1) Gather overrides from sys.argv
-    #    sys.argv might look like: ['run_crew', '--topic=NewTopic']
-    #    But be aware that if you're calling "uv run run_crew", sys.argv might have
-    #    additional items. So we typically skip the first 1 or 2 items to get only overrides.
-    overrides = parse_cli_overrides(sys.argv[1:])
-
-    # 2) Merge the overrides into defaults
-    inputs.update(overrides)
-
-    # 3) Kick off the crew with final inputs
-    try:
-        {{crew_name}}().crew().kickoff(inputs=inputs)
-    except Exception as e:
-        raise Exception(f"An error occurred while running the crew: {e}")
+    {{crew_name}}().crew().kickoff(inputs=inputs)
 
 
 def train():
@@ -75,94 +55,4 @@ def test():
         {{crew_name}}().crew().test(n_iterations=int(sys.argv[1]), openai_model_name=sys.argv[2], inputs=inputs)
 
     except Exception as e:
-        raise Exception(f"An error occurred while testing the crew: {e}")
-
-def fetch_inputs():
-    """
-    Command that gathers required placeholders/inputs from the Crew, then
-    prints them as JSON to stdout so external scripts can parse them easily.
-    """
-    try:
-        crew = {{crew_name}}().crew()
-        crew_inputs = crew.fetch_inputs()
-        json_string = json.dumps(list(crew_inputs))
-        print(json_string)
-    except Exception as e:
-        raise Exception(f"An error occurred while fetching inputs: {e}")
-
-def fetch_chat_llm():
-    """
-    Command that fetches the 'chat_llm' property from the Crew,
-    instantiates it via create_llm(),
-    and prints the resulting LLM as JSON (using LLM.to_dict()) to stdout.
-    """
-    try:
-        crew = {{crew_name}}().crew()
-        raw_chat_llm = getattr(crew, "chat_llm", None)
-
-        if not raw_chat_llm:
-            # If the crew doesn't have chat_llm, fallback to create_llm(None)
-            final_llm = create_llm(None)
-        else:
-            # raw_chat_llm might be a dict, or an LLM, or something else
-            final_llm = create_llm(raw_chat_llm)
-
-        if final_llm:
-            # Print the final LLM as JSON, so fetch_chat_llm.py can parse it
-            from crewai.llm import LLM  # Import here to avoid circular references
-
-            # Make sure it's an instance of the LLM class:
-            if isinstance(final_llm, LLM):
-                print(json.dumps(final_llm.to_dict()))
-            else:
-                # If somehow it's not an LLM, try to interpret as a dict
-                # or revert to an empty fallback
-                if isinstance(final_llm, dict):
-                    print(json.dumps(final_llm))
-                else:
-                    print(json.dumps({}))
-        else:
-            print(json.dumps({}))
-    except Exception as e:
-        raise Exception(f"An error occurred while fetching chat LLM: {e}")
-
-# TODO: Talk to Joao about making using LLM calls to analyze the crew
-# and generate all of this information automatically
-def fetch_chat_inputs():
-    """
-    Command that fetches the 'chat_inputs' property from the Crew,
-    and prints it as JSON to stdout.
-    """
-    try:
-        crew = {{crew_name}}().crew()
-        raw_chat_inputs = getattr(crew, "chat_inputs", None)
-
-        if raw_chat_inputs:
-            # Convert to dictionary to print JSON
-            print(json.dumps(raw_chat_inputs.model_dump()))
-        else:
-            # If crew.chat_inputs is None or empty, print an empty JSON
-            print(json.dumps({}))
-    except Exception as e:
-        raise Exception(f"An error occurred while fetching chat inputs: {e}")
-    
-    
-def parse_cli_overrides(args_list) -> dict:
-    """
-    Parse arguments in the form of --key=value from a list of CLI arguments.
-    Return them as a dict. For example:
-    ['--topic=AI LLMs', '--username=John'] => {'topic': 'AI LLMs', 'username': 'John'}
-    """
-    overrides = {}
-    for arg in args_list:
-        if arg.startswith("--"):
-            # remove the leading --
-            trimmed = arg[2:]
-            if "=" in trimmed:
-                key, val = trimmed.split("=", 1)
-                overrides[key] = val
-            else:
-                # If someone passed something like --topic (no =),
-                # either handle differently or ignore
-                pass
-    return overrides
+        raise Exception(f"An error occurred while replaying the crew: {e}")

src/crewai/crew.py

@@ -1,11 +1,10 @@
 import asyncio
 import json
-import re
 import uuid
 import warnings
 from concurrent.futures import Future
 from hashlib import md5
-from typing import Any, Callable, Dict, List, Optional, Set, Tuple, Union
+from typing import Any, Callable, Dict, List, Optional, Tuple, Union
 
 from pydantic import (
     UUID4,
@@ -37,7 +36,6 @@ from crewai.tasks.task_output import TaskOutput
 from crewai.telemetry import Telemetry
 from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.tools.base_tool import Tool
-from crewai.types.crew_chat import ChatInputs
 from crewai.types.usage_metrics import UsageMetrics
 from crewai.utilities import I18N, FileHandler, Logger, RPMController
 from crewai.utilities.constants import TRAINING_DATA_FILE
@@ -205,14 +203,6 @@ class Crew(BaseModel):
         default=None,
         description="Knowledge sources for the crew. Add knowledge sources to the knowledge object.",
     )
-    chat_llm: Optional[Any] = Field(
-        default=None,
-        description="LLM used to handle chatting with the crew.",
-    )
-    chat_inputs: Optional[ChatInputs] = Field(
-        default=None,
-        description="Holds descriptions of the crew as well as named inputs for chat usage.",
-    )
     _knowledge: Optional[Knowledge] = PrivateAttr(
         default=None,
     )
@@ -736,7 +726,11 @@ class Crew(BaseModel):
 
             # Determine which tools to use - task tools take precedence over agent tools
             tools_for_task = task.tools or agent_to_use.tools or []
-            tools_for_task = self._prepare_tools(agent_to_use, task, tools_for_task)
+            tools_for_task = self._prepare_tools(
+                agent_to_use,
+                task,
+                tools_for_task
+            )
 
             self._log_task_start(task, agent_to_use.role)
 
@@ -803,18 +797,14 @@ class Crew(BaseModel):
             return skipped_task_output
         return None
 
-    def _prepare_tools(
-        self, agent: BaseAgent, task: Task, tools: List[Tool]
-    ) -> List[Tool]:
+    def _prepare_tools(self, agent: BaseAgent, task: Task, tools: List[Tool]) -> List[Tool]:
         # Add delegation tools if agent allows delegation
         if agent.allow_delegation:
             if self.process == Process.hierarchical:
                 if self.manager_agent:
                     tools = self._update_manager_tools(task, tools)
                 else:
-                    raise ValueError(
-                        "Manager agent is required for hierarchical process."
-                    )
+                    raise ValueError("Manager agent is required for hierarchical process.")
 
             elif agent and agent.allow_delegation:
                 tools = self._add_delegation_tools(task, tools)
@@ -833,9 +823,7 @@ class Crew(BaseModel):
             return self.manager_agent
         return task.agent
 
-    def _merge_tools(
-        self, existing_tools: List[Tool], new_tools: List[Tool]
-    ) -> List[Tool]:
+    def _merge_tools(self, existing_tools: List[Tool], new_tools: List[Tool]) -> List[Tool]:
         """Merge new tools into existing tools list, avoiding duplicates by tool name."""
         if not new_tools:
             return existing_tools
@@ -851,9 +839,7 @@ class Crew(BaseModel):
 
         return tools
 
-    def _inject_delegation_tools(
-        self, tools: List[Tool], task_agent: BaseAgent, agents: List[BaseAgent]
-    ):
+    def _inject_delegation_tools(self, tools: List[Tool], task_agent: BaseAgent, agents: List[BaseAgent]):
         delegation_tools = task_agent.get_delegation_tools(agents)
         return self._merge_tools(tools, delegation_tools)
 
@@ -870,9 +856,7 @@ class Crew(BaseModel):
         if len(self.agents) > 1 and len(agents_for_delegation) > 0 and task.agent:
             if not tools:
                 tools = []
-            tools = self._inject_delegation_tools(
-                tools, task.agent, agents_for_delegation
-            )
+            tools = self._inject_delegation_tools(tools, task.agent, agents_for_delegation)
         return tools
 
     def _log_task_start(self, task: Task, role: str = "None"):
@@ -886,9 +870,7 @@ class Crew(BaseModel):
             if task.agent:
                 tools = self._inject_delegation_tools(tools, task.agent, [task.agent])
             else:
-                tools = self._inject_delegation_tools(
-                    tools, self.manager_agent, self.agents
-                )
+                tools = self._inject_delegation_tools(tools, self.manager_agent, self.agents)
         return tools
 
     def _get_context(self, task: Task, task_outputs: List[TaskOutput]):
@@ -1001,31 +983,6 @@ class Crew(BaseModel):
             return self._knowledge.query(query)
         return None
 
-    def fetch_inputs(self) -> Set[str]:
-        """
-        Gathers placeholders (e.g., {something}) referenced in tasks or agents.
-        Scans each task's 'description' + 'expected_output', and each agent's
-        'role', 'goal', and 'backstory'.
-
-        Returns a set of all discovered placeholder names.
-        """
-        placeholder_pattern = re.compile(r"\{(.+?)\}")
-        required_inputs: Set[str] = set()
-
-        # Scan tasks for inputs
-        for task in self.tasks:
-            # description and expected_output might contain e.g. {topic}, {user_name}, etc.
-            text = f"{task.description or ''} {task.expected_output or ''}"
-            required_inputs.update(placeholder_pattern.findall(text))
-
-        # Scan agents for inputs
-        for agent in self.agents:
-            # role, goal, backstory might have placeholders like {role_detail}, etc.
-            text = f"{agent.role or ''} {agent.goal or ''} {agent.backstory or ''}"
-            required_inputs.update(placeholder_pattern.findall(text))
-
-        return required_inputs
-
     def copy(self):
         """Create a deep copy of the Crew."""
 
@@ -1081,7 +1038,7 @@ class Crew(BaseModel):
     def _interpolate_inputs(self, inputs: Dict[str, Any]) -> None:
         """Interpolates the inputs in the tasks and agents."""
         [
-            task.interpolate_inputs_and_add_conversation_history(
+            task.interpolate_inputs(
                 # type: ignore # "interpolate_inputs" of "Task" does not return a value (it only ever returns None)
                 inputs
             )

src/crewai/flow/flow.py

@@ -30,47 +30,7 @@ from crewai.telemetry import Telemetry
 T = TypeVar("T", bound=Union[BaseModel, Dict[str, Any]])
 
 
-def start(condition: Optional[Union[str, dict, Callable]] = None) -> Callable:
-    """
-    Marks a method as a flow's starting point.
-
-    This decorator designates a method as an entry point for the flow execution.
-    It can optionally specify conditions that trigger the start based on other
-    method executions.
-
-    Parameters
-    ----------
-    condition : Optional[Union[str, dict, Callable]], optional
-        Defines when the start method should execute. Can be:
-        - str: Name of a method that triggers this start
-        - dict: Contains "type" ("AND"/"OR") and "methods" (list of triggers)
-        - Callable: A method reference that triggers this start
-        Default is None, meaning unconditional start.
-
-    Returns
-    -------
-    Callable
-        A decorator function that marks the method as a flow start point.
-
-    Raises
-    ------
-    ValueError
-        If the condition format is invalid.
-
-    Examples
-    --------
-    >>> @start()  # Unconditional start
-    >>> def begin_flow(self):
-    ...     pass
-
-    >>> @start("method_name")  # Start after specific method
-    >>> def conditional_start(self):
-    ...     pass
-
-    >>> @start(and_("method1", "method2"))  # Start after multiple methods
-    >>> def complex_start(self):
-    ...     pass
-    """
+def start(condition=None):
     def decorator(func):
         func.__is_start_method__ = True
         if condition is not None:
@@ -95,42 +55,8 @@ def start(condition: Optional[Union[str, dict, Callable]] = None) -> Callable:
 
     return decorator
 
-def listen(condition: Union[str, dict, Callable]) -> Callable:
-    """
-    Creates a listener that executes when specified conditions are met.
 
-    This decorator sets up a method to execute in response to other method
-    executions in the flow. It supports both simple and complex triggering
-    conditions.
-
-    Parameters
-    ----------
-    condition : Union[str, dict, Callable]
-        Specifies when the listener should execute. Can be:
-        - str: Name of a method that triggers this listener
-        - dict: Contains "type" ("AND"/"OR") and "methods" (list of triggers)
-        - Callable: A method reference that triggers this listener
-
-    Returns
-    -------
-    Callable
-        A decorator function that sets up the method as a listener.
-
-    Raises
-    ------
-    ValueError
-        If the condition format is invalid.
-
-    Examples
-    --------
-    >>> @listen("process_data")  # Listen to single method
-    >>> def handle_processed_data(self):
-    ...     pass
-
-    >>> @listen(or_("success", "failure"))  # Listen to multiple methods
-    >>> def handle_completion(self):
-    ...     pass
-    """
+def listen(condition):
     def decorator(func):
         if isinstance(condition, str):
             func.__trigger_methods__ = [condition]
@@ -154,49 +80,10 @@ def listen(condition: Union[str, dict, Callable]) -> Callable:
     return decorator
 
 
-def router(condition: Union[str, dict, Callable]) -> Callable:
-    """
-    Creates a routing method that directs flow execution based on conditions.
-
-    This decorator marks a method as a router, which can dynamically determine
-    the next steps in the flow based on its return value. Routers are triggered
-    by specified conditions and can return constants that determine which path
-    the flow should take.
-
-    Parameters
-    ----------
-    condition : Union[str, dict, Callable]
-        Specifies when the router should execute. Can be:
-        - str: Name of a method that triggers this router
-        - dict: Contains "type" ("AND"/"OR") and "methods" (list of triggers)
-        - Callable: A method reference that triggers this router
-
-    Returns
-    -------
-    Callable
-        A decorator function that sets up the method as a router.
-
-    Raises
-    ------
-    ValueError
-        If the condition format is invalid.
-
-    Examples
-    --------
-    >>> @router("check_status")
-    >>> def route_based_on_status(self):
-    ...     if self.state.status == "success":
-    ...         return SUCCESS
-    ...     return FAILURE
-
-    >>> @router(and_("validate", "process"))
-    >>> def complex_routing(self):
-    ...     if all([self.state.valid, self.state.processed]):
-    ...         return CONTINUE
-    ...     return STOP
-    """
+def router(condition):
     def decorator(func):
         func.__is_router__ = True
+        # Handle conditions like listen/start
         if isinstance(condition, str):
             func.__trigger_methods__ = [condition]
             func.__condition_type__ = "OR"
@@ -218,39 +105,8 @@ def router(condition: Union[str, dict, Callable]) -> Callable:
 
     return decorator
 
-def or_(*conditions: Union[str, dict, Callable]) -> dict:
-    """
-    Combines multiple conditions with OR logic for flow control.
 
-    Creates a condition that is satisfied when any of the specified conditions
-    are met. This is used with @start, @listen, or @router decorators to create
-    complex triggering conditions.
-
-    Parameters
-    ----------
-    *conditions : Union[str, dict, Callable]
-        Variable number of conditions that can be:
-        - str: Method names
-        - dict: Existing condition dictionaries
-        - Callable: Method references
-
-    Returns
-    -------
-    dict
-        A condition dictionary with format:
-        {"type": "OR", "methods": list_of_method_names}
-
-    Raises
-    ------
-    ValueError
-        If any condition is invalid.
-
-    Examples
-    --------
-    >>> @listen(or_("success", "timeout"))
-    >>> def handle_completion(self):
-    ...     pass
-    """
+def or_(*conditions):
     methods = []
     for condition in conditions:
         if isinstance(condition, dict) and "methods" in condition:
@@ -264,39 +120,7 @@ def or_(*conditions: Union[str, dict, Callable]) -> dict:
     return {"type": "OR", "methods": methods}
 
 
-def and_(*conditions: Union[str, dict, Callable]) -> dict:
-    """
-    Combines multiple conditions with AND logic for flow control.
-
-    Creates a condition that is satisfied only when all specified conditions
-    are met. This is used with @start, @listen, or @router decorators to create
-    complex triggering conditions.
-
-    Parameters
-    ----------
-    *conditions : Union[str, dict, Callable]
-        Variable number of conditions that can be:
-        - str: Method names
-        - dict: Existing condition dictionaries
-        - Callable: Method references
-
-    Returns
-    -------
-    dict
-        A condition dictionary with format:
-        {"type": "AND", "methods": list_of_method_names}
-
-    Raises
-    ------
-    ValueError
-        If any condition is invalid.
-
-    Examples
-    --------
-    >>> @listen(and_("validated", "processed"))
-    >>> def handle_complete_data(self):
-    ...     pass
-    """
+def and_(*conditions):
     methods = []
     for condition in conditions:
         if isinstance(condition, dict) and "methods" in condition:
@@ -462,23 +286,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
         return final_output
 
     async def _execute_start_method(self, start_method_name: str) -> None:
-        """
-        Executes a flow's start method and its triggered listeners.
-
-        This internal method handles the execution of methods marked with @start
-        decorator and manages the subsequent chain of listener executions.
-
-        Parameters
-        ----------
-        start_method_name : str
-            The name of the start method to execute.
-
-        Notes
-        -----
-        - Executes the start method and captures its result
-        - Triggers execution of any listeners waiting on this start method
-        - Part of the flow's initialization sequence
-        """
         result = await self._execute_method(
             start_method_name, self._methods[start_method_name]
         )
@@ -499,28 +306,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
         return result
 
     async def _execute_listeners(self, trigger_method: str, result: Any) -> None:
-        """
-        Executes all listeners and routers triggered by a method completion.
-
-        This internal method manages the execution flow by:
-        1. First executing all triggered routers sequentially
-        2. Then executing all triggered listeners in parallel
-
-        Parameters
-        ----------
-        trigger_method : str
-            The name of the method that triggered these listeners.
-        result : Any
-            The result from the triggering method, passed to listeners
-            that accept parameters.
-
-        Notes
-        -----
-        - Routers are executed sequentially to maintain flow control
-        - Each router's result becomes the new trigger_method
-        - Normal listeners are executed in parallel for efficiency
-        - Listeners can receive the trigger method's result as a parameter
-        """
         # First, handle routers repeatedly until no router triggers anymore
         while True:
             routers_triggered = self._find_triggered_methods(
@@ -550,33 +335,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
     def _find_triggered_methods(
         self, trigger_method: str, router_only: bool
     ) -> List[str]:
-        """
-        Finds all methods that should be triggered based on conditions.
-
-        This internal method evaluates both OR and AND conditions to determine
-        which methods should be executed next in the flow.
-
-        Parameters
-        ----------
-        trigger_method : str
-            The name of the method that just completed execution.
-        router_only : bool
-            If True, only consider router methods.
-            If False, only consider non-router methods.
-
-        Returns
-        -------
-        List[str]
-            Names of methods that should be triggered.
-
-        Notes
-        -----
-        - Handles both OR and AND conditions:
-          * OR: Triggers if any condition is met
-          * AND: Triggers only when all conditions are met
-        - Maintains state for AND conditions using _pending_and_listeners
-        - Separates router and normal listener evaluation
-        """
         triggered = []
         for listener_name, (condition_type, methods) in self._listeners.items():
             is_router = listener_name in self._routers
@@ -605,33 +363,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
         return triggered
 
     async def _execute_single_listener(self, listener_name: str, result: Any) -> None:
-        """
-        Executes a single listener method with proper event handling.
-
-        This internal method manages the execution of an individual listener,
-        including parameter inspection, event emission, and error handling.
-
-        Parameters
-        ----------
-        listener_name : str
-            The name of the listener method to execute.
-        result : Any
-            The result from the triggering method, which may be passed
-            to the listener if it accepts parameters.
-
-        Notes
-        -----
-        - Inspects method signature to determine if it accepts the trigger result
-        - Emits events for method execution start and finish
-        - Handles errors gracefully with detailed logging
-        - Recursively triggers listeners of this listener
-        - Supports both parameterized and parameter-less listeners
-
-        Error Handling
-        -------------
-        Catches and logs any exceptions during execution, preventing
-        individual listener failures from breaking the entire flow.
-        """
         try:
             method = self._methods[listener_name]
 

src/crewai/flow/flow_visualizer.py

@@ -1,14 +1,12 @@
 # flow_visualizer.py
 
 import os
-from pathlib import Path
 
 from pyvis.network import Network
 
 from crewai.flow.config import COLORS, NODE_STYLES
 from crewai.flow.html_template_handler import HTMLTemplateHandler
 from crewai.flow.legend_generator import generate_legend_items_html, get_legend_items
-from crewai.flow.path_utils import safe_path_join, validate_path_exists
 from crewai.flow.utils import calculate_node_levels
 from crewai.flow.visualization_utils import (
     add_edges,
@@ -18,209 +16,89 @@ from crewai.flow.visualization_utils import (
 
 
 class FlowPlot:
-    """Handles the creation and rendering of flow visualization diagrams."""
-
     def __init__(self, flow):
-        """
-        Initialize FlowPlot with a flow object.
-
-        Parameters
-        ----------
-        flow : Flow
-            A Flow instance to visualize.
-
-        Raises
-        ------
-        ValueError
-            If flow object is invalid or missing required attributes.
-        """
-        if not hasattr(flow, '_methods'):
-            raise ValueError("Invalid flow object: missing '_methods' attribute")
-        if not hasattr(flow, '_listeners'):
-            raise ValueError("Invalid flow object: missing '_listeners' attribute")
-        if not hasattr(flow, '_start_methods'):
-            raise ValueError("Invalid flow object: missing '_start_methods' attribute")
-            
         self.flow = flow
         self.colors = COLORS
         self.node_styles = NODE_STYLES
 
     def plot(self, filename):
-        """
-        Generate and save an HTML visualization of the flow.
+        net = Network(
+            directed=True,
+            height="750px",
+            width="100%",
+            bgcolor=self.colors["bg"],
+            layout=None,
+        )
 
-        Parameters
-        ----------
-        filename : str
-            Name of the output file (without extension).
-
-        Raises
-        ------
-        ValueError
-            If filename is invalid or network generation fails.
-        IOError
-            If file operations fail or visualization cannot be generated.
-        RuntimeError
-            If network visualization generation fails.
-        """
-        if not filename or not isinstance(filename, str):
-            raise ValueError("Filename must be a non-empty string")
-            
-        try:
-            # Initialize network
-            net = Network(
-                directed=True,
-                height="750px",
-                width="100%",
-                bgcolor=self.colors["bg"],
-                layout=None,
-            )
-
-            # Set options to disable physics
-            net.set_options(
-                """
-                var options = {
-                    "nodes": {
-                        "font": {
-                            "multi": "html"
-                        }
-                    },
-                    "physics": {
-                        "enabled": false
-                    }
-                }
+        # Set options to disable physics
+        net.set_options(
             """
-            )
+            var options = {
+                "nodes": {
+                    "font": {
+                        "multi": "html"
+                    }
+                },
+                "physics": {
+                    "enabled": false
+                }
+            }
+        """
+        )
 
-            # Calculate levels for nodes
-            try:
-                node_levels = calculate_node_levels(self.flow)
-            except Exception as e:
-                raise ValueError(f"Failed to calculate node levels: {str(e)}")
+        # Calculate levels for nodes
+        node_levels = calculate_node_levels(self.flow)
 
-            # Compute positions
-            try:
-                node_positions = compute_positions(self.flow, node_levels)
-            except Exception as e:
-                raise ValueError(f"Failed to compute node positions: {str(e)}")
+        # Compute positions
+        node_positions = compute_positions(self.flow, node_levels)
 
-            # Add nodes to the network
-            try:
-                add_nodes_to_network(net, self.flow, node_positions, self.node_styles)
-            except Exception as e:
-                raise RuntimeError(f"Failed to add nodes to network: {str(e)}")
+        # Add nodes to the network
+        add_nodes_to_network(net, self.flow, node_positions, self.node_styles)
 
-            # Add edges to the network
-            try:
-                add_edges(net, self.flow, node_positions, self.colors)
-            except Exception as e:
-                raise RuntimeError(f"Failed to add edges to network: {str(e)}")
+        # Add edges to the network
+        add_edges(net, self.flow, node_positions, self.colors)
 
-            # Generate HTML
-            try:
-                network_html = net.generate_html()
-                final_html_content = self._generate_final_html(network_html)
-            except Exception as e:
-                raise RuntimeError(f"Failed to generate network visualization: {str(e)}")
+        network_html = net.generate_html()
+        final_html_content = self._generate_final_html(network_html)
 
-            # Save the final HTML content to the file
-            try:
-                with open(f"{filename}.html", "w", encoding="utf-8") as f:
-                    f.write(final_html_content)
-                print(f"Plot saved as {filename}.html")
-            except IOError as e:
-                raise IOError(f"Failed to save flow visualization to {filename}.html: {str(e)}")
+        # Save the final HTML content to the file
+        with open(f"{filename}.html", "w", encoding="utf-8") as f:
+            f.write(final_html_content)
+        print(f"Plot saved as {filename}.html")
 
-        except (ValueError, RuntimeError, IOError) as e:
-            raise e
-        except Exception as e:
-            raise RuntimeError(f"Unexpected error during flow visualization: {str(e)}")
-        finally:
-            self._cleanup_pyvis_lib()
+        self._cleanup_pyvis_lib()
 
     def _generate_final_html(self, network_html):
-        """
-        Generate the final HTML content with network visualization and legend.
+        # Extract just the body content from the generated HTML
+        current_dir = os.path.dirname(__file__)
+        template_path = os.path.join(
+            current_dir, "assets", "crewai_flow_visual_template.html"
+        )
+        logo_path = os.path.join(current_dir, "assets", "crewai_logo.svg")
 
-        Parameters
-        ----------
-        network_html : str
-            HTML content generated by pyvis Network.
+        html_handler = HTMLTemplateHandler(template_path, logo_path)
+        network_body = html_handler.extract_body_content(network_html)
 
-        Returns
-        -------
-        str
-            Complete HTML content with styling and legend.
-
-        Raises
-        ------
-        IOError
-            If template or logo files cannot be accessed.
-        ValueError
-            If network_html is invalid.
-        """
-        if not network_html:
-            raise ValueError("Invalid network HTML content")
-
-        try:
-            # Extract just the body content from the generated HTML
-            current_dir = os.path.dirname(__file__)
-            template_path = safe_path_join("assets", "crewai_flow_visual_template.html", root=current_dir)
-            logo_path = safe_path_join("assets", "crewai_logo.svg", root=current_dir)
-
-            if not os.path.exists(template_path):
-                raise IOError(f"Template file not found: {template_path}")
-            if not os.path.exists(logo_path):
-                raise IOError(f"Logo file not found: {logo_path}")
-
-            html_handler = HTMLTemplateHandler(template_path, logo_path)
-            network_body = html_handler.extract_body_content(network_html)
-
-            # Generate the legend items HTML
-            legend_items = get_legend_items(self.colors)
-            legend_items_html = generate_legend_items_html(legend_items)
-            final_html_content = html_handler.generate_final_html(
-                network_body, legend_items_html
-            )
-            return final_html_content
-        except Exception as e:
-            raise IOError(f"Failed to generate visualization HTML: {str(e)}")
+        # Generate the legend items HTML
+        legend_items = get_legend_items(self.colors)
+        legend_items_html = generate_legend_items_html(legend_items)
+        final_html_content = html_handler.generate_final_html(
+            network_body, legend_items_html
+        )
+        return final_html_content
 
     def _cleanup_pyvis_lib(self):
-        """
-        Clean up the generated lib folder from pyvis.
-
-        This method safely removes the temporary lib directory created by pyvis
-        during network visualization generation.
-        """
+        # Clean up the generated lib folder
+        lib_folder = os.path.join(os.getcwd(), "lib")
         try:
-            lib_folder = safe_path_join("lib", root=os.getcwd())
             if os.path.exists(lib_folder) and os.path.isdir(lib_folder):
                 import shutil
+
                 shutil.rmtree(lib_folder)
-        except ValueError as e:
-            print(f"Error validating lib folder path: {e}")
         except Exception as e:
-            print(f"Error cleaning up lib folder: {e}")
+            print(f"Error cleaning up {lib_folder}: {e}")
 
 
 def plot_flow(flow, filename="flow_plot"):
-    """
-    Convenience function to create and save a flow visualization.
-
-    Parameters
-    ----------
-    flow : Flow
-        Flow instance to visualize.
-    filename : str, optional
-        Output filename without extension, by default "flow_plot".
-
-    Raises
-    ------
-    ValueError
-        If flow object or filename is invalid.
-    IOError
-        If file operations fail.
-    """
     visualizer = FlowPlot(flow)
     visualizer.plot(filename)

src/crewai/flow/html_template_handler.py

@@ -1,53 +1,26 @@
 import base64
 import re
-from pathlib import Path
-
-from crewai.flow.path_utils import safe_path_join, validate_path_exists
 
 
 class HTMLTemplateHandler:
-    """Handles HTML template processing and generation for flow visualization diagrams."""
-
     def __init__(self, template_path, logo_path):
-        """
-        Initialize HTMLTemplateHandler with validated template and logo paths.
-
-        Parameters
-        ----------
-        template_path : str
-            Path to the HTML template file.
-        logo_path : str
-            Path to the logo image file.
-
-        Raises
-        ------
-        ValueError
-            If template or logo paths are invalid or files don't exist.
-        """
-        try:
-            self.template_path = validate_path_exists(template_path, "file")
-            self.logo_path = validate_path_exists(logo_path, "file")
-        except ValueError as e:
-            raise ValueError(f"Invalid template or logo path: {e}")
+        self.template_path = template_path
+        self.logo_path = logo_path
 
     def read_template(self):
-        """Read and return the HTML template file contents."""
         with open(self.template_path, "r", encoding="utf-8") as f:
             return f.read()
 
     def encode_logo(self):
-        """Convert the logo SVG file to base64 encoded string."""
         with open(self.logo_path, "rb") as logo_file:
             logo_svg_data = logo_file.read()
             return base64.b64encode(logo_svg_data).decode("utf-8")
 
     def extract_body_content(self, html):
-        """Extract and return content between body tags from HTML string."""
         match = re.search("<body.*?>(.*?)</body>", html, re.DOTALL)
         return match.group(1) if match else ""
 
     def generate_legend_items_html(self, legend_items):
-        """Generate HTML markup for the legend items."""
         legend_items_html = ""
         for item in legend_items:
             if "border" in item:
@@ -75,7 +48,6 @@ class HTMLTemplateHandler:
         return legend_items_html
 
     def generate_final_html(self, network_body, legend_items_html, title="Flow Plot"):
-        """Combine all components into final HTML document with network visualization."""
         html_template = self.read_template()
         logo_svg_base64 = self.encode_logo()
 

src/crewai/flow/legend_generator.py

@@ -1,4 +1,3 @@
-
 def get_legend_items(colors):
     return [
         {"label": "Start Method", "color": colors["start"]},

src/crewai/flow/path_utils.py

@@ -1,135 +0,0 @@
-"""
-Path utilities for secure file operations in CrewAI flow module.
-
-This module provides utilities for secure path handling to prevent directory
-traversal attacks and ensure paths remain within allowed boundaries.
-"""
-
-import os
-from pathlib import Path
-from typing import List, Union
-
-
-def safe_path_join(*parts: str, root: Union[str, Path, None] = None) -> str:
-    """
-    Safely join path components and ensure the result is within allowed boundaries.
-
-    Parameters
-    ----------
-    *parts : str
-        Variable number of path components to join.
-    root : Union[str, Path, None], optional
-        Root directory to use as base. If None, uses current working directory.
-
-    Returns
-    -------
-    str
-        String representation of the resolved path.
-
-    Raises
-    ------
-    ValueError
-        If the resulting path would be outside the root directory
-        or if any path component is invalid.
-    """
-    if not parts:
-        raise ValueError("No path components provided")
-
-    try:
-        # Convert all parts to strings and clean them
-        clean_parts = [str(part).strip() for part in parts if part]
-        if not clean_parts:
-            raise ValueError("No valid path components provided")
-
-        # Establish root directory
-        root_path = Path(root).resolve() if root else Path.cwd()
-        
-        # Join and resolve the full path
-        full_path = Path(root_path, *clean_parts).resolve()
-        
-        # Check if the resolved path is within root
-        if not str(full_path).startswith(str(root_path)):
-            raise ValueError(
-                f"Invalid path: Potential directory traversal. Path must be within {root_path}"
-            )
-            
-        return str(full_path)
-        
-    except Exception as e:
-        if isinstance(e, ValueError):
-            raise
-        raise ValueError(f"Invalid path components: {str(e)}")
-
-
-def validate_path_exists(path: Union[str, Path], file_type: str = "file") -> str:
-    """
-    Validate that a path exists and is of the expected type.
-
-    Parameters
-    ----------
-    path : Union[str, Path]
-        Path to validate.
-    file_type : str, optional
-        Expected type ('file' or 'directory'), by default 'file'.
-
-    Returns
-    -------
-    str
-        Validated path as string.
-
-    Raises
-    ------
-    ValueError
-        If path doesn't exist or is not of expected type.
-    """
-    try:
-        path_obj = Path(path).resolve()
-        
-        if not path_obj.exists():
-            raise ValueError(f"Path does not exist: {path}")
-            
-        if file_type == "file" and not path_obj.is_file():
-            raise ValueError(f"Path is not a file: {path}")
-        elif file_type == "directory" and not path_obj.is_dir():
-            raise ValueError(f"Path is not a directory: {path}")
-            
-        return str(path_obj)
-        
-    except Exception as e:
-        if isinstance(e, ValueError):
-            raise
-        raise ValueError(f"Invalid path: {str(e)}")
-
-
-def list_files(directory: Union[str, Path], pattern: str = "*") -> List[str]:
-    """
-    Safely list files in a directory matching a pattern.
-
-    Parameters
-    ----------
-    directory : Union[str, Path]
-        Directory to search in.
-    pattern : str, optional
-        Glob pattern to match files against, by default "*".
-
-    Returns
-    -------
-    List[str]
-        List of matching file paths.
-
-    Raises
-    ------
-    ValueError
-        If directory is invalid or inaccessible.
-    """
-    try:
-        dir_path = Path(directory).resolve()
-        if not dir_path.is_dir():
-            raise ValueError(f"Not a directory: {directory}")
-            
-        return [str(p) for p in dir_path.glob(pattern) if p.is_file()]
-        
-    except Exception as e:
-        if isinstance(e, ValueError):
-            raise
-        raise ValueError(f"Error listing files: {str(e)}")

src/crewai/flow/utils.py

@@ -1,25 +1,9 @@
-"""
-Utility functions for flow visualization and dependency analysis.
-
-This module provides core functionality for analyzing and manipulating flow structures,
-including node level calculation, ancestor tracking, and return value analysis.
-Functions in this module are primarily used by the visualization system to create
-accurate and informative flow diagrams.
-
-Example
--------
->>> flow = Flow()
->>> node_levels = calculate_node_levels(flow)
->>> ancestors = build_ancestor_dict(flow)
-"""
-
 import ast
 import inspect
 import textwrap
-from typing import Any, Dict, List, Optional, Set, Union
 
 
-def get_possible_return_constants(function: Any) -> Optional[List[str]]:
+def get_possible_return_constants(function):
     try:
         source = inspect.getsource(function)
     except OSError:
@@ -93,34 +77,11 @@ def get_possible_return_constants(function: Any) -> Optional[List[str]]:
     return list(return_values) if return_values else None
 
 
-def calculate_node_levels(flow: Any) -> Dict[str, int]:
-    """
-    Calculate the hierarchical level of each node in the flow.
-
-    Performs a breadth-first traversal of the flow graph to assign levels
-    to nodes, starting with start methods at level 0.
-
-    Parameters
-    ----------
-    flow : Any
-        The flow instance containing methods, listeners, and router configurations.
-
-    Returns
-    -------
-    Dict[str, int]
-        Dictionary mapping method names to their hierarchical levels.
-
-    Notes
-    -----
-    - Start methods are assigned level 0
-    - Each subsequent connected node is assigned level = parent_level + 1
-    - Handles both OR and AND conditions for listeners
-    - Processes router paths separately
-    """
-    levels: Dict[str, int] = {}
-    queue: List[str] = []
-    visited: Set[str] = set()
-    pending_and_listeners: Dict[str, Set[str]] = {}
+def calculate_node_levels(flow):
+    levels = {}
+    queue = []
+    visited = set()
+    pending_and_listeners = {}
 
     # Make all start methods at level 0
     for method_name, method in flow._methods.items():
@@ -179,20 +140,7 @@ def calculate_node_levels(flow: Any) -> Dict[str, int]:
     return levels
 
 
-def count_outgoing_edges(flow: Any) -> Dict[str, int]:
-    """
-    Count the number of outgoing edges for each method in the flow.
-
-    Parameters
-    ----------
-    flow : Any
-        The flow instance to analyze.
-
-    Returns
-    -------
-    Dict[str, int]
-        Dictionary mapping method names to their outgoing edge count.
-    """
+def count_outgoing_edges(flow):
     counts = {}
     for method_name in flow._methods:
         counts[method_name] = 0
@@ -204,53 +152,16 @@ def count_outgoing_edges(flow: Any) -> Dict[str, int]:
     return counts
 
 
-def build_ancestor_dict(flow: Any) -> Dict[str, Set[str]]:
-    """
-    Build a dictionary mapping each node to its ancestor nodes.
-
-    Parameters
-    ----------
-    flow : Any
-        The flow instance to analyze.
-
-    Returns
-    -------
-    Dict[str, Set[str]]
-        Dictionary mapping each node to a set of its ancestor nodes.
-    """
-    ancestors: Dict[str, Set[str]] = {node: set() for node in flow._methods}
-    visited: Set[str] = set()
+def build_ancestor_dict(flow):
+    ancestors = {node: set() for node in flow._methods}
+    visited = set()
     for node in flow._methods:
         if node not in visited:
             dfs_ancestors(node, ancestors, visited, flow)
     return ancestors
 
 
-def dfs_ancestors(
-    node: str,
-    ancestors: Dict[str, Set[str]],
-    visited: Set[str],
-    flow: Any
-) -> None:
-    """
-    Perform depth-first search to build ancestor relationships.
-
-    Parameters
-    ----------
-    node : str
-        Current node being processed.
-    ancestors : Dict[str, Set[str]]
-        Dictionary tracking ancestor relationships.
-    visited : Set[str]
-        Set of already visited nodes.
-    flow : Any
-        The flow instance being analyzed.
-
-    Notes
-    -----
-    This function modifies the ancestors dictionary in-place to build
-    the complete ancestor graph.
-    """
+def dfs_ancestors(node, ancestors, visited, flow):
     if node in visited:
         return
     visited.add(node)
@@ -274,48 +185,12 @@ def dfs_ancestors(
                     dfs_ancestors(listener_name, ancestors, visited, flow)
 
 
-def is_ancestor(node: str, ancestor_candidate: str, ancestors: Dict[str, Set[str]]) -> bool:
-    """
-    Check if one node is an ancestor of another.
-
-    Parameters
-    ----------
-    node : str
-        The node to check ancestors for.
-    ancestor_candidate : str
-        The potential ancestor node.
-    ancestors : Dict[str, Set[str]]
-        Dictionary containing ancestor relationships.
-
-    Returns
-    -------
-    bool
-        True if ancestor_candidate is an ancestor of node, False otherwise.
-    """
+def is_ancestor(node, ancestor_candidate, ancestors):
     return ancestor_candidate in ancestors.get(node, set())
 
 
-def build_parent_children_dict(flow: Any) -> Dict[str, List[str]]:
-    """
-    Build a dictionary mapping parent nodes to their children.
-
-    Parameters
-    ----------
-    flow : Any
-        The flow instance to analyze.
-
-    Returns
-    -------
-    Dict[str, List[str]]
-        Dictionary mapping parent method names to lists of their child method names.
-
-    Notes
-    -----
-    - Maps listeners to their trigger methods
-    - Maps router methods to their paths and listeners
-    - Children lists are sorted for consistent ordering
-    """
-    parent_children: Dict[str, List[str]] = {}
+def build_parent_children_dict(flow):
+    parent_children = {}
 
     # Map listeners to their trigger methods
     for listener_name, (_, trigger_methods) in flow._listeners.items():
@@ -339,24 +214,7 @@ def build_parent_children_dict(flow: Any) -> Dict[str, List[str]]:
     return parent_children
 
 
-def get_child_index(parent: str, child: str, parent_children: Dict[str, List[str]]) -> int:
-    """
-    Get the index of a child node in its parent's sorted children list.
-
-    Parameters
-    ----------
-    parent : str
-        The parent node name.
-    child : str
-        The child node name to find the index for.
-    parent_children : Dict[str, List[str]]
-        Dictionary mapping parents to their children lists.
-
-    Returns
-    -------
-    int
-        Zero-based index of the child in its parent's sorted children list.
-    """
+def get_child_index(parent, child, parent_children):
     children = parent_children.get(parent, [])
     children.sort()
     return children.index(child)

src/crewai/flow/visualization_utils.py

@@ -1,23 +1,5 @@
-"""
-Utilities for creating visual representations of flow structures.
-
-This module provides functions for generating network visualizations of flows,
-including node placement, edge creation, and visual styling. It handles the
-conversion of flow structures into visual network graphs with appropriate
-styling and layout.
-
-Example
--------
->>> flow = Flow()
->>> net = Network(directed=True)
->>> node_positions = compute_positions(flow, node_levels)
->>> add_nodes_to_network(net, flow, node_positions, node_styles)
->>> add_edges(net, flow, node_positions, colors)
-"""
-
 import ast
 import inspect
-from typing import Any, Dict, List, Optional, Tuple, Union
 
 from .utils import (
     build_ancestor_dict,
@@ -27,25 +9,8 @@ from .utils import (
 )
 
 
-def method_calls_crew(method: Any) -> bool:
-    """
-    Check if the method contains a call to `.crew()`.
-
-    Parameters
-    ----------
-    method : Any
-        The method to analyze for crew() calls.
-
-    Returns
-    -------
-    bool
-        True if the method calls .crew(), False otherwise.
-
-    Notes
-    -----
-    Uses AST analysis to detect method calls, specifically looking for
-    attribute access of 'crew'.
-    """
+def method_calls_crew(method):
+    """Check if the method calls `.crew()`."""
     try:
         source = inspect.getsource(method)
         source = inspect.cleandoc(source)
@@ -55,7 +20,6 @@ def method_calls_crew(method: Any) -> bool:
         return False
 
     class CrewCallVisitor(ast.NodeVisitor):
-        """AST visitor to detect .crew() method calls."""
         def __init__(self):
             self.found = False
 
@@ -70,34 +34,7 @@ def method_calls_crew(method: Any) -> bool:
     return visitor.found
 
 
-def add_nodes_to_network(
-    net: Any,
-    flow: Any,
-    node_positions: Dict[str, Tuple[float, float]],
-    node_styles: Dict[str, Dict[str, Any]]
-) -> None:
-    """
-    Add nodes to the network visualization with appropriate styling.
-
-    Parameters
-    ----------
-    net : Any
-        The pyvis Network instance to add nodes to.
-    flow : Any
-        The flow instance containing method information.
-    node_positions : Dict[str, Tuple[float, float]]
-        Dictionary mapping node names to their (x, y) positions.
-    node_styles : Dict[str, Dict[str, Any]]
-        Dictionary containing style configurations for different node types.
-
-    Notes
-    -----
-    Node types include:
-    - Start methods
-    - Router methods
-    - Crew methods
-    - Regular methods
-    """
+def add_nodes_to_network(net, flow, node_positions, node_styles):
     def human_friendly_label(method_name):
         return method_name.replace("_", " ").title()
 
@@ -136,33 +73,9 @@ def add_nodes_to_network(
         )
 
 
-def compute_positions(
-    flow: Any,
-    node_levels: Dict[str, int],
-    y_spacing: float = 150,
-    x_spacing: float = 150
-) -> Dict[str, Tuple[float, float]]:
-    """
-    Compute the (x, y) positions for each node in the flow graph.
-
-    Parameters
-    ----------
-    flow : Any
-        The flow instance to compute positions for.
-    node_levels : Dict[str, int]
-        Dictionary mapping node names to their hierarchical levels.
-    y_spacing : float, optional
-        Vertical spacing between levels, by default 150.
-    x_spacing : float, optional
-        Horizontal spacing between nodes, by default 150.
-
-    Returns
-    -------
-    Dict[str, Tuple[float, float]]
-        Dictionary mapping node names to their (x, y) coordinates.
-    """
-    level_nodes: Dict[int, List[str]] = {}
-    node_positions: Dict[str, Tuple[float, float]] = {}
+def compute_positions(flow, node_levels, y_spacing=150, x_spacing=150):
+    level_nodes = {}
+    node_positions = {}
 
     for method_name, level in node_levels.items():
         level_nodes.setdefault(level, []).append(method_name)
@@ -177,33 +90,7 @@ def compute_positions(
     return node_positions
 
 
-def add_edges(
-    net: Any,
-    flow: Any,
-    node_positions: Dict[str, Tuple[float, float]],
-    colors: Dict[str, str]
-) -> None:
-    edge_smooth: Dict[str, Union[str, float]] = {"type": "continuous"}  # Default value
-    """
-    Add edges to the network visualization with appropriate styling.
-
-    Parameters
-    ----------
-    net : Any
-        The pyvis Network instance to add edges to.
-    flow : Any
-        The flow instance containing edge information.
-    node_positions : Dict[str, Tuple[float, float]]
-        Dictionary mapping node names to their positions.
-    colors : Dict[str, str]
-        Dictionary mapping edge types to their colors.
-
-    Notes
-    -----
-    - Handles both normal listener edges and router edges
-    - Applies appropriate styling (color, dashes) based on edge type
-    - Adds curvature to edges when needed (cycles or multiple children)
-    """
+def add_edges(net, flow, node_positions, colors):
     ancestors = build_ancestor_dict(flow)
     parent_children = build_parent_children_dict(flow)
 
@@ -239,7 +126,7 @@ def add_edges(
                     else:
                         edge_smooth = {"type": "cubicBezier"}
                 else:
-                    edge_smooth.update({"type": "continuous"})
+                    edge_smooth = False
 
                 edge_style = {
                     "color": edge_color,
@@ -302,7 +189,7 @@ def add_edges(
                             else:
                                 edge_smooth = {"type": "cubicBezier"}
                         else:
-                            edge_smooth.update({"type": "continuous"})
+                            edge_smooth = False
 
                         edge_style = {
                             "color": colors["router_edge"],

src/crewai/knowledge/source/crew_docling_source.py

@@ -2,16 +2,11 @@ from pathlib import Path
 from typing import Iterator, List, Optional, Union
 from urllib.parse import urlparse
 
-try:
-    from docling.datamodel.base_models import InputFormat
-    from docling.document_converter import DocumentConverter
-    from docling.exceptions import ConversionError
-    from docling_core.transforms.chunker.hierarchical_chunker import HierarchicalChunker
-    from docling_core.types.doc.document import DoclingDocument
-    DOCLING_AVAILABLE = True
-except ImportError:
-    DOCLING_AVAILABLE = False
-
+from docling.datamodel.base_models import InputFormat
+from docling.document_converter import DocumentConverter
+from docling.exceptions import ConversionError
+from docling_core.transforms.chunker.hierarchical_chunker import HierarchicalChunker
+from docling_core.types.doc.document import DoclingDocument
 from pydantic import Field
 
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
@@ -24,14 +19,6 @@ class CrewDoclingSource(BaseKnowledgeSource):
     This will auto support PDF, DOCX, and TXT, XLSX, Images, and HTML files without any additional dependencies and follows the docling package as the source of truth.
     """
 
-    def __init__(self, *args, **kwargs):
-        if not DOCLING_AVAILABLE:
-            raise ImportError(
-                "The docling package is required to use CrewDoclingSource. "
-                "Please install it using: uv add docling"
-            )
-        super().__init__(*args, **kwargs)
-
     _logger: Logger = Logger(verbose=True)
 
     file_path: Optional[List[Union[Path, str]]] = Field(default=None)

src/crewai/llm.py

@@ -1,27 +1,18 @@
-import json
 import logging
 import os
 import sys
 import threading
 import warnings
 from contextlib import contextmanager
-from typing import Any, Dict, List, Optional, Union, cast
-
-from dotenv import load_dotenv
-
-with warnings.catch_warnings():
-    warnings.simplefilter("ignore", UserWarning)
-    import litellm
-    from litellm import Choices, get_supported_openai_params
-    from litellm.types.utils import ModelResponse
+from typing import Any, Dict, List, Optional, Union
 
+import litellm
+from litellm import get_supported_openai_params
 
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededException,
 )
 
-load_dotenv()
-
 
 class FilteredStream:
     def __init__(self, original_stream):
@@ -30,7 +21,6 @@ class FilteredStream:
 
     def write(self, s) -> int:
         with self._lock:
-            # Filter out extraneous messages from LiteLLM
             if (
                 "Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new"
                 in s
@@ -92,9 +82,11 @@ def suppress_warnings():
         old_stderr = sys.stderr
         sys.stdout = FilteredStream(old_stdout)
         sys.stderr = FilteredStream(old_stderr)
+
         try:
             yield
         finally:
+            # Restore stdout and stderr
             sys.stdout = old_stdout
             sys.stderr = old_stderr
 
@@ -115,12 +107,13 @@ class LLM:
         logit_bias: Optional[Dict[int, float]] = None,
         response_format: Optional[Dict[str, Any]] = None,
         seed: Optional[int] = None,
-        logprobs: Optional[int] = None,
+        logprobs: Optional[bool] = None,
         top_logprobs: Optional[int] = None,
         base_url: Optional[str] = None,
         api_version: Optional[str] = None,
         api_key: Optional[str] = None,
         callbacks: List[Any] = [],
+        **kwargs,
     ):
         self.model = model
         self.timeout = timeout
@@ -142,96 +135,19 @@ class LLM:
         self.api_key = api_key
         self.callbacks = callbacks
         self.context_window_size = 0
+        self.kwargs = kwargs
 
-        # For safety, we disable passing init params to next calls
         litellm.drop_params = True
-
+        litellm.set_verbose = False
         self.set_callbacks(callbacks)
         self.set_env_callbacks()
 
-    def to_dict(self) -> dict:
-        """
-        Return a dict of all relevant parameters for serialization.
-        """
-        return {
-            "model": self.model,
-            "timeout": self.timeout,
-            "temperature": self.temperature,
-            "top_p": self.top_p,
-            "n": self.n,
-            "stop": self.stop,
-            "max_completion_tokens": self.max_completion_tokens,
-            "max_tokens": self.max_tokens,
-            "presence_penalty": self.presence_penalty,
-            "frequency_penalty": self.frequency_penalty,
-            "logit_bias": self.logit_bias,
-            "response_format": self.response_format,
-            "seed": self.seed,
-            "logprobs": self.logprobs,
-            "top_logprobs": self.top_logprobs,
-            "base_url": self.base_url,
-            "api_version": self.api_version,
-            "api_key": self.api_key,
-            "callbacks": self.callbacks,
-        }
-
-    @classmethod
-    def from_dict(cls, data: dict) -> "LLM":
-        """
-        Create an LLM instance from a dict.
-        We assume the dict has all relevant keys that match what's in the constructor.
-        """
-        known_fields = {}
-        known_fields["model"] = data.pop("model", None)
-        known_fields["timeout"] = data.pop("timeout", None)
-        known_fields["temperature"] = data.pop("temperature", None)
-        known_fields["top_p"] = data.pop("top_p", None)
-        known_fields["n"] = data.pop("n", None)
-        known_fields["stop"] = data.pop("stop", None)
-        known_fields["max_completion_tokens"] = data.pop("max_completion_tokens", None)
-        known_fields["max_tokens"] = data.pop("max_tokens", None)
-        known_fields["presence_penalty"] = data.pop("presence_penalty", None)
-        known_fields["frequency_penalty"] = data.pop("frequency_penalty", None)
-        known_fields["logit_bias"] = data.pop("logit_bias", None)
-        known_fields["response_format"] = data.pop("response_format", None)
-        known_fields["seed"] = data.pop("seed", None)
-        known_fields["logprobs"] = data.pop("logprobs", None)
-        known_fields["top_logprobs"] = data.pop("top_logprobs", None)
-        known_fields["base_url"] = data.pop("base_url", None)
-        known_fields["api_version"] = data.pop("api_version", None)
-        known_fields["api_key"] = data.pop("api_key", None)
-        known_fields["callbacks"] = data.pop("callbacks", None)
-
-        return cls(**known_fields, **data)
-
-    def call(
-        self,
-        messages: List[Dict[str, str]],
-        tools: Optional[List[dict]] = None,
-        callbacks: Optional[List[Any]] = None,
-        available_functions: Optional[Dict[str, Any]] = None,
-    ) -> str:
-        """
-        High-level call method that:
-          1) Calls litellm.completion
-          2) Checks for function/tool calls
-          3) If a tool call is found:
-               a) executes the function
-               b) returns the result
-          4) If no tool call, returns the text response
-
-        :param messages: The conversation messages
-        :param tools: Optional list of function schemas for function calling
-        :param callbacks: Optional list of callbacks
-        :param available_functions: A dictionary mapping function_name -> actual Python function
-        :return: Final text response from the LLM or the tool result
-        """
+    def call(self, messages: List[Dict[str, str]], callbacks: List[Any] = []) -> str:
         with suppress_warnings():
-            if callbacks:
+            if callbacks and len(callbacks) > 0:
                 self.set_callbacks(callbacks)
 
             try:
-                # --- 1) Make the completion call
                 params = {
                     "model": self.model,
                     "messages": messages,
@@ -252,65 +168,21 @@ class LLM:
                     "api_version": self.api_version,
                     "api_key": self.api_key,
                     "stream": False,
-                    "tools": tools,  # pass the tool schema
+                    **self.kwargs,
                 }
 
-                # Remove None values
+                # Remove None values to avoid passing unnecessary parameters
                 params = {k: v for k, v in params.items() if v is not None}
 
                 response = litellm.completion(**params)
-                response_message = cast(Choices, cast(ModelResponse, response).choices)[
-                    0
-                ].message
-                text_response = response_message.content or ""
-                tool_calls = getattr(response_message, "tool_calls", [])
-
-                # --- 2) If no tool calls, return the text response
-                if not tool_calls or not available_functions:
-                    return text_response
-
-                # --- 3) Handle the tool call
-                tool_call = tool_calls[0]
-                function_name = tool_call.function.name
-
-                if function_name in available_functions:
-                    # Parse arguments
-                    try:
-                        function_args = json.loads(tool_call.function.arguments)
-                    except json.JSONDecodeError as e:
-                        logging.warning(f"Failed to parse function arguments: {e}")
-                        return text_response  # Fallback to text response
-
-                    fn = available_functions[function_name]
-                    try:
-                        # Call the actual tool function
-                        result = fn(**function_args)
-
-                        print(f"Result from function '{function_name}': {result}")
-
-                        # Return the result directly
-                        return result
-
-                    except Exception as e:
-                        logging.error(
-                            f"Error executing function '{function_name}': {e}"
-                        )
-                        return text_response  # Fallback to text response
-
-                else:
-                    logging.warning(
-                        f"Tool call requested unknown function '{function_name}'"
-                    )
-                    return text_response  # Fallback to text response
-
+                return response["choices"][0]["message"]["content"]
             except Exception as e:
-                # Check if context length was exceeded, otherwise log
                 if not LLMContextLengthExceededException(
                     str(e)
                 )._is_context_limit_error(str(e)):
                     logging.error(f"LiteLLM call failed: {str(e)}")
-                # Re-raise the exception
-                raise
+
+                raise  # Re-raise the exception after logging
 
     def supports_function_calling(self) -> bool:
         try:
@@ -329,10 +201,7 @@ class LLM:
             return False
 
     def get_context_window_size(self) -> int:
-        """
-        Returns the context window size, using 75% of the maximum to avoid
-        cutting off messages mid-thread.
-        """
+        # Only using 75% of the context window size to avoid cutting the message in the middle
         if self.context_window_size != 0:
             return self.context_window_size
 
@@ -345,10 +214,6 @@ class LLM:
         return self.context_window_size
 
     def set_callbacks(self, callbacks: List[Any]):
-        """
-        Attempt to keep a single set of callbacks in litellm by removing old
-        duplicates and adding new ones.
-        """
         callback_types = [type(callback) for callback in callbacks]
         for callback in litellm.success_callback[:]:
             if type(callback) in callback_types:
@@ -363,19 +228,34 @@ class LLM:
     def set_env_callbacks(self):
         """
         Sets the success and failure callbacks for the LiteLLM library from environment variables.
+
+        This method reads the `LITELLM_SUCCESS_CALLBACKS` and `LITELLM_FAILURE_CALLBACKS`
+        environment variables, which should contain comma-separated lists of callback names.
+        It then assigns these lists to `litellm.success_callback` and `litellm.failure_callback`,
+        respectively.
+
+        If the environment variables are not set or are empty, the corresponding callback lists
+        will be set to empty lists.
+
+        Example:
+            LITELLM_SUCCESS_CALLBACKS="langfuse,langsmith"
+            LITELLM_FAILURE_CALLBACKS="langfuse"
+
+        This will set `litellm.success_callback` to ["langfuse", "langsmith"] and
+        `litellm.failure_callback` to ["langfuse"].
         """
         success_callbacks_str = os.environ.get("LITELLM_SUCCESS_CALLBACKS", "")
         success_callbacks = []
         if success_callbacks_str:
             success_callbacks = [
-                cb.strip() for cb in success_callbacks_str.split(",") if cb.strip()
+                callback.strip() for callback in success_callbacks_str.split(",")
             ]
 
         failure_callbacks_str = os.environ.get("LITELLM_FAILURE_CALLBACKS", "")
         failure_callbacks = []
         if failure_callbacks_str:
             failure_callbacks = [
-                cb.strip() for cb in failure_callbacks_str.split(",") if cb.strip()
+                callback.strip() for callback in failure_callbacks_str.split(",")
             ]
 
         litellm.success_callback = success_callbacks

src/crewai/project/annotations.py

@@ -4,23 +4,18 @@ from typing import Callable
 from crewai import Crew
 from crewai.project.utils import memoize
 
-"""Decorators for defining crew components and their behaviors."""
-
 
 def before_kickoff(func):
-    """Marks a method to execute before crew kickoff."""
     func.is_before_kickoff = True
     return func
 
 
 def after_kickoff(func):
-    """Marks a method to execute after crew kickoff."""
     func.is_after_kickoff = True
     return func
 
 
 def task(func):
-    """Marks a method as a crew task."""
     func.is_task = True
 
     @wraps(func)
@@ -34,51 +29,43 @@ def task(func):
 
 
 def agent(func):
-    """Marks a method as a crew agent."""
     func.is_agent = True
     func = memoize(func)
     return func
 
 
 def llm(func):
-    """Marks a method as an LLM provider."""
     func.is_llm = True
     func = memoize(func)
     return func
 
 
 def output_json(cls):
-    """Marks a class as JSON output format."""
     cls.is_output_json = True
     return cls
 
 
 def output_pydantic(cls):
-    """Marks a class as Pydantic output format."""
     cls.is_output_pydantic = True
     return cls
 
 
 def tool(func):
-    """Marks a method as a crew tool."""
     func.is_tool = True
     return memoize(func)
 
 
 def callback(func):
-    """Marks a method as a crew callback."""
     func.is_callback = True
     return memoize(func)
 
 
 def cache_handler(func):
-    """Marks a method as a cache handler."""
     func.is_cache_handler = True
     return memoize(func)
 
 
 def crew(func) -> Callable[..., Crew]:
-    """Marks a method as the main crew execution point."""
 
     @wraps(func)
     def wrapper(self, *args, **kwargs) -> Crew:

src/crewai/project/crew_base.py

@@ -9,10 +9,8 @@ load_dotenv()
 
 T = TypeVar("T", bound=type)
 
-"""Base decorator for creating crew classes with configuration and function management."""
 
 def CrewBase(cls: T) -> T:
-    """Wraps a class with crew functionality and configuration management."""
     class WrappedClass(cls):  # type: ignore
         is_crew_class: bool = True  # type: ignore
 
@@ -218,5 +216,5 @@ def CrewBase(cls: T) -> T:
     # Include base class (qual)name in the wrapper class (qual)name.
     WrappedClass.__name__ = CrewBase.__name__ + "(" + cls.__name__ + ")"
     WrappedClass.__qualname__ = CrewBase.__qualname__ + "(" + cls.__name__ + ")"
-
+  
     return cast(T, WrappedClass)

src/crewai/task.py

@@ -127,41 +127,38 @@ class Task(BaseModel):
     processed_by_agents: Set[str] = Field(default_factory=set)
     guardrail: Optional[Callable[[TaskOutput], Tuple[bool, Any]]] = Field(
         default=None,
-        description="Function to validate task output before proceeding to next task",
+        description="Function to validate task output before proceeding to next task"
     )
     max_retries: int = Field(
-        default=3, description="Maximum number of retries when guardrail fails"
+        default=3,
+        description="Maximum number of retries when guardrail fails"
     )
-    retry_count: int = Field(default=0, description="Current number of retries")
-
-    start_time: Optional[datetime.datetime] = Field(
-        default=None, description="Start time of the task execution"
-    )
-    end_time: Optional[datetime.datetime] = Field(
-        default=None, description="End time of the task execution"
+    retry_count: int = Field(
+        default=0,
+        description="Current number of retries"
     )
 
     @field_validator("guardrail")
     @classmethod
     def validate_guardrail_function(cls, v: Optional[Callable]) -> Optional[Callable]:
         """Validate that the guardrail function has the correct signature and behavior.
-
+        
         While type hints provide static checking, this validator ensures runtime safety by:
         1. Verifying the function accepts exactly one parameter (the TaskOutput)
         2. Checking return type annotations match Tuple[bool, Any] if present
         3. Providing clear, immediate error messages for debugging
-
+        
         This runtime validation is crucial because:
         - Type hints are optional and can be ignored at runtime
         - Function signatures need immediate validation before task execution
         - Clear error messages help users debug guardrail implementation issues
-
+        
         Args:
             v: The guardrail function to validate
-
+            
         Returns:
             The validated guardrail function
-
+            
         Raises:
             ValueError: If the function signature is invalid or return annotation
                        doesn't match Tuple[bool, Any]
@@ -174,13 +171,8 @@ class Task(BaseModel):
             # Check return annotation if present, but don't require it
             return_annotation = sig.return_annotation
             if return_annotation != inspect.Signature.empty:
-                if not (
-                    return_annotation == Tuple[bool, Any]
-                    or str(return_annotation) == "Tuple[bool, Any]"
-                ):
-                    raise ValueError(
-                        "If return type is annotated, it must be Tuple[bool, Any]"
-                    )
+                if not (return_annotation == Tuple[bool, Any] or str(return_annotation) == 'Tuple[bool, Any]'):
+                    raise ValueError("If return type is annotated, it must be Tuple[bool, Any]")
         return v
 
     _telemetry: Telemetry = PrivateAttr(default_factory=Telemetry)
@@ -189,6 +181,7 @@ class Task(BaseModel):
     _original_expected_output: Optional[str] = PrivateAttr(default=None)
     _original_output_file: Optional[str] = PrivateAttr(default=None)
     _thread: Optional[threading.Thread] = PrivateAttr(default=None)
+    _execution_time: Optional[float] = PrivateAttr(default=None)
 
     @model_validator(mode="before")
     @classmethod
@@ -213,19 +206,25 @@ class Task(BaseModel):
                 "may_not_set_field", "This field is not to be set by the user.", {}
             )
 
+    def _set_start_execution_time(self) -> float:
+        return datetime.datetime.now().timestamp()
+
+    def _set_end_execution_time(self, start_time: float) -> None:
+        self._execution_time = datetime.datetime.now().timestamp() - start_time
+
     @field_validator("output_file")
     @classmethod
     def output_file_validation(cls, value: Optional[str]) -> Optional[str]:
         """Validate the output file path.
-
+        
         Args:
             value: The output file path to validate. Can be None or a string.
                   If the path contains template variables (e.g. {var}), leading slashes are preserved.
                   For regular paths, leading slashes are stripped.
-
+        
         Returns:
             The validated and potentially modified path, or None if no path was provided.
-
+            
         Raises:
             ValueError: If the path contains invalid characters, path traversal attempts,
                       or other security concerns.
@@ -235,24 +234,18 @@ class Task(BaseModel):
 
         # Basic security checks
         if ".." in value:
-            raise ValueError(
-                "Path traversal attempts are not allowed in output_file paths"
-            )
-
+            raise ValueError("Path traversal attempts are not allowed in output_file paths")
+        
         # Check for shell expansion first
-        if value.startswith("~") or value.startswith("$"):
-            raise ValueError(
-                "Shell expansion characters are not allowed in output_file paths"
-            )
-
+        if value.startswith('~') or value.startswith('$'):
+            raise ValueError("Shell expansion characters are not allowed in output_file paths")
+            
         # Then check other shell special characters
-        if any(char in value for char in ["|", ">", "<", "&", ";"]):
-            raise ValueError(
-                "Shell special characters are not allowed in output_file paths"
-            )
+        if any(char in value for char in ['|', '>', '<', '&', ';']):
+            raise ValueError("Shell special characters are not allowed in output_file paths")
 
         # Don't strip leading slash if it's a template path with variables
-        if "{" in value or "}" in value:
+        if "{" in value or "}" in value: 
             # Validate template variable format
             template_vars = [part.split("}")[0] for part in value.split("{")[1:]]
             for var in template_vars:
@@ -309,12 +302,6 @@ class Task(BaseModel):
 
         return md5("|".join(source).encode(), usedforsecurity=False).hexdigest()
 
-    @property
-    def execution_duration(self) -> float | None:
-        if not self.start_time or not self.end_time:
-            return None
-        return (self.end_time - self.start_time).total_seconds()
-
     def execute_async(
         self,
         agent: BaseAgent | None = None,
@@ -355,7 +342,7 @@ class Task(BaseModel):
                 f"The task '{self.description}' has no agent assigned, therefore it can't be executed directly and should be executed in a Crew using a specific process that support that, like hierarchical."
             )
 
-        self.start_time = datetime.datetime.now()
+        start_time = self._set_start_execution_time()
         self._execution_span = self._telemetry.task_started(crew=agent.crew, task=self)
 
         self.prompt_context = context
@@ -405,17 +392,15 @@ class Task(BaseModel):
 
             if isinstance(guardrail_result.result, str):
                 task_output.raw = guardrail_result.result
-                pydantic_output, json_output = self._export_output(
-                    guardrail_result.result
-                )
+                pydantic_output, json_output = self._export_output(guardrail_result.result)
                 task_output.pydantic = pydantic_output
                 task_output.json_dict = json_output
             elif isinstance(guardrail_result.result, TaskOutput):
                 task_output = guardrail_result.result
 
         self.output = task_output
-        self.end_time = datetime.datetime.now()
 
+        self._set_end_execution_time(start_time)
         if self.callback:
             self.callback(self.output)
 
@@ -427,9 +412,7 @@ class Task(BaseModel):
             content = (
                 json_output
                 if json_output
-                else pydantic_output.model_dump_json()
-                if pydantic_output
-                else result
+                else pydantic_output.model_dump_json() if pydantic_output else result
             )
             self._save_file(content)
 
@@ -449,15 +432,13 @@ class Task(BaseModel):
         tasks_slices = [self.description, output]
         return "\n".join(tasks_slices)
 
-
-    def interpolate_inputs_and_add_conversation_history(self, inputs: Dict[str, Union[str, int, float]]) -> None:
+    def interpolate_inputs(self, inputs: Dict[str, Union[str, int, float]]) -> None:
         """Interpolate inputs into the task description, expected output, and output file path.
-           Add conversation history if present.
         
         Args:
             inputs: Dictionary mapping template variables to their values.
                    Supported value types are strings, integers, and floats.
-
+        
         Raises:
             ValueError: If a required template variable is missing from inputs.
         """
@@ -474,9 +455,7 @@ class Task(BaseModel):
         try:
             self.description = self._original_description.format(**inputs)
         except KeyError as e:
-            raise ValueError(
-                f"Missing required template variable '{e.args[0]}' in description"
-            ) from e
+            raise ValueError(f"Missing required template variable '{e.args[0]}' in description") from e
         except ValueError as e:
             raise ValueError(f"Error interpolating description: {str(e)}") from e
 
@@ -494,49 +473,21 @@ class Task(BaseModel):
                 )
             except (KeyError, ValueError) as e:
                 raise ValueError(f"Error interpolating output_file path: {str(e)}") from e
-                
-        if "crew_chat_messages" in inputs and inputs["crew_chat_messages"]:
-            # Fetch the conversation history instruction using self.i18n.slice
-            conversation_instruction = self.i18n.slice(
-                "conversation_history_instruction"
-            )
-            print("crew_chat_messages:", inputs["crew_chat_messages"])
 
-            # Ensure that inputs["crew_chat_messages"] is a string
-            crew_chat_messages_json = str(inputs["crew_chat_messages"])
-
-            try:
-                crew_chat_messages = json.loads(crew_chat_messages_json)
-            except json.JSONDecodeError as e:
-                print("An error occurred while parsing crew chat messages:", e)
-                raise
-
-            # Process the messages to build conversation history
-            conversation_history = "\n".join(
-                f"{msg['role'].capitalize()}: {msg['content']}"
-                for msg in crew_chat_messages
-                if isinstance(msg, dict) and "role" in msg and "content" in msg
-            )
-
-            # Add the instruction and conversation history to the description
-            self.description += f"\n\n{conversation_instruction}\n\n{conversation_history}"
-
-    def interpolate_only(
-        self, input_string: Optional[str], inputs: Dict[str, Union[str, int, float]]
-    ) -> str:
+    def interpolate_only(self, input_string: Optional[str], inputs: Dict[str, Union[str, int, float]]) -> str:
         """Interpolate placeholders (e.g., {key}) in a string while leaving JSON untouched.
-
+        
         Args:
             input_string: The string containing template variables to interpolate.
                          Can be None or empty, in which case an empty string is returned.
             inputs: Dictionary mapping template variables to their values.
                    Supported value types are strings, integers, and floats.
                    If input_string is empty or has no placeholders, inputs can be empty.
-
+        
         Returns:
             The interpolated string with all template variables replaced with their values.
             Empty string if input_string is None or empty.
-
+            
         Raises:
             ValueError: If a required template variable is missing from inputs.
             KeyError: If a template variable is not found in the inputs dictionary.
@@ -546,17 +497,13 @@ class Task(BaseModel):
         if "{" not in input_string and "}" not in input_string:
             return input_string
         if not inputs:
-            raise ValueError(
-                "Inputs dictionary cannot be empty when interpolating variables"
-            )
+            raise ValueError("Inputs dictionary cannot be empty when interpolating variables")
 
         try:
             # Validate input types
             for key, value in inputs.items():
                 if not isinstance(value, (str, int, float)):
-                    raise ValueError(
-                        f"Value for key '{key}' must be a string, integer, or float, got {type(value).__name__}"
-                    )
+                    raise ValueError(f"Value for key '{key}' must be a string, integer, or float, got {type(value).__name__}")
 
             escaped_string = input_string.replace("{", "{{").replace("}", "}}")
 
@@ -565,9 +512,7 @@ class Task(BaseModel):
 
             return escaped_string.format(**inputs)
         except KeyError as e:
-            raise KeyError(
-                f"Template variable '{e.args[0]}' not found in inputs dictionary"
-            ) from e
+            raise KeyError(f"Template variable '{e.args[0]}' not found in inputs dictionary") from e
         except ValueError as e:
             raise ValueError(f"Error during string interpolation: {str(e)}") from e
 
@@ -652,10 +597,10 @@ class Task(BaseModel):
 
     def _save_file(self, result: Any) -> None:
         """Save task output to a file.
-
+        
         Args:
             result: The result to save to the file. Can be a dict or any stringifiable object.
-
+            
         Raises:
             ValueError: If output_file is not set
             RuntimeError: If there is an error writing to the file
@@ -673,7 +618,6 @@ class Task(BaseModel):
             with resolved_path.open("w", encoding="utf-8") as file:
                 if isinstance(result, dict):
                     import json
-
                     json.dump(result, file, ensure_ascii=False, indent=2)
                 else:
                     file.write(str(result))

src/crewai/tools/tool_usage.py

@@ -169,7 +169,7 @@ class ToolUsage:
 
                 if calling.arguments:
                     try:
-                        acceptable_args = tool.args_schema.model_json_schema()["properties"].keys()  # type: ignore
+                        acceptable_args = tool.args_schema.schema()["properties"].keys()  # type: ignore # Item "None" of "type[BaseModel] | None" has no attribute "schema"
                         arguments = {
                             k: v
                             for k, v in calling.arguments.items()

src/crewai/translations/en.json

@@ -23,8 +23,7 @@
     "summary": "This is a summary of our conversation so far:\n{merged_summary}",
     "manager_request": "Your best answer to your coworker asking you this, accounting for the context shared.",
     "formatted_task_instructions": "Ensure your final answer contains only the content in the following format: {output_format}\n\nEnsure the final output does not include any code block markers like ```json or ```python.",
-    "human_feedback_classification": "Determine if the following feedback indicates that the user is satisfied or if further changes are needed. Respond with 'True' if further changes are needed, or 'False' if the user is satisfied. **Important** Do not include any additional commentary outside of your 'True' or 'False' response.\n\nFeedback: \"{feedback}\"",
-    "conversation_history_instruction": "You are a member of a crew collaborating to achieve a common goal. Your task is a specific action that contributes to this larger objective. For additional context, please review the conversation history between you and the user that led to the initiation of this crew. Use any relevant information or feedback from the conversation to inform your task execution and ensure your response aligns with both the immediate task and the crew's overall goals."
+    "human_feedback_classification": "Determine if the following feedback indicates that the user is satisfied or if further changes are needed. Respond with 'True' if further changes are needed, or 'False' if the user is satisfied. **Important** Do not include any additional commentary outside of your 'True' or 'False' response.\n\nFeedback: \"{feedback}\""
   },
   "errors": {
     "force_final_answer_error": "You can't keep going, this was the best you could do.\n {formatted_answer.text}",

src/crewai/types/crew_chat.py

@@ -1,44 +0,0 @@
-from typing import List, Optional
-
-from pydantic import BaseModel, Field
-
-
-class ChatInputField(BaseModel):
-    """
-    Represents a single required input for the crew, with a name and short description.
-    Example:
-        {
-            "name": "topic",
-            "description": "The topic to focus on for the conversation"
-        }
-    """
-
-    name: str = Field(..., description="The name of the input field")
-    description: str = Field(
-        ...,
-        description="A short description of the input field",
-    )
-
-
-class ChatInputs(BaseModel):
-    """
-    Holds a high-level crew_description plus a list of ChatInputFields.
-    Example:
-        {
-            "crew_name": "topic-based-qa",
-            "crew_description": "Use this crew for topic-based Q&A",
-            "inputs": [
-                {"name": "topic", "description": "The topic to focus on"},
-                {"name": "username", "description": "Name of the user"},
-            ]
-        }
-    """
-
-    crew_name: str = Field(..., description="The name of the crew")
-    crew_description: str = Field(
-        ...,
-        description="A description of the crew's purpose",
-    )
-    inputs: List[ChatInputField] = Field(
-        default_factory=list, description="A list of input fields for the crew"
-    )

src/crewai/utilities/crew_json_encoder.py

@@ -1,5 +1,3 @@
-"""JSON encoder for handling CrewAI specific types."""
-
 import json
 from datetime import date, datetime
 from decimal import Decimal
@@ -10,7 +8,6 @@ from pydantic import BaseModel
 
 
 class CrewJSONEncoder(json.JSONEncoder):
-    """Custom JSON encoder for CrewAI objects and special types."""
     def default(self, obj):
         if isinstance(obj, BaseModel):
             return self._handle_pydantic_model(obj)

src/crewai/utilities/crew_pydantic_output_parser.py

@@ -6,10 +6,9 @@ from pydantic import BaseModel, ValidationError
 
 from crewai.agents.parser import OutputParserException
 
-"""Parser for converting text outputs into Pydantic models."""
 
 class CrewPydanticOutputParser:
-    """Parses text outputs into specified Pydantic models."""
+    """Parses the text into pydantic models"""
 
     pydantic_object: Type[BaseModel]
 

src/crewai/utilities/evaluators/crew_evaluator_handler.py

@@ -180,12 +180,12 @@ class CrewEvaluator:
             self._test_result_span = self._telemetry.individual_test_result_span(
                 self.crew,
                 evaluation_result.pydantic.quality,
-                current_task.execution_duration,
+                current_task._execution_time,
                 self.openai_model_name,
             )
             self.tasks_scores[self.iteration].append(evaluation_result.pydantic.quality)
             self.run_execution_times[self.iteration].append(
-                current_task.execution_duration
+                current_task._execution_time
             )
         else:
             raise ValueError("Evaluation result is not in the expected format")

src/crewai/utilities/i18n.py

@@ -4,10 +4,8 @@ from typing import Dict, Optional, Union
 
 from pydantic import BaseModel, Field, PrivateAttr, model_validator
 
-"""Internationalization support for CrewAI prompts and messages."""
 
 class I18N(BaseModel):
-    """Handles loading and retrieving internationalized prompts."""
     _prompts: Dict[str, Dict[str, str]] = PrivateAttr()
     prompt_file: Optional[str] = Field(
         default=None,

src/crewai/utilities/internal_instructor.py

@@ -1,4 +1,3 @@
-import warnings
 from typing import Any, Optional, Type
 
 
@@ -26,10 +25,9 @@ class InternalInstructor:
         if self.agent and not self.llm:
             self.llm = self.agent.function_calling_llm or self.agent.llm
 
-        with warnings.catch_warnings():
-            warnings.simplefilter("ignore", UserWarning)
-            import instructor
-            from litellm import completion
+        # Lazy import
+        import instructor
+        from litellm import completion
 
         self._client = instructor.from_litellm(
             completion,

src/crewai/utilities/llm_utils.py

@@ -1,215 +0,0 @@
-import os
-from typing import Any, Dict, List, Optional, Union
-
-from packaging import version
-
-from crewai.cli.constants import DEFAULT_LLM_MODEL, ENV_VARS, LITELLM_PARAMS
-from crewai.cli.utils import read_toml
-from crewai.cli.version import get_crewai_version
-from crewai.llm import LLM
-
-
-def create_llm(
-    llm_value: Union[str, LLM, Any, None] = None,
-) -> Optional[LLM]:
-    """
-    Creates or returns an LLM instance based on the given llm_value.
-
-    Args:
-        llm_value (str | LLM | Any | None):
-            - str: The model name (e.g., "gpt-4").
-            - LLM: Already instantiated LLM, returned as-is.
-            - Any: Attempt to extract known attributes like model_name, temperature, etc.
-            - None: Use environment-based or fallback default model.
-
-    Returns:
-        An LLM instance if successful, or None if something fails.
-    """
-
-    # 1) If llm_value is already an LLM object, return it directly
-    if isinstance(llm_value, LLM):
-        return llm_value
-
-    # 2) If llm_value is a string (model name)
-    if isinstance(llm_value, str):
-        try:
-            created_llm = LLM(model=llm_value)
-            print(f"LLM created with model='{llm_value}'")
-            return created_llm
-        except Exception as e:
-            print(f"Failed to instantiate LLM with model='{llm_value}': {e}")
-            return None
-
-    # 3) If llm_value is None, parse environment variables or use default
-    if llm_value is None:
-        return _llm_via_environment_or_fallback()
-
-    # 4) Otherwise, attempt to extract relevant attributes from an unknown object
-    try:
-        # Extract attributes with explicit types
-        model = (
-            getattr(llm_value, "model_name", None)
-            or getattr(llm_value, "deployment_name", None)
-            or str(llm_value)
-        )
-        temperature: Optional[float] = getattr(llm_value, "temperature", None)
-        max_tokens: Optional[int] = getattr(llm_value, "max_tokens", None)
-        logprobs: Optional[int] = getattr(llm_value, "logprobs", None)
-        timeout: Optional[float] = getattr(llm_value, "timeout", None)
-        api_key: Optional[str] = getattr(llm_value, "api_key", None)
-        base_url: Optional[str] = getattr(llm_value, "base_url", None)
-
-        created_llm = LLM(
-            model=model,
-            temperature=temperature,
-            max_tokens=max_tokens,
-            logprobs=logprobs,
-            timeout=timeout,
-            api_key=api_key,
-            base_url=base_url,
-        )
-        print(
-            "LLM created with extracted parameters; "
-            f"model='{model}'"
-        )
-        return created_llm
-    except Exception as e:
-        print(f"Error instantiating LLM from unknown object type: {e}")
-        return None
-
-
-def create_chat_llm() -> Optional[LLM]:
-    """
-    Creates a Chat LLM with additional checks, such as verifying crewAI version
-    or reading from pyproject.toml. Then calls `create_llm(None, default_model)`.
-
-    Args:
-        default_model (str): Fallback model if not set in environment.
-
-    Returns:
-        An instance of LLM or None if instantiation fails.
-    """
-    print("[create_chat_llm] Checking environment and version info...")
-
-    crewai_version = get_crewai_version()
-    min_required_version = "0.87.0"  # Update to latest if needed
-
-    pyproject_data = read_toml()
-    if pyproject_data.get("tool", {}).get("poetry") and (
-        version.parse(crewai_version) < version.parse(min_required_version)
-    ):
-        print(
-            f"You are running an older version of crewAI ({crewai_version}) that uses poetry.\n"
-            "Please run `crewai update` to switch to uv-based builds."
-        )
-
-    # After checks, simply call create_llm with None (meaning "use env or fallback"):
-    return create_llm(None)
-
-
-def _llm_via_environment_or_fallback() -> Optional[LLM]:
-    """
-    Helper function: if llm_value is None, we load environment variables or fallback default model.
-    """
-    model_name = (
-        os.environ.get("OPENAI_MODEL_NAME")
-        or os.environ.get("MODEL")
-        or DEFAULT_LLM_MODEL
-    )
-
-    # Initialize parameters with correct types
-    model: str = model_name
-    temperature: Optional[float] = None
-    max_tokens: Optional[int] = None
-    max_completion_tokens: Optional[int] = None
-    logprobs: Optional[int] = None
-    timeout: Optional[float] = None
-    api_key: Optional[str] = None
-    base_url: Optional[str] = None
-    api_version: Optional[str] = None
-    presence_penalty: Optional[float] = None
-    frequency_penalty: Optional[float] = None
-    top_p: Optional[float] = None
-    n: Optional[int] = None
-    stop: Optional[Union[str, List[str]]] = None
-    logit_bias: Optional[Dict[int, float]] = None
-    response_format: Optional[Dict[str, Any]] = None
-    seed: Optional[int] = None
-    top_logprobs: Optional[int] = None
-    callbacks: List[Any] = []
-
-    # Optional base URL from env
-    api_base = os.environ.get("OPENAI_API_BASE") or os.environ.get("OPENAI_BASE_URL")
-    if api_base:
-        base_url = api_base
-
-    # Initialize llm_params dictionary
-    llm_params: Dict[str, Any] = {
-        "model": model,
-        "temperature": temperature,
-        "max_tokens": max_tokens,
-        "max_completion_tokens": max_completion_tokens,
-        "logprobs": logprobs,
-        "timeout": timeout,
-        "api_key": api_key,
-        "base_url": base_url,
-        "api_version": api_version,
-        "presence_penalty": presence_penalty,
-        "frequency_penalty": frequency_penalty,
-        "top_p": top_p,
-        "n": n,
-        "stop": stop,
-        "logit_bias": logit_bias,
-        "response_format": response_format,
-        "seed": seed,
-        "top_logprobs": top_logprobs,
-        "callbacks": callbacks,
-    }
-
-    UNACCEPTED_ATTRIBUTES = [
-        "AWS_ACCESS_KEY_ID",
-        "AWS_SECRET_ACCESS_KEY",
-        "AWS_REGION_NAME",
-    ]
-    set_provider = model_name.split("/")[0] if "/" in model_name else "openai"
-
-    if set_provider in ENV_VARS:
-        for env_var in ENV_VARS[set_provider]:
-            key_name = env_var.get("key_name")
-            if key_name and key_name not in UNACCEPTED_ATTRIBUTES:
-                env_value = os.environ.get(key_name)
-                if env_value:
-                    # Map environment variable names to recognized parameters
-                    param_key = _normalize_key_name(key_name.lower())
-                    llm_params[param_key] = env_value
-            elif isinstance(env_var, dict):
-                if env_var.get("default", False):
-                    for key, value in env_var.items():
-                        if key not in ["prompt", "key_name", "default"]:
-                            if key in os.environ:
-                                llm_params[key] = os.environ[key]
-            else:
-                print(f"Expected env_var to be a dictionary, but got {type(env_var)}")
-
-    # Remove None values
-    llm_params = {k: v for k, v in llm_params.items() if v is not None}
-
-    # Try creating the LLM
-    try:
-        new_llm = LLM(**llm_params)
-        print(f"LLM created with model='{model_name}'")
-        return new_llm
-    except Exception as e:
-        print(f"Error instantiating LLM from environment/fallback: {type(e).__name__}: {e}")
-        return None
-
-
-def _normalize_key_name(key_name: str) -> str:
-    """
-    Maps environment variable names to recognized litellm parameter keys,
-    using patterns from LITELLM_PARAMS.
-    """
-    for pattern in LITELLM_PARAMS:
-        if pattern in key_name:
-            return pattern
-    return key_name

src/crewai/utilities/paths.py

@@ -3,10 +3,8 @@ from pathlib import Path
 
 import appdirs
 
-"""Path management utilities for CrewAI storage and configuration."""
 
 def db_storage_path():
-    """Returns the path for database storage."""
     app_name = get_project_directory_name()
     app_author = "CrewAI"
 
@@ -16,7 +14,6 @@ def db_storage_path():
 
 
 def get_project_directory_name():
-    """Returns the current project directory name."""
     project_directory_name = os.environ.get("CREWAI_STORAGE_DIR")
 
     if project_directory_name:

src/crewai/utilities/planning_handler.py

@@ -1,5 +1,3 @@
-import json
-import logging
 from typing import Any, List, Optional
 
 from pydantic import BaseModel, Field
@@ -7,11 +5,8 @@ from pydantic import BaseModel, Field
 from crewai.agent import Agent
 from crewai.task import Task
 
-"""Handles planning and coordination of crew tasks."""
-logger = logging.getLogger(__name__)
 
 class PlanPerTask(BaseModel):
-    """Represents a plan for a specific task."""
     task: str = Field(..., description="The task for which the plan is created")
     plan: str = Field(
         ...,
@@ -20,7 +15,6 @@ class PlanPerTask(BaseModel):
 
 
 class PlannerTaskPydanticOutput(BaseModel):
-    """Output format for task planning results."""
     list_of_plans_per_task: List[PlanPerTask] = Field(
         ...,
         description="Step by step plan on how the agents can execute their tasks using the available tools with mastery",
@@ -28,7 +22,6 @@ class PlannerTaskPydanticOutput(BaseModel):
 
 
 class CrewPlanner:
-    """Plans and coordinates the execution of crew tasks."""
     def __init__(self, tasks: List[Task], planning_agent_llm: Optional[Any] = None):
         self.tasks = tasks
 
@@ -75,39 +68,19 @@ class CrewPlanner:
             output_pydantic=PlannerTaskPydanticOutput,
         )
 
-    def _get_agent_knowledge(self, task: Task) -> List[str]:
-        """
-        Safely retrieve knowledge source content from the task's agent.
-        
-        Args:
-            task: The task containing an agent with potential knowledge sources
-            
-        Returns:
-            List[str]: A list of knowledge source strings
-        """
-        try:
-            if task.agent and task.agent.knowledge_sources:
-                return [source.content for source in task.agent.knowledge_sources]
-        except AttributeError:
-            logger.warning("Error accessing agent knowledge sources")
-        return []
-
     def _create_tasks_summary(self) -> str:
         """Creates a summary of all tasks."""
         tasks_summary = []
         for idx, task in enumerate(self.tasks):
-            knowledge_list = self._get_agent_knowledge(task)
-            task_summary = f"""
+            tasks_summary.append(
+                f"""
                 Task Number {idx + 1} - {task.description}
                 "task_description": {task.description}
                 "task_expected_output": {task.expected_output}
                 "agent": {task.agent.role if task.agent else "None"}
                 "agent_goal": {task.agent.goal if task.agent else "None"}
                 "task_tools": {task.tools}
-                "agent_tools": %s%s""" % (
-                    f"[{', '.join(str(tool) for tool in task.agent.tools)}]" if task.agent and task.agent.tools else '"agent has no tools"',
-                    f',\n                "agent_knowledge": "[\\"{knowledge_list[0]}\\"]"' if knowledge_list and str(knowledge_list) != "None" else ""
-                )
-            
-            tasks_summary.append(task_summary)
+                "agent_tools": {task.agent.tools if task.agent else "None"}
+                """
+            )
         return " ".join(tasks_summary)

src/crewai/utilities/printer.py

@@ -1,11 +1,7 @@
-"""Utility for colored console output."""
-
 from typing import Optional
 
 
 class Printer:
-    """Handles colored console output formatting."""
-
     def print(self, content: str, color: Optional[str] = None):
         if color == "purple":
             self._print_purple(content)

src/crewai/utilities/rpm_controller.py

@@ -6,10 +6,8 @@ from pydantic import BaseModel, Field, PrivateAttr, model_validator
 
 from crewai.utilities.logger import Logger
 
-"""Controls request rate limiting for API calls."""
 
 class RPMController(BaseModel):
-    """Manages requests per minute limiting."""
     max_rpm: Optional[int] = Field(default=None)
     logger: Logger = Field(default_factory=lambda: Logger(verbose=False))
     _current_rpm: int = PrivateAttr(default=0)

src/crewai/utilities/task_output_storage_handler.py

@@ -8,10 +8,8 @@ from crewai.memory.storage.kickoff_task_outputs_storage import (
 )
 from crewai.task import Task
 
-"""Handles storage and retrieval of task execution outputs."""
 
 class ExecutionLog(BaseModel):
-    """Represents a log entry for task execution."""
     task_id: str
     expected_output: Optional[str] = None
     output: Dict[str, Any]
@@ -24,8 +22,6 @@ class ExecutionLog(BaseModel):
         return getattr(self, key)
 
 
-"""Manages storage and retrieval of task outputs."""
-
 class TaskOutputStorageHandler:
     def __init__(self) -> None:
         self.storage = KickoffTaskOutputsSQLiteStorage()

src/crewai/utilities/token_counter_callback.py

@@ -1,6 +1,3 @@
-import warnings
-from typing import Any, Dict, Optional
-
 from litellm.integrations.custom_logger import CustomLogger
 from litellm.types.utils import Usage
 
@@ -8,26 +5,18 @@ from crewai.agents.agent_builder.utilities.base_token_process import TokenProces
 
 
 class TokenCalcHandler(CustomLogger):
-    def __init__(self, token_cost_process: Optional[TokenProcess]):
+    def __init__(self, token_cost_process: TokenProcess):
         self.token_cost_process = token_cost_process
 
-    def log_success_event(
-        self,
-        kwargs: Dict[str, Any],
-        response_obj: Dict[str, Any],
-        start_time: float,
-        end_time: float,
-    ) -> None:
+    def log_success_event(self, kwargs, response_obj, start_time, end_time):
         if self.token_cost_process is None:
             return
 
-        with warnings.catch_warnings():
-            warnings.simplefilter("ignore", UserWarning)
-            usage: Usage = response_obj["usage"]
-            self.token_cost_process.sum_successful_requests(1)
-            self.token_cost_process.sum_prompt_tokens(usage.prompt_tokens)
-            self.token_cost_process.sum_completion_tokens(usage.completion_tokens)
-            if usage.prompt_tokens_details:
-                self.token_cost_process.sum_cached_prompt_tokens(
-                    usage.prompt_tokens_details.cached_tokens
-                )
+        usage: Usage = response_obj["usage"]
+        self.token_cost_process.sum_successful_requests(1)
+        self.token_cost_process.sum_prompt_tokens(usage.prompt_tokens)
+        self.token_cost_process.sum_completion_tokens(usage.completion_tokens)
+        if usage.prompt_tokens_details:
+            self.token_cost_process.sum_cached_prompt_tokens(
+                usage.prompt_tokens_details.cached_tokens
+            )

tests/agent_test.py

@@ -1445,43 +1445,44 @@ def test_llm_call_with_all_attributes():
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
-def test_agent_with_ollama_llama3():
+def test_agent_with_ollama_gemma():
     agent = Agent(
         role="test role",
         goal="test goal",
         backstory="test backstory",
-        llm=LLM(model="ollama/llama3.2:3b", base_url="http://localhost:11434"),
+        llm=LLM(
+            model="ollama/gemma2:latest",
+            base_url="http://localhost:8080",
+        ),
     )
 
     assert isinstance(agent.llm, LLM)
-    assert agent.llm.model == "ollama/llama3.2:3b"
-    assert agent.llm.base_url == "http://localhost:11434"
+    assert agent.llm.model == "ollama/gemma2:latest"
+    assert agent.llm.base_url == "http://localhost:8080"
 
-    task = "Respond in 20 words. Which model are you?"
+    task = "Respond in 20 words. Who are you?"
     response = agent.llm.call([{"role": "user", "content": task}])
 
     assert response
     assert len(response.split()) <= 25  # Allow a little flexibility in word count
-    assert "Llama3" in response or "AI" in response or "language model" in response
+    assert "Gemma" in response or "AI" in response or "language model" in response
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
-def test_llm_call_with_ollama_llama3():
+def test_llm_call_with_ollama_gemma():
     llm = LLM(
-        model="ollama/llama3.2:3b",
-        base_url="http://localhost:11434",
+        model="ollama/gemma2:latest",
+        base_url="http://localhost:8080",
         temperature=0.7,
         max_tokens=30,
     )
-    messages = [
-        {"role": "user", "content": "Respond in 20 words. Which model are you?"}
-    ]
+    messages = [{"role": "user", "content": "Respond in 20 words. Who are you?"}]
 
     response = llm.call(messages)
 
     assert response
     assert len(response.split()) <= 25  # Allow a little flexibility in word count
-    assert "Llama3" in response or "AI" in response or "language model" in response
+    assert "Gemma" in response or "AI" in response or "language model" in response
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -1577,7 +1578,7 @@ def test_agent_execute_task_with_ollama():
         role="test role",
         goal="test goal",
         backstory="test backstory",
-        llm=LLM(model="ollama/llama3.2:3b", base_url="http://localhost:11434"),
+        llm=LLM(model="ollama/gemma2:latest", base_url="http://localhost:8080"),
     )
 
     task = Task(

tests/cassettes/test_agent_execute_task_with_ollama.yaml

@@ -1,6 +1,42 @@
 interactions:
 - request:
-    body: '{"model": "llama3.2:3b", "prompt": "### System:\nYou are test role. test
+    body: !!binary |
+      CrcCCiQKIgoMc2VydmljZS5uYW1lEhIKEGNyZXdBSS10ZWxlbWV0cnkSjgIKEgoQY3Jld2FpLnRl
+      bGVtZXRyeRJoChA/Q8UW5bidCRtKvri5fOaNEgh5qLzvLvZJkioQVG9vbCBVc2FnZSBFcnJvcjAB
+      OYjFVQr1TPgXQXCXhwr1TPgXShoKDmNyZXdhaV92ZXJzaW9uEggKBjAuNjEuMHoCGAGFAQABAAAS
+      jQEKEChQTWQ07t26ELkZmP5RresSCHEivRGBpsP7KgpUb29sIFVzYWdlMAE5sKkbC/VM+BdB8MIc
+      C/VM+BdKGgoOY3Jld2FpX3ZlcnNpb24SCAoGMC42MS4wShkKCXRvb2xfbmFtZRIMCgpkdW1teV90
+      b29sSg4KCGF0dGVtcHRzEgIYAXoCGAGFAQABAAA=
+    headers:
+      Accept:
+      - '*/*'
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '314'
+      Content-Type:
+      - application/x-protobuf
+      User-Agent:
+      - OTel-OTLP-Exporter-Python/1.27.0
+    method: POST
+    uri: https://telemetry.crewai.com:4319/v1/traces
+  response:
+    body:
+      string: "\n\0"
+    headers:
+      Content-Length:
+      - '2'
+      Content-Type:
+      - application/x-protobuf
+      Date:
+      - Tue, 24 Sep 2024 21:57:54 GMT
+    status:
+      code: 200
+      message: OK
+- request:
+    body: '{"model": "gemma2:latest", "prompt": "### System:\nYou are test role. test
       backstory\nYour personal goal is: test goal\nTo give my best complete final
       answer to the task use the exact following format:\n\nThought: I now can give
       a great answer\nFinal Answer: Your final answer must be the great and the most
@@ -10,7 +46,7 @@ interactions:
       explanation of AI\nyou MUST return the actual complete content as the final
       answer, not a summary.\n\nBegin! This is VERY important to you, use the tools
       available and give your best Final Answer, your job depends on it!\n\nThought:\n\n",
-      "options": {"stop": ["\nObservation:"]}, "stream": false}'
+      "options": {}, "stream": false}'
     headers:
       Accept:
       - '*/*'
@@ -19,26 +55,26 @@ interactions:
       Connection:
       - keep-alive
       Content-Length:
-      - '839'
+      - '815'
       Content-Type:
       - application/json
       User-Agent:
-      - python-requests/2.32.3
+      - python-requests/2.31.0
     method: POST
-    uri: http://localhost:11434/api/generate
+    uri: http://localhost:8080/api/generate
   response:
     body:
-      string: '{"model":"llama3.2:3b","created_at":"2025-01-02T20:05:52.24992Z","response":"Final
-        Answer: Artificial Intelligence (AI) refers to the development of computer
-        systems capable of performing tasks that typically require human intelligence,
-        such as learning, problem-solving, decision-making, and perception.","done":true,"done_reason":"stop","context":[128006,9125,128007,271,38766,1303,33025,2696,25,6790,220,2366,18,271,128009,128006,882,128007,271,14711,744,512,2675,527,1296,3560,13,1296,93371,198,7927,4443,5915,374,25,1296,5915,198,1271,3041,856,1888,4686,1620,4320,311,279,3465,1005,279,4839,2768,3645,1473,85269,25,358,1457,649,3041,264,2294,4320,198,19918,22559,25,4718,1620,4320,2011,387,279,2294,323,279,1455,4686,439,3284,11,433,2011,387,15632,7633,382,40,28832,1005,1521,20447,11,856,2683,14117,389,433,2268,14711,2724,1473,5520,5546,25,83017,1148,15592,374,304,832,11914,271,2028,374,279,1755,13186,369,701,1620,4320,25,362,832,1355,18886,16540,315,15592,198,9514,28832,471,279,5150,4686,2262,439,279,1620,4320,11,539,264,12399,382,11382,0,1115,374,48174,3062,311,499,11,1005,279,7526,2561,323,3041,701,1888,13321,22559,11,701,2683,14117,389,433,2268,85269,1473,128009,128006,78191,128007,271,19918,22559,25,59294,22107,320,15836,8,19813,311,279,4500,315,6500,6067,13171,315,16785,9256,430,11383,1397,3823,11478,11,1778,439,6975,11,3575,99246,11,5597,28846,11,323,21063,13],"total_duration":1461909875,"load_duration":39886208,"prompt_eval_count":181,"prompt_eval_duration":701000000,"eval_count":39,"eval_duration":719000000}'
+      string: '{"model":"gemma2:latest","created_at":"2024-09-24T21:57:55.835715Z","response":"Thought:
+        I can explain AI in one sentence. \n\nFinal Answer: Artificial intelligence
+        (AI) is the ability of computer systems to perform tasks that typically require
+        human intelligence, such as learning, problem-solving, and decision-making.  \n","done":true,"done_reason":"stop","context":[106,1645,108,6176,1479,235292,108,2045,708,2121,4731,235265,2121,135147,108,6922,3749,6789,603,235292,2121,6789,108,1469,2734,970,1963,3407,2048,3448,577,573,6911,1281,573,5463,2412,5920,235292,109,65366,235292,590,1490,798,2734,476,1775,3448,108,11263,10358,235292,3883,2048,3448,2004,614,573,1775,578,573,1546,3407,685,3077,235269,665,2004,614,17526,6547,235265,109,235285,44472,1281,1450,32808,235269,970,3356,12014,611,665,235341,109,6176,4926,235292,109,6846,12297,235292,36576,1212,16481,603,575,974,13060,109,1596,603,573,5246,12830,604,861,2048,3448,235292,586,974,235290,47366,15844,576,16481,108,4747,44472,2203,573,5579,3407,3381,685,573,2048,3448,235269,780,476,13367,235265,109,12694,235341,1417,603,50471,2845,577,692,235269,1281,573,8112,2506,578,2734,861,1963,14124,10358,235269,861,3356,12014,611,665,235341,109,65366,235292,109,107,108,106,2516,108,65366,235292,590,798,10200,16481,575,974,13060,235265,235248,109,11263,10358,235292,42456,17273,591,11716,235275,603,573,7374,576,6875,5188,577,3114,13333,674,15976,2817,3515,17273,235269,1582,685,6044,235269,3210,235290,60495,235269,578,4530,235290,14577,235265,139,108],"total_duration":3370959792,"load_duration":20611750,"prompt_eval_count":173,"prompt_eval_duration":688036000,"eval_count":51,"eval_duration":2660291000}'
     headers:
       Content-Length:
-      - '1537'
+      - '1662'
       Content-Type:
       - application/json; charset=utf-8
       Date:
-      - Thu, 02 Jan 2025 20:05:52 GMT
+      - Tue, 24 Sep 2024 21:57:55 GMT
     status:
       code: 200
       message: OK

tests/cassettes/test_agent_with_ollama_gemma.yaml

@@ -0,0 +1,397 @@
+interactions:
+- request:
+    body: !!binary |
+      CumTAQokCiIKDHNlcnZpY2UubmFtZRISChBjcmV3QUktdGVsZW1ldHJ5Er+TAQoSChBjcmV3YWku
+      dGVsZW1ldHJ5EqoHChDvqD2QZooz9BkEwtbWjp4OEgjxh72KACHvZSoMQ3JldyBDcmVhdGVkMAE5
+      qMhNnvBM+BdBcO9PnvBM+BdKGgoOY3Jld2FpX3ZlcnNpb24SCAoGMC42MS4wShoKDnB5dGhvbl92
+      ZXJzaW9uEggKBjMuMTEuN0ouCghjcmV3X2tleRIiCiBkNTUxMTNiZTRhYTQxYmE2NDNkMzI2MDQy
+      YjJmMDNmMUoxCgdjcmV3X2lkEiYKJGY4YTA1OTA1LTk0OGEtNDQ0YS04NmJmLTJiNTNiNDkyYjgy
+      MkocCgxjcmV3X3Byb2Nlc3MSDAoKc2VxdWVudGlhbEoRCgtjcmV3X21lbW9yeRICEABKGgoUY3Jl
+      d19udW1iZXJfb2ZfdGFza3MSAhgBShsKFWNyZXdfbnVtYmVyX29mX2FnZW50cxICGAFKxwIKC2Ny
+      ZXdfYWdlbnRzErcCCrQCW3sia2V5IjogImUxNDhlNTMyMDI5MzQ5OWY4Y2ViZWE4MjZlNzI1ODJi
+      IiwgImlkIjogIjg1MGJjNWUwLTk4NTctNDhkOC1iNWZlLTJmZjk2OWExYTU3YiIsICJyb2xlIjog
+      InRlc3Qgcm9sZSIsICJ2ZXJib3NlPyI6IHRydWUsICJtYXhfaXRlciI6IDQsICJtYXhfcnBtIjog
+      MTAsICJmdW5jdGlvbl9jYWxsaW5nX2xsbSI6ICIiLCAibGxtIjogImdwdC00byIsICJkZWxlZ2F0
+      aW9uX2VuYWJsZWQ/IjogZmFsc2UsICJhbGxvd19jb2RlX2V4ZWN1dGlvbj8iOiBmYWxzZSwgIm1h
+      eF9yZXRyeV9saW1pdCI6IDIsICJ0b29sc19uYW1lcyI6IFtdfV1KkAIKCmNyZXdfdGFza3MSgQIK
+      /gFbeyJrZXkiOiAiNGEzMWI4NTEzM2EzYTI5NGM2ODUzZGE3NTdkNGJhZTciLCAiaWQiOiAiOTc1
+      ZDgwMjItMWJkMS00NjBlLTg2NmEtYjJmZGNiYjA4ZDliIiwgImFzeW5jX2V4ZWN1dGlvbj8iOiBm
+      YWxzZSwgImh1bWFuX2lucHV0PyI6IGZhbHNlLCAiYWdlbnRfcm9sZSI6ICJ0ZXN0IHJvbGUiLCAi
+      YWdlbnRfa2V5IjogImUxNDhlNTMyMDI5MzQ5OWY4Y2ViZWE4MjZlNzI1ODJiIiwgInRvb2xzX25h
+      bWVzIjogWyJnZXRfZmluYWxfYW5zd2VyIl19XXoCGAGFAQABAAASjgIKEP9UYSAOFQbZquSppN1j
+      IeUSCAgZmXUoJKFmKgxUYXNrIENyZWF0ZWQwATloPV+e8Ez4F0GYsl+e8Ez4F0ouCghjcmV3X2tl
+      eRIiCiBkNTUxMTNiZTRhYTQxYmE2NDNkMzI2MDQyYjJmMDNmMUoxCgdjcmV3X2lkEiYKJGY4YTA1
+      OTA1LTk0OGEtNDQ0YS04NmJmLTJiNTNiNDkyYjgyMkouCgh0YXNrX2tleRIiCiA0YTMxYjg1MTMz
+      YTNhMjk0YzY4NTNkYTc1N2Q0YmFlN0oxCgd0YXNrX2lkEiYKJDk3NWQ4MDIyLTFiZDEtNDYwZS04
+      NjZhLWIyZmRjYmIwOGQ5YnoCGAGFAQABAAASkwEKEEfiywgqgiUXE3KoUbrnHDQSCGmv+iM7Wc1Z
+      KgpUb29sIFVzYWdlMAE5kOybnvBM+BdBIM+cnvBM+BdKGgoOY3Jld2FpX3ZlcnNpb24SCAoGMC42
+      MS4wSh8KCXRvb2xfbmFtZRISChBnZXRfZmluYWxfYW5zd2VySg4KCGF0dGVtcHRzEgIYAXoCGAGF
+      AQABAAASkwEKEH7AHXpfmvwIkA45HB8YyY0SCAFRC+uJpsEZKgpUb29sIFVzYWdlMAE56PLdnvBM
+      +BdBYFbfnvBM+BdKGgoOY3Jld2FpX3ZlcnNpb24SCAoGMC42MS4wSh8KCXRvb2xfbmFtZRISChBn
+      ZXRfZmluYWxfYW5zd2VySg4KCGF0dGVtcHRzEgIYAXoCGAGFAQABAAASkwEKEIDKKEbYU4lcJF+a
+      WsAVZwESCI+/La7oL86MKgpUb29sIFVzYWdlMAE5yIkgn/BM+BdBWGwhn/BM+BdKGgoOY3Jld2Fp
+      X3ZlcnNpb24SCAoGMC42MS4wSh8KCXRvb2xfbmFtZRISChBnZXRfZmluYWxfYW5zd2VySg4KCGF0
+      dGVtcHRzEgIYAXoCGAGFAQABAAASnAEKEMTZ2IhpLz6J2hJhHBQ8/M4SCEuWz+vjzYifKhNUb29s
+      IFJlcGVhdGVkIFVzYWdlMAE5mAVhn/BM+BdBKOhhn/BM+BdKGgoOY3Jld2FpX3ZlcnNpb24SCAoG
+      MC42MS4wSh8KCXRvb2xfbmFtZRISChBnZXRfZmluYWxfYW5zd2VySg4KCGF0dGVtcHRzEgIYAXoC
+      GAGFAQABAAASkAIKED8C+t95p855kLcXs5Nnt/sSCM4XAhL6u8O8Kg5UYXNrIEV4ZWN1dGlvbjAB
+      OdD8X57wTPgXQUgno5/wTPgXSi4KCGNyZXdfa2V5EiIKIGQ1NTExM2JlNGFhNDFiYTY0M2QzMjYw
+      NDJiMmYwM2YxSjEKB2NyZXdfaWQSJgokZjhhMDU5MDUtOTQ4YS00NDRhLTg2YmYtMmI1M2I0OTJi
+      ODIySi4KCHRhc2tfa2V5EiIKIDRhMzFiODUxMzNhM2EyOTRjNjg1M2RhNzU3ZDRiYWU3SjEKB3Rh
+      c2tfaWQSJgokOTc1ZDgwMjItMWJkMS00NjBlLTg2NmEtYjJmZGNiYjA4ZDliegIYAYUBAAEAABLO
+      CwoQFlnZCfbZ3Dj0L9TAE5LrLBIIoFr7BZErFNgqDENyZXcgQ3JlYXRlZDABOVhDDaDwTPgXQSg/
+      D6DwTPgXShoKDmNyZXdhaV92ZXJzaW9uEggKBjAuNjEuMEoaCg5weXRob25fdmVyc2lvbhIICgYz
+      LjExLjdKLgoIY3Jld19rZXkSIgogOTRjMzBkNmMzYjJhYzhmYjk0YjJkY2ZjNTcyZDBmNTlKMQoH
+      Y3Jld19pZBImCiQyMzM2MzRjNi1lNmQ2LTQ5ZTYtODhhZS1lYWUxYTM5YjBlMGZKHAoMY3Jld19w
+      cm9jZXNzEgwKCnNlcXVlbnRpYWxKEQoLY3Jld19tZW1vcnkSAhAAShoKFGNyZXdfbnVtYmVyX29m
+      X3Rhc2tzEgIYAkobChVjcmV3X251bWJlcl9vZl9hZ2VudHMSAhgCSv4ECgtjcmV3X2FnZW50cxLu
+      BArrBFt7ImtleSI6ICJlMTQ4ZTUzMjAyOTM0OTlmOGNlYmVhODI2ZTcyNTgyYiIsICJpZCI6ICI0
+      MjAzZjIyYi0wNWM3LTRiNjUtODBjMS1kM2Y0YmFlNzZhNDYiLCAicm9sZSI6ICJ0ZXN0IHJvbGUi
+      LCAidmVyYm9zZT8iOiB0cnVlLCAibWF4X2l0ZXIiOiAyLCAibWF4X3JwbSI6IDEwLCAiZnVuY3Rp
+      b25fY2FsbGluZ19sbG0iOiAiIiwgImxsbSI6ICJncHQtNG8iLCAiZGVsZWdhdGlvbl9lbmFibGVk
+      PyI6IGZhbHNlLCAiYWxsb3dfY29kZV9leGVjdXRpb24/IjogZmFsc2UsICJtYXhfcmV0cnlfbGlt
+      aXQiOiAyLCAidG9vbHNfbmFtZXMiOiBbXX0sIHsia2V5IjogImU3ZThlZWE4ODZiY2I4ZjEwNDVh
+      YmVlY2YxNDI1ZGI3IiwgImlkIjogImZjOTZjOTQ1LTY4ZDUtNDIxMy05NmNkLTNmYTAwNmUyZTYz
+      MCIsICJyb2xlIjogInRlc3Qgcm9sZTIiLCAidmVyYm9zZT8iOiB0cnVlLCAibWF4X2l0ZXIiOiAx
+      LCAibWF4X3JwbSI6IG51bGwsICJmdW5jdGlvbl9jYWxsaW5nX2xsbSI6ICIiLCAibGxtIjogImdw
+      dC00byIsICJkZWxlZ2F0aW9uX2VuYWJsZWQ/IjogZmFsc2UsICJhbGxvd19jb2RlX2V4ZWN1dGlv
+      bj8iOiBmYWxzZSwgIm1heF9yZXRyeV9saW1pdCI6IDIsICJ0b29sc19uYW1lcyI6IFtdfV1K/QMK
+      CmNyZXdfdGFza3MS7gMK6wNbeyJrZXkiOiAiMzIyZGRhZTNiYzgwYzFkNDViODVmYTc3NTZkYjg2
+      NjUiLCAiaWQiOiAiOTVjYTg4NDItNmExMi00MGQ5LWIwZDItNGI0MzYxYmJlNTZkIiwgImFzeW5j
+      X2V4ZWN1dGlvbj8iOiBmYWxzZSwgImh1bWFuX2lucHV0PyI6IGZhbHNlLCAiYWdlbnRfcm9sZSI6
+      ICJ0ZXN0IHJvbGUiLCAiYWdlbnRfa2V5IjogImUxNDhlNTMyMDI5MzQ5OWY4Y2ViZWE4MjZlNzI1
+      ODJiIiwgInRvb2xzX25hbWVzIjogW119LCB7ImtleSI6ICI1ZTljYTdkNjRiNDIwNWJiN2M0N2Uw
+      YjNmY2I1ZDIxZiIsICJpZCI6ICI5NzI5MTg2Yy1kN2JlLTRkYjQtYTk0ZS02OWU5OTk2NTI3MDAi
+      LCAiYXN5bmNfZXhlY3V0aW9uPyI6IGZhbHNlLCAiaHVtYW5faW5wdXQ/IjogZmFsc2UsICJhZ2Vu
+      dF9yb2xlIjogInRlc3Qgcm9sZTIiLCAiYWdlbnRfa2V5IjogImU3ZThlZWE4ODZiY2I4ZjEwNDVh
+      YmVlY2YxNDI1ZGI3IiwgInRvb2xzX25hbWVzIjogWyJnZXRfZmluYWxfYW5zd2VyIl19XXoCGAGF
+      AQABAAASjgIKEC/YM2OukRrSg+ZAev4VhGESCOQ5RvzSS5IEKgxUYXNrIENyZWF0ZWQwATmQJx6g
+      8Ez4F0EgjR6g8Ez4F0ouCghjcmV3X2tleRIiCiA5NGMzMGQ2YzNiMmFjOGZiOTRiMmRjZmM1NzJk
+      MGY1OUoxCgdjcmV3X2lkEiYKJDIzMzYzNGM2LWU2ZDYtNDllNi04OGFlLWVhZTFhMzliMGUwZkou
+      Cgh0YXNrX2tleRIiCiAzMjJkZGFlM2JjODBjMWQ0NWI4NWZhNzc1NmRiODY2NUoxCgd0YXNrX2lk
+      EiYKJDk1Y2E4ODQyLTZhMTItNDBkOS1iMGQyLTRiNDM2MWJiZTU2ZHoCGAGFAQABAAASkAIKEHqZ
+      L8s3clXQyVTemNcTCcQSCA0tzK95agRQKg5UYXNrIEV4ZWN1dGlvbjABOQC8HqDwTPgXQdgNSqDw
+      TPgXSi4KCGNyZXdfa2V5EiIKIDk0YzMwZDZjM2IyYWM4ZmI5NGIyZGNmYzU3MmQwZjU5SjEKB2Ny
+      ZXdfaWQSJgokMjMzNjM0YzYtZTZkNi00OWU2LTg4YWUtZWFlMWEzOWIwZTBmSi4KCHRhc2tfa2V5
+      EiIKIDMyMmRkYWUzYmM4MGMxZDQ1Yjg1ZmE3NzU2ZGI4NjY1SjEKB3Rhc2tfaWQSJgokOTVjYTg4
+      NDItNmExMi00MGQ5LWIwZDItNGI0MzYxYmJlNTZkegIYAYUBAAEAABKOAgoQjhKzodMUmQ8NWtdy
+      Uj99whIIBsGtAymZibwqDFRhc2sgQ3JlYXRlZDABOXjVVaDwTPgXQXhSVqDwTPgXSi4KCGNyZXdf
+      a2V5EiIKIDk0YzMwZDZjM2IyYWM4ZmI5NGIyZGNmYzU3MmQwZjU5SjEKB2NyZXdfaWQSJgokMjMz
+      NjM0YzYtZTZkNi00OWU2LTg4YWUtZWFlMWEzOWIwZTBmSi4KCHRhc2tfa2V5EiIKIDVlOWNhN2Q2
+      NGI0MjA1YmI3YzQ3ZTBiM2ZjYjVkMjFmSjEKB3Rhc2tfaWQSJgokOTcyOTE4NmMtZDdiZS00ZGI0
+      LWE5NGUtNjllOTk5NjUyNzAwegIYAYUBAAEAABKTAQoQx5IUsjAFMGNUaz5MHy20OBIIzl2tr25P
+      LL8qClRvb2wgVXNhZ2UwATkgt5Sg8Ez4F0GwFpag8Ez4F0oaCg5jcmV3YWlfdmVyc2lvbhIICgYw
+      LjYxLjBKHwoJdG9vbF9uYW1lEhIKEGdldF9maW5hbF9hbnN3ZXJKDgoIYXR0ZW1wdHMSAhgBegIY
+      AYUBAAEAABKQAgoQEkfcfCrzTYIM6GQXhknlexIIa/oxeT78OL8qDlRhc2sgRXhlY3V0aW9uMAE5
+      WIFWoPBM+BdBuL/GoPBM+BdKLgoIY3Jld19rZXkSIgogOTRjMzBkNmMzYjJhYzhmYjk0YjJkY2Zj
+      NTcyZDBmNTlKMQoHY3Jld19pZBImCiQyMzM2MzRjNi1lNmQ2LTQ5ZTYtODhhZS1lYWUxYTM5YjBl
+      MGZKLgoIdGFza19rZXkSIgogNWU5Y2E3ZDY0YjQyMDViYjdjNDdlMGIzZmNiNWQyMWZKMQoHdGFz
+      a19pZBImCiQ5NzI5MTg2Yy1kN2JlLTRkYjQtYTk0ZS02OWU5OTk2NTI3MDB6AhgBhQEAAQAAEqwH
+      ChDrKBdEe+Z5276g9fgg6VzjEgiJfnDwsv1SrCoMQ3JldyBDcmVhdGVkMAE5MLQYofBM+BdBQFIa
+      ofBM+BdKGgoOY3Jld2FpX3ZlcnNpb24SCAoGMC42MS4wShoKDnB5dGhvbl92ZXJzaW9uEggKBjMu
+      MTEuN0ouCghjcmV3X2tleRIiCiA3M2FhYzI4NWU2NzQ2NjY3Zjc1MTQ3NjcwMDAzNDExMEoxCgdj
+      cmV3X2lkEiYKJDg0NDY0YjhlLTRiZjctNDRiYy05MmUxLWE4ZDE1NGZlNWZkN0ocCgxjcmV3X3By
+      b2Nlc3MSDAoKc2VxdWVudGlhbEoRCgtjcmV3X21lbW9yeRICEABKGgoUY3Jld19udW1iZXJfb2Zf
+      dGFza3MSAhgBShsKFWNyZXdfbnVtYmVyX29mX2FnZW50cxICGAFKyQIKC2NyZXdfYWdlbnRzErkC
+      CrYCW3sia2V5IjogImUxNDhlNTMyMDI5MzQ5OWY4Y2ViZWE4MjZlNzI1ODJiIiwgImlkIjogIjk4
+      YmIwNGYxLTBhZGMtNGZiNC04YzM2LWM3M2Q1MzQ1ZGRhZCIsICJyb2xlIjogInRlc3Qgcm9sZSIs
+      ICJ2ZXJib3NlPyI6IHRydWUsICJtYXhfaXRlciI6IDEsICJtYXhfcnBtIjogbnVsbCwgImZ1bmN0
+      aW9uX2NhbGxpbmdfbGxtIjogIiIsICJsbG0iOiAiZ3B0LTRvIiwgImRlbGVnYXRpb25fZW5hYmxl
+      ZD8iOiBmYWxzZSwgImFsbG93X2NvZGVfZXhlY3V0aW9uPyI6IGZhbHNlLCAibWF4X3JldHJ5X2xp
+      bWl0IjogMiwgInRvb2xzX25hbWVzIjogW119XUqQAgoKY3Jld190YXNrcxKBAgr+AVt7ImtleSI6
+      ICJmN2E5ZjdiYjFhZWU0YjZlZjJjNTI2ZDBhOGMyZjJhYyIsICJpZCI6ICIxZjRhYzJhYS03YmQ4
+      LTQ1NWQtODgyMC1jMzZmMjJjMDY4MzciLCAiYXN5bmNfZXhlY3V0aW9uPyI6IGZhbHNlLCAiaHVt
+      YW5faW5wdXQ/IjogZmFsc2UsICJhZ2VudF9yb2xlIjogInRlc3Qgcm9sZSIsICJhZ2VudF9rZXki
+      OiAiZTE0OGU1MzIwMjkzNDk5ZjhjZWJlYTgyNmU3MjU4MmIiLCAidG9vbHNfbmFtZXMiOiBbImdl
+      dF9maW5hbF9hbnN3ZXIiXX1degIYAYUBAAEAABKOAgoQ0/vrakH7zD0uSvmVBUV8lxIIYe4YKcYG
+      hNgqDFRhc2sgQ3JlYXRlZDABOdBXKqHwTPgXQcCtKqHwTPgXSi4KCGNyZXdfa2V5EiIKIDczYWFj
+      Mjg1ZTY3NDY2NjdmNzUxNDc2NzAwMDM0MTEwSjEKB2NyZXdfaWQSJgokODQ0NjRiOGUtNGJmNy00
+      NGJjLTkyZTEtYThkMTU0ZmU1ZmQ3Si4KCHRhc2tfa2V5EiIKIGY3YTlmN2JiMWFlZTRiNmVmMmM1
+      MjZkMGE4YzJmMmFjSjEKB3Rhc2tfaWQSJgokMWY0YWMyYWEtN2JkOC00NTVkLTg4MjAtYzM2ZjIy
+      YzA2ODM3egIYAYUBAAEAABKkAQoQ5GDzHNlSdlcVDdxsI3abfRIIhYu8fZS3iA4qClRvb2wgVXNh
+      Z2UwATnIi2eh8Ez4F0FYbmih8Ez4F0oaCg5jcmV3YWlfdmVyc2lvbhIICgYwLjYxLjBKHwoJdG9v
+      bF9uYW1lEhIKEGdldF9maW5hbF9hbnN3ZXJKDgoIYXR0ZW1wdHMSAhgBSg8KA2xsbRIICgZncHQt
+      NG96AhgBhQEAAQAAEpACChAy85Jfr/EEIe1THU8koXoYEgjlkNn7xfysjioOVGFzayBFeGVjdXRp
+      b24wATm42Cqh8Ez4F0GgxZah8Ez4F0ouCghjcmV3X2tleRIiCiA3M2FhYzI4NWU2NzQ2NjY3Zjc1
+      MTQ3NjcwMDAzNDExMEoxCgdjcmV3X2lkEiYKJDg0NDY0YjhlLTRiZjctNDRiYy05MmUxLWE4ZDE1
+      NGZlNWZkN0ouCgh0YXNrX2tleRIiCiBmN2E5ZjdiYjFhZWU0YjZlZjJjNTI2ZDBhOGMyZjJhY0ox
+      Cgd0YXNrX2lkEiYKJDFmNGFjMmFhLTdiZDgtNDU1ZC04ODIwLWMzNmYyMmMwNjgzN3oCGAGFAQAB
+      AAASrAcKEG0ZVq5Ww+/A0wOY3HmKgq4SCMe0ooxqjqBlKgxDcmV3IENyZWF0ZWQwATlwmISi8Ez4
+      F0HYUYai8Ez4F0oaCg5jcmV3YWlfdmVyc2lvbhIICgYwLjYxLjBKGgoOcHl0aG9uX3ZlcnNpb24S
+      CAoGMy4xMS43Si4KCGNyZXdfa2V5EiIKIGQ1NTExM2JlNGFhNDFiYTY0M2QzMjYwNDJiMmYwM2Yx
+      SjEKB2NyZXdfaWQSJgokNzkyMWVlYmItMWI4NS00MzNjLWIxMDAtZDU4MmMyOTg5MzBkShwKDGNy
+      ZXdfcHJvY2VzcxIMCgpzZXF1ZW50aWFsShEKC2NyZXdfbWVtb3J5EgIQAEoaChRjcmV3X251bWJl
+      cl9vZl90YXNrcxICGAFKGwoVY3Jld19udW1iZXJfb2ZfYWdlbnRzEgIYAUrJAgoLY3Jld19hZ2Vu
+      dHMSuQIKtgJbeyJrZXkiOiAiZTE0OGU1MzIwMjkzNDk5ZjhjZWJlYTgyNmU3MjU4MmIiLCAiaWQi
+      OiAiZmRiZDI1MWYtYzUwOC00YmFhLTkwNjctN2U5YzQ2ZGZiZTJhIiwgInJvbGUiOiAidGVzdCBy
+      b2xlIiwgInZlcmJvc2U/IjogdHJ1ZSwgIm1heF9pdGVyIjogNiwgIm1heF9ycG0iOiBudWxsLCAi
+      ZnVuY3Rpb25fY2FsbGluZ19sbG0iOiAiIiwgImxsbSI6ICJncHQtNG8iLCAiZGVsZWdhdGlvbl9l
+      bmFibGVkPyI6IGZhbHNlLCAiYWxsb3dfY29kZV9leGVjdXRpb24/IjogZmFsc2UsICJtYXhfcmV0
+      cnlfbGltaXQiOiAyLCAidG9vbHNfbmFtZXMiOiBbXX1dSpACCgpjcmV3X3Rhc2tzEoECCv4BW3si
+      a2V5IjogIjRhMzFiODUxMzNhM2EyOTRjNjg1M2RhNzU3ZDRiYWU3IiwgImlkIjogIjA2YWFmM2Y1
+      LTE5ODctNDAxYS05Yzk0LWY3ZjM1YmQzMDg3OSIsICJhc3luY19leGVjdXRpb24/IjogZmFsc2Us
+      ICJodW1hbl9pbnB1dD8iOiBmYWxzZSwgImFnZW50X3JvbGUiOiAidGVzdCByb2xlIiwgImFnZW50
+      X2tleSI6ICJlMTQ4ZTUzMjAyOTM0OTlmOGNlYmVhODI2ZTcyNTgyYiIsICJ0b29sc19uYW1lcyI6
+      IFsiZ2V0X2ZpbmFsX2Fuc3dlciJdfV16AhgBhQEAAQAAEo4CChDT+zPZHwfacDilkzaZJ9uGEgip
+      Kr5r62JB+ioMVGFzayBDcmVhdGVkMAE56KeTovBM+BdB8PmTovBM+BdKLgoIY3Jld19rZXkSIgog
+      ZDU1MTEzYmU0YWE0MWJhNjQzZDMyNjA0MmIyZjAzZjFKMQoHY3Jld19pZBImCiQ3OTIxZWViYi0x
+      Yjg1LTQzM2MtYjEwMC1kNTgyYzI5ODkzMGRKLgoIdGFza19rZXkSIgogNGEzMWI4NTEzM2EzYTI5
+      NGM2ODUzZGE3NTdkNGJhZTdKMQoHdGFza19pZBImCiQwNmFhZjNmNS0xOTg3LTQwMWEtOWM5NC1m
+      N2YzNWJkMzA4Nzl6AhgBhQEAAQAAEpMBChCl85ZcL2Fa0N5QTl6EsIfnEghyDo3bxT+AkyoKVG9v
+      bCBVc2FnZTABOVBA2aLwTPgXQYAy2qLwTPgXShoKDmNyZXdhaV92ZXJzaW9uEggKBjAuNjEuMEof
+      Cgl0b29sX25hbWUSEgoQZ2V0X2ZpbmFsX2Fuc3dlckoOCghhdHRlbXB0cxICGAF6AhgBhQEAAQAA
+      EpwBChB22uwKhaur9zmeoeEMaRKzEgjrtSEzMbRdIioTVG9vbCBSZXBlYXRlZCBVc2FnZTABOQga
+      C6PwTPgXQaDRC6PwTPgXShoKDmNyZXdhaV92ZXJzaW9uEggKBjAuNjEuMEofCgl0b29sX25hbWUS
+      EgoQZ2V0X2ZpbmFsX2Fuc3dlckoOCghhdHRlbXB0cxICGAF6AhgBhQEAAQAAEpMBChArAfcRpE+W
+      02oszyzccbaWEghTAO9J3zq/kyoKVG9vbCBVc2FnZTABORBRTqPwTPgXQegnT6PwTPgXShoKDmNy
+      ZXdhaV92ZXJzaW9uEggKBjAuNjEuMEofCgl0b29sX25hbWUSEgoQZ2V0X2ZpbmFsX2Fuc3dlckoO
+      CghhdHRlbXB0cxICGAF6AhgBhQEAAQAAEpwBChBdtM3p3aqT7wTGaXi6el/4Egie6lFQpa+AfioT
+      VG9vbCBSZXBlYXRlZCBVc2FnZTABOdBg2KPwTPgXQehW2aPwTPgXShoKDmNyZXdhaV92ZXJzaW9u
+      EggKBjAuNjEuMEofCgl0b29sX25hbWUSEgoQZ2V0X2ZpbmFsX2Fuc3dlckoOCghhdHRlbXB0cxIC
+      GAF6AhgBhQEAAQAAEpMBChDq4OuaUKkNoi6jlMyahPJpEgg1MFDHktBxNSoKVG9vbCBVc2FnZTAB
+      ORD/K6TwTPgXQZgMLaTwTPgXShoKDmNyZXdhaV92ZXJzaW9uEggKBjAuNjEuMEofCgl0b29sX25h
+      bWUSEgoQZ2V0X2ZpbmFsX2Fuc3dlckoOCghhdHRlbXB0cxICGAF6AhgBhQEAAQAAEpACChBhvTmu
+      QWP+bx9JMmGpt+w5Egh1J17yki7s8ioOVGFzayBFeGVjdXRpb24wATnoJJSi8Ez4F0HwNX6k8Ez4
+      F0ouCghjcmV3X2tleRIiCiBkNTUxMTNiZTRhYTQxYmE2NDNkMzI2MDQyYjJmMDNmMUoxCgdjcmV3
+      X2lkEiYKJDc5MjFlZWJiLTFiODUtNDMzYy1iMTAwLWQ1ODJjMjk4OTMwZEouCgh0YXNrX2tleRIi
+      CiA0YTMxYjg1MTMzYTNhMjk0YzY4NTNkYTc1N2Q0YmFlN0oxCgd0YXNrX2lkEiYKJDA2YWFmM2Y1
+      LTE5ODctNDAxYS05Yzk0LWY3ZjM1YmQzMDg3OXoCGAGFAQABAAASrg0KEOJZEqiJ7LTTX/J+tuLR
+      stQSCHKjy4tIcmKEKgxDcmV3IENyZWF0ZWQwATmIEuGk8Ez4F0FYDuOk8Ez4F0oaCg5jcmV3YWlf
+      dmVyc2lvbhIICgYwLjYxLjBKGgoOcHl0aG9uX3ZlcnNpb24SCAoGMy4xMS43Si4KCGNyZXdfa2V5
+      EiIKIDExMWI4NzJkOGYwY2Y3MDNmMmVmZWYwNGNmM2FjNzk4SjEKB2NyZXdfaWQSJgokYWFiYmU5
+      MmQtYjg3NC00NTZmLWE0NzAtM2FmMDc4ZTdjYThlShwKDGNyZXdfcHJvY2VzcxIMCgpzZXF1ZW50
+      aWFsShEKC2NyZXdfbWVtb3J5EgIQAEoaChRjcmV3X251bWJlcl9vZl90YXNrcxICGANKGwoVY3Jl
+      d19udW1iZXJfb2ZfYWdlbnRzEgIYAkqEBQoLY3Jld19hZ2VudHMS9AQK8QRbeyJrZXkiOiAiZTE0
+      OGU1MzIwMjkzNDk5ZjhjZWJlYTgyNmU3MjU4MmIiLCAiaWQiOiAiZmYzOTE0OGEtZWI2NS00Nzkx
+      LWI3MTMtM2Q4ZmE1YWQ5NTJlIiwgInJvbGUiOiAidGVzdCByb2xlIiwgInZlcmJvc2U/IjogZmFs
+      c2UsICJtYXhfaXRlciI6IDE1LCAibWF4X3JwbSI6IG51bGwsICJmdW5jdGlvbl9jYWxsaW5nX2xs
+      bSI6ICIiLCAibGxtIjogImdwdC00byIsICJkZWxlZ2F0aW9uX2VuYWJsZWQ/IjogZmFsc2UsICJh
+      bGxvd19jb2RlX2V4ZWN1dGlvbj8iOiBmYWxzZSwgIm1heF9yZXRyeV9saW1pdCI6IDIsICJ0b29s
+      c19uYW1lcyI6IFtdfSwgeyJrZXkiOiAiZTdlOGVlYTg4NmJjYjhmMTA0NWFiZWVjZjE0MjVkYjci
+      LCAiaWQiOiAiYzYyNDJmNDMtNmQ2Mi00N2U4LTliYmMtNjM0ZDQwYWI4YTQ2IiwgInJvbGUiOiAi
+      dGVzdCByb2xlMiIsICJ2ZXJib3NlPyI6IGZhbHNlLCAibWF4X2l0ZXIiOiAxNSwgIm1heF9ycG0i
+      OiBudWxsLCAiZnVuY3Rpb25fY2FsbGluZ19sbG0iOiAiIiwgImxsbSI6ICJncHQtNG8iLCAiZGVs
+      ZWdhdGlvbl9lbmFibGVkPyI6IGZhbHNlLCAiYWxsb3dfY29kZV9leGVjdXRpb24/IjogZmFsc2Us
+      ICJtYXhfcmV0cnlfbGltaXQiOiAyLCAidG9vbHNfbmFtZXMiOiBbXX1dStcFCgpjcmV3X3Rhc2tz
+      EsgFCsUFW3sia2V5IjogIjMyMmRkYWUzYmM4MGMxZDQ1Yjg1ZmE3NzU2ZGI4NjY1IiwgImlkIjog
+      IjRmZDZhZDdiLTFjNWMtNDE1ZC1hMWQ4LTgwYzExZGNjMTY4NiIsICJhc3luY19leGVjdXRpb24/
+      IjogZmFsc2UsICJodW1hbl9pbnB1dD8iOiBmYWxzZSwgImFnZW50X3JvbGUiOiAidGVzdCByb2xl
+      IiwgImFnZW50X2tleSI6ICJlMTQ4ZTUzMjAyOTM0OTlmOGNlYmVhODI2ZTcyNTgyYiIsICJ0b29s
+      c19uYW1lcyI6IFtdfSwgeyJrZXkiOiAiY2M0ODc2ZjZlNTg4ZTcxMzQ5YmJkM2E2NTg4OGMzZTki
+      LCAiaWQiOiAiOTFlYWFhMWMtMWI4ZC00MDcxLTk2ZmQtM2QxZWVkMjhjMzZjIiwgImFzeW5jX2V4
+      ZWN1dGlvbj8iOiBmYWxzZSwgImh1bWFuX2lucHV0PyI6IGZhbHNlLCAiYWdlbnRfcm9sZSI6ICJ0
+      ZXN0IHJvbGUiLCAiYWdlbnRfa2V5IjogImUxNDhlNTMyMDI5MzQ5OWY4Y2ViZWE4MjZlNzI1ODJi
+      IiwgInRvb2xzX25hbWVzIjogW119LCB7ImtleSI6ICJlMGIxM2UxMGQ3YTE0NmRjYzRjNDg4ZmNm
+      OGQ3NDhhMCIsICJpZCI6ICI4NjExZjhjZS1jNDVlLTQ2OTgtYWEyMS1jMGJkNzdhOGY2ZWYiLCAi
+      YXN5bmNfZXhlY3V0aW9uPyI6IGZhbHNlLCAiaHVtYW5faW5wdXQ/IjogZmFsc2UsICJhZ2VudF9y
+      b2xlIjogInRlc3Qgcm9sZTIiLCAiYWdlbnRfa2V5IjogImU3ZThlZWE4ODZiY2I4ZjEwNDVhYmVl
+      Y2YxNDI1ZGI3IiwgInRvb2xzX25hbWVzIjogW119XXoCGAGFAQABAAASjgIKEMbX6YsWK7RRf4L1
+      NBRKD6cSCFLJiNmspsyjKgxUYXNrIENyZWF0ZWQwATnonPGk8Ez4F0EotvKk8Ez4F0ouCghjcmV3
+      X2tleRIiCiAxMTFiODcyZDhmMGNmNzAzZjJlZmVmMDRjZjNhYzc5OEoxCgdjcmV3X2lkEiYKJGFh
+      YmJlOTJkLWI4NzQtNDU2Zi1hNDcwLTNhZjA3OGU3Y2E4ZUouCgh0YXNrX2tleRIiCiAzMjJkZGFl
+      M2JjODBjMWQ0NWI4NWZhNzc1NmRiODY2NUoxCgd0YXNrX2lkEiYKJDRmZDZhZDdiLTFjNWMtNDE1
+      ZC1hMWQ4LTgwYzExZGNjMTY4NnoCGAGFAQABAAASkAIKEM9JnUNanFbE9AtnSxqA7H8SCBWlG0WJ
+      sMgKKg5UYXNrIEV4ZWN1dGlvbjABOfDo8qTwTPgXQWhEH6XwTPgXSi4KCGNyZXdfa2V5EiIKIDEx
+      MWI4NzJkOGYwY2Y3MDNmMmVmZWYwNGNmM2FjNzk4SjEKB2NyZXdfaWQSJgokYWFiYmU5MmQtYjg3
+      NC00NTZmLWE0NzAtM2FmMDc4ZTdjYThlSi4KCHRhc2tfa2V5EiIKIDMyMmRkYWUzYmM4MGMxZDQ1
+      Yjg1ZmE3NzU2ZGI4NjY1SjEKB3Rhc2tfaWQSJgokNGZkNmFkN2ItMWM1Yy00MTVkLWExZDgtODBj
+      MTFkY2MxNjg2egIYAYUBAAEAABKOAgoQaQALCJNe5ByN4Wu7FE0kABIIYW/UfVfnYscqDFRhc2sg
+      Q3JlYXRlZDABOWhzLKXwTPgXQSD8LKXwTPgXSi4KCGNyZXdfa2V5EiIKIDExMWI4NzJkOGYwY2Y3
+      MDNmMmVmZWYwNGNmM2FjNzk4SjEKB2NyZXdfaWQSJgokYWFiYmU5MmQtYjg3NC00NTZmLWE0NzAt
+      M2FmMDc4ZTdjYThlSi4KCHRhc2tfa2V5EiIKIGNjNDg3NmY2ZTU4OGU3MTM0OWJiZDNhNjU4ODhj
+      M2U5SjEKB3Rhc2tfaWQSJgokOTFlYWFhMWMtMWI4ZC00MDcxLTk2ZmQtM2QxZWVkMjhjMzZjegIY
+      AYUBAAEAABKQAgoQpPfkgFlpIsR/eN2zn+x3MRIILoWF4/HvceAqDlRhc2sgRXhlY3V0aW9uMAE5
+      GCctpfBM+BdBQLNapfBM+BdKLgoIY3Jld19rZXkSIgogMTExYjg3MmQ4ZjBjZjcwM2YyZWZlZjA0
+      Y2YzYWM3OThKMQoHY3Jld19pZBImCiRhYWJiZTkyZC1iODc0LTQ1NmYtYTQ3MC0zYWYwNzhlN2Nh
+      OGVKLgoIdGFza19rZXkSIgogY2M0ODc2ZjZlNTg4ZTcxMzQ5YmJkM2E2NTg4OGMzZTlKMQoHdGFz
+      a19pZBImCiQ5MWVhYWExYy0xYjhkLTQwNzEtOTZmZC0zZDFlZWQyOGMzNmN6AhgBhQEAAQAAEo4C
+      ChCdvXmXZRltDxEwZx2XkhWhEghoKdomHHhLGSoMVGFzayBDcmVhdGVkMAE54HpmpfBM+BdB4Pdm
+      pfBM+BdKLgoIY3Jld19rZXkSIgogMTExYjg3MmQ4ZjBjZjcwM2YyZWZlZjA0Y2YzYWM3OThKMQoH
+      Y3Jld19pZBImCiRhYWJiZTkyZC1iODc0LTQ1NmYtYTQ3MC0zYWYwNzhlN2NhOGVKLgoIdGFza19r
+      ZXkSIgogZTBiMTNlMTBkN2ExNDZkY2M0YzQ4OGZjZjhkNzQ4YTBKMQoHdGFza19pZBImCiQ4NjEx
+      ZjhjZS1jNDVlLTQ2OTgtYWEyMS1jMGJkNzdhOGY2ZWZ6AhgBhQEAAQAAEpACChAIvs/XQL53haTt
+      NV8fk6geEgicgSOcpcYulyoOVGFzayBFeGVjdXRpb24wATnYImel8Ez4F0Gw5ZSl8Ez4F0ouCghj
+      cmV3X2tleRIiCiAxMTFiODcyZDhmMGNmNzAzZjJlZmVmMDRjZjNhYzc5OEoxCgdjcmV3X2lkEiYK
+      JGFhYmJlOTJkLWI4NzQtNDU2Zi1hNDcwLTNhZjA3OGU3Y2E4ZUouCgh0YXNrX2tleRIiCiBlMGIx
+      M2UxMGQ3YTE0NmRjYzRjNDg4ZmNmOGQ3NDhhMEoxCgd0YXNrX2lkEiYKJDg2MTFmOGNlLWM0NWUt
+      NDY5OC1hYTIxLWMwYmQ3N2E4ZjZlZnoCGAGFAQABAAASvAcKEARTPn0s+U/k8GclUc+5rRoSCHF3
+      KCh8OS0FKgxDcmV3IENyZWF0ZWQwATlo+Pul8Ez4F0EQ0f2l8Ez4F0oaCg5jcmV3YWlfdmVyc2lv
+      bhIICgYwLjYxLjBKGgoOcHl0aG9uX3ZlcnNpb24SCAoGMy4xMS43Si4KCGNyZXdfa2V5EiIKIDQ5
+      NGYzNjU3MjM3YWQ4YTMwMzViMmYxYmVlY2RjNjc3SjEKB2NyZXdfaWQSJgokOWMwNzg3NWUtMTMz
+      Mi00MmMzLWFhZTEtZjNjMjc1YTQyNjYwShwKDGNyZXdfcHJvY2VzcxIMCgpzZXF1ZW50aWFsShEK
+      C2NyZXdfbWVtb3J5EgIQAEoaChRjcmV3X251bWJlcl9vZl90YXNrcxICGAFKGwoVY3Jld19udW1i
+      ZXJfb2ZfYWdlbnRzEgIYAUrbAgoLY3Jld19hZ2VudHMSywIKyAJbeyJrZXkiOiAiZTE0OGU1MzIw
+      MjkzNDk5ZjhjZWJlYTgyNmU3MjU4MmIiLCAiaWQiOiAiNGFkYzNmMmItN2IwNC00MDRlLWEwNDQt
+      N2JkNjVmYTMyZmE4IiwgInJvbGUiOiAidGVzdCByb2xlIiwgInZlcmJvc2U/IjogZmFsc2UsICJt
+      YXhfaXRlciI6IDE1LCAibWF4X3JwbSI6IG51bGwsICJmdW5jdGlvbl9jYWxsaW5nX2xsbSI6ICIi
+      LCAibGxtIjogImdwdC00byIsICJkZWxlZ2F0aW9uX2VuYWJsZWQ/IjogZmFsc2UsICJhbGxvd19j
+      b2RlX2V4ZWN1dGlvbj8iOiBmYWxzZSwgIm1heF9yZXRyeV9saW1pdCI6IDIsICJ0b29sc19uYW1l
+      cyI6IFsibGVhcm5fYWJvdXRfYWkiXX1dSo4CCgpjcmV3X3Rhc2tzEv8BCvwBW3sia2V5IjogImYy
+      NTk3Yzc4NjdmYmUzMjRkYzY1ZGMwOGRmZGJmYzZjIiwgImlkIjogIjg2YzZiODE2LTgyOWMtNDUx
+      Zi1iMDZkLTUyZjQ4YTdhZWJiMyIsICJhc3luY19leGVjdXRpb24/IjogZmFsc2UsICJodW1hbl9p
+      bnB1dD8iOiBmYWxzZSwgImFnZW50X3JvbGUiOiAidGVzdCByb2xlIiwgImFnZW50X2tleSI6ICJl
+      MTQ4ZTUzMjAyOTM0OTlmOGNlYmVhODI2ZTcyNTgyYiIsICJ0b29sc19uYW1lcyI6IFsibGVhcm5f
+      YWJvdXRfYWkiXX1degIYAYUBAAEAABKOAgoQZWSU3+i71QSqlD8iiLdyWBII1Pawtza2ZHsqDFRh
+      c2sgQ3JlYXRlZDABOdj2FKbwTPgXQZhUFabwTPgXSi4KCGNyZXdfa2V5EiIKIDQ5NGYzNjU3MjM3
+      YWQ4YTMwMzViMmYxYmVlY2RjNjc3SjEKB2NyZXdfaWQSJgokOWMwNzg3NWUtMTMzMi00MmMzLWFh
+      ZTEtZjNjMjc1YTQyNjYwSi4KCHRhc2tfa2V5EiIKIGYyNTk3Yzc4NjdmYmUzMjRkYzY1ZGMwOGRm
+      ZGJmYzZjSjEKB3Rhc2tfaWQSJgokODZjNmI4MTYtODI5Yy00NTFmLWIwNmQtNTJmNDhhN2FlYmIz
+      egIYAYUBAAEAABKRAQoQl3nNMLhrOg+OgsWWX6A9LxIINbCKrQzQ3JkqClRvb2wgVXNhZ2UwATlA
+      TlCm8Ez4F0FASFGm8Ez4F0oaCg5jcmV3YWlfdmVyc2lvbhIICgYwLjYxLjBKHQoJdG9vbF9uYW1l
+      EhAKDmxlYXJuX2Fib3V0X0FJSg4KCGF0dGVtcHRzEgIYAXoCGAGFAQABAAASkAIKEL9YI/QwoVBJ
+      1HBkTLyQxOESCCcKWhev/Dc8Kg5UYXNrIEV4ZWN1dGlvbjABOXiDFabwTPgXQcjEfqbwTPgXSi4K
+      CGNyZXdfa2V5EiIKIDQ5NGYzNjU3MjM3YWQ4YTMwMzViMmYxYmVlY2RjNjc3SjEKB2NyZXdfaWQS
+      JgokOWMwNzg3NWUtMTMzMi00MmMzLWFhZTEtZjNjMjc1YTQyNjYwSi4KCHRhc2tfa2V5EiIKIGYy
+      NTk3Yzc4NjdmYmUzMjRkYzY1ZGMwOGRmZGJmYzZjSjEKB3Rhc2tfaWQSJgokODZjNmI4MTYtODI5
+      Yy00NTFmLWIwNmQtNTJmNDhhN2FlYmIzegIYAYUBAAEAABLBBwoQ0Le1256mT8wmcvnuLKYeNRII
+      IYBlVsTs+qEqDENyZXcgQ3JlYXRlZDABOYCBiKrwTPgXQRBeiqrwTPgXShoKDmNyZXdhaV92ZXJz
+      aW9uEggKBjAuNjEuMEoaCg5weXRob25fdmVyc2lvbhIICgYzLjExLjdKLgoIY3Jld19rZXkSIgog
+      NDk0ZjM2NTcyMzdhZDhhMzAzNWIyZjFiZWVjZGM2NzdKMQoHY3Jld19pZBImCiQyN2VlMGYyYy1h
+      ZjgwLTQxYWMtYjg3ZC0xNmViYWQyMTVhNTJKHAoMY3Jld19wcm9jZXNzEgwKCnNlcXVlbnRpYWxK
+      EQoLY3Jld19tZW1vcnkSAhAAShoKFGNyZXdfbnVtYmVyX29mX3Rhc2tzEgIYAUobChVjcmV3X251
+      bWJlcl9vZl9hZ2VudHMSAhgBSuACCgtjcmV3X2FnZW50cxLQAgrNAlt7ImtleSI6ICJlMTQ4ZTUz
+      MjAyOTM0OTlmOGNlYmVhODI2ZTcyNTgyYiIsICJpZCI6ICJmMTYyMTFjNS00YWJlLTRhZDAtOWI0
+      YS0yN2RmMTJhODkyN2UiLCAicm9sZSI6ICJ0ZXN0IHJvbGUiLCAidmVyYm9zZT8iOiBmYWxzZSwg
+      Im1heF9pdGVyIjogMiwgIm1heF9ycG0iOiBudWxsLCAiZnVuY3Rpb25fY2FsbGluZ19sbG0iOiAi
+      Z3B0LTRvIiwgImxsbSI6ICJncHQtNG8iLCAiZGVsZWdhdGlvbl9lbmFibGVkPyI6IGZhbHNlLCAi
+      YWxsb3dfY29kZV9leGVjdXRpb24/IjogZmFsc2UsICJtYXhfcmV0cnlfbGltaXQiOiAyLCAidG9v
+      bHNfbmFtZXMiOiBbImxlYXJuX2Fib3V0X2FpIl19XUqOAgoKY3Jld190YXNrcxL/AQr8AVt7Imtl
+      eSI6ICJmMjU5N2M3ODY3ZmJlMzI0ZGM2NWRjMDhkZmRiZmM2YyIsICJpZCI6ICJjN2FiOWRiYi0y
+      MTc4LTRmOGItOGFiNi1kYTU1YzE0YTBkMGMiLCAiYXN5bmNfZXhlY3V0aW9uPyI6IGZhbHNlLCAi
+      aHVtYW5faW5wdXQ/IjogZmFsc2UsICJhZ2VudF9yb2xlIjogInRlc3Qgcm9sZSIsICJhZ2VudF9r
+      ZXkiOiAiZTE0OGU1MzIwMjkzNDk5ZjhjZWJlYTgyNmU3MjU4MmIiLCAidG9vbHNfbmFtZXMiOiBb
+      ImxlYXJuX2Fib3V0X2FpIl19XXoCGAGFAQABAAASjgIKECr4ueCUCo/tMB7EuBQt6TcSCD/UepYl
+      WGqAKgxUYXNrIENyZWF0ZWQwATk4kpyq8Ez4F0Hg85yq8Ez4F0ouCghjcmV3X2tleRIiCiA0OTRm
+      MzY1NzIzN2FkOGEzMDM1YjJmMWJlZWNkYzY3N0oxCgdjcmV3X2lkEiYKJDI3ZWUwZjJjLWFmODAt
+      NDFhYy1iODdkLTE2ZWJhZDIxNWE1MkouCgh0YXNrX2tleRIiCiBmMjU5N2M3ODY3ZmJlMzI0ZGM2
+      NWRjMDhkZmRiZmM2Y0oxCgd0YXNrX2lkEiYKJGM3YWI5ZGJiLTIxNzgtNGY4Yi04YWI2LWRhNTVj
+      MTRhMGQwY3oCGAGFAQABAAASeQoQkj0vmbCBIZPi33W9KrvrYhIIM2g73dOAN9QqEFRvb2wgVXNh
+      Z2UgRXJyb3IwATnQgsyr8Ez4F0GghM2r8Ez4F0oaCg5jcmV3YWlfdmVyc2lvbhIICgYwLjYxLjBK
+      DwoDbGxtEggKBmdwdC00b3oCGAGFAQABAAASeQoQavr4/1SWr8x7HD5mAzlM0hIIXPx740Skkd0q
+      EFRvb2wgVXNhZ2UgRXJyb3IwATkouH9C8Uz4F0FQ1YBC8Uz4F0oaCg5jcmV3YWlfdmVyc2lvbhII
+      CgYwLjYxLjBKDwoDbGxtEggKBmdwdC00b3oCGAGFAQABAAASkAIKEIgmJ3QURJvSsEifMScSiUsS
+      CCyiPHcZT8AnKg5UYXNrIEV4ZWN1dGlvbjABOcAinarwTPgXQeBEynvxTPgXSi4KCGNyZXdfa2V5
+      EiIKIDQ5NGYzNjU3MjM3YWQ4YTMwMzViMmYxYmVlY2RjNjc3SjEKB2NyZXdfaWQSJgokMjdlZTBm
+      MmMtYWY4MC00MWFjLWI4N2QtMTZlYmFkMjE1YTUySi4KCHRhc2tfa2V5EiIKIGYyNTk3Yzc4Njdm
+      YmUzMjRkYzY1ZGMwOGRmZGJmYzZjSjEKB3Rhc2tfaWQSJgokYzdhYjlkYmItMjE3OC00ZjhiLThh
+      YjYtZGE1NWMxNGEwZDBjegIYAYUBAAEAABLEBwoQY+GZuYkP6mwdaVQQc11YuhII7ADKOlFZlzQq
+      DENyZXcgQ3JlYXRlZDABObCoi3zxTPgXQeCUjXzxTPgXShoKDmNyZXdhaV92ZXJzaW9uEggKBjAu
+      NjEuMEoaCg5weXRob25fdmVyc2lvbhIICgYzLjExLjdKLgoIY3Jld19rZXkSIgogN2U2NjA4OTg5
+      ODU5YTY3ZWVjODhlZWY3ZmNlODUyMjVKMQoHY3Jld19pZBImCiQxMmE0OTFlNS00NDgwLTQ0MTYt
+      OTAxYi1iMmI1N2U1ZWU4ZThKHAoMY3Jld19wcm9jZXNzEgwKCnNlcXVlbnRpYWxKEQoLY3Jld19t
+      ZW1vcnkSAhAAShoKFGNyZXdfbnVtYmVyX29mX3Rhc2tzEgIYAUobChVjcmV3X251bWJlcl9vZl9h
+      Z2VudHMSAhgBSt8CCgtjcmV3X2FnZW50cxLPAgrMAlt7ImtleSI6ICIyMmFjZDYxMWU0NGVmNWZh
+      YzA1YjUzM2Q3NWU4ODkzYiIsICJpZCI6ICI5NjljZjhlMy0yZWEwLTQ5ZjgtODNlMS02MzEzYmE4
+      ODc1ZjUiLCAicm9sZSI6ICJEYXRhIFNjaWVudGlzdCIsICJ2ZXJib3NlPyI6IGZhbHNlLCAibWF4
+      X2l0ZXIiOiAxNSwgIm1heF9ycG0iOiBudWxsLCAiZnVuY3Rpb25fY2FsbGluZ19sbG0iOiAiIiwg
+      ImxsbSI6ICJncHQtNG8iLCAiZGVsZWdhdGlvbl9lbmFibGVkPyI6IGZhbHNlLCAiYWxsb3dfY29k
+      ZV9leGVjdXRpb24/IjogZmFsc2UsICJtYXhfcmV0cnlfbGltaXQiOiAyLCAidG9vbHNfbmFtZXMi
+      OiBbImdldCBncmVldGluZ3MiXX1dSpICCgpjcmV3X3Rhc2tzEoMCCoACW3sia2V5IjogImEyNzdi
+      MzRiMmMxNDZmMGM1NmM1ZTEzNTZlOGY4YTU3IiwgImlkIjogImIwMTg0NTI2LTJlOWItNDA0My1h
+      M2JiLTFiM2QzNWIxNTNhOCIsICJhc3luY19leGVjdXRpb24/IjogZmFsc2UsICJodW1hbl9pbnB1
+      dD8iOiBmYWxzZSwgImFnZW50X3JvbGUiOiAiRGF0YSBTY2llbnRpc3QiLCAiYWdlbnRfa2V5Ijog
+      IjIyYWNkNjExZTQ0ZWY1ZmFjMDViNTMzZDc1ZTg4OTNiIiwgInRvb2xzX25hbWVzIjogWyJnZXQg
+      Z3JlZXRpbmdzIl19XXoCGAGFAQABAAASjgIKEI/rrKkPz08VpVWNehfvxJ0SCIpeq76twGj3KgxU
+      YXNrIENyZWF0ZWQwATlA9aR88Uz4F0HoVqV88Uz4F0ouCghjcmV3X2tleRIiCiA3ZTY2MDg5ODk4
+      NTlhNjdlZWM4OGVlZjdmY2U4NTIyNUoxCgdjcmV3X2lkEiYKJDEyYTQ5MWU1LTQ0ODAtNDQxNi05
+      MDFiLWIyYjU3ZTVlZThlOEouCgh0YXNrX2tleRIiCiBhMjc3YjM0YjJjMTQ2ZjBjNTZjNWUxMzU2
+      ZThmOGE1N0oxCgd0YXNrX2lkEiYKJGIwMTg0NTI2LTJlOWItNDA0My1hM2JiLTFiM2QzNWIxNTNh
+      OHoCGAGFAQABAAASkAEKEKKr5LR8SkqfqqktFhniLdkSCPMnqI2ma9UoKgpUb29sIFVzYWdlMAE5
+      sCHgfPFM+BdB+A/hfPFM+BdKGgoOY3Jld2FpX3ZlcnNpb24SCAoGMC42MS4wShwKCXRvb2xfbmFt
+      ZRIPCg1HZXQgR3JlZXRpbmdzSg4KCGF0dGVtcHRzEgIYAXoCGAGFAQABAAASkAIKEOj2bALdBlz6
+      1kP1MvHE5T0SCLw4D7D331IOKg5UYXNrIEV4ZWN1dGlvbjABOeCBpXzxTPgXQSjiEH3xTPgXSi4K
+      CGNyZXdfa2V5EiIKIDdlNjYwODk4OTg1OWE2N2VlYzg4ZWVmN2ZjZTg1MjI1SjEKB2NyZXdfaWQS
+      JgokMTJhNDkxZTUtNDQ4MC00NDE2LTkwMWItYjJiNTdlNWVlOGU4Si4KCHRhc2tfa2V5EiIKIGEy
+      NzdiMzRiMmMxNDZmMGM1NmM1ZTEzNTZlOGY4YTU3SjEKB3Rhc2tfaWQSJgokYjAxODQ1MjYtMmU5
+      Yi00MDQzLWEzYmItMWIzZDM1YjE1M2E4egIYAYUBAAEAABLQBwoQLjz7NWyGPgGU4tVFJ0sh9BII
+      N6EzU5f/sykqDENyZXcgQ3JlYXRlZDABOajOcX3xTPgXQUCAc33xTPgXShoKDmNyZXdhaV92ZXJz
+      aW9uEggKBjAuNjEuMEoaCg5weXRob25fdmVyc2lvbhIICgYzLjExLjdKLgoIY3Jld19rZXkSIgog
+      YzMwNzYwMDkzMjY3NjE0NDRkNTdjNzFkMWRhM2YyN2NKMQoHY3Jld19pZBImCiQ1N2Y0NjVhNC03
+      Zjk1LTQ5Y2MtODNmZC0zZTIwNWRhZDBjZTJKHAoMY3Jld19wcm9jZXNzEgwKCnNlcXVlbnRpYWxK
+      EQoLY3Jld19tZW1vcnkSAhAAShoKFGNyZXdfbnVtYmVyX29mX3Rhc2tzEgIYAUobChVjcmV3X251
+      bWJlcl9vZl9hZ2VudHMSAhgBSuUCCgtjcmV3X2FnZW50cxLVAgrSAlt7ImtleSI6ICI5OGYzYjFk
+      NDdjZTk2OWNmMDU3NzI3Yjc4NDE0MjVjZCIsICJpZCI6ICJjZjcyZDlkNy01MjQwLTRkMzEtYjA2
+      Mi0xMmNjMDU2OGNjM2MiLCAicm9sZSI6ICJGcmllbmRseSBOZWlnaGJvciIsICJ2ZXJib3NlPyI6
+      IGZhbHNlLCAibWF4X2l0ZXIiOiAxNSwgIm1heF9ycG0iOiBudWxsLCAiZnVuY3Rpb25fY2FsbGlu
+      Z19sbG0iOiAiIiwgImxsbSI6ICJncHQtNG8iLCAiZGVsZWdhdGlvbl9lbmFibGVkPyI6IGZhbHNl
+      LCAiYWxsb3dfY29kZV9leGVjdXRpb24/IjogZmFsc2UsICJtYXhfcmV0cnlfbGltaXQiOiAyLCAi
+      dG9vbHNfbmFtZXMiOiBbImRlY2lkZSBncmVldGluZ3MiXX1dSpgCCgpjcmV3X3Rhc2tzEokCCoYC
+      W3sia2V5IjogIjgwZDdiY2Q0OTA5OTI5MDA4MzgzMmYwZTk4MzM4MGRmIiwgImlkIjogIjUxNTJk
+      MmQ2LWYwODYtNGIyMi1hOGMxLTMyODA5NzU1NjZhZCIsICJhc3luY19leGVjdXRpb24/IjogZmFs
+      c2UsICJodW1hbl9pbnB1dD8iOiBmYWxzZSwgImFnZW50X3JvbGUiOiAiRnJpZW5kbHkgTmVpZ2hi
+      b3IiLCAiYWdlbnRfa2V5IjogIjk4ZjNiMWQ0N2NlOTY5Y2YwNTc3MjdiNzg0MTQyNWNkIiwgInRv
+      b2xzX25hbWVzIjogWyJkZWNpZGUgZ3JlZXRpbmdzIl19XXoCGAGFAQABAAASjgIKEM+95r2LzVVg
+      kqAMolHjl9oSCN9WyhdF/ucVKgxUYXNrIENyZWF0ZWQwATnoCoJ98Uz4F0HwXIJ98Uz4F0ouCghj
+      cmV3X2tleRIiCiBjMzA3NjAwOTMyNjc2MTQ0NGQ1N2M3MWQxZGEzZjI3Y0oxCgdjcmV3X2lkEiYK
+      JDU3ZjQ2NWE0LTdmOTUtNDljYy04M2ZkLTNlMjA1ZGFkMGNlMkouCgh0YXNrX2tleRIiCiA4MGQ3
+      YmNkNDkwOTkyOTAwODM4MzJmMGU5ODMzODBkZkoxCgd0YXNrX2lkEiYKJDUxNTJkMmQ2LWYwODYt
+      NGIyMi1hOGMxLTMyODA5NzU1NjZhZHoCGAGFAQABAAASkwEKENJjTKn4eTP/P11ERMIGcdYSCIKF
+      bGEmcS7bKgpUb29sIFVzYWdlMAE5EFu5ffFM+BdBoD26ffFM+BdKGgoOY3Jld2FpX3ZlcnNpb24S
+      CAoGMC42MS4wSh8KCXRvb2xfbmFtZRISChBEZWNpZGUgR3JlZXRpbmdzSg4KCGF0dGVtcHRzEgIY
+      AXoCGAGFAQABAAASkAIKEG29htC06tLF7ihE5Yz6NyMSCAAsKzOcj25nKg5UYXNrIEV4ZWN1dGlv
+      bjABOQCEgn3xTPgXQfgg7X3xTPgXSi4KCGNyZXdfa2V5EiIKIGMzMDc2MDA5MzI2NzYxNDQ0ZDU3
+      YzcxZDFkYTNmMjdjSjEKB2NyZXdfaWQSJgokNTdmNDY1YTQtN2Y5NS00OWNjLTgzZmQtM2UyMDVk
+      YWQwY2UySi4KCHRhc2tfa2V5EiIKIDgwZDdiY2Q0OTA5OTI5MDA4MzgzMmYwZTk4MzM4MGRmSjEK
+      B3Rhc2tfaWQSJgokNTE1MmQyZDYtZjA4Ni00YjIyLWE4YzEtMzI4MDk3NTU2NmFkegIYAYUBAAEA
+      AA==
+    headers:
+      Accept:
+      - '*/*'
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '18925'
+      Content-Type:
+      - application/x-protobuf
+      User-Agent:
+      - OTel-OTLP-Exporter-Python/1.27.0
+    method: POST
+    uri: https://telemetry.crewai.com:4319/v1/traces
+  response:
+    body:
+      string: "\n\0"
+    headers:
+      Content-Length:
+      - '2'
+      Content-Type:
+      - application/x-protobuf
+      Date:
+      - Tue, 24 Sep 2024 21:57:39 GMT
+    status:
+      code: 200
+      message: OK
+- request:
+    body: '{"model": "gemma2:latest", "prompt": "### User:\nRespond in 20 words. Who
+      are you?\n\n", "options": {}, "stream": false}'
+    headers:
+      Accept:
+      - '*/*'
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '120'
+      Content-Type:
+      - application/json
+      User-Agent:
+      - python-requests/2.31.0
+    method: POST
+    uri: http://localhost:8080/api/generate
+  response:
+    body:
+      string: '{"model":"gemma2:latest","created_at":"2024-09-24T21:57:51.284303Z","response":"I
+        am Gemma, an open-weights AI assistant developed by Google DeepMind.  \n","done":true,"done_reason":"stop","context":[106,1645,108,6176,4926,235292,108,54657,575,235248,235284,235276,3907,235265,7702,708,692,235336,109,107,108,106,2516,108,235285,1144,137061,235269,671,2174,235290,30316,16481,20409,6990,731,6238,20555,35777,235265,139,108],"total_duration":14046647083,"load_duration":12942541833,"prompt_eval_count":25,"prompt_eval_duration":177695000,"eval_count":19,"eval_duration":923120000}'
+    headers:
+      Content-Length:
+      - '579'
+      Content-Type:
+      - application/json; charset=utf-8
+      Date:
+      - Tue, 24 Sep 2024 21:57:51 GMT
+    status:
+      code: 200
+      message: OK
+version: 1

tests/cassettes/test_agent_with_ollama_llama3.yaml

@@ -1,36 +0,0 @@
-interactions:
-- request:
-    body: '{"model": "llama3.2:3b", "prompt": "### User:\nRespond in 20 words. Who
-      which model are you?\n\n", "options": {"stop": ["\nObservation:"]}, "stream":
-      false}'
-    headers:
-      Accept:
-      - '*/*'
-      Accept-Encoding:
-      - gzip, deflate
-      Connection:
-      - keep-alive
-      Content-Length:
-      - '156'
-      Content-Type:
-      - application/json
-      User-Agent:
-      - python-requests/2.32.3
-    method: POST
-    uri: http://localhost:11434/api/generate
-  response:
-    body:
-      string: '{"model":"llama3.2:3b","created_at":"2025-01-02T20:07:07.623404Z","response":"I''m
-        an AI designed to assist and communicate with users, utilizing a combination
-        of natural language processing models.","done":true,"done_reason":"stop","context":[128006,9125,128007,271,38766,1303,33025,2696,25,6790,220,2366,18,271,128009,128006,882,128007,271,14711,2724,512,66454,304,220,508,4339,13,10699,902,1646,527,499,1980,128009,128006,78191,128007,271,40,2846,459,15592,6319,311,7945,323,19570,449,3932,11,35988,264,10824,315,5933,4221,8863,4211,13],"total_duration":1076617833,"load_duration":46505416,"prompt_eval_count":40,"prompt_eval_duration":626000000,"eval_count":22,"eval_duration":399000000}'
-    headers:
-      Content-Length:
-      - '690'
-      Content-Type:
-      - application/json; charset=utf-8
-      Date:
-      - Thu, 02 Jan 2025 20:07:07 GMT
-    status:
-      code: 200
-      message: OK
-version: 1

tests/cassettes/test_llm_call_with_ollama_gemma.yaml

@@ -0,0 +1,35 @@
+interactions:
+- request:
+    body: '{"model": "gemma2:latest", "prompt": "### User:\nRespond in 20 words. Who
+      are you?\n\n", "options": {"num_predict": 30, "temperature": 0.7}, "stream":
+      false}'
+    headers:
+      Accept:
+      - '*/*'
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '157'
+      Content-Type:
+      - application/json
+      User-Agent:
+      - python-requests/2.31.0
+    method: POST
+    uri: http://localhost:8080/api/generate
+  response:
+    body:
+      string: '{"model":"gemma2:latest","created_at":"2024-09-24T21:57:52.329049Z","response":"I
+        am Gemma, an open-weights AI assistant trained by Google DeepMind.  \n","done":true,"done_reason":"stop","context":[106,1645,108,6176,4926,235292,108,54657,575,235248,235284,235276,3907,235265,7702,708,692,235336,109,107,108,106,2516,108,235285,1144,137061,235269,671,2174,235290,30316,16481,20409,17363,731,6238,20555,35777,235265,139,108],"total_duration":991843667,"load_duration":31664750,"prompt_eval_count":25,"prompt_eval_duration":51409000,"eval_count":19,"eval_duration":908132000}'
+    headers:
+      Content-Length:
+      - '572'
+      Content-Type:
+      - application/json; charset=utf-8
+      Date:
+      - Tue, 24 Sep 2024 21:57:52 GMT
+    status:
+      code: 200
+      message: OK
+version: 1

tests/cassettes/test_llm_call_with_ollama_llama3.yaml

@@ -1,36 +0,0 @@
-interactions:
-- request:
-    body: '{"model": "llama3.2:3b", "prompt": "### User:\nRespond in 20 words. Which
-      model are you??\n\n", "options": {"num_predict": 30, "temperature": 0.7}, "stream":
-      false}'
-    headers:
-      Accept:
-      - '*/*'
-      Accept-Encoding:
-      - gzip, deflate
-      Connection:
-      - keep-alive
-      Content-Length:
-      - '164'
-      Content-Type:
-      - application/json
-      User-Agent:
-      - python-requests/2.32.3
-    method: POST
-    uri: http://localhost:11434/api/generate
-  response:
-    body:
-      string: '{"model":"llama3.2:3b","created_at":"2025-01-02T20:24:24.812595Z","response":"I''m
-        an AI, specifically a large language model, designed to understand and respond
-        to user queries with accuracy.","done":true,"done_reason":"stop","context":[128006,9125,128007,271,38766,1303,33025,2696,25,6790,220,2366,18,271,128009,128006,882,128007,271,14711,2724,512,66454,304,220,508,4339,13,16299,1646,527,499,71291,128009,128006,78191,128007,271,40,2846,459,15592,11,11951,264,3544,4221,1646,11,6319,311,3619,323,6013,311,1217,20126,449,13708,13],"total_duration":827817584,"load_duration":41560542,"prompt_eval_count":39,"prompt_eval_duration":384000000,"eval_count":23,"eval_duration":400000000}'
-    headers:
-      Content-Length:
-      - '683'
-      Content-Type:
-      - application/json; charset=utf-8
-      Date:
-      - Thu, 02 Jan 2025 20:24:24 GMT
-    status:
-      code: 200
-      message: OK
-version: 1

tests/cassettes/test_task_execution_times.yaml

@@ -1,146 +0,0 @@
-interactions:
-- request:
-    body: '{"messages": [{"role": "system", "content": "You are Researcher. You''re
-      an expert researcher, specialized in technology, software engineering, AI and
-      startups. You work as a freelancer and is now working on doing research and
-      analysis for a new customer.\nYour personal goal is: Make the best research
-      and analysis on content about AI and AI agents\nTo give my best complete final
-      answer to the task use the exact following format:\n\nThought: I now can give
-      a great answer\nFinal Answer: Your final answer must be the great and the most
-      complete as possible, it must be outcome described.\n\nI MUST use these formats,
-      my job depends on it!"}, {"role": "user", "content": "\nCurrent Task: Give me
-      a list of 5 interesting ideas to explore for na article, what makes them unique
-      and interesting.\n\nThis is the expect criteria for your final answer: Bullet
-      point list of 5 interesting ideas.\nyou MUST return the actual complete content
-      as the final answer, not a summary.\n\nBegin! This is VERY important to you,
-      use the tools available and give your best Final Answer, your job depends on
-      it!\n\nThought:"}], "model": "gpt-4o-mini", "stop": ["\nObservation:"], "stream":
-      false}'
-    headers:
-      accept:
-      - application/json
-      accept-encoding:
-      - gzip, deflate
-      connection:
-      - keep-alive
-      content-length:
-      - '1177'
-      content-type:
-      - application/json
-      host:
-      - api.openai.com
-      user-agent:
-      - OpenAI/Python 1.52.1
-      x-stainless-arch:
-      - arm64
-      x-stainless-async:
-      - 'false'
-      x-stainless-lang:
-      - python
-      x-stainless-os:
-      - MacOS
-      x-stainless-package-version:
-      - 1.52.1
-      x-stainless-raw-response:
-      - 'true'
-      x-stainless-retry-count:
-      - '0'
-      x-stainless-runtime:
-      - CPython
-      x-stainless-runtime-version:
-      - 3.12.7
-    method: POST
-    uri: https://api.openai.com/v1/chat/completions
-  response:
-    content: "{\n  \"id\": \"chatcmpl-AlfwrGToOoVtDhb3ryZMpA07aZy4m\",\n  \"object\":
-      \"chat.completion\",\n  \"created\": 1735926029,\n  \"model\": \"gpt-4o-mini-2024-07-18\",\n
-      \ \"choices\": [\n    {\n      \"index\": 0,\n      \"message\": {\n        \"role\":
-      \"assistant\",\n        \"content\": \"I now can give a great answer  \\nFinal
-      Answer: \\n- **The Role of Emotional Intelligence in AI Agents**: Explore how
-      developing emotional intelligence in AI can change user interactions. Investigate
-      algorithms that enable AI agents to recognize and respond to human emotions,
-      enhancing user experience in sectors such as therapy, customer service, and
-      education. This idea is unique as it blends psychology with artificial intelligence,
-      presenting a new frontier for AI applications.\\n\\n- **AI Agents in Problem-Solving
-      for Climate Change**: Analyze how AI agents can contribute to developing innovative
-      solutions for climate change challenges. Focus on their role in predicting climate
-      patterns, optimizing energy consumption, and managing resources more efficiently.
-      This topic is unique because it highlights the practical impact of AI on one
-      of the most pressing global issues.\\n\\n- **The Ethics of Autonomous Decision-Making
-      AI**: Delve into the ethical implications surrounding AI agents that make autonomous
-      decisions, especially in critical areas like healthcare, transportation, and
-      law enforcement. This idea raises questions about accountability and bias, making
-      it a vital discussion point as AI continues to advance. The unique aspect lies
-      in the intersection of technology and moral philosophy.\\n\\n- **AI Agents Shaping
-      the Future of Remote Work**: Investigate how AI agents are transforming remote
-      work environments through automation, communication facilitation, and performance
-      monitoring. Discuss unique applications such as virtual assistants, project
-      management tools, and AI-driven team collaboration platforms. This topic is
-      particularly relevant as the workforce becomes increasingly remote, making it
-      an appealing area of exploration.\\n\\n- **Cultural Impacts of AI Agents in
-      Media and Entertainment**: Examine how AI-driven characters and narratives are
-      changing the media landscape, from video games to films and animations. Analyze
-      audience reception and the role of AI in personalizing content. This concept
-      is unique due to its intersection with digital culture and artistic expression,
-      offering insights into how technology influences social norms and preferences.\",\n
-      \       \"refusal\": null\n      },\n      \"logprobs\": null,\n      \"finish_reason\":
-      \"stop\"\n    }\n  ],\n  \"usage\": {\n    \"prompt_tokens\": 220,\n    \"completion_tokens\":
-      376,\n    \"total_tokens\": 596,\n    \"prompt_tokens_details\": {\n      \"cached_tokens\":
-      0,\n      \"audio_tokens\": 0\n    },\n    \"completion_tokens_details\": {\n
-      \     \"reasoning_tokens\": 0,\n      \"audio_tokens\": 0,\n      \"accepted_prediction_tokens\":
-      0,\n      \"rejected_prediction_tokens\": 0\n    }\n  },\n  \"system_fingerprint\":
-      \"fp_0aa8d3e20b\"\n}\n"
-    headers:
-      CF-Cache-Status:
-      - DYNAMIC
-      CF-RAY:
-      - 8fc4c6324d42ad5a-POA
-      Connection:
-      - keep-alive
-      Content-Encoding:
-      - gzip
-      Content-Type:
-      - application/json
-      Date:
-      - Fri, 03 Jan 2025 17:40:34 GMT
-      Server:
-      - cloudflare
-      Set-Cookie:
-      - __cf_bm=zdRUS9YIvR7oCmJGeB7BOAnmxI7FOE5Jae5yRZDCnPE-1735926034-1.0.1.1-gvIEXrMfT69wL2mv4ApivWX67OOpDegjf1LE6g9u3GEDuQdLQok.vlLZD.SdGzK0bMug86JZhBeDZMleJlI2EQ;
-        path=/; expires=Fri, 03-Jan-25 18:10:34 GMT; domain=.api.openai.com; HttpOnly;
-        Secure; SameSite=None
-      - _cfuvid=CW_cKQGYWY3cL.S6Xo5z0cmkmWHy5Q50OA_KjPEijNk-1735926034530-0.0.1.1-604800000;
-        path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
-      Transfer-Encoding:
-      - chunked
-      X-Content-Type-Options:
-      - nosniff
-      access-control-expose-headers:
-      - X-Request-ID
-      alt-svc:
-      - h3=":443"; ma=86400
-      openai-organization:
-      - crewai-iuxna1
-      openai-processing-ms:
-      - '5124'
-      openai-version:
-      - '2020-10-01'
-      strict-transport-security:
-      - max-age=31536000; includeSubDomains; preload
-      x-ratelimit-limit-requests:
-      - '30000'
-      x-ratelimit-limit-tokens:
-      - '150000000'
-      x-ratelimit-remaining-requests:
-      - '29999'
-      x-ratelimit-remaining-tokens:
-      - '149999729'
-      x-ratelimit-reset-requests:
-      - 2ms
-      x-ratelimit-reset-tokens:
-      - 0s
-      x-request-id:
-      - req_95ae59da1099e02c0d95bf25ba179fed
-    http_version: HTTP/1.1
-    status_code: 200
-version: 1

tests/cli/tools/test_main.py

@@ -28,10 +28,9 @@ def test_create_success(mock_subprocess):
     with in_temp_dir():
         tool_command = ToolCommand()
 
-        with (
-            patch.object(tool_command, "login") as mock_login,
-            patch("sys.stdout", new=StringIO()) as fake_out,
-        ):
+        with patch.object(tool_command, "login") as mock_login, patch(
+            "sys.stdout", new=StringIO()
+        ) as fake_out:
             tool_command.create("test-tool")
             output = fake_out.getvalue()
 
@@ -83,7 +82,7 @@ def test_install_success(mock_get, mock_subprocess_run):
         capture_output=False,
         text=True,
         check=True,
-        env=unittest.mock.ANY,
+        env=unittest.mock.ANY
     )
 
     assert "Successfully installed sample-tool" in output

tests/crew_test.py

@@ -333,16 +333,16 @@ def test_manager_agent_delegating_to_assigned_task_agent():
     )
 
     mock_task_output = TaskOutput(
-        description="Mock description", raw="mocked output", agent="mocked agent"
+        description="Mock description",
+        raw="mocked output",
+        agent="mocked agent"
     )
 
     # Because we are mocking execute_sync, we never hit the underlying _execute_core
     # which sets the output attribute of the task
     task.output = mock_task_output
 
-    with patch.object(
-        Task, "execute_sync", return_value=mock_task_output
-    ) as mock_execute_sync:
+    with patch.object(Task, 'execute_sync', return_value=mock_task_output) as mock_execute_sync:
         crew.kickoff()
 
         # Verify execute_sync was called once
@@ -350,20 +350,12 @@ def test_manager_agent_delegating_to_assigned_task_agent():
 
         # Get the tools argument from the call
         _, kwargs = mock_execute_sync.call_args
-        tools = kwargs["tools"]
+        tools = kwargs['tools']
 
         # Verify the delegation tools were passed correctly
         assert len(tools) == 2
-        assert any(
-            "Delegate a specific task to one of the following coworkers: Researcher"
-            in tool.description
-            for tool in tools
-        )
-        assert any(
-            "Ask a specific question to one of the following coworkers: Researcher"
-            in tool.description
-            for tool in tools
-        )
+        assert any("Delegate a specific task to one of the following coworkers: Researcher" in tool.description for tool in tools)
+        assert any("Ask a specific question to one of the following coworkers: Researcher" in tool.description for tool in tools)
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -412,7 +404,7 @@ def test_manager_agent_delegates_with_varied_role_cases():
         backstory="A researcher with spaces in role name",
         allow_delegation=False,
     )
-
+    
     writer_caps = Agent(
         role="SENIOR WRITER",  # All caps
         goal="Write with caps in role",
@@ -434,13 +426,13 @@ def test_manager_agent_delegates_with_varied_role_cases():
     )
 
     mock_task_output = TaskOutput(
-        description="Mock description", raw="mocked output", agent="mocked agent"
+        description="Mock description",
+        raw="mocked output",
+        agent="mocked agent"
     )
     task.output = mock_task_output
 
-    with patch.object(
-        Task, "execute_sync", return_value=mock_task_output
-    ) as mock_execute_sync:
+    with patch.object(Task, 'execute_sync', return_value=mock_task_output) as mock_execute_sync:
         crew.kickoff()
 
         # Verify execute_sync was called once
@@ -448,32 +440,20 @@ def test_manager_agent_delegates_with_varied_role_cases():
 
         # Get the tools argument from the call
         _, kwargs = mock_execute_sync.call_args
-        tools = kwargs["tools"]
+        tools = kwargs['tools']
 
         # Verify the delegation tools were passed correctly and can handle case/whitespace variations
         assert len(tools) == 2
-
+        
         # Check delegation tool descriptions (should work despite case/whitespace differences)
         delegation_tool = tools[0]
         question_tool = tools[1]
-
-        assert (
-            "Delegate a specific task to one of the following coworkers:"
-            in delegation_tool.description
-        )
-        assert (
-            " Researcher " in delegation_tool.description
-            or "SENIOR WRITER" in delegation_tool.description
-        )
-
-        assert (
-            "Ask a specific question to one of the following coworkers:"
-            in question_tool.description
-        )
-        assert (
-            " Researcher " in question_tool.description
-            or "SENIOR WRITER" in question_tool.description
-        )
+        
+        assert "Delegate a specific task to one of the following coworkers:" in delegation_tool.description
+        assert " Researcher " in delegation_tool.description or "SENIOR WRITER" in delegation_tool.description
+        
+        assert "Ask a specific question to one of the following coworkers:" in question_tool.description
+        assert " Researcher " in question_tool.description or "SENIOR WRITER" in question_tool.description
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -499,7 +479,6 @@ def test_crew_with_delegating_agents():
         == "In the rapidly evolving landscape of technology, AI agents have emerged as formidable tools, revolutionizing how we interact with data and automate tasks. These sophisticated systems leverage machine learning and natural language processing to perform a myriad of functions, from virtual personal assistants to complex decision-making companions in industries such as finance, healthcare, and education. By mimicking human intelligence, AI agents can analyze massive data sets at unparalleled speeds, enabling businesses to uncover valuable insights, enhance productivity, and elevate user experiences to unprecedented levels.\n\nOne of the most striking aspects of AI agents is their adaptability; they learn from their interactions and continuously improve their performance over time. This feature is particularly valuable in customer service where AI agents can address inquiries, resolve issues, and provide personalized recommendations without the limitations of human fatigue. Moreover, with intuitive interfaces, AI agents enhance user interactions, making technology more accessible and user-friendly, thereby breaking down barriers that have historically hindered digital engagement.\n\nDespite their immense potential, the deployment of AI agents raises important ethical and practical considerations. Issues related to privacy, data security, and the potential for job displacement necessitate thoughtful dialogue and proactive measures. Striking a balance between technological innovation and societal impact will be crucial as organizations integrate these agents into their operations. Additionally, ensuring transparency in AI decision-making processes is vital to maintain public trust as AI agents become an integral part of daily life.\n\nLooking ahead, the future of AI agents appears bright, with ongoing advancements promising even greater capabilities. As we continue to harness the power of AI, we can expect these agents to play a transformative role in shaping various sectors—streamlining workflows, enabling smarter decision-making, and fostering more personalized experiences. Embracing this technology responsibly can lead to a future where AI agents not only augment human effort but also inspire creativity and efficiency across the board, ultimately redefining our interaction with the digital world."
     )
 
-
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_crew_with_delegating_agents_should_not_override_task_tools():
     from typing import Type
@@ -510,7 +489,6 @@ def test_crew_with_delegating_agents_should_not_override_task_tools():
 
     class TestToolInput(BaseModel):
         """Input schema for TestTool."""
-
         query: str = Field(..., description="Query to process")
 
     class TestTool(BaseTool):
@@ -538,29 +516,24 @@ def test_crew_with_delegating_agents_should_not_override_task_tools():
     )
 
     mock_task_output = TaskOutput(
-        description="Mock description", raw="mocked output", agent="mocked agent"
+        description="Mock description",
+        raw="mocked output",
+        agent="mocked agent"
     )
 
     # Because we are mocking execute_sync, we never hit the underlying _execute_core
     # which sets the output attribute of the task
     tasks[0].output = mock_task_output
 
-    with patch.object(
-        Task, "execute_sync", return_value=mock_task_output
-    ) as mock_execute_sync:
+    with patch.object(Task, 'execute_sync', return_value=mock_task_output) as mock_execute_sync:
         crew.kickoff()
 
         # Execute the task and verify both tools are present
         _, kwargs = mock_execute_sync.call_args
-        tools = kwargs["tools"]
-
-        assert any(
-            isinstance(tool, TestTool) for tool in tools
-        ), "TestTool should be present"
-        assert any(
-            "delegate" in tool.name.lower() for tool in tools
-        ), "Delegation tool should be present"
+        tools = kwargs['tools']
 
+        assert any(isinstance(tool, TestTool) for tool in tools), "TestTool should be present"
+        assert any("delegate" in tool.name.lower() for tool in tools), "Delegation tool should be present"
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_crew_with_delegating_agents_should_not_override_agent_tools():
@@ -572,7 +545,6 @@ def test_crew_with_delegating_agents_should_not_override_agent_tools():
 
     class TestToolInput(BaseModel):
         """Input schema for TestTool."""
-
         query: str = Field(..., description="Query to process")
 
     class TestTool(BaseTool):
@@ -591,7 +563,7 @@ def test_crew_with_delegating_agents_should_not_override_agent_tools():
         Task(
             description="Produce and amazing 1 paragraph draft of an article about AI Agents.",
             expected_output="A 4 paragraph article about AI.",
-            agent=new_ceo,
+            agent=new_ceo
         )
     ]
 
@@ -602,29 +574,24 @@ def test_crew_with_delegating_agents_should_not_override_agent_tools():
     )
 
     mock_task_output = TaskOutput(
-        description="Mock description", raw="mocked output", agent="mocked agent"
+        description="Mock description",
+        raw="mocked output",
+        agent="mocked agent"
     )
 
     # Because we are mocking execute_sync, we never hit the underlying _execute_core
     # which sets the output attribute of the task
     tasks[0].output = mock_task_output
 
-    with patch.object(
-        Task, "execute_sync", return_value=mock_task_output
-    ) as mock_execute_sync:
+    with patch.object(Task, 'execute_sync', return_value=mock_task_output) as mock_execute_sync:
         crew.kickoff()
 
         # Execute the task and verify both tools are present
         _, kwargs = mock_execute_sync.call_args
-        tools = kwargs["tools"]
-
-        assert any(
-            isinstance(tool, TestTool) for tool in new_ceo.tools
-        ), "TestTool should be present"
-        assert any(
-            "delegate" in tool.name.lower() for tool in tools
-        ), "Delegation tool should be present"
+        tools = kwargs['tools']
 
+        assert any(isinstance(tool, TestTool) for tool in new_ceo.tools), "TestTool should be present"
+        assert any("delegate" in tool.name.lower() for tool in tools), "Delegation tool should be present"
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_task_tools_override_agent_tools():
@@ -636,7 +603,6 @@ def test_task_tools_override_agent_tools():
 
     class TestToolInput(BaseModel):
         """Input schema for TestTool."""
-
         query: str = Field(..., description="Query to process")
 
     class TestTool(BaseTool):
@@ -664,10 +630,14 @@ def test_task_tools_override_agent_tools():
         description="Write a test task",
         expected_output="Test output",
         agent=new_researcher,
-        tools=[AnotherTestTool()],
+        tools=[AnotherTestTool()]
     )
 
-    crew = Crew(agents=[new_researcher], tasks=[task], process=Process.sequential)
+    crew = Crew(
+        agents=[new_researcher],
+        tasks=[task],
+        process=Process.sequential
+    )
 
     crew.kickoff()
 
@@ -680,7 +650,6 @@ def test_task_tools_override_agent_tools():
     assert len(new_researcher.tools) == 1
     assert isinstance(new_researcher.tools[0], TestTool)
 
-
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_task_tools_override_agent_tools_with_allow_delegation():
     """
@@ -733,13 +702,13 @@ def test_task_tools_override_agent_tools_with_allow_delegation():
     )
 
     mock_task_output = TaskOutput(
-        description="Mock description", raw="mocked output", agent="mocked agent"
+        description="Mock description",
+        raw="mocked output",
+        agent="mocked agent"
     )
 
     # We mock execute_sync to verify which tools get used at runtime
-    with patch.object(
-        Task, "execute_sync", return_value=mock_task_output
-    ) as mock_execute_sync:
+    with patch.object(Task, "execute_sync", return_value=mock_task_output) as mock_execute_sync:
         crew.kickoff()
 
         # Inspect the call kwargs to verify the actual tools passed to execution
@@ -747,23 +716,16 @@ def test_task_tools_override_agent_tools_with_allow_delegation():
         used_tools = kwargs["tools"]
 
         # Confirm AnotherTestTool is present but TestTool is not
-        assert any(
-            isinstance(tool, AnotherTestTool) for tool in used_tools
-        ), "AnotherTestTool should be present"
-        assert not any(
-            isinstance(tool, TestTool) for tool in used_tools
-        ), "TestTool should not be present among used tools"
+        assert any(isinstance(tool, AnotherTestTool) for tool in used_tools), "AnotherTestTool should be present"
+        assert not any(isinstance(tool, TestTool) for tool in used_tools), "TestTool should not be present among used tools"
 
         # Confirm delegation tool(s) are present
-        assert any(
-            "delegate" in tool.name.lower() for tool in used_tools
-        ), "Delegation tool should be present"
+        assert any("delegate" in tool.name.lower() for tool in used_tools), "Delegation tool should be present"
 
     # Finally, make sure the agent's original tools remain unchanged
     assert len(researcher_with_delegation.tools) == 1
     assert isinstance(researcher_with_delegation.tools[0], TestTool)
 
-
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_crew_verbose_output(capsys):
     tasks = [
@@ -1050,8 +1012,8 @@ def test_three_task_with_async_execution():
     )
 
 
-@pytest.mark.asyncio
 @pytest.mark.vcr(filter_headers=["authorization"])
+@pytest.mark.asyncio
 async def test_crew_async_kickoff():
     inputs = [
         {"topic": "dog"},
@@ -1098,9 +1060,8 @@ async def test_crew_async_kickoff():
             assert result[0].token_usage.successful_requests > 0  # type: ignore
 
 
-@pytest.mark.asyncio
 @pytest.mark.vcr(filter_headers=["authorization"])
-async def test_async_task_execution_call_count():
+def test_async_task_execution_call_count():
     from unittest.mock import MagicMock, patch
 
     list_ideas = Task(
@@ -1227,6 +1188,7 @@ def test_kickoff_for_each_empty_input():
     assert results == []
 
 
+@pytest.mark.vcr(filter_headers=["authorization"])
 def test_kickoff_for_each_invalid_input():
     """Tests if kickoff_for_each raises TypeError for invalid input types."""
 
@@ -1249,6 +1211,7 @@ def test_kickoff_for_each_invalid_input():
         crew.kickoff_for_each("invalid input")
 
 
+@pytest.mark.vcr(filter_headers=["authorization"])
 def test_kickoff_for_each_error_handling():
     """Tests error handling in kickoff_for_each when kickoff raises an error."""
     from unittest.mock import patch
@@ -1285,6 +1248,7 @@ def test_kickoff_for_each_error_handling():
             crew.kickoff_for_each(inputs=inputs)
 
 
+@pytest.mark.vcr(filter_headers=["authorization"])
 @pytest.mark.asyncio
 async def test_kickoff_async_basic_functionality_and_output():
     """Tests the basic functionality and output of kickoff_async."""
@@ -1319,6 +1283,7 @@ async def test_kickoff_async_basic_functionality_and_output():
         mock_kickoff.assert_called_once_with(inputs)
 
 
+@pytest.mark.vcr(filter_headers=["authorization"])
 @pytest.mark.asyncio
 async def test_async_kickoff_for_each_async_basic_functionality_and_output():
     """Tests the basic functionality and output of kickoff_for_each_async."""
@@ -1365,6 +1330,7 @@ async def test_async_kickoff_for_each_async_basic_functionality_and_output():
             mock_kickoff_async.assert_any_call(inputs=input_data)
 
 
+@pytest.mark.vcr(filter_headers=["authorization"])
 @pytest.mark.asyncio
 async def test_async_kickoff_for_each_async_empty_input():
     """Tests if akickoff_for_each_async handles an empty input list."""
@@ -1548,12 +1514,12 @@ def test_code_execution_flag_adds_code_tool_upon_kickoff():
     crew = Crew(agents=[programmer], tasks=[task])
 
     mock_task_output = TaskOutput(
-        description="Mock description", raw="mocked output", agent="mocked agent"
+        description="Mock description",
+        raw="mocked output",
+        agent="mocked agent"
     )
 
-    with patch.object(
-        Task, "execute_sync", return_value=mock_task_output
-    ) as mock_execute_sync:
+    with patch.object(Task, "execute_sync", return_value=mock_task_output) as mock_execute_sync:
         crew.kickoff()
 
         # Get the tools that were actually used in execution
@@ -1562,10 +1528,7 @@ def test_code_execution_flag_adds_code_tool_upon_kickoff():
 
         # Verify that exactly one tool was used and it was a CodeInterpreterTool
         assert len(used_tools) == 1, "Should have exactly one tool"
-        assert isinstance(
-            used_tools[0], CodeInterpreterTool
-        ), "Tool should be CodeInterpreterTool"
-
+        assert isinstance(used_tools[0], CodeInterpreterTool), "Tool should be CodeInterpreterTool"
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_delegation_is_not_enabled_if_there_are_only_one_agent():
@@ -1676,16 +1639,16 @@ def test_hierarchical_crew_creation_tasks_with_agents():
     )
 
     mock_task_output = TaskOutput(
-        description="Mock description", raw="mocked output", agent="mocked agent"
+        description="Mock description",
+        raw="mocked output",
+        agent="mocked agent"
     )
 
     # Because we are mocking execute_sync, we never hit the underlying _execute_core
     # which sets the output attribute of the task
     task.output = mock_task_output
 
-    with patch.object(
-        Task, "execute_sync", return_value=mock_task_output
-    ) as mock_execute_sync:
+    with patch.object(Task, 'execute_sync', return_value=mock_task_output) as mock_execute_sync:
         crew.kickoff()
 
         # Verify execute_sync was called once
@@ -1693,20 +1656,12 @@ def test_hierarchical_crew_creation_tasks_with_agents():
 
         # Get the tools argument from the call
         _, kwargs = mock_execute_sync.call_args
-        tools = kwargs["tools"]
+        tools = kwargs['tools']
 
         # Verify the delegation tools were passed correctly
         assert len(tools) == 2
-        assert any(
-            "Delegate a specific task to one of the following coworkers: Senior Writer"
-            in tool.description
-            for tool in tools
-        )
-        assert any(
-            "Ask a specific question to one of the following coworkers: Senior Writer"
-            in tool.description
-            for tool in tools
-        )
+        assert any("Delegate a specific task to one of the following coworkers: Senior Writer" in tool.description for tool in tools)
+        assert any("Ask a specific question to one of the following coworkers: Senior Writer" in tool.description for tool in tools)
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -1729,7 +1684,9 @@ def test_hierarchical_crew_creation_tasks_with_async_execution():
     )
 
     mock_task_output = TaskOutput(
-        description="Mock description", raw="mocked output", agent="mocked agent"
+        description="Mock description",
+        raw="mocked output",
+        agent="mocked agent"
     )
 
     # Create a mock Future that returns our TaskOutput
@@ -1740,9 +1697,7 @@ def test_hierarchical_crew_creation_tasks_with_async_execution():
     # which sets the output attribute of the task
     task.output = mock_task_output
 
-    with patch.object(
-        Task, "execute_async", return_value=mock_future
-    ) as mock_execute_async:
+    with patch.object(Task, 'execute_async', return_value=mock_future) as mock_execute_async:
         crew.kickoff()
 
         # Verify execute_async was called once
@@ -1750,20 +1705,12 @@ def test_hierarchical_crew_creation_tasks_with_async_execution():
 
         # Get the tools argument from the call
         _, kwargs = mock_execute_async.call_args
-        tools = kwargs["tools"]
+        tools = kwargs['tools']
 
         # Verify the delegation tools were passed correctly
         assert len(tools) == 2
-        assert any(
-            "Delegate a specific task to one of the following coworkers: Senior Writer\n"
-            in tool.description
-            for tool in tools
-        )
-        assert any(
-            "Ask a specific question to one of the following coworkers: Senior Writer\n"
-            in tool.description
-            for tool in tools
-        )
+        assert any("Delegate a specific task to one of the following coworkers: Senior Writer\n" in tool.description for tool in tools)
+        assert any("Ask a specific question to one of the following coworkers: Senior Writer\n" in tool.description for tool in tools)
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -2092,6 +2039,7 @@ def test_crew_output_file_end_to_end(tmp_path):
     assert expected_file.exists(), f"Output file {expected_file} was not created"
 
 
+@pytest.mark.vcr(filter_headers=["authorization"])
 def test_crew_output_file_validation_failures():
     """Test output file validation failures in a crew context."""
     agent = Agent(
@@ -2107,7 +2055,7 @@ def test_crew_output_file_validation_failures():
             description="Analyze data",
             expected_output="Analysis results",
             agent=agent,
-            output_file="../output.txt",
+            output_file="../output.txt"
         )
         Crew(agents=[agent], tasks=[task]).kickoff()
 
@@ -2117,7 +2065,7 @@ def test_crew_output_file_validation_failures():
             description="Analyze data",
             expected_output="Analysis results",
             agent=agent,
-            output_file="output.txt | rm -rf /",
+            output_file="output.txt | rm -rf /"
         )
         Crew(agents=[agent], tasks=[task]).kickoff()
 
@@ -2127,7 +2075,7 @@ def test_crew_output_file_validation_failures():
             description="Analyze data",
             expected_output="Analysis results",
             agent=agent,
-            output_file="~/output.txt",
+            output_file="~/output.txt"
         )
         Crew(agents=[agent], tasks=[task]).kickoff()
 
@@ -2137,11 +2085,12 @@ def test_crew_output_file_validation_failures():
             description="Analyze data",
             expected_output="Analysis results",
             agent=agent,
-            output_file="{invalid-name}/output.txt",
+            output_file="{invalid-name}/output.txt"
         )
         Crew(agents=[agent], tasks=[task]).kickoff()
 
 
+@pytest.mark.vcr(filter_headers=["authorization"])
 def test_manager_agent():
     from unittest.mock import patch
 
@@ -3087,28 +3036,6 @@ def test_hierarchical_verbose_false_manager_agent():
     assert not crew.manager_agent.verbose
 
 
-def test_fetch_inputs():
-    agent = Agent(
-        role="{role_detail} Researcher",
-        goal="Research on {topic}.",
-        backstory="Expert in {field}.",
-    )
-
-    task = Task(
-        description="Analyze the data on {topic}.",
-        expected_output="Summary of {topic} analysis.",
-        agent=agent,
-    )
-
-    crew = Crew(agents=[agent], tasks=[task])
-
-    expected_placeholders = {"role_detail", "topic", "field"}
-    actual_placeholders = crew.fetch_inputs()
-
-    assert (
-        actual_placeholders == expected_placeholders
-    ), f"Expected {expected_placeholders}, but got {actual_placeholders}"
-
 def test_task_tools_preserve_code_execution_tools():
     """
     Test that task tools don't override code execution tools when allow_code_execution=True
@@ -3122,7 +3049,6 @@ def test_task_tools_preserve_code_execution_tools():
 
     class TestToolInput(BaseModel):
         """Input schema for TestTool."""
-
         query: str = Field(..., description="Query to process")
 
     class TestTool(BaseTool):
@@ -3156,7 +3082,7 @@ def test_task_tools_preserve_code_execution_tools():
         description="Write a program to calculate fibonacci numbers.",
         expected_output="A working fibonacci calculator.",
         agent=programmer,
-        tools=[TestTool()],
+        tools=[TestTool()]
     )
 
     crew = Crew(
@@ -3166,12 +3092,12 @@ def test_task_tools_preserve_code_execution_tools():
     )
 
     mock_task_output = TaskOutput(
-        description="Mock description", raw="mocked output", agent="mocked agent"
+        description="Mock description",
+        raw="mocked output",
+        agent="mocked agent"
     )
 
-    with patch.object(
-        Task, "execute_sync", return_value=mock_task_output
-    ) as mock_execute_sync:
+    with patch.object(Task, "execute_sync", return_value=mock_task_output) as mock_execute_sync:
         crew.kickoff()
 
         # Get the tools that were actually used in execution
@@ -3179,21 +3105,12 @@ def test_task_tools_preserve_code_execution_tools():
         used_tools = kwargs["tools"]
 
         # Verify all expected tools are present
-        assert any(
-            isinstance(tool, TestTool) for tool in used_tools
-        ), "Task's TestTool should be present"
-        assert any(
-            isinstance(tool, CodeInterpreterTool) for tool in used_tools
-        ), "CodeInterpreterTool should be present"
-        assert any(
-            "delegate" in tool.name.lower() for tool in used_tools
-        ), "Delegation tool should be present"
+        assert any(isinstance(tool, TestTool) for tool in used_tools), "Task's TestTool should be present"
+        assert any(isinstance(tool, CodeInterpreterTool) for tool in used_tools), "CodeInterpreterTool should be present"
+        assert any("delegate" in tool.name.lower() for tool in used_tools), "Delegation tool should be present"
 
         # Verify the total number of tools (TestTool + CodeInterpreter + 2 delegation tools)
-        assert (
-            len(used_tools) == 4
-        ), "Should have TestTool, CodeInterpreter, and 2 delegation tools"
-
+        assert len(used_tools) == 4, "Should have TestTool, CodeInterpreter, and 2 delegation tools"
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_multimodal_flag_adds_multimodal_tools():
@@ -3222,13 +3139,13 @@ def test_multimodal_flag_adds_multimodal_tools():
     crew = Crew(agents=[multimodal_agent], tasks=[task], process=Process.sequential)
 
     mock_task_output = TaskOutput(
-        description="Mock description", raw="mocked output", agent="mocked agent"
+        description="Mock description",
+        raw="mocked output",
+        agent="mocked agent"
     )
 
     # Mock execute_sync to verify the tools passed at runtime
-    with patch.object(
-        Task, "execute_sync", return_value=mock_task_output
-    ) as mock_execute_sync:
+    with patch.object(Task, "execute_sync", return_value=mock_task_output) as mock_execute_sync:
         crew.kickoff()
 
         # Get the tools that were actually used in execution
@@ -3236,14 +3153,13 @@ def test_multimodal_flag_adds_multimodal_tools():
         used_tools = kwargs["tools"]
 
         # Check that the multimodal tool was added
-        assert any(
-            isinstance(tool, AddImageTool) for tool in used_tools
-        ), "AddImageTool should be present when agent is multimodal"
+        assert any(isinstance(tool, AddImageTool) for tool in used_tools), (
+            "AddImageTool should be present when agent is multimodal"
+        )
 
         # Verify we have exactly one tool (just the AddImageTool)
         assert len(used_tools) == 1, "Should only have the AddImageTool"
 
-
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_multimodal_agent_image_tool_handling():
     """
@@ -3285,10 +3201,10 @@ def test_multimodal_agent_image_tool_handling():
     mock_task_output = TaskOutput(
         description="Mock description",
         raw="A detailed analysis of the image",
-        agent="Image Analyst",
+        agent="Image Analyst"
     )
 
-    with patch.object(Task, "execute_sync") as mock_execute_sync:
+    with patch.object(Task, 'execute_sync') as mock_execute_sync:
         # Set up the mock to return our task output
         mock_execute_sync.return_value = mock_task_output
 
@@ -3297,7 +3213,7 @@ def test_multimodal_agent_image_tool_handling():
 
         # Get the tools that were passed to execute_sync
         _, kwargs = mock_execute_sync.call_args
-        tools = kwargs["tools"]
+        tools = kwargs['tools']
 
         # Verify the AddImageTool is present and properly configured
         image_tools = [tool for tool in tools if tool.name == "Add image to content"]
@@ -3307,7 +3223,7 @@ def test_multimodal_agent_image_tool_handling():
         image_tool = image_tools[0]
         result = image_tool._run(
             image_url="https://example.com/test-image.jpg",
-            action="Please analyze this image",
+            action="Please analyze this image"
         )
 
         # Verify the tool returns the expected format
@@ -3317,7 +3233,6 @@ def test_multimodal_agent_image_tool_handling():
         assert result["content"][0]["type"] == "text"
         assert result["content"][1]["type"] == "image_url"
 
-
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_multimodal_agent_live_image_analysis():
     """
@@ -3331,7 +3246,7 @@ def test_multimodal_agent_live_image_analysis():
         allow_delegation=False,
         multimodal=True,
         verbose=True,
-        llm="gpt-4o",
+        llm="gpt-4o"
     )
 
     # Create a task for image analysis
@@ -3342,18 +3257,19 @@ def test_multimodal_agent_live_image_analysis():
         Image: {image_url}
         """,
         expected_output="A comprehensive description of the image contents.",
-        agent=image_analyst,
+        agent=image_analyst
     )
 
     # Create and run the crew
-    crew = Crew(agents=[image_analyst], tasks=[analyze_image])
+    crew = Crew(
+        agents=[image_analyst],
+        tasks=[analyze_image]
+    )
 
     # Execute with an image URL
-    result = crew.kickoff(
-        inputs={
-            "image_url": "https://media.istockphoto.com/id/946087016/photo/aerial-view-of-lower-manhattan-new-york.jpg?s=612x612&w=0&k=20&c=viLiMRznQ8v5LzKTt_LvtfPFUVl1oiyiemVdSlm29_k="
-        }
-    )
+    result = crew.kickoff(inputs={
+        "image_url": "https://media.istockphoto.com/id/946087016/photo/aerial-view-of-lower-manhattan-new-york.jpg?s=612x612&w=0&k=20&c=viLiMRznQ8v5LzKTt_LvtfPFUVl1oiyiemVdSlm29_k="
+    })
 
     # Verify we got a meaningful response
     assert isinstance(result.raw, str)

tests/knowledge/knowledge_test.py

@@ -578,6 +578,14 @@ def test_multiple_docling_sources():
     assert docling_source.content is not None
 
 
+def test_docling_source_with_local_file():
+    current_dir = Path(__file__).parent
+    pdf_path = current_dir / "crewai_quickstart.pdf"
+    docling_source = CrewDoclingSource(file_paths=[pdf_path])
+    assert docling_source.file_paths == [pdf_path]
+    assert docling_source.content is not None
+
+
 def test_file_path_validation():
     """Test file path validation for knowledge sources."""
     current_dir = Path(__file__).parent
@@ -598,6 +606,6 @@ def test_file_path_validation():
     # Test neither file_path nor file_paths provided
     with pytest.raises(
         ValueError,
-        match="file_path/file_paths must be a Path, str, or a list of these types",
+        match="file_path/file_paths must be a Path, str, or a list of these types"
     ):
         PDFKnowledgeSource()

tests/task_test.py

@@ -719,7 +719,7 @@ def test_interpolate_inputs():
     task = Task(
         description="Give me a list of 5 interesting ideas about {topic} to explore for an article, what makes them unique and interesting.",
         expected_output="Bullet point list of 5 interesting ideas about {topic}.",
-        output_file="/tmp/{topic}/output_{date}.txt",
+        output_file="/tmp/{topic}/output_{date}.txt"
     )
 
     task.interpolate_inputs(inputs={"topic": "AI", "date": "2024"})
@@ -742,35 +742,41 @@ def test_interpolate_inputs():
 def test_interpolate_only():
     """Test the interpolate_only method for various scenarios including JSON structure preservation."""
     task = Task(
-        description="Unused in this test", expected_output="Unused in this test"
+        description="Unused in this test",
+        expected_output="Unused in this test"
     )
-
+    
     # Test JSON structure preservation
     json_string = '{"info": "Look at {placeholder}", "nested": {"val": "{nestedVal}"}}'
     result = task.interpolate_only(
         input_string=json_string,
-        inputs={"placeholder": "the data", "nestedVal": "something else"},
+        inputs={"placeholder": "the data", "nestedVal": "something else"}
     )
     assert '"info": "Look at the data"' in result
     assert '"val": "something else"' in result
     assert "{placeholder}" not in result
     assert "{nestedVal}" not in result
-
+    
     # Test normal string interpolation
     normal_string = "Hello {name}, welcome to {place}!"
     result = task.interpolate_only(
-        input_string=normal_string, inputs={"name": "John", "place": "CrewAI"}
+        input_string=normal_string,
+        inputs={"name": "John", "place": "CrewAI"}
     )
     assert result == "Hello John, welcome to CrewAI!"
-
+    
     # Test empty string
-    result = task.interpolate_only(input_string="", inputs={"unused": "value"})
+    result = task.interpolate_only(
+        input_string="",
+        inputs={"unused": "value"}
+    )
     assert result == ""
-
+    
     # Test string with no placeholders
     no_placeholders = "Hello, this is a test"
     result = task.interpolate_only(
-        input_string=no_placeholders, inputs={"unused": "value"}
+        input_string=no_placeholders,
+        inputs={"unused": "value"}
     )
     assert result == no_placeholders
 
@@ -874,91 +880,56 @@ def test_key():
 def test_output_file_validation():
     """Test output file path validation."""
     # Valid paths
-    assert (
-        Task(
-            description="Test task",
-            expected_output="Test output",
-            output_file="output.txt",
-        ).output_file
-        == "output.txt"
-    )
-    assert (
-        Task(
-            description="Test task",
-            expected_output="Test output",
-            output_file="/tmp/output.txt",
-        ).output_file
-        == "tmp/output.txt"
-    )
-    assert (
-        Task(
-            description="Test task",
-            expected_output="Test output",
-            output_file="{dir}/output_{date}.txt",
-        ).output_file
-        == "{dir}/output_{date}.txt"
-    )
-
+    assert Task(
+        description="Test task",
+        expected_output="Test output",
+        output_file="output.txt"
+    ).output_file == "output.txt"
+    assert Task(
+        description="Test task",
+        expected_output="Test output",
+        output_file="/tmp/output.txt"
+    ).output_file == "tmp/output.txt"
+    assert Task(
+        description="Test task",
+        expected_output="Test output",
+        output_file="{dir}/output_{date}.txt"
+    ).output_file == "{dir}/output_{date}.txt"
+    
     # Invalid paths
     with pytest.raises(ValueError, match="Path traversal"):
         Task(
             description="Test task",
             expected_output="Test output",
-            output_file="../output.txt",
+            output_file="../output.txt"
         )
     with pytest.raises(ValueError, match="Path traversal"):
         Task(
             description="Test task",
             expected_output="Test output",
-            output_file="folder/../output.txt",
+            output_file="folder/../output.txt"
         )
     with pytest.raises(ValueError, match="Shell special characters"):
         Task(
             description="Test task",
             expected_output="Test output",
-            output_file="output.txt | rm -rf /",
+            output_file="output.txt | rm -rf /"
         )
     with pytest.raises(ValueError, match="Shell expansion"):
         Task(
             description="Test task",
             expected_output="Test output",
-            output_file="~/output.txt",
+            output_file="~/output.txt"
         )
     with pytest.raises(ValueError, match="Shell expansion"):
         Task(
             description="Test task",
             expected_output="Test output",
-            output_file="$HOME/output.txt",
+            output_file="$HOME/output.txt"
         )
     with pytest.raises(ValueError, match="Invalid template variable"):
         Task(
             description="Test task",
             expected_output="Test output",
-            output_file="{invalid-name}/output.txt",
+            output_file="{invalid-name}/output.txt"
         )
-
-
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_task_execution_times():
-    researcher = Agent(
-        role="Researcher",
-        goal="Make the best research and analysis on content about AI and AI agents",
-        backstory="You're an expert researcher, specialized in technology, software engineering, AI and startups. You work as a freelancer and is now working on doing research and analysis for a new customer.",
-        allow_delegation=False,
-    )
-
-    task = Task(
-        description="Give me a list of 5 interesting ideas to explore for na article, what makes them unique and interesting.",
-        expected_output="Bullet point list of 5 interesting ideas.",
-        agent=researcher,
-    )
-
-    assert task.start_time is None
-    assert task.end_time is None
-    assert task.execution_duration is None
-
-    task.execute_sync(agent=researcher)
-
-    assert task.start_time is not None
-    assert task.end_time is not None
-    assert task.execution_duration == (task.end_time - task.start_time).total_seconds()

tests/test_manager_llm_delegation.py

@@ -8,49 +8,48 @@ from crewai.tools.agent_tools.base_agent_tools import BaseAgentTool
 
 class TestAgentTool(BaseAgentTool):
     """Concrete implementation of BaseAgentTool for testing."""
-
     def _run(self, *args, **kwargs):
         """Implement required _run method."""
         return "Test response"
 
-
-@pytest.mark.parametrize(
-    "role_name,should_match",
-    [
-        ("Futel Official Infopoint", True),  # exact match
-        ('  "Futel Official Infopoint"  ', True),  # extra quotes and spaces
-        ("Futel Official Infopoint\n", True),  # trailing newline
-        ('"Futel Official Infopoint"', True),  # embedded quotes
-        (" FUTEL\nOFFICIAL   INFOPOINT ", True),  # multiple whitespace and newline
-        ("futel official infopoint", True),  # lowercase
-        ("FUTEL OFFICIAL INFOPOINT", True),  # uppercase
-        ("Non Existent Agent", False),  # non-existent agent
-        (None, False),  # None agent name
-    ],
-)
+@pytest.mark.parametrize("role_name,should_match", [
+    ('Futel Official Infopoint', True),                    # exact match
+    ('  "Futel Official Infopoint"  ', True),             # extra quotes and spaces
+    ('Futel Official Infopoint\n', True),                 # trailing newline
+    ('"Futel Official Infopoint"', True),                 # embedded quotes
+    (' FUTEL\nOFFICIAL   INFOPOINT ', True),             # multiple whitespace and newline
+    ('futel official infopoint', True),                   # lowercase
+    ('FUTEL OFFICIAL INFOPOINT', True),                   # uppercase
+    ('Non Existent Agent', False),                        # non-existent agent
+    (None, False),                                        # None agent name
+])
 def test_agent_tool_role_matching(role_name, should_match):
     """Test that agent tools can match roles regardless of case, whitespace, and special characters."""
     # Create test agent
     test_agent = Agent(
-        role="Futel Official Infopoint",
-        goal="Answer questions about Futel",
-        backstory="Futel Football Club info",
-        allow_delegation=False,
+        role='Futel Official Infopoint',
+        goal='Answer questions about Futel',
+        backstory='Futel Football Club info',
+        allow_delegation=False
     )
 
     # Create test agent tool
     agent_tool = TestAgentTool(
-        name="test_tool", description="Test tool", agents=[test_agent]
+        name="test_tool",
+        description="Test tool",
+        agents=[test_agent]
     )
 
     # Test role matching
-    result = agent_tool._execute(agent_name=role_name, task="Test task", context=None)
+    result = agent_tool._execute(
+        agent_name=role_name,
+        task='Test task',
+        context=None
+    )
 
     if should_match:
-        assert (
-            "coworker mentioned not found" not in result.lower()
-        ), f"Should find agent with role name: {role_name}"
+        assert "coworker mentioned not found" not in result.lower(), \
+            f"Should find agent with role name: {role_name}"
     else:
-        assert (
-            "coworker mentioned not found" in result.lower()
-        ), f"Should not find agent with role name: {role_name}"
+        assert "coworker mentioned not found" in result.lower(), \
+            f"Should not find agent with role name: {role_name}"

tests/test_task_guardrails.py

@@ -15,7 +15,10 @@ def test_task_without_guardrail():
     agent.execute_task.return_value = "test result"
     agent.crew = None
 
-    task = Task(description="Test task", expected_output="Output")
+    task = Task(
+        description="Test task",
+        expected_output="Output"
+    )
 
     result = task.execute_sync(agent=agent)
     assert isinstance(result, TaskOutput)
@@ -24,7 +27,6 @@ def test_task_without_guardrail():
 
 def test_task_with_successful_guardrail():
     """Test that successful guardrail validation passes transformed result."""
-
     def guardrail(result: TaskOutput):
         return (True, result.raw.upper())
 
@@ -33,7 +35,11 @@ def test_task_with_successful_guardrail():
     agent.execute_task.return_value = "test result"
     agent.crew = None
 
-    task = Task(description="Test task", expected_output="Output", guardrail=guardrail)
+    task = Task(
+        description="Test task",
+        expected_output="Output",
+        guardrail=guardrail
+    )
 
     result = task.execute_sync(agent=agent)
     assert isinstance(result, TaskOutput)
@@ -42,20 +48,22 @@ def test_task_with_successful_guardrail():
 
 def test_task_with_failing_guardrail():
     """Test that failing guardrail triggers retry with error context."""
-
     def guardrail(result: TaskOutput):
         return (False, "Invalid format")
 
     agent = Mock()
     agent.role = "test_agent"
-    agent.execute_task.side_effect = ["bad result", "good result"]
+    agent.execute_task.side_effect = [
+        "bad result",
+        "good result"
+    ]
     agent.crew = None
 
     task = Task(
         description="Test task",
         expected_output="Output",
         guardrail=guardrail,
-        max_retries=1,
+        max_retries=1
     )
 
     # First execution fails guardrail, second succeeds
@@ -69,7 +77,6 @@ def test_task_with_failing_guardrail():
 
 def test_task_with_guardrail_retries():
     """Test that guardrail respects max_retries configuration."""
-
     def guardrail(result: TaskOutput):
         return (False, "Invalid format")
 
@@ -82,7 +89,7 @@ def test_task_with_guardrail_retries():
         description="Test task",
         expected_output="Output",
         guardrail=guardrail,
-        max_retries=2,
+        max_retries=2
     )
 
     with pytest.raises(Exception) as exc_info:
@@ -95,7 +102,6 @@ def test_task_with_guardrail_retries():
 
 def test_guardrail_error_in_context():
     """Test that guardrail error is passed in context for retry."""
-
     def guardrail(result: TaskOutput):
         return (False, "Expected JSON, got string")
 
@@ -107,12 +113,11 @@ def test_guardrail_error_in_context():
         description="Test task",
         expected_output="Output",
         guardrail=guardrail,
-        max_retries=1,
+        max_retries=1
     )
 
     # Mock execute_task to succeed on second attempt
     first_call = True
-
     def execute_task(task, context, tools):
         nonlocal first_call
         if first_call:

tests/utilities/test_knowledge_planning.py

@@ -1,84 +0,0 @@
-"""
-Tests for verifying the integration of knowledge sources in the planning process.
-This module ensures that agent knowledge is properly included during task planning.
-"""
-
-from unittest.mock import patch
-
-import pytest
-
-from crewai.agent import Agent
-from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
-from crewai.task import Task
-from crewai.utilities.planning_handler import CrewPlanner
-
-
-@pytest.fixture
-def mock_knowledge_source():
-    """
-    Create a mock knowledge source with test content.
-    Returns:
-        StringKnowledgeSource:
-            A knowledge source containing AI-related test content
-    """
-    content = """
-    Important context about AI:
-    1. AI systems use machine learning algorithms
-    2. Neural networks are a key component
-    3. Training data is essential for good performance
-    """
-    return StringKnowledgeSource(content=content)
-
-@patch('crewai.knowledge.storage.knowledge_storage.chromadb')
-def test_knowledge_included_in_planning(mock_chroma):
-    """Test that verifies knowledge sources are properly included in planning."""
-    # Mock ChromaDB collection
-    mock_collection = mock_chroma.return_value.get_or_create_collection.return_value
-    mock_collection.add.return_value = None
-    
-    # Create an agent with knowledge
-    agent = Agent(
-        role="AI Researcher",
-        goal="Research and explain AI concepts",
-        backstory="Expert in artificial intelligence",
-        knowledge_sources=[
-            StringKnowledgeSource(
-                content="AI systems require careful training and validation."
-            )
-        ]
-    )
-
-    # Create a task for the agent
-    task = Task(
-        description="Explain the basics of AI systems",
-        expected_output="A clear explanation of AI fundamentals",
-        agent=agent
-    )
-
-    # Create a crew planner
-    planner = CrewPlanner([task], None)
-
-    # Get the task summary
-    task_summary = planner._create_tasks_summary()
-
-    # Verify that knowledge is included in planning when present
-    assert "AI systems require careful training" in task_summary, \
-        "Knowledge content should be present in task summary when knowledge exists"
-    assert '"agent_knowledge"' in task_summary, \
-        "agent_knowledge field should be present in task summary when knowledge exists"
-
-    # Verify that knowledge is properly formatted
-    assert isinstance(task.agent.knowledge_sources, list), \
-        "Knowledge sources should be stored in a list"
-    assert len(task.agent.knowledge_sources) > 0, \
-        "At least one knowledge source should be present"
-    assert task.agent.knowledge_sources[0].content in task_summary, \
-        "Knowledge source content should be included in task summary"
-
-    # Verify that other expected components are still present
-    assert task.description in task_summary, \
-        "Task description should be present in task summary"
-    assert task.expected_output in task_summary, \
-        "Expected output should be present in task summary"
-    assert agent.role in task_summary, \
-        "Agent role should be present in task summary"

tests/utilities/test_planning_handler.py

@@ -1,14 +1,10 @@
-from typing import Optional
-from unittest.mock import MagicMock, patch
+from unittest.mock import patch
 
 import pytest
-from pydantic import BaseModel
 
 from crewai.agent import Agent
-from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
 from crewai.task import Task
 from crewai.tasks.task_output import TaskOutput
-from crewai.tools.base_tool import BaseTool
 from crewai.utilities.planning_handler import (
     CrewPlanner,
     PlannerTaskPydanticOutput,
@@ -96,72 +92,7 @@ class TestCrewPlanner:
         tasks_summary = crew_planner._create_tasks_summary()
         assert isinstance(tasks_summary, str)
         assert tasks_summary.startswith("\n                Task Number 1 - Task 1")
-        assert '"agent_tools": "agent has no tools"' in tasks_summary
-        # Knowledge field should not be present when empty
-        assert '"agent_knowledge"' not in tasks_summary
-
-    @patch('crewai.knowledge.storage.knowledge_storage.chromadb')
-    def test_create_tasks_summary_with_knowledge_and_tools(self, mock_chroma):
-        """Test task summary generation with both knowledge and tools present."""
-        # Mock ChromaDB collection
-        mock_collection = mock_chroma.return_value.get_or_create_collection.return_value
-        mock_collection.add.return_value = None
-
-        # Create mock tools with proper string descriptions and structured tool support
-        class MockTool(BaseTool):
-            name: str
-            description: str
-
-            def __init__(self, name: str, description: str):
-                tool_data = {"name": name, "description": description}
-                super().__init__(**tool_data)
-            
-            def __str__(self):
-                return self.name
-            
-            def __repr__(self):
-                return self.name
-            
-            def to_structured_tool(self):
-                return self
-
-            def _run(self, *args, **kwargs):
-                pass
-
-            def _generate_description(self) -> str:
-                """Override _generate_description to avoid args_schema handling."""
-                return self.description
-
-        tool1 = MockTool("tool1", "Tool 1 description")
-        tool2 = MockTool("tool2", "Tool 2 description")
-
-        # Create a task with knowledge and tools
-        task = Task(
-            description="Task with knowledge and tools",
-            expected_output="Expected output",
-            agent=Agent(
-                role="Test Agent",
-                goal="Test Goal",
-                backstory="Test Backstory",
-                tools=[tool1, tool2],
-                knowledge_sources=[
-                    StringKnowledgeSource(content="Test knowledge content")
-                ]
-            )
-        )
-        
-        # Create planner with the new task
-        planner = CrewPlanner([task], None)
-        tasks_summary = planner._create_tasks_summary()
-        
-        # Verify task summary content
-        assert isinstance(tasks_summary, str)
-        assert task.description in tasks_summary
-        assert task.expected_output in tasks_summary
-        assert '"agent_tools": [tool1, tool2]' in tasks_summary
-        assert '"agent_knowledge": "[\\"Test knowledge content\\"]"' in tasks_summary
-        assert task.agent.role in tasks_summary
-        assert task.agent.goal in tasks_summary
+        assert tasks_summary.endswith('"agent_tools": []\n                ')
 
     def test_handle_crew_planning_different_llm(self, crew_planner_different_llm):
         with patch.object(Task, "execute_sync") as execute:

uv.lock

@@ -1,42 +1,10 @@
 version = 1
 requires-python = ">=3.10, <3.13"
 resolution-markers = [
-    "python_full_version < '3.11' and platform_system == 'Darwin' and sys_platform == 'darwin'",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'darwin'",
-    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Darwin' and sys_platform == 'linux'",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
-    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
-    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version == '3.11.*' and platform_system == 'Darwin' and sys_platform == 'darwin'",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'darwin'",
-    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Darwin' and sys_platform == 'linux'",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
-    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
-    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_system == 'Darwin' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'darwin'",
-    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Darwin' and sys_platform == 'linux'",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
-    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
-    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version >= '3.12.4' and platform_system == 'Darwin' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'darwin'",
-    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Darwin' and sys_platform == 'linux'",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform == 'linux'",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
-    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
-    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11'",
+    "python_full_version == '3.11.*'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4'",
+    "python_full_version >= '3.12.4'",
 ]
 
 [[package]]
@@ -66,7 +34,7 @@ wheels = [
 
 [[package]]
 name = "aiohttp"
-version = "3.11.11"
+version = "3.10.10"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -75,56 +43,55 @@ dependencies = [
     { name = "attrs" },
     { name = "frozenlist" },
     { name = "multidict" },
-    { name = "propcache" },
     { name = "yarl" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/fe/ed/f26db39d29cd3cb2f5a3374304c713fe5ab5a0e4c8ee25a0c45cc6adf844/aiohttp-3.11.11.tar.gz", hash = "sha256:bb49c7f1e6ebf3821a42d81d494f538107610c3a705987f53068546b0e90303e", size = 7669618 }
+sdist = { url = "https://files.pythonhosted.org/packages/17/7e/16e57e6cf20eb62481a2f9ce8674328407187950ccc602ad07c685279141/aiohttp-3.10.10.tar.gz", hash = "sha256:0631dd7c9f0822cc61c88586ca76d5b5ada26538097d0f1df510b082bad3411a", size = 7542993 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/75/7d/ff2e314b8f9e0b1df833e2d4778eaf23eae6b8cc8f922495d110ddcbf9e1/aiohttp-3.11.11-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a60804bff28662cbcf340a4d61598891f12eea3a66af48ecfdc975ceec21e3c8", size = 708550 },
-    { url = "https://files.pythonhosted.org/packages/09/b8/aeb4975d5bba233d6f246941f5957a5ad4e3def8b0855a72742e391925f2/aiohttp-3.11.11-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:4b4fa1cb5f270fb3eab079536b764ad740bb749ce69a94d4ec30ceee1b5940d5", size = 468430 },
-    { url = "https://files.pythonhosted.org/packages/9c/5b/5b620279b3df46e597008b09fa1e10027a39467387c2332657288e25811a/aiohttp-3.11.11-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:731468f555656767cda219ab42e033355fe48c85fbe3ba83a349631541715ba2", size = 455593 },
-    { url = "https://files.pythonhosted.org/packages/d8/75/0cdf014b816867d86c0bc26f3d3e3f194198dbf33037890beed629cd4f8f/aiohttp-3.11.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cb23d8bb86282b342481cad4370ea0853a39e4a32a0042bb52ca6bdde132df43", size = 1584635 },
-    { url = "https://files.pythonhosted.org/packages/df/2f/95b8f4e4dfeb57c1d9ad9fa911ede35a0249d75aa339edd2c2270dc539da/aiohttp-3.11.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f047569d655f81cb70ea5be942ee5d4421b6219c3f05d131f64088c73bb0917f", size = 1632363 },
-    { url = "https://files.pythonhosted.org/packages/39/cb/70cf69ea7c50f5b0021a84f4c59c3622b2b3b81695f48a2f0e42ef7eba6e/aiohttp-3.11.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:dd7659baae9ccf94ae5fe8bfaa2c7bc2e94d24611528395ce88d009107e00c6d", size = 1668315 },
-    { url = "https://files.pythonhosted.org/packages/2f/cc/3a3fc7a290eabc59839a7e15289cd48f33dd9337d06e301064e1e7fb26c5/aiohttp-3.11.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:af01e42ad87ae24932138f154105e88da13ce7d202a6de93fafdafb2883a00ef", size = 1589546 },
-    { url = "https://files.pythonhosted.org/packages/15/b4/0f7b0ed41ac6000e283e7332f0f608d734b675a8509763ca78e93714cfb0/aiohttp-3.11.11-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5854be2f3e5a729800bac57a8d76af464e160f19676ab6aea74bde18ad19d438", size = 1544581 },
-    { url = "https://files.pythonhosted.org/packages/58/b9/4d06470fd85c687b6b0e31935ef73dde6e31767c9576d617309a2206556f/aiohttp-3.11.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:6526e5fb4e14f4bbf30411216780c9967c20c5a55f2f51d3abd6de68320cc2f3", size = 1529256 },
-    { url = "https://files.pythonhosted.org/packages/61/a2/6958b1b880fc017fd35f5dfb2c26a9a50c755b75fd9ae001dc2236a4fb79/aiohttp-3.11.11-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:85992ee30a31835fc482468637b3e5bd085fa8fe9392ba0bdcbdc1ef5e9e3c55", size = 1536592 },
-    { url = "https://files.pythonhosted.org/packages/0f/dd/b974012a9551fd654f5bb95a6dd3f03d6e6472a17e1a8216dd42e9638d6c/aiohttp-3.11.11-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:88a12ad8ccf325a8a5ed80e6d7c3bdc247d66175afedbe104ee2aaca72960d8e", size = 1607446 },
-    { url = "https://files.pythonhosted.org/packages/e0/d3/6c98fd87e638e51f074a3f2061e81fcb92123bcaf1439ac1b4a896446e40/aiohttp-3.11.11-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:0a6d3fbf2232e3a08c41eca81ae4f1dff3d8f1a30bae415ebe0af2d2458b8a33", size = 1628809 },
-    { url = "https://files.pythonhosted.org/packages/a8/2e/86e6f85cbca02be042c268c3d93e7f35977a0e127de56e319bdd1569eaa8/aiohttp-3.11.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:84a585799c58b795573c7fa9b84c455adf3e1d72f19a2bf498b54a95ae0d194c", size = 1564291 },
-    { url = "https://files.pythonhosted.org/packages/0b/8d/1f4ef3503b767717f65e1f5178b0173ab03cba1a19997ebf7b052161189f/aiohttp-3.11.11-cp310-cp310-win32.whl", hash = "sha256:bfde76a8f430cf5c5584553adf9926534352251d379dcb266ad2b93c54a29745", size = 416601 },
-    { url = "https://files.pythonhosted.org/packages/ad/86/81cb83691b5ace3d9aa148dc42bacc3450d749fc88c5ec1973573c1c1779/aiohttp-3.11.11-cp310-cp310-win_amd64.whl", hash = "sha256:0fd82b8e9c383af11d2b26f27a478640b6b83d669440c0a71481f7c865a51da9", size = 442007 },
-    { url = "https://files.pythonhosted.org/packages/34/ae/e8806a9f054e15f1d18b04db75c23ec38ec954a10c0a68d3bd275d7e8be3/aiohttp-3.11.11-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:ba74ec819177af1ef7f59063c6d35a214a8fde6f987f7661f4f0eecc468a8f76", size = 708624 },
-    { url = "https://files.pythonhosted.org/packages/c7/e0/313ef1a333fb4d58d0c55a6acb3cd772f5d7756604b455181049e222c020/aiohttp-3.11.11-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4af57160800b7a815f3fe0eba9b46bf28aafc195555f1824555fa2cfab6c1538", size = 468507 },
-    { url = "https://files.pythonhosted.org/packages/a9/60/03455476bf1f467e5b4a32a465c450548b2ce724eec39d69f737191f936a/aiohttp-3.11.11-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ffa336210cf9cd8ed117011085817d00abe4c08f99968deef0013ea283547204", size = 455571 },
-    { url = "https://files.pythonhosted.org/packages/be/f9/469588603bd75bf02c8ffb8c8a0d4b217eed446b49d4a767684685aa33fd/aiohttp-3.11.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:81b8fe282183e4a3c7a1b72f5ade1094ed1c6345a8f153506d114af5bf8accd9", size = 1685694 },
-    { url = "https://files.pythonhosted.org/packages/88/b9/1b7fa43faf6c8616fa94c568dc1309ffee2b6b68b04ac268e5d64b738688/aiohttp-3.11.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3af41686ccec6a0f2bdc66686dc0f403c41ac2089f80e2214a0f82d001052c03", size = 1743660 },
-    { url = "https://files.pythonhosted.org/packages/2a/8b/0248d19dbb16b67222e75f6aecedd014656225733157e5afaf6a6a07e2e8/aiohttp-3.11.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:70d1f9dde0e5dd9e292a6d4d00058737052b01f3532f69c0c65818dac26dc287", size = 1785421 },
-    { url = "https://files.pythonhosted.org/packages/c4/11/f478e071815a46ca0a5ae974651ff0c7a35898c55063305a896e58aa1247/aiohttp-3.11.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:249cc6912405917344192b9f9ea5cd5b139d49e0d2f5c7f70bdfaf6b4dbf3a2e", size = 1675145 },
-    { url = "https://files.pythonhosted.org/packages/26/5d/284d182fecbb5075ae10153ff7374f57314c93a8681666600e3a9e09c505/aiohttp-3.11.11-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0eb98d90b6690827dcc84c246811feeb4e1eea683c0eac6caed7549be9c84665", size = 1619804 },
-    { url = "https://files.pythonhosted.org/packages/1b/78/980064c2ad685c64ce0e8aeeb7ef1e53f43c5b005edcd7d32e60809c4992/aiohttp-3.11.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:ec82bf1fda6cecce7f7b915f9196601a1bd1a3079796b76d16ae4cce6d0ef89b", size = 1654007 },
-    { url = "https://files.pythonhosted.org/packages/21/8d/9e658d63b1438ad42b96f94da227f2e2c1d5c6001c9e8ffcc0bfb22e9105/aiohttp-3.11.11-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:9fd46ce0845cfe28f108888b3ab17abff84ff695e01e73657eec3f96d72eef34", size = 1650022 },
-    { url = "https://files.pythonhosted.org/packages/85/fd/a032bf7f2755c2df4f87f9effa34ccc1ef5cea465377dbaeef93bb56bbd6/aiohttp-3.11.11-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:bd176afcf8f5d2aed50c3647d4925d0db0579d96f75a31e77cbaf67d8a87742d", size = 1732899 },
-    { url = "https://files.pythonhosted.org/packages/c5/0c/c2b85fde167dd440c7ba50af2aac20b5a5666392b174df54c00f888c5a75/aiohttp-3.11.11-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:ec2aa89305006fba9ffb98970db6c8221541be7bee4c1d027421d6f6df7d1ce2", size = 1755142 },
-    { url = "https://files.pythonhosted.org/packages/bc/78/91ae1a3b3b3bed8b893c5d69c07023e151b1c95d79544ad04cf68f596c2f/aiohttp-3.11.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:92cde43018a2e17d48bb09c79e4d4cb0e236de5063ce897a5e40ac7cb4878773", size = 1692736 },
-    { url = "https://files.pythonhosted.org/packages/77/89/a7ef9c4b4cdb546fcc650ca7f7395aaffbd267f0e1f648a436bec33c9b95/aiohttp-3.11.11-cp311-cp311-win32.whl", hash = "sha256:aba807f9569455cba566882c8938f1a549f205ee43c27b126e5450dc9f83cc62", size = 416418 },
-    { url = "https://files.pythonhosted.org/packages/fc/db/2192489a8a51b52e06627506f8ac8df69ee221de88ab9bdea77aa793aa6a/aiohttp-3.11.11-cp311-cp311-win_amd64.whl", hash = "sha256:ae545f31489548c87b0cced5755cfe5a5308d00407000e72c4fa30b19c3220ac", size = 442509 },
-    { url = "https://files.pythonhosted.org/packages/69/cf/4bda538c502f9738d6b95ada11603c05ec260807246e15e869fc3ec5de97/aiohttp-3.11.11-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:e595c591a48bbc295ebf47cb91aebf9bd32f3ff76749ecf282ea7f9f6bb73886", size = 704666 },
-    { url = "https://files.pythonhosted.org/packages/46/7b/87fcef2cad2fad420ca77bef981e815df6904047d0a1bd6aeded1b0d1d66/aiohttp-3.11.11-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:3ea1b59dc06396b0b424740a10a0a63974c725b1c64736ff788a3689d36c02d2", size = 464057 },
-    { url = "https://files.pythonhosted.org/packages/5a/a6/789e1f17a1b6f4a38939fbc39d29e1d960d5f89f73d0629a939410171bc0/aiohttp-3.11.11-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8811f3f098a78ffa16e0ea36dffd577eb031aea797cbdba81be039a4169e242c", size = 455996 },
-    { url = "https://files.pythonhosted.org/packages/b7/dd/485061fbfef33165ce7320db36e530cd7116ee1098e9c3774d15a732b3fd/aiohttp-3.11.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bd7227b87a355ce1f4bf83bfae4399b1f5bb42e0259cb9405824bd03d2f4336a", size = 1682367 },
-    { url = "https://files.pythonhosted.org/packages/e9/d7/9ec5b3ea9ae215c311d88b2093e8da17e67b8856673e4166c994e117ee3e/aiohttp-3.11.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d40f9da8cabbf295d3a9dae1295c69975b86d941bc20f0a087f0477fa0a66231", size = 1736989 },
-    { url = "https://files.pythonhosted.org/packages/d6/fb/ea94927f7bfe1d86178c9d3e0a8c54f651a0a655214cce930b3c679b8f64/aiohttp-3.11.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ffb3dc385f6bb1568aa974fe65da84723210e5d9707e360e9ecb51f59406cd2e", size = 1793265 },
-    { url = "https://files.pythonhosted.org/packages/40/7f/6de218084f9b653026bd7063cd8045123a7ba90c25176465f266976d8c82/aiohttp-3.11.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a8f5f7515f3552d899c61202d99dcb17d6e3b0de777900405611cd747cecd1b8", size = 1691841 },
-    { url = "https://files.pythonhosted.org/packages/77/e2/992f43d87831cbddb6b09c57ab55499332f60ad6fdbf438ff4419c2925fc/aiohttp-3.11.11-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3499c7ffbfd9c6a3d8d6a2b01c26639da7e43d47c7b4f788016226b1e711caa8", size = 1619317 },
-    { url = "https://files.pythonhosted.org/packages/96/74/879b23cdd816db4133325a201287c95bef4ce669acde37f8f1b8669e1755/aiohttp-3.11.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8e2bf8029dbf0810c7bfbc3e594b51c4cc9101fbffb583a3923aea184724203c", size = 1641416 },
-    { url = "https://files.pythonhosted.org/packages/30/98/b123f6b15d87c54e58fd7ae3558ff594f898d7f30a90899718f3215ad328/aiohttp-3.11.11-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:b6212a60e5c482ef90f2d788835387070a88d52cf6241d3916733c9176d39eab", size = 1646514 },
-    { url = "https://files.pythonhosted.org/packages/d7/38/257fda3dc99d6978ab943141d5165ec74fd4b4164baa15e9c66fa21da86b/aiohttp-3.11.11-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:d119fafe7b634dbfa25a8c597718e69a930e4847f0b88e172744be24515140da", size = 1702095 },
-    { url = "https://files.pythonhosted.org/packages/0c/f4/ddab089053f9fb96654df5505c0a69bde093214b3c3454f6bfdb1845f558/aiohttp-3.11.11-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:6fba278063559acc730abf49845d0e9a9e1ba74f85f0ee6efd5803f08b285853", size = 1734611 },
-    { url = "https://files.pythonhosted.org/packages/c3/d6/f30b2bc520c38c8aa4657ed953186e535ae84abe55c08d0f70acd72ff577/aiohttp-3.11.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:92fc484e34b733704ad77210c7957679c5c3877bd1e6b6d74b185e9320cc716e", size = 1694576 },
-    { url = "https://files.pythonhosted.org/packages/bc/97/b0a88c3f4c6d0020b34045ee6d954058abc870814f6e310c4c9b74254116/aiohttp-3.11.11-cp312-cp312-win32.whl", hash = "sha256:9f5b3c1ed63c8fa937a920b6c1bec78b74ee09593b3f5b979ab2ae5ef60d7600", size = 411363 },
-    { url = "https://files.pythonhosted.org/packages/7f/23/cc36d9c398980acaeeb443100f0216f50a7cfe20c67a9fd0a2f1a5a846de/aiohttp-3.11.11-cp312-cp312-win_amd64.whl", hash = "sha256:1e69966ea6ef0c14ee53ef7a3d68b564cc408121ea56c0caa2dc918c1b2f553d", size = 437666 },
+    { url = "https://files.pythonhosted.org/packages/3d/dd/3d40c0e67e79c5c42671e3e268742f1ff96c6573ca43823563d01abd9475/aiohttp-3.10.10-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:be7443669ae9c016b71f402e43208e13ddf00912f47f623ee5994e12fc7d4b3f", size = 586969 },
+    { url = "https://files.pythonhosted.org/packages/75/64/8de41b5555e5b43ef6d4ed1261891d33fe45ecc6cb62875bfafb90b9ab93/aiohttp-3.10.10-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:7b06b7843929e41a94ea09eb1ce3927865387e3e23ebe108e0d0d09b08d25be9", size = 399367 },
+    { url = "https://files.pythonhosted.org/packages/96/36/27bd62ea7ce43906d1443a73691823fc82ffb8fa03276b0e2f7e1037c286/aiohttp-3.10.10-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:333cf6cf8e65f6a1e06e9eb3e643a0c515bb850d470902274239fea02033e9a8", size = 390720 },
+    { url = "https://files.pythonhosted.org/packages/e8/4d/d516b050d811ce0dd26325c383013c104ffa8b58bd361b82e52833f68e78/aiohttp-3.10.10-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:274cfa632350225ce3fdeb318c23b4a10ec25c0e2c880eff951a3842cf358ac1", size = 1228820 },
+    { url = "https://files.pythonhosted.org/packages/53/94/964d9327a3e336d89aad52260836e4ec87fdfa1207176550fdf384eaffe7/aiohttp-3.10.10-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d9e5e4a85bdb56d224f412d9c98ae4cbd032cc4f3161818f692cd81766eee65a", size = 1264616 },
+    { url = "https://files.pythonhosted.org/packages/0c/20/70ce17764b685ca8f5bf4d568881b4e1f1f4ea5e8170f512fdb1a33859d2/aiohttp-3.10.10-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:2b606353da03edcc71130b52388d25f9a30a126e04caef1fd637e31683033abd", size = 1298402 },
+    { url = "https://files.pythonhosted.org/packages/d1/d1/5248225ccc687f498d06c3bca5af2647a361c3687a85eb3aedcc247ee1aa/aiohttp-3.10.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ab5a5a0c7a7991d90446a198689c0535be89bbd6b410a1f9a66688f0880ec026", size = 1222205 },
+    { url = "https://files.pythonhosted.org/packages/f2/a3/9296b27cc5d4feadf970a14d0694902a49a985f3fae71b8322a5f77b0baa/aiohttp-3.10.10-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:578a4b875af3e0daaf1ac6fa983d93e0bbfec3ead753b6d6f33d467100cdc67b", size = 1193804 },
+    { url = "https://files.pythonhosted.org/packages/d9/07/f3760160feb12ac51a6168a6da251a4a8f2a70733d49e6ceb9b3e6ee2f03/aiohttp-3.10.10-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:8105fd8a890df77b76dd3054cddf01a879fc13e8af576805d667e0fa0224c35d", size = 1193544 },
+    { url = "https://files.pythonhosted.org/packages/7e/4c/93a70f9a4ba1c30183a6dd68bfa79cddbf9a674f162f9c62e823a74a5515/aiohttp-3.10.10-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:3bcd391d083f636c06a68715e69467963d1f9600f85ef556ea82e9ef25f043f7", size = 1193047 },
+    { url = "https://files.pythonhosted.org/packages/ff/a3/36a1e23ff00c7a0cd696c5a28db05db25dc42bfc78c508bd78623ff62a4a/aiohttp-3.10.10-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:fbc6264158392bad9df19537e872d476f7c57adf718944cc1e4495cbabf38e2a", size = 1247201 },
+    { url = "https://files.pythonhosted.org/packages/55/ae/95399848557b98bb2c402d640b2276ce3a542b94dba202de5a5a1fe29abe/aiohttp-3.10.10-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:e48d5021a84d341bcaf95c8460b152cfbad770d28e5fe14a768988c461b821bc", size = 1264102 },
+    { url = "https://files.pythonhosted.org/packages/38/f5/02e5c72c1b60d7cceb30b982679a26167e84ac029fd35a93dd4da52c50a3/aiohttp-3.10.10-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:2609e9ab08474702cc67b7702dbb8a80e392c54613ebe80db7e8dbdb79837c68", size = 1215760 },
+    { url = "https://files.pythonhosted.org/packages/30/17/1463840bad10d02d0439068f37ce5af0b383884b0d5838f46fb027e233bf/aiohttp-3.10.10-cp310-cp310-win32.whl", hash = "sha256:84afcdea18eda514c25bc68b9af2a2b1adea7c08899175a51fe7c4fb6d551257", size = 362678 },
+    { url = "https://files.pythonhosted.org/packages/dd/01/a0ef707d93e867a43abbffee3a2cdf30559910750b9176b891628c7ad074/aiohttp-3.10.10-cp310-cp310-win_amd64.whl", hash = "sha256:9c72109213eb9d3874f7ac8c0c5fa90e072d678e117d9061c06e30c85b4cf0e6", size = 381097 },
+    { url = "https://files.pythonhosted.org/packages/72/31/3c351d17596194e5a38ef169a4da76458952b2497b4b54645b9d483cbbb0/aiohttp-3.10.10-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:c30a0eafc89d28e7f959281b58198a9fa5e99405f716c0289b7892ca345fe45f", size = 586501 },
+    { url = "https://files.pythonhosted.org/packages/a4/a8/a559d09eb08478cdead6b7ce05b0c4a133ba27fcdfa91e05d2e62867300d/aiohttp-3.10.10-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:258c5dd01afc10015866114e210fb7365f0d02d9d059c3c3415382ab633fcbcb", size = 398993 },
+    { url = "https://files.pythonhosted.org/packages/c5/47/7736d4174613feef61d25332c3bd1a4f8ff5591fbd7331988238a7299485/aiohttp-3.10.10-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:15ecd889a709b0080f02721255b3f80bb261c2293d3c748151274dfea93ac871", size = 390647 },
+    { url = "https://files.pythonhosted.org/packages/27/21/e9ba192a04b7160f5a8952c98a1de7cf8072ad150fa3abd454ead1ab1d7f/aiohttp-3.10.10-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f3935f82f6f4a3820270842e90456ebad3af15810cf65932bd24da4463bc0a4c", size = 1306481 },
+    { url = "https://files.pythonhosted.org/packages/cf/50/f364c01c8d0def1dc34747b2470969e216f5a37c7ece00fe558810f37013/aiohttp-3.10.10-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:413251f6fcf552a33c981c4709a6bba37b12710982fec8e558ae944bfb2abd38", size = 1344652 },
+    { url = "https://files.pythonhosted.org/packages/1d/c2/74f608e984e9b585649e2e83883facad6fa3fc1d021de87b20cc67e8e5ae/aiohttp-3.10.10-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d1720b4f14c78a3089562b8875b53e36b51c97c51adc53325a69b79b4b48ebcb", size = 1378498 },
+    { url = "https://files.pythonhosted.org/packages/9f/a7/05a48c7c0a7a80a5591b1203bf1b64ca2ed6a2050af918d09c05852dc42b/aiohttp-3.10.10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:679abe5d3858b33c2cf74faec299fda60ea9de62916e8b67e625d65bf069a3b7", size = 1292718 },
+    { url = "https://files.pythonhosted.org/packages/7d/78/a925655018747e9790350180330032e27d6e0d7ed30bde545fae42f8c49c/aiohttp-3.10.10-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:79019094f87c9fb44f8d769e41dbb664d6e8fcfd62f665ccce36762deaa0e911", size = 1251776 },
+    { url = "https://files.pythonhosted.org/packages/47/9d/85c6b69f702351d1236594745a4fdc042fc43f494c247a98dac17e004026/aiohttp-3.10.10-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:fe2fb38c2ed905a2582948e2de560675e9dfbee94c6d5ccdb1301c6d0a5bf092", size = 1271716 },
+    { url = "https://files.pythonhosted.org/packages/7f/a7/55fc805ff9b14af818903882ece08e2235b12b73b867b521b92994c52b14/aiohttp-3.10.10-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:a3f00003de6eba42d6e94fabb4125600d6e484846dbf90ea8e48a800430cc142", size = 1266263 },
+    { url = "https://files.pythonhosted.org/packages/1f/ec/d2be2ca7b063e4f91519d550dbc9c1cb43040174a322470deed90b3d3333/aiohttp-3.10.10-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:1bbb122c557a16fafc10354b9d99ebf2f2808a660d78202f10ba9d50786384b9", size = 1321617 },
+    { url = "https://files.pythonhosted.org/packages/c9/a3/b29f7920e1cd0a9a68a45dd3eb16140074d2efb1518d2e1f3e140357dc37/aiohttp-3.10.10-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:30ca7c3b94708a9d7ae76ff281b2f47d8eaf2579cd05971b5dc681db8caac6e1", size = 1339227 },
+    { url = "https://files.pythonhosted.org/packages/8a/81/34b67235c47e232d807b4bbc42ba9b927c7ce9476872372fddcfd1e41b3d/aiohttp-3.10.10-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:df9270660711670e68803107d55c2b5949c2e0f2e4896da176e1ecfc068b974a", size = 1299068 },
+    { url = "https://files.pythonhosted.org/packages/04/1f/26a7fe11b6ad3184f214733428353c89ae9fe3e4f605a657f5245c5e720c/aiohttp-3.10.10-cp311-cp311-win32.whl", hash = "sha256:aafc8ee9b742ce75044ae9a4d3e60e3d918d15a4c2e08a6c3c3e38fa59b92d94", size = 362223 },
+    { url = "https://files.pythonhosted.org/packages/10/91/85dcd93f64011434359ce2666bece981f08d31bc49df33261e625b28595d/aiohttp-3.10.10-cp311-cp311-win_amd64.whl", hash = "sha256:362f641f9071e5f3ee6f8e7d37d5ed0d95aae656adf4ef578313ee585b585959", size = 381576 },
+    { url = "https://files.pythonhosted.org/packages/ae/99/4c5aefe5ad06a1baf206aed6598c7cdcbc7c044c46801cd0d1ecb758cae3/aiohttp-3.10.10-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:9294bbb581f92770e6ed5c19559e1e99255e4ca604a22c5c6397b2f9dd3ee42c", size = 583536 },
+    { url = "https://files.pythonhosted.org/packages/a9/36/8b3bc49b49cb6d2da40ee61ff15dbcc44fd345a3e6ab5bb20844df929821/aiohttp-3.10.10-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:a8fa23fe62c436ccf23ff930149c047f060c7126eae3ccea005f0483f27b2e28", size = 395693 },
+    { url = "https://files.pythonhosted.org/packages/e1/77/0aa8660dcf11fa65d61712dbb458c4989de220a844bd69778dff25f2d50b/aiohttp-3.10.10-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5c6a5b8c7926ba5d8545c7dd22961a107526562da31a7a32fa2456baf040939f", size = 390898 },
+    { url = "https://files.pythonhosted.org/packages/38/d2/b833d95deb48c75db85bf6646de0a697e7fb5d87bd27cbade4f9746b48b1/aiohttp-3.10.10-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:007ec22fbc573e5eb2fb7dec4198ef8f6bf2fe4ce20020798b2eb5d0abda6138", size = 1312060 },
+    { url = "https://files.pythonhosted.org/packages/aa/5f/29fd5113165a0893de8efedf9b4737e0ba92dfcd791415a528f947d10299/aiohttp-3.10.10-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9627cc1a10c8c409b5822a92d57a77f383b554463d1884008e051c32ab1b3742", size = 1350553 },
+    { url = "https://files.pythonhosted.org/packages/ad/cc/f835f74b7d344428469200105236d44606cfa448be1e7c95ca52880d9bac/aiohttp-3.10.10-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:50edbcad60d8f0e3eccc68da67f37268b5144ecc34d59f27a02f9611c1d4eec7", size = 1392646 },
+    { url = "https://files.pythonhosted.org/packages/bf/fe/1332409d845ca601893bbf2d76935e0b93d41686e5f333841c7d7a4a770d/aiohttp-3.10.10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a45d85cf20b5e0d0aa5a8dca27cce8eddef3292bc29d72dcad1641f4ed50aa16", size = 1306310 },
+    { url = "https://files.pythonhosted.org/packages/e4/a1/25a7633a5a513278a9892e333501e2e69c83e50be4b57a62285fb7a008c3/aiohttp-3.10.10-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0b00807e2605f16e1e198f33a53ce3c4523114059b0c09c337209ae55e3823a8", size = 1260255 },
+    { url = "https://files.pythonhosted.org/packages/f2/39/30eafe89e0e2a06c25e4762844c8214c0c0cd0fd9ffc3471694a7986f421/aiohttp-3.10.10-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:f2d4324a98062be0525d16f768a03e0bbb3b9fe301ceee99611dc9a7953124e6", size = 1271141 },
+    { url = "https://files.pythonhosted.org/packages/5b/fc/33125df728b48391ef1fcb512dfb02072158cc10d041414fb79803463020/aiohttp-3.10.10-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:438cd072f75bb6612f2aca29f8bd7cdf6e35e8f160bc312e49fbecab77c99e3a", size = 1280244 },
+    { url = "https://files.pythonhosted.org/packages/3b/61/e42bf2c2934b5caa4e2ec0b5e5fd86989adb022b5ee60c2572a9d77cf6fe/aiohttp-3.10.10-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:baa42524a82f75303f714108fea528ccacf0386af429b69fff141ffef1c534f9", size = 1316805 },
+    { url = "https://files.pythonhosted.org/packages/18/32/f52a5e2ae9ad3bba10e026a63a7a23abfa37c7d97aeeb9004eaa98df3ce3/aiohttp-3.10.10-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:a7d8d14fe962153fc681f6366bdec33d4356f98a3e3567782aac1b6e0e40109a", size = 1343930 },
+    { url = "https://files.pythonhosted.org/packages/05/be/6a403b464dcab3631fe8e27b0f1d906d9e45c5e92aca97ee007e5a895560/aiohttp-3.10.10-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:c1277cd707c465cd09572a774559a3cc7c7a28802eb3a2a9472588f062097205", size = 1306186 },
+    { url = "https://files.pythonhosted.org/packages/8e/fd/bb50fe781068a736a02bf5c7ad5f3ab53e39f1d1e63110da6d30f7605edc/aiohttp-3.10.10-cp312-cp312-win32.whl", hash = "sha256:59bb3c54aa420521dc4ce3cc2c3fe2ad82adf7b09403fa1f48ae45c0cbde6628", size = 359289 },
+    { url = "https://files.pythonhosted.org/packages/70/9e/5add7e240f77ef67c275c82cc1d08afbca57b77593118c1f6e920ae8ad3f/aiohttp-3.10.10-cp312-cp312-win_amd64.whl", hash = "sha256:0e1b370d8007c4ae31ee6db7f9a2fe801a42b146cec80a86766e7ad5c4a259cf", size = 379313 },
 ]
 
 [[package]]
@@ -244,18 +211,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/e4/0e/38cb7b781371e79e9c697fb78f3ccd18fda8bd547d0a2e76e616561a3792/auth0_python-4.7.2-py3-none-any.whl", hash = "sha256:df2224f9b1e170b3aa12d8bc7ff02eadb7cc229307a09ec6b8a55fd1e0e05dc8", size = 131834 },
 ]
 
-[[package]]
-name = "authlib"
-version = "1.3.1"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "cryptography" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/09/47/df70ecd34fbf86d69833fe4e25bb9ecbaab995c8e49df726dd416f6bb822/authlib-1.3.1.tar.gz", hash = "sha256:7ae843f03c06c5c0debd63c9db91f9fda64fa62a42a77419fa15fbb7e7a58917", size = 146074 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/87/1f/bc95e43ffb57c05b8efcc376dd55a0240bf58f47ddf5a0f92452b6457b75/Authlib-1.3.1-py2.py3-none-any.whl", hash = "sha256:d35800b973099bbadc49b42b256ecb80041ad56b7fe1216a362c7943c088f377", size = 223827 },
-]
-
 [[package]]
 name = "autoflake"
 version = "2.3.1"
@@ -665,9 +620,6 @@ agentops = [
 docling = [
     { name = "docling" },
 ]
-embeddings = [
-    { name = "tiktoken" },
-]
 fastembed = [
     { name = "fastembed" },
 ]
@@ -690,6 +642,7 @@ tools = [
 [package.dev-dependencies]
 dev = [
     { name = "cairosvg" },
+    { name = "crewai-tools" },
     { name = "mkdocs" },
     { name = "mkdocs-material" },
     { name = "mkdocs-material-extensions" },
@@ -714,7 +667,7 @@ requires-dist = [
     { name = "blinker", specifier = ">=1.9.0" },
     { name = "chromadb", specifier = ">=0.5.23" },
     { name = "click", specifier = ">=8.1.7" },
-    { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.25.5" },
+    { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.17.0" },
     { name = "docling", marker = "extra == 'docling'", specifier = ">=2.12.0" },
     { name = "fastembed", marker = "extra == 'fastembed'", specifier = ">=0.4.1" },
     { name = "instructor", specifier = ">=1.3.3" },
@@ -735,7 +688,6 @@ requires-dist = [
     { name = "python-dotenv", specifier = ">=1.0.0" },
     { name = "pyvis", specifier = ">=0.3.2" },
     { name = "regex", specifier = ">=2024.9.11" },
-    { name = "tiktoken", marker = "extra == 'embeddings'", specifier = "~=0.7.0" },
     { name = "tomli", specifier = ">=2.0.2" },
     { name = "tomli-w", specifier = ">=1.1.0" },
     { name = "uv", specifier = ">=0.4.25" },
@@ -744,6 +696,7 @@ requires-dist = [
 [package.metadata.requires-dev]
 dev = [
     { name = "cairosvg", specifier = ">=2.7.1" },
+    { name = "crewai-tools", specifier = ">=0.17.0" },
     { name = "mkdocs", specifier = ">=1.4.3" },
     { name = "mkdocs-material", specifier = ">=9.5.7" },
     { name = "mkdocs-material-extensions", specifier = ">=1.3.1" },
@@ -762,32 +715,26 @@ dev = [
 
 [[package]]
 name = "crewai-tools"
-version = "0.25.6"
+version = "0.17.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "beautifulsoup4" },
     { name = "chromadb" },
-    { name = "crewai" },
     { name = "docker" },
     { name = "docx2txt" },
     { name = "embedchain" },
     { name = "lancedb" },
-    { name = "linkup-sdk" },
     { name = "openai" },
     { name = "pydantic" },
     { name = "pyright" },
     { name = "pytest" },
     { name = "pytube" },
     { name = "requests" },
-    { name = "scrapegraph-py" },
     { name = "selenium" },
-    { name = "serpapi" },
-    { name = "spider-client" },
-    { name = "weaviate-client" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/23/2f/fbfd0dc8912d375a2d1272c503f79c83c25f3d2b4b72c230b0672278a1bd/crewai_tools-0.25.6.tar.gz", hash = "sha256:442a7e7e579cb3c671a53c5b7afce645cd31d2db913ecc6d1e22a4c5e1baa840", size = 883175 }
+sdist = { url = "https://files.pythonhosted.org/packages/cc/15/365f74e0e8313e7a3399bf01d908aa73575c823275f9196ec14c23159878/crewai_tools-0.17.0.tar.gz", hash = "sha256:2a2986000775c76bad45b9f3a2be857d293cf5daffe5f316abc052e630b1e5ce", size = 818983 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/ce/21/561a81b4f8cfcc2ac6a0c3db3ec86b70a7db6dabb0dd7d13c96be981b2fc/crewai_tools-0.25.6-py3-none-any.whl", hash = "sha256:463e0ee8d780ab7a801992e3960471fb8e64d038866429f70995ddd0a83e0679", size = 514758 },
+    { url = "https://files.pythonhosted.org/packages/f4/1d/976adc2a4e5237cb03625de412cd051dea7d524084ed442adedfda871526/crewai_tools-0.17.0-py3-none-any.whl", hash = "sha256:85cf15286684ecad579b5a497888c6bf8a079ca443f7dd63a52bf1709655e4a3", size = 467975 },
 ]
 
 [[package]]
@@ -1625,19 +1572,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/1d/1f/acf03ee901313446d52c3916d527d4981de9f6f3edc69267d05509dcfa7b/grpcio-1.67.0-cp312-cp312-win_amd64.whl", hash = "sha256:985b2686f786f3e20326c4367eebdaed3e7aa65848260ff0c6644f817042cb15", size = 4343545 },
 ]
 
-[[package]]
-name = "grpcio-health-checking"
-version = "1.62.3"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "grpcio" },
-    { name = "protobuf" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/eb/9f/09df9b02fc8eafa3031d878c8a4674a0311293c8c6f1c942cdaeec204126/grpcio-health-checking-1.62.3.tar.gz", hash = "sha256:5074ba0ce8f0dcfe328408ec5c7551b2a835720ffd9b69dade7fa3e0dc1c7a93", size = 15640 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/40/4c/ee3173906196b741ac6ba55a9788ba9ebf2cd05f91715a49b6c3bfbb9d73/grpcio_health_checking-1.62.3-py3-none-any.whl", hash = "sha256:f29da7dd144d73b4465fe48f011a91453e9ff6c8af0d449254cf80021cab3e0d", size = 18547 },
-]
-
 [[package]]
 name = "grpcio-status"
 version = "1.62.3"
@@ -1764,7 +1698,7 @@ wheels = [
 
 [[package]]
 name = "httpx"
-version = "0.27.0"
+version = "0.27.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "anyio" },
@@ -1773,9 +1707,9 @@ dependencies = [
     { name = "idna" },
     { name = "sniffio" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/5c/2d/3da5bdf4408b8b2800061c339f240c1802f2e82d55e50bd39c5a881f47f0/httpx-0.27.0.tar.gz", hash = "sha256:a0cb88a46f32dc874e04ee956e4c2764aba2aa228f650b06788ba6bda2962ab5", size = 126413 }
+sdist = { url = "https://files.pythonhosted.org/packages/78/82/08f8c936781f67d9e6b9eeb8a0c8b4e406136ea4c3d1f89a5db71d42e0e6/httpx-0.27.2.tar.gz", hash = "sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2", size = 144189 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/41/7b/ddacf6dcebb42466abd03f368782142baa82e08fc0c1f8eaa05b4bae87d5/httpx-0.27.0-py3-none-any.whl", hash = "sha256:71d5465162c13681bff01ad59b2cc68dd838ea1f10e51574bac27103f00c91a5", size = 75590 },
+    { url = "https://files.pythonhosted.org/packages/56/95/9377bcb415797e44274b51d46e3249eba641711cf3348050f76ee7b15ffc/httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0", size = 76395 },
 ]
 
 [package.optional-dependencies]
@@ -1849,52 +1783,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/76/c6/c88e154df9c4e1a2a66ccf0005a88dfb2650c1dffb6f5ce603dfbd452ce3/idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3", size = 70442 },
 ]
 
-[[package]]
-name = "ijson"
-version = "3.3.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/6c/83/28e9e93a3a61913e334e3a2e78ea9924bb9f9b1ac45898977f9d9dd6133f/ijson-3.3.0.tar.gz", hash = "sha256:7f172e6ba1bee0d4c8f8ebd639577bfe429dee0f3f96775a067b8bae4492d8a0", size = 60079 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/ad/89/96e3608499b4a500b9bc27aa8242704e675849dd65bdfa8682b00a92477e/ijson-3.3.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7f7a5250599c366369fbf3bc4e176f5daa28eb6bc7d6130d02462ed335361675", size = 85009 },
-    { url = "https://files.pythonhosted.org/packages/e4/7e/1098503500f5316c5f7912a51c91aca5cbc609c09ce4ecd9c4809983c560/ijson-3.3.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:f87a7e52f79059f9c58f6886c262061065eb6f7554a587be7ed3aa63e6b71b34", size = 57796 },
-    { url = "https://files.pythonhosted.org/packages/78/f7/27b8c27a285628719ff55b68507581c86b551eb162ce810fe51e3e1a25f2/ijson-3.3.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b73b493af9e947caed75d329676b1b801d673b17481962823a3e55fe529c8b8b", size = 57218 },
-    { url = "https://files.pythonhosted.org/packages/0c/c5/1698094cb6a336a223c30e1167cc1b15cdb4bfa75399c1a2eb82fa76cc3c/ijson-3.3.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d5576415f3d76290b160aa093ff968f8bf6de7d681e16e463a0134106b506f49", size = 117153 },
-    { url = "https://files.pythonhosted.org/packages/4b/21/c206dda0945bd832cc9b0894596b0efc2cb1819a0ac61d8be1429ac09494/ijson-3.3.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:4e9ffe358d5fdd6b878a8a364e96e15ca7ca57b92a48f588378cef315a8b019e", size = 110781 },
-    { url = "https://files.pythonhosted.org/packages/f4/f5/2d733e64577109a9b255d14d031e44a801fa20df9ccc58b54a31e8ecf9e6/ijson-3.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8643c255a25824ddd0895c59f2319c019e13e949dc37162f876c41a283361527", size = 114527 },
-    { url = "https://files.pythonhosted.org/packages/8d/a8/78bfee312aa23417b86189a65f30b0edbceaee96dc6a616cc15f611187d1/ijson-3.3.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:df3ab5e078cab19f7eaeef1d5f063103e1ebf8c26d059767b26a6a0ad8b250a3", size = 116824 },
-    { url = "https://files.pythonhosted.org/packages/5d/a4/aff410f7d6aa1a77ee2ab2d6a2d2758422726270cb149c908a9baf33cf58/ijson-3.3.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:3dc1fb02c6ed0bae1b4bf96971258bf88aea72051b6e4cebae97cff7090c0607", size = 112647 },
-    { url = "https://files.pythonhosted.org/packages/77/ee/2b5122dc4713f5a954267147da36e7156240ca21b04ed5295bc0cabf0fbe/ijson-3.3.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:e9afd97339fc5a20f0542c971f90f3ca97e73d3050cdc488d540b63fae45329a", size = 114156 },
-    { url = "https://files.pythonhosted.org/packages/b3/d7/ad3b266490b60c6939e8a07fd8e4b7e2002aea08eaa9572a016c3e3a9129/ijson-3.3.0-cp310-cp310-win32.whl", hash = "sha256:844c0d1c04c40fd1b60f148dc829d3f69b2de789d0ba239c35136efe9a386529", size = 48931 },
-    { url = "https://files.pythonhosted.org/packages/0b/68/b9e1c743274c8a23dddb12d2ed13b5f021f6d21669d51ff7fa2e9e6c19df/ijson-3.3.0-cp310-cp310-win_amd64.whl", hash = "sha256:d654d045adafdcc6c100e8e911508a2eedbd2a1b5f93f930ba13ea67d7704ee9", size = 50965 },
-    { url = "https://files.pythonhosted.org/packages/fd/df/565ba72a6f4b2c833d051af8e2228cfa0b1fef17bb44995c00ad27470c52/ijson-3.3.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:501dce8eaa537e728aa35810656aa00460a2547dcb60937c8139f36ec344d7fc", size = 85041 },
-    { url = "https://files.pythonhosted.org/packages/f0/42/1361eaa57ece921d0239881bae6a5e102333be5b6e0102a05ec3caadbd5a/ijson-3.3.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:658ba9cad0374d37b38c9893f4864f284cdcc7d32041f9808fba8c7bcaadf134", size = 57829 },
-    { url = "https://files.pythonhosted.org/packages/f5/b0/143dbfe12e1d1303ea8d8cd6f40e95cea8f03bcad5b79708614a7856c22e/ijson-3.3.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2636cb8c0f1023ef16173f4b9a233bcdb1df11c400c603d5f299fac143ca8d70", size = 57217 },
-    { url = "https://files.pythonhosted.org/packages/0d/80/b3b60c5e5be2839365b03b915718ca462c544fdc71e7a79b7262837995ef/ijson-3.3.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cd174b90db68c3bcca273e9391934a25d76929d727dc75224bf244446b28b03b", size = 121878 },
-    { url = "https://files.pythonhosted.org/packages/8d/eb/7560fafa4d40412efddf690cb65a9bf2d3429d6035e544103acbf5561dc4/ijson-3.3.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:97a9aea46e2a8371c4cf5386d881de833ed782901ac9f67ebcb63bb3b7d115af", size = 115620 },
-    { url = "https://files.pythonhosted.org/packages/51/2b/5a34c7841388dce161966e5286931518de832067cd83e6f003d93271e324/ijson-3.3.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c594c0abe69d9d6099f4ece17763d53072f65ba60b372d8ba6de8695ce6ee39e", size = 119200 },
-    { url = "https://files.pythonhosted.org/packages/3e/b7/1d64fbec0d0a7b0c02e9ad988a89614532028ead8bb52a2456c92e6ee35a/ijson-3.3.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8e0ff16c224d9bfe4e9e6bd0395826096cda4a3ef51e6c301e1b61007ee2bd24", size = 121107 },
-    { url = "https://files.pythonhosted.org/packages/d4/b9/01044f09850bc545ffc85b35aaec473d4f4ca2b6667299033d252c1b60dd/ijson-3.3.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:0015354011303175eae7e2ef5136414e91de2298e5a2e9580ed100b728c07e51", size = 116658 },
-    { url = "https://files.pythonhosted.org/packages/fb/0d/53856b61f3d952d299d1695c487e8e28058d01fa2adfba3d6d4b4660c242/ijson-3.3.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:034642558afa57351a0ffe6de89e63907c4cf6849070cc10a3b2542dccda1afe", size = 118186 },
-    { url = "https://files.pythonhosted.org/packages/95/2d/5bd86e2307dd594840ee51c4e32de953fee837f028acf0f6afb08914cd06/ijson-3.3.0-cp311-cp311-win32.whl", hash = "sha256:192e4b65495978b0bce0c78e859d14772e841724d3269fc1667dc6d2f53cc0ea", size = 48938 },
-    { url = "https://files.pythonhosted.org/packages/55/e1/4ba2b65b87f67fb19d698984d92635e46d9ce9dd748ce7d009441a586710/ijson-3.3.0-cp311-cp311-win_amd64.whl", hash = "sha256:72e3488453754bdb45c878e31ce557ea87e1eb0f8b4fc610373da35e8074ce42", size = 50972 },
-    { url = "https://files.pythonhosted.org/packages/8a/4d/3992f7383e26a950e02dc704bc6c5786a080d5c25fe0fc5543ef477c1883/ijson-3.3.0-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:988e959f2f3d59ebd9c2962ae71b97c0df58323910d0b368cc190ad07429d1bb", size = 84550 },
-    { url = "https://files.pythonhosted.org/packages/1b/cc/3d4372e0d0b02a821b982f1fdf10385512dae9b9443c1597719dd37769a9/ijson-3.3.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:b2f73f0d0fce5300f23a1383d19b44d103bb113b57a69c36fd95b7c03099b181", size = 57572 },
-    { url = "https://files.pythonhosted.org/packages/02/de/970d48b1ff9da5d9513c86fdd2acef5cb3415541c8069e0d92a151b84adb/ijson-3.3.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:0ee57a28c6bf523d7cb0513096e4eb4dac16cd935695049de7608ec110c2b751", size = 56902 },
-    { url = "https://files.pythonhosted.org/packages/5e/a0/4537722c8b3b05e82c23dfe09a3a64dd1e44a013a5ca58b1e77dfe48b2f1/ijson-3.3.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e0155a8f079c688c2ccaea05de1ad69877995c547ba3d3612c1c336edc12a3a5", size = 127400 },
-    { url = "https://files.pythonhosted.org/packages/b2/96/54956062a99cf49f7a7064b573dcd756da0563ce57910dc34e27a473d9b9/ijson-3.3.0-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7ab00721304af1ae1afa4313ecfa1bf16b07f55ef91e4a5b93aeaa3e2bd7917c", size = 118786 },
-    { url = "https://files.pythonhosted.org/packages/07/74/795319531c5b5504508f595e631d592957f24bed7ff51a15bc4c61e7b24c/ijson-3.3.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:40ee3821ee90be0f0e95dcf9862d786a7439bd1113e370736bfdf197e9765bfb", size = 126288 },
-    { url = "https://files.pythonhosted.org/packages/69/6a/e0cec06fbd98851d5d233b59058c1dc2ea767c9bb6feca41aa9164fff769/ijson-3.3.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:da3b6987a0bc3e6d0f721b42c7a0198ef897ae50579547b0345f7f02486898f5", size = 129569 },
-    { url = "https://files.pythonhosted.org/packages/2a/4f/82c0d896d8dcb175f99ced7d87705057bcd13523998b48a629b90139a0dc/ijson-3.3.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:63afea5f2d50d931feb20dcc50954e23cef4127606cc0ecf7a27128ed9f9a9e6", size = 121508 },
-    { url = "https://files.pythonhosted.org/packages/2b/b6/8973474eba4a917885e289d9e138267d3d1f052c2d93b8c968755661a42d/ijson-3.3.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b5c3e285e0735fd8c5a26d177eca8b52512cdd8687ca86ec77a0c66e9c510182", size = 127896 },
-    { url = "https://files.pythonhosted.org/packages/94/25/00e66af887adbbe70002e0479c3c2340bdfa17a168e25d4ab5a27b53582d/ijson-3.3.0-cp312-cp312-win32.whl", hash = "sha256:907f3a8674e489abdcb0206723e5560a5cb1fa42470dcc637942d7b10f28b695", size = 49272 },
-    { url = "https://files.pythonhosted.org/packages/25/a2/e187beee237808b2c417109ae0f4f7ee7c81ecbe9706305d6ac2a509cc45/ijson-3.3.0-cp312-cp312-win_amd64.whl", hash = "sha256:8f890d04ad33262d0c77ead53c85f13abfb82f2c8f078dfbf24b78f59534dfdd", size = 51272 },
-    { url = "https://files.pythonhosted.org/packages/c3/28/2e1cf00abe5d97aef074e7835b86a94c9a06be4629a0e2c12600792b51ba/ijson-3.3.0-pp310-pypy310_pp73-macosx_10_9_x86_64.whl", hash = "sha256:2af323a8aec8a50fa9effa6d640691a30a9f8c4925bd5364a1ca97f1ac6b9b5c", size = 54308 },
-    { url = "https://files.pythonhosted.org/packages/04/d2/8c541c28da4f931bac8177e251efe2b6902f7c486d2d4bdd669eed4ff5c0/ijson-3.3.0-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f64f01795119880023ba3ce43072283a393f0b90f52b66cc0ea1a89aa64a9ccb", size = 66010 },
-    { url = "https://files.pythonhosted.org/packages/d0/02/8fec0b9037a368811dba7901035e8e0973ebda308f57f30c42101a16a5f7/ijson-3.3.0-pp310-pypy310_pp73-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a716e05547a39b788deaf22725490855337fc36613288aa8ae1601dc8c525553", size = 66770 },
-    { url = "https://files.pythonhosted.org/packages/47/23/90c61f978c83647112460047ea0137bde9c7fe26600ce255bb3e17ea7a21/ijson-3.3.0-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:473f5d921fadc135d1ad698e2697025045cd8ed7e5e842258295012d8a3bc702", size = 64159 },
-    { url = "https://files.pythonhosted.org/packages/20/af/aab1a36072590af62d848f03981f1c587ca40a391fc61e418e388d8b0d46/ijson-3.3.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:dd26b396bc3a1e85f4acebeadbf627fa6117b97f4c10b177d5779577c6607744", size = 51095 },
-]
-
 [[package]]
 name = "imageio"
 version = "2.36.1"
@@ -2329,19 +2217,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/83/60/d497a310bde3f01cb805196ac61b7ad6dc5dcf8dce66634dc34364b20b4f/lazy_loader-0.4-py3-none-any.whl", hash = "sha256:342aa8e14d543a154047afb4ba8ef17f5563baad3fc610d7b15b213b0f119efc", size = 12097 },
 ]
 
-[[package]]
-name = "linkup-sdk"
-version = "0.2.1"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "httpx" },
-    { name = "pydantic" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/2e/ba/b06e8f2ca2f0ce255a40ee4505637536acfe83ec997cd8b61bd5cd031513/linkup_sdk-0.2.1.tar.gz", hash = "sha256:b00ba7cb0117358e975d50196501ac49b247509fd236121e40abe40e6a2a3e9a", size = 8918 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/4f/90/2903b9e2eba501ceb6c6b4fc57bbeddde7e8964921a05d424f5a6125cbd0/linkup_sdk-0.2.1-py3-none-any.whl", hash = "sha256:bf50c88e659c6d9291cbd5e3e99b6a20a14c9b1eb2dc7acca763a3ae6f84b26e", size = 7961 },
-]
-
 [[package]]
 name = "litellm"
 version = "1.50.2"
@@ -3015,7 +2890,7 @@ name = "nvidia-cudnn-cu12"
 version = "9.1.0.70"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
+    { name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/9f/fd/713452cd72343f682b1c7b9321e23829f00b842ceaedcda96e742ea0b0b3/nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl", hash = "sha256:165764f44ef8c61fcdfdfdbe769d687e06374059fbb388b6c89ecb0e28793a6f", size = 664752741 },
@@ -3042,9 +2917,9 @@ name = "nvidia-cusolver-cu12"
 version = "11.4.5.107"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
-    { name = "nvidia-cusparse-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
-    { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
+    { name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
+    { name = "nvidia-cusparse-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
+    { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/bc/1d/8de1e5c67099015c834315e333911273a8c6aaba78923dd1d1e25fc5f217/nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl", hash = "sha256:8a7ec542f0412294b15072fa7dab71d31334014a69f953004ea7a118206fe0dd", size = 124161928 },
@@ -3055,7 +2930,7 @@ name = "nvidia-cusparse-cu12"
 version = "12.1.0.106"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
+    { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/65/5b/cfaeebf25cd9fdec14338ccb16f6b2c4c7fa9163aefcf057d86b9cc248bb/nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:f3b50f42cf363f86ab21f720998517a659a48131e8d538dc02f8768237bd884c", size = 195958278 },
@@ -3912,77 +3787,71 @@ wheels = [
 
 [[package]]
 name = "pydantic"
-version = "2.10.4"
+version = "2.9.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "annotated-types" },
     { name = "pydantic-core" },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/70/7e/fb60e6fee04d0ef8f15e4e01ff187a196fa976eb0f0ab524af4599e5754c/pydantic-2.10.4.tar.gz", hash = "sha256:82f12e9723da6de4fe2ba888b5971157b3be7ad914267dea8f05f82b28254f06", size = 762094 }
+sdist = { url = "https://files.pythonhosted.org/packages/a9/b7/d9e3f12af310e1120c21603644a1cd86f59060e040ec5c3a80b8f05fae30/pydantic-2.9.2.tar.gz", hash = "sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f", size = 769917 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/f3/26/3e1bbe954fde7ee22a6e7d31582c642aad9e84ffe4b5fb61e63b87cd326f/pydantic-2.10.4-py3-none-any.whl", hash = "sha256:597e135ea68be3a37552fb524bc7d0d66dcf93d395acd93a00682f1efcb8ee3d", size = 431765 },
+    { url = "https://files.pythonhosted.org/packages/df/e4/ba44652d562cbf0bf320e0f3810206149c8a4e99cdbf66da82e97ab53a15/pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12", size = 434928 },
 ]
 
 [[package]]
 name = "pydantic-core"
-version = "2.27.2"
+version = "2.23.4"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/fc/01/f3e5ac5e7c25833db5eb555f7b7ab24cd6f8c322d3a3ad2d67a952dc0abc/pydantic_core-2.27.2.tar.gz", hash = "sha256:eb026e5a4c1fee05726072337ff51d1efb6f59090b7da90d30ea58625b1ffb39", size = 413443 }
+sdist = { url = "https://files.pythonhosted.org/packages/e2/aa/6b6a9b9f8537b872f552ddd46dd3da230367754b6f707b8e1e963f515ea3/pydantic_core-2.23.4.tar.gz", hash = "sha256:2584f7cf844ac4d970fba483a717dbe10c1c1c96a969bf65d61ffe94df1b2863", size = 402156 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/3a/bc/fed5f74b5d802cf9a03e83f60f18864e90e3aed7223adaca5ffb7a8d8d64/pydantic_core-2.27.2-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:2d367ca20b2f14095a8f4fa1210f5a7b78b8a20009ecced6b12818f455b1e9fa", size = 1895938 },
-    { url = "https://files.pythonhosted.org/packages/71/2a/185aff24ce844e39abb8dd680f4e959f0006944f4a8a0ea372d9f9ae2e53/pydantic_core-2.27.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:491a2b73db93fab69731eaee494f320faa4e093dbed776be1a829c2eb222c34c", size = 1815684 },
-    { url = "https://files.pythonhosted.org/packages/c3/43/fafabd3d94d159d4f1ed62e383e264f146a17dd4d48453319fd782e7979e/pydantic_core-2.27.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7969e133a6f183be60e9f6f56bfae753585680f3b7307a8e555a948d443cc05a", size = 1829169 },
-    { url = "https://files.pythonhosted.org/packages/a2/d1/f2dfe1a2a637ce6800b799aa086d079998959f6f1215eb4497966efd2274/pydantic_core-2.27.2-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3de9961f2a346257caf0aa508a4da705467f53778e9ef6fe744c038119737ef5", size = 1867227 },
-    { url = "https://files.pythonhosted.org/packages/7d/39/e06fcbcc1c785daa3160ccf6c1c38fea31f5754b756e34b65f74e99780b5/pydantic_core-2.27.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e2bb4d3e5873c37bb3dd58714d4cd0b0e6238cebc4177ac8fe878f8b3aa8e74c", size = 2037695 },
-    { url = "https://files.pythonhosted.org/packages/7a/67/61291ee98e07f0650eb756d44998214231f50751ba7e13f4f325d95249ab/pydantic_core-2.27.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:280d219beebb0752699480fe8f1dc61ab6615c2046d76b7ab7ee38858de0a4e7", size = 2741662 },
-    { url = "https://files.pythonhosted.org/packages/32/90/3b15e31b88ca39e9e626630b4c4a1f5a0dfd09076366f4219429e6786076/pydantic_core-2.27.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47956ae78b6422cbd46f772f1746799cbb862de838fd8d1fbd34a82e05b0983a", size = 1993370 },
-    { url = "https://files.pythonhosted.org/packages/ff/83/c06d333ee3a67e2e13e07794995c1535565132940715931c1c43bfc85b11/pydantic_core-2.27.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:14d4a5c49d2f009d62a2a7140d3064f686d17a5d1a268bc641954ba181880236", size = 1996813 },
-    { url = "https://files.pythonhosted.org/packages/7c/f7/89be1c8deb6e22618a74f0ca0d933fdcb8baa254753b26b25ad3acff8f74/pydantic_core-2.27.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:337b443af21d488716f8d0b6164de833e788aa6bd7e3a39c005febc1284f4962", size = 2005287 },
-    { url = "https://files.pythonhosted.org/packages/b7/7d/8eb3e23206c00ef7feee17b83a4ffa0a623eb1a9d382e56e4aa46fd15ff2/pydantic_core-2.27.2-cp310-cp310-musllinux_1_1_armv7l.whl", hash = "sha256:03d0f86ea3184a12f41a2d23f7ccb79cdb5a18e06993f8a45baa8dfec746f0e9", size = 2128414 },
-    { url = "https://files.pythonhosted.org/packages/4e/99/fe80f3ff8dd71a3ea15763878d464476e6cb0a2db95ff1c5c554133b6b83/pydantic_core-2.27.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:7041c36f5680c6e0f08d922aed302e98b3745d97fe1589db0a3eebf6624523af", size = 2155301 },
-    { url = "https://files.pythonhosted.org/packages/2b/a3/e50460b9a5789ca1451b70d4f52546fa9e2b420ba3bfa6100105c0559238/pydantic_core-2.27.2-cp310-cp310-win32.whl", hash = "sha256:50a68f3e3819077be2c98110c1f9dcb3817e93f267ba80a2c05bb4f8799e2ff4", size = 1816685 },
-    { url = "https://files.pythonhosted.org/packages/57/4c/a8838731cb0f2c2a39d3535376466de6049034d7b239c0202a64aaa05533/pydantic_core-2.27.2-cp310-cp310-win_amd64.whl", hash = "sha256:e0fd26b16394ead34a424eecf8a31a1f5137094cabe84a1bcb10fa6ba39d3d31", size = 1982876 },
-    { url = "https://files.pythonhosted.org/packages/c2/89/f3450af9d09d44eea1f2c369f49e8f181d742f28220f88cc4dfaae91ea6e/pydantic_core-2.27.2-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:8e10c99ef58cfdf2a66fc15d66b16c4a04f62bca39db589ae8cba08bc55331bc", size = 1893421 },
-    { url = "https://files.pythonhosted.org/packages/9e/e3/71fe85af2021f3f386da42d291412e5baf6ce7716bd7101ea49c810eda90/pydantic_core-2.27.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:26f32e0adf166a84d0cb63be85c562ca8a6fa8de28e5f0d92250c6b7e9e2aff7", size = 1814998 },
-    { url = "https://files.pythonhosted.org/packages/a6/3c/724039e0d848fd69dbf5806894e26479577316c6f0f112bacaf67aa889ac/pydantic_core-2.27.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8c19d1ea0673cd13cc2f872f6c9ab42acc4e4f492a7ca9d3795ce2b112dd7e15", size = 1826167 },
-    { url = "https://files.pythonhosted.org/packages/2b/5b/1b29e8c1fb5f3199a9a57c1452004ff39f494bbe9bdbe9a81e18172e40d3/pydantic_core-2.27.2-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5e68c4446fe0810e959cdff46ab0a41ce2f2c86d227d96dc3847af0ba7def306", size = 1865071 },
-    { url = "https://files.pythonhosted.org/packages/89/6c/3985203863d76bb7d7266e36970d7e3b6385148c18a68cc8915fd8c84d57/pydantic_core-2.27.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d9640b0059ff4f14d1f37321b94061c6db164fbe49b334b31643e0528d100d99", size = 2036244 },
-    { url = "https://files.pythonhosted.org/packages/0e/41/f15316858a246b5d723f7d7f599f79e37493b2e84bfc789e58d88c209f8a/pydantic_core-2.27.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:40d02e7d45c9f8af700f3452f329ead92da4c5f4317ca9b896de7ce7199ea459", size = 2737470 },
-    { url = "https://files.pythonhosted.org/packages/a8/7c/b860618c25678bbd6d1d99dbdfdf0510ccb50790099b963ff78a124b754f/pydantic_core-2.27.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1c1fd185014191700554795c99b347d64f2bb637966c4cfc16998a0ca700d048", size = 1992291 },
-    { url = "https://files.pythonhosted.org/packages/bf/73/42c3742a391eccbeab39f15213ecda3104ae8682ba3c0c28069fbcb8c10d/pydantic_core-2.27.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d81d2068e1c1228a565af076598f9e7451712700b673de8f502f0334f281387d", size = 1994613 },
-    { url = "https://files.pythonhosted.org/packages/94/7a/941e89096d1175d56f59340f3a8ebaf20762fef222c298ea96d36a6328c5/pydantic_core-2.27.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:1a4207639fb02ec2dbb76227d7c751a20b1a6b4bc52850568e52260cae64ca3b", size = 2002355 },
-    { url = "https://files.pythonhosted.org/packages/6e/95/2359937a73d49e336a5a19848713555605d4d8d6940c3ec6c6c0ca4dcf25/pydantic_core-2.27.2-cp311-cp311-musllinux_1_1_armv7l.whl", hash = "sha256:3de3ce3c9ddc8bbd88f6e0e304dea0e66d843ec9de1b0042b0911c1663ffd474", size = 2126661 },
-    { url = "https://files.pythonhosted.org/packages/2b/4c/ca02b7bdb6012a1adef21a50625b14f43ed4d11f1fc237f9d7490aa5078c/pydantic_core-2.27.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:30c5f68ded0c36466acede341551106821043e9afaad516adfb6e8fa80a4e6a6", size = 2153261 },
-    { url = "https://files.pythonhosted.org/packages/72/9d/a241db83f973049a1092a079272ffe2e3e82e98561ef6214ab53fe53b1c7/pydantic_core-2.27.2-cp311-cp311-win32.whl", hash = "sha256:c70c26d2c99f78b125a3459f8afe1aed4d9687c24fd677c6a4436bc042e50d6c", size = 1812361 },
-    { url = "https://files.pythonhosted.org/packages/e8/ef/013f07248041b74abd48a385e2110aa3a9bbfef0fbd97d4e6d07d2f5b89a/pydantic_core-2.27.2-cp311-cp311-win_amd64.whl", hash = "sha256:08e125dbdc505fa69ca7d9c499639ab6407cfa909214d500897d02afb816e7cc", size = 1982484 },
-    { url = "https://files.pythonhosted.org/packages/10/1c/16b3a3e3398fd29dca77cea0a1d998d6bde3902fa2706985191e2313cc76/pydantic_core-2.27.2-cp311-cp311-win_arm64.whl", hash = "sha256:26f0d68d4b235a2bae0c3fc585c585b4ecc51382db0e3ba402a22cbc440915e4", size = 1867102 },
-    { url = "https://files.pythonhosted.org/packages/d6/74/51c8a5482ca447871c93e142d9d4a92ead74de6c8dc5e66733e22c9bba89/pydantic_core-2.27.2-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9e0c8cfefa0ef83b4da9588448b6d8d2a2bf1a53c3f1ae5fca39eb3061e2f0b0", size = 1893127 },
-    { url = "https://files.pythonhosted.org/packages/d3/f3/c97e80721735868313c58b89d2de85fa80fe8dfeeed84dc51598b92a135e/pydantic_core-2.27.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:83097677b8e3bd7eaa6775720ec8e0405f1575015a463285a92bfdfe254529ef", size = 1811340 },
-    { url = "https://files.pythonhosted.org/packages/9e/91/840ec1375e686dbae1bd80a9e46c26a1e0083e1186abc610efa3d9a36180/pydantic_core-2.27.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:172fce187655fece0c90d90a678424b013f8fbb0ca8b036ac266749c09438cb7", size = 1822900 },
-    { url = "https://files.pythonhosted.org/packages/f6/31/4240bc96025035500c18adc149aa6ffdf1a0062a4b525c932065ceb4d868/pydantic_core-2.27.2-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:519f29f5213271eeeeb3093f662ba2fd512b91c5f188f3bb7b27bc5973816934", size = 1869177 },
-    { url = "https://files.pythonhosted.org/packages/fa/20/02fbaadb7808be578317015c462655c317a77a7c8f0ef274bc016a784c54/pydantic_core-2.27.2-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:05e3a55d124407fffba0dd6b0c0cd056d10e983ceb4e5dbd10dda135c31071d6", size = 2038046 },
-    { url = "https://files.pythonhosted.org/packages/06/86/7f306b904e6c9eccf0668248b3f272090e49c275bc488a7b88b0823444a4/pydantic_core-2.27.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9c3ed807c7b91de05e63930188f19e921d1fe90de6b4f5cd43ee7fcc3525cb8c", size = 2685386 },
-    { url = "https://files.pythonhosted.org/packages/8d/f0/49129b27c43396581a635d8710dae54a791b17dfc50c70164866bbf865e3/pydantic_core-2.27.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6fb4aadc0b9a0c063206846d603b92030eb6f03069151a625667f982887153e2", size = 1997060 },
-    { url = "https://files.pythonhosted.org/packages/0d/0f/943b4af7cd416c477fd40b187036c4f89b416a33d3cc0ab7b82708a667aa/pydantic_core-2.27.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:28ccb213807e037460326424ceb8b5245acb88f32f3d2777427476e1b32c48c4", size = 2004870 },
-    { url = "https://files.pythonhosted.org/packages/35/40/aea70b5b1a63911c53a4c8117c0a828d6790483f858041f47bab0b779f44/pydantic_core-2.27.2-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:de3cd1899e2c279b140adde9357c4495ed9d47131b4a4eaff9052f23398076b3", size = 1999822 },
-    { url = "https://files.pythonhosted.org/packages/f2/b3/807b94fd337d58effc5498fd1a7a4d9d59af4133e83e32ae39a96fddec9d/pydantic_core-2.27.2-cp312-cp312-musllinux_1_1_armv7l.whl", hash = "sha256:220f892729375e2d736b97d0e51466252ad84c51857d4d15f5e9692f9ef12be4", size = 2130364 },
-    { url = "https://files.pythonhosted.org/packages/fc/df/791c827cd4ee6efd59248dca9369fb35e80a9484462c33c6649a8d02b565/pydantic_core-2.27.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:a0fcd29cd6b4e74fe8ddd2c90330fd8edf2e30cb52acda47f06dd615ae72da57", size = 2158303 },
-    { url = "https://files.pythonhosted.org/packages/9b/67/4e197c300976af185b7cef4c02203e175fb127e414125916bf1128b639a9/pydantic_core-2.27.2-cp312-cp312-win32.whl", hash = "sha256:1e2cb691ed9834cd6a8be61228471d0a503731abfb42f82458ff27be7b2186fc", size = 1834064 },
-    { url = "https://files.pythonhosted.org/packages/1f/ea/cd7209a889163b8dcca139fe32b9687dd05249161a3edda62860430457a5/pydantic_core-2.27.2-cp312-cp312-win_amd64.whl", hash = "sha256:cc3f1a99a4f4f9dd1de4fe0312c114e740b5ddead65bb4102884b384c15d8bc9", size = 1989046 },
-    { url = "https://files.pythonhosted.org/packages/bc/49/c54baab2f4658c26ac633d798dab66b4c3a9bbf47cff5284e9c182f4137a/pydantic_core-2.27.2-cp312-cp312-win_arm64.whl", hash = "sha256:3911ac9284cd8a1792d3cb26a2da18f3ca26c6908cc434a18f730dc0db7bfa3b", size = 1885092 },
-    { url = "https://files.pythonhosted.org/packages/46/72/af70981a341500419e67d5cb45abe552a7c74b66326ac8877588488da1ac/pydantic_core-2.27.2-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:2bf14caea37e91198329b828eae1618c068dfb8ef17bb33287a7ad4b61ac314e", size = 1891159 },
-    { url = "https://files.pythonhosted.org/packages/ad/3d/c5913cccdef93e0a6a95c2d057d2c2cba347815c845cda79ddd3c0f5e17d/pydantic_core-2.27.2-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:b0cb791f5b45307caae8810c2023a184c74605ec3bcbb67d13846c28ff731ff8", size = 1768331 },
-    { url = "https://files.pythonhosted.org/packages/f6/f0/a3ae8fbee269e4934f14e2e0e00928f9346c5943174f2811193113e58252/pydantic_core-2.27.2-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:688d3fd9fcb71f41c4c015c023d12a79d1c4c0732ec9eb35d96e3388a120dcf3", size = 1822467 },
-    { url = "https://files.pythonhosted.org/packages/d7/7a/7bbf241a04e9f9ea24cd5874354a83526d639b02674648af3f350554276c/pydantic_core-2.27.2-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3d591580c34f4d731592f0e9fe40f9cc1b430d297eecc70b962e93c5c668f15f", size = 1979797 },
-    { url = "https://files.pythonhosted.org/packages/4f/5f/4784c6107731f89e0005a92ecb8a2efeafdb55eb992b8e9d0a2be5199335/pydantic_core-2.27.2-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:82f986faf4e644ffc189a7f1aafc86e46ef70372bb153e7001e8afccc6e54133", size = 1987839 },
-    { url = "https://files.pythonhosted.org/packages/6d/a7/61246562b651dff00de86a5f01b6e4befb518df314c54dec187a78d81c84/pydantic_core-2.27.2-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:bec317a27290e2537f922639cafd54990551725fc844249e64c523301d0822fc", size = 1998861 },
-    { url = "https://files.pythonhosted.org/packages/86/aa/837821ecf0c022bbb74ca132e117c358321e72e7f9702d1b6a03758545e2/pydantic_core-2.27.2-pp310-pypy310_pp73-musllinux_1_1_armv7l.whl", hash = "sha256:0296abcb83a797db256b773f45773da397da75a08f5fcaef41f2044adec05f50", size = 2116582 },
-    { url = "https://files.pythonhosted.org/packages/81/b0/5e74656e95623cbaa0a6278d16cf15e10a51f6002e3ec126541e95c29ea3/pydantic_core-2.27.2-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:0d75070718e369e452075a6017fbf187f788e17ed67a3abd47fa934d001863d9", size = 2151985 },
-    { url = "https://files.pythonhosted.org/packages/63/37/3e32eeb2a451fddaa3898e2163746b0cffbbdbb4740d38372db0490d67f3/pydantic_core-2.27.2-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:7e17b560be3c98a8e3aa66ce828bdebb9e9ac6ad5466fba92eb74c4c95cb1151", size = 2004715 },
+    { url = "https://files.pythonhosted.org/packages/5c/8b/d3ae387f66277bd8104096d6ec0a145f4baa2966ebb2cad746c0920c9526/pydantic_core-2.23.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b", size = 1867835 },
+    { url = "https://files.pythonhosted.org/packages/46/76/f68272e4c3a7df8777798282c5e47d508274917f29992d84e1898f8908c7/pydantic_core-2.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4fc714bdbfb534f94034efaa6eadd74e5b93c8fa6315565a222f7b6f42ca1166", size = 1776689 },
+    { url = "https://files.pythonhosted.org/packages/cc/69/5f945b4416f42ea3f3bc9d2aaec66c76084a6ff4ff27555bf9415ab43189/pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:63e46b3169866bd62849936de036f901a9356e36376079b05efa83caeaa02ceb", size = 1800748 },
+    { url = "https://files.pythonhosted.org/packages/50/ab/891a7b0054bcc297fb02d44d05c50e68154e31788f2d9d41d0b72c89fdf7/pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ed1a53de42fbe34853ba90513cea21673481cd81ed1be739f7f2efb931b24916", size = 1806469 },
+    { url = "https://files.pythonhosted.org/packages/31/7c/6e3fa122075d78f277a8431c4c608f061881b76c2b7faca01d317ee39b5d/pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cfdd16ab5e59fc31b5e906d1a3f666571abc367598e3e02c83403acabc092e07", size = 2002246 },
+    { url = "https://files.pythonhosted.org/packages/ad/6f/22d5692b7ab63fc4acbc74de6ff61d185804a83160adba5e6cc6068e1128/pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:255a8ef062cbf6674450e668482456abac99a5583bbafb73f9ad469540a3a232", size = 2659404 },
+    { url = "https://files.pythonhosted.org/packages/11/ac/1e647dc1121c028b691028fa61a4e7477e6aeb5132628fde41dd34c1671f/pydantic_core-2.23.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:4a7cd62e831afe623fbb7aabbb4fe583212115b3ef38a9f6b71869ba644624a2", size = 2053940 },
+    { url = "https://files.pythonhosted.org/packages/91/75/984740c17f12c3ce18b5a2fcc4bdceb785cce7df1511a4ce89bca17c7e2d/pydantic_core-2.23.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f09e2ff1f17c2b51f2bc76d1cc33da96298f0a036a137f5440ab3ec5360b624f", size = 1921437 },
+    { url = "https://files.pythonhosted.org/packages/a0/74/13c5f606b64d93f0721e7768cd3e8b2102164866c207b8cd6f90bb15d24f/pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e38e63e6f3d1cec5a27e0afe90a085af8b6806ee208b33030e65b6516353f1a3", size = 1966129 },
+    { url = "https://files.pythonhosted.org/packages/18/03/9c4aa5919457c7b57a016c1ab513b1a926ed9b2bb7915bf8e506bf65c34b/pydantic_core-2.23.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0dbd8dbed2085ed23b5c04afa29d8fd2771674223135dc9bc937f3c09284d071", size = 2110908 },
+    { url = "https://files.pythonhosted.org/packages/92/2c/053d33f029c5dc65e5cf44ff03ceeefb7cce908f8f3cca9265e7f9b540c8/pydantic_core-2.23.4-cp310-none-win32.whl", hash = "sha256:6531b7ca5f951d663c339002e91aaebda765ec7d61b7d1e3991051906ddde119", size = 1735278 },
+    { url = "https://files.pythonhosted.org/packages/de/81/7dfe464eca78d76d31dd661b04b5f2036ec72ea8848dd87ab7375e185c23/pydantic_core-2.23.4-cp310-none-win_amd64.whl", hash = "sha256:7c9129eb40958b3d4500fa2467e6a83356b3b61bfff1b414c7361d9220f9ae8f", size = 1917453 },
+    { url = "https://files.pythonhosted.org/packages/5d/30/890a583cd3f2be27ecf32b479d5d615710bb926d92da03e3f7838ff3e58b/pydantic_core-2.23.4-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:77733e3892bb0a7fa797826361ce8a9184d25c8dffaec60b7ffe928153680ba8", size = 1865160 },
+    { url = "https://files.pythonhosted.org/packages/1d/9a/b634442e1253bc6889c87afe8bb59447f106ee042140bd57680b3b113ec7/pydantic_core-2.23.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1b84d168f6c48fabd1f2027a3d1bdfe62f92cade1fb273a5d68e621da0e44e6d", size = 1776777 },
+    { url = "https://files.pythonhosted.org/packages/75/9a/7816295124a6b08c24c96f9ce73085032d8bcbaf7e5a781cd41aa910c891/pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:df49e7a0861a8c36d089c1ed57d308623d60416dab2647a4a17fe050ba85de0e", size = 1799244 },
+    { url = "https://files.pythonhosted.org/packages/a9/8f/89c1405176903e567c5f99ec53387449e62f1121894aa9fc2c4fdc51a59b/pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ff02b6d461a6de369f07ec15e465a88895f3223eb75073ffea56b84d9331f607", size = 1805307 },
+    { url = "https://files.pythonhosted.org/packages/d5/a5/1a194447d0da1ef492e3470680c66048fef56fc1f1a25cafbea4bc1d1c48/pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:996a38a83508c54c78a5f41456b0103c30508fed9abcad0a59b876d7398f25fd", size = 2000663 },
+    { url = "https://files.pythonhosted.org/packages/13/a5/1df8541651de4455e7d587cf556201b4f7997191e110bca3b589218745a5/pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d97683ddee4723ae8c95d1eddac7c192e8c552da0c73a925a89fa8649bf13eea", size = 2655941 },
+    { url = "https://files.pythonhosted.org/packages/44/31/a3899b5ce02c4316865e390107f145089876dff7e1dfc770a231d836aed8/pydantic_core-2.23.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:216f9b2d7713eb98cb83c80b9c794de1f6b7e3145eef40400c62e86cee5f4e1e", size = 2052105 },
+    { url = "https://files.pythonhosted.org/packages/1b/aa/98e190f8745d5ec831f6d5449344c48c0627ac5fed4e5340a44b74878f8e/pydantic_core-2.23.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6f783e0ec4803c787bcea93e13e9932edab72068f68ecffdf86a99fd5918878b", size = 1919967 },
+    { url = "https://files.pythonhosted.org/packages/ae/35/b6e00b6abb2acfee3e8f85558c02a0822e9a8b2f2d812ea8b9079b118ba0/pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:d0776dea117cf5272382634bd2a5c1b6eb16767c223c6a5317cd3e2a757c61a0", size = 1964291 },
+    { url = "https://files.pythonhosted.org/packages/13/46/7bee6d32b69191cd649bbbd2361af79c472d72cb29bb2024f0b6e350ba06/pydantic_core-2.23.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:d5f7a395a8cf1621939692dba2a6b6a830efa6b3cee787d82c7de1ad2930de64", size = 2109666 },
+    { url = "https://files.pythonhosted.org/packages/39/ef/7b34f1b122a81b68ed0a7d0e564da9ccdc9a2924c8d6c6b5b11fa3a56970/pydantic_core-2.23.4-cp311-none-win32.whl", hash = "sha256:74b9127ffea03643e998e0c5ad9bd3811d3dac8c676e47db17b0ee7c3c3bf35f", size = 1732940 },
+    { url = "https://files.pythonhosted.org/packages/2f/76/37b7e76c645843ff46c1d73e046207311ef298d3f7b2f7d8f6ac60113071/pydantic_core-2.23.4-cp311-none-win_amd64.whl", hash = "sha256:98d134c954828488b153d88ba1f34e14259284f256180ce659e8d83e9c05eaa3", size = 1916804 },
+    { url = "https://files.pythonhosted.org/packages/74/7b/8e315f80666194b354966ec84b7d567da77ad927ed6323db4006cf915f3f/pydantic_core-2.23.4-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:f3e0da4ebaef65158d4dfd7d3678aad692f7666877df0002b8a522cdf088f231", size = 1856459 },
+    { url = "https://files.pythonhosted.org/packages/14/de/866bdce10ed808323d437612aca1ec9971b981e1c52e5e42ad9b8e17a6f6/pydantic_core-2.23.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f69a8e0b033b747bb3e36a44e7732f0c99f7edd5cea723d45bc0d6e95377ffee", size = 1770007 },
+    { url = "https://files.pythonhosted.org/packages/dc/69/8edd5c3cd48bb833a3f7ef9b81d7666ccddd3c9a635225214e044b6e8281/pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:723314c1d51722ab28bfcd5240d858512ffd3116449c557a1336cbe3919beb87", size = 1790245 },
+    { url = "https://files.pythonhosted.org/packages/80/33/9c24334e3af796ce80d2274940aae38dd4e5676298b4398eff103a79e02d/pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bb2802e667b7051a1bebbfe93684841cc9351004e2badbd6411bf357ab8d5ac8", size = 1801260 },
+    { url = "https://files.pythonhosted.org/packages/a5/6f/e9567fd90104b79b101ca9d120219644d3314962caa7948dd8b965e9f83e/pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d18ca8148bebe1b0a382a27a8ee60350091a6ddaf475fa05ef50dc35b5df6327", size = 1996872 },
+    { url = "https://files.pythonhosted.org/packages/2d/ad/b5f0fe9e6cfee915dd144edbd10b6e9c9c9c9d7a56b69256d124b8ac682e/pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:33e3d65a85a2a4a0dc3b092b938a4062b1a05f3a9abde65ea93b233bca0e03f2", size = 2661617 },
+    { url = "https://files.pythonhosted.org/packages/06/c8/7d4b708f8d05a5cbfda3243aad468052c6e99de7d0937c9146c24d9f12e9/pydantic_core-2.23.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:128585782e5bfa515c590ccee4b727fb76925dd04a98864182b22e89a4e6ed36", size = 2071831 },
+    { url = "https://files.pythonhosted.org/packages/89/4d/3079d00c47f22c9a9a8220db088b309ad6e600a73d7a69473e3a8e5e3ea3/pydantic_core-2.23.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:68665f4c17edcceecc112dfed5dbe6f92261fb9d6054b47d01bf6371a6196126", size = 1917453 },
+    { url = "https://files.pythonhosted.org/packages/e9/88/9df5b7ce880a4703fcc2d76c8c2d8eb9f861f79d0c56f4b8f5f2607ccec8/pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:20152074317d9bed6b7a95ade3b7d6054845d70584216160860425f4fbd5ee9e", size = 1968793 },
+    { url = "https://files.pythonhosted.org/packages/e3/b9/41f7efe80f6ce2ed3ee3c2dcfe10ab7adc1172f778cc9659509a79518c43/pydantic_core-2.23.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:9261d3ce84fa1d38ed649c3638feefeae23d32ba9182963e465d58d62203bd24", size = 2116872 },
+    { url = "https://files.pythonhosted.org/packages/63/08/b59b7a92e03dd25554b0436554bf23e7c29abae7cce4b1c459cd92746811/pydantic_core-2.23.4-cp312-none-win32.whl", hash = "sha256:4ba762ed58e8d68657fc1281e9bb72e1c3e79cc5d464be146e260c541ec12d84", size = 1738535 },
+    { url = "https://files.pythonhosted.org/packages/88/8d/479293e4d39ab409747926eec4329de5b7129beaedc3786eca070605d07f/pydantic_core-2.23.4-cp312-none-win_amd64.whl", hash = "sha256:97df63000f4fea395b2824da80e169731088656d1818a11b95f3b173747b6cd9", size = 1917992 },
+    { url = "https://files.pythonhosted.org/packages/13/a9/5d582eb3204464284611f636b55c0a7410d748ff338756323cb1ce721b96/pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:f455ee30a9d61d3e1a15abd5068827773d6e4dc513e795f380cdd59932c782d5", size = 1857135 },
+    { url = "https://files.pythonhosted.org/packages/2c/57/faf36290933fe16717f97829eabfb1868182ac495f99cf0eda9f59687c9d/pydantic_core-2.23.4-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:1e90d2e3bd2c3863d48525d297cd143fe541be8bbf6f579504b9712cb6b643ec", size = 1740583 },
+    { url = "https://files.pythonhosted.org/packages/91/7c/d99e3513dc191c4fec363aef1bf4c8af9125d8fa53af7cb97e8babef4e40/pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2e203fdf807ac7e12ab59ca2bfcabb38c7cf0b33c41efeb00f8e5da1d86af480", size = 1793637 },
+    { url = "https://files.pythonhosted.org/packages/29/18/812222b6d18c2d13eebbb0f7cdc170a408d9ced65794fdb86147c77e1982/pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e08277a400de01bc72436a0ccd02bdf596631411f592ad985dcee21445bd0068", size = 1941963 },
+    { url = "https://files.pythonhosted.org/packages/0f/36/c1f3642ac3f05e6bb4aec3ffc399fa3f84895d259cf5f0ce3054b7735c29/pydantic_core-2.23.4-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:f220b0eea5965dec25480b6333c788fb72ce5f9129e8759ef876a1d805d00801", size = 1915332 },
+    { url = "https://files.pythonhosted.org/packages/f7/ca/9c0854829311fb446020ebb540ee22509731abad886d2859c855dd29b904/pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:d06b0c8da4f16d1d1e352134427cb194a0a6e19ad5db9161bf32b2113409e728", size = 1957926 },
+    { url = "https://files.pythonhosted.org/packages/c0/1c/7836b67c42d0cd4441fcd9fafbf6a027ad4b79b6559f80cf11f89fd83648/pydantic_core-2.23.4-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:ba1a0996f6c2773bd83e63f18914c1de3c9dd26d55f4ac302a7efe93fb8e7433", size = 2100342 },
+    { url = "https://files.pythonhosted.org/packages/a9/f9/b6bcaf874f410564a78908739c80861a171788ef4d4f76f5009656672dfe/pydantic_core-2.23.4-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:9a5bce9d23aac8f0cf0836ecfc033896aa8443b501c58d0602dbfd5bd5b37753", size = 1920344 },
 ]
 
 [[package]]
@@ -4800,22 +4669,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/aa/7d/43ab67228ef98c6b5dd42ab386eae2d7877036970a0d7e3dd3eb47a0d530/scipy-1.14.1-cp312-cp312-win_amd64.whl", hash = "sha256:2ff38e22128e6c03ff73b6bb0f85f897d2362f8c052e3b8ad00532198fbdae3f", size = 44521212 },
 ]
 
-[[package]]
-name = "scrapegraph-py"
-version = "1.8.0"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "aiohttp" },
-    { name = "beautifulsoup4" },
-    { name = "pydantic" },
-    { name = "python-dotenv" },
-    { name = "requests" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/33/90/2388754061394a6c95fd5ad48cf4550208ce081c99cbc883672d52ccc360/scrapegraph_py-1.8.0.tar.gz", hash = "sha256:e075f6e6012a14a038537d0664609229069d9d2c2956bcbf9362f0c5c48de786", size = 108112 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/f7/80/14aeb7ba092cfc6928844a6726855f0c33489107f344e71dd8071f6433ed/scrapegraph_py-1.8.0-py3-none-any.whl", hash = "sha256:279176c972a770bac37a284e0bc25e34793797f30ff24dfba8fbcbfda79c8c88", size = 14460 },
-]
-
 [[package]]
 name = "selenium"
 version = "4.25.0"
@@ -4846,18 +4699,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/f8/85/3940bb4c586e10603d169d13ffccd59ed32fcb8d1b8104c3aef0e525b3b2/semchunk-2.2.0-py3-none-any.whl", hash = "sha256:7db19ca90ddb48f99265e789e07a7bb111ae25185f9cc3d44b94e1e61b9067fc", size = 10243 },
 ]
 
-[[package]]
-name = "serpapi"
-version = "0.1.5"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "requests" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/f0/fa/3fd8809287f3977a3e752bb88610e918d49cb1038b14f4bc51e13e594197/serpapi-0.1.5.tar.gz", hash = "sha256:b9707ed54750fdd2f62dc3a17c6a3fb7fa421dc37902fd65b2263c0ac765a1a5", size = 14191 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/df/6a/21deade04100d64844e494353a5d65e7971fbdfddf78eb1f248423593ad0/serpapi-0.1.5-py2.py3-none-any.whl", hash = "sha256:6467b6adec1231059f754ccaa952b229efeaa8b9cae6e71f879703ec9e5bb3d1", size = 10966 },
-]
-
 [[package]]
 name = "setuptools"
 version = "75.2.0"
@@ -4941,18 +4782,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d1/c2/fe97d779f3ef3b15f05c94a2f1e3d21732574ed441687474db9d342a7315/soupsieve-2.6-py3-none-any.whl", hash = "sha256:e72c4ff06e4fb6e4b5a9f0f55fe6e81514581fca1515028625d0f299c602ccc9", size = 36186 },
 ]
 
-[[package]]
-name = "spider-client"
-version = "0.1.25"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "aiohttp" },
-    { name = "ijson" },
-    { name = "requests" },
-    { name = "tenacity" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/b8/f2/06d89322f0054ea72e8d5580199f580e29df23476cb3cfe83a70a2a58a1b/spider-client-0.1.25.tar.gz", hash = "sha256:92ca4ce1d9d715dd8db52684ea417653940d8f3bbc13383d78683bc4fbb899a2", size = 15412 }
-
 [[package]]
 name = "sqlalchemy"
 version = "2.0.36"
@@ -5326,7 +5155,7 @@ name = "triton"
 version = "3.0.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "filelock", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
+    { name = "filelock", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
 ]
 wheels = [
     { url = "https://files.pythonhosted.org/packages/45/27/14cc3101409b9b4b9241d2ba7deaa93535a217a211c86c4cc7151fb12181/triton-3.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e1efef76935b2febc365bfadf74bcb65a6f959a9872e5bddf44cc9e0adce1e1a", size = 209376304 },
@@ -5482,15 +5311,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/8f/eb/f7032be105877bcf924709c97b1bf3b90255b4ec251f9340cef912559f28/uvloop-0.21.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:183aef7c8730e54c9a3ee3227464daed66e37ba13040bb3f350bc2ddc040f22f", size = 4659022 },
 ]
 
-[[package]]
-name = "validators"
-version = "0.34.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/64/07/91582d69320f6f6daaf2d8072608a4ad8884683d4840e7e4f3a9dbdcc639/validators-0.34.0.tar.gz", hash = "sha256:647fe407b45af9a74d245b943b18e6a816acf4926974278f6dd617778e1e781f", size = 70955 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/6e/78/36828a4d857b25896f9774c875714ba4e9b3bc8a92d2debe3f4df3a83d4f/validators-0.34.0-py3-none-any.whl", hash = "sha256:c804b476e3e6d3786fa07a30073a4ef694e617805eb1946ceee3fe5a9b8b1321", size = 43536 },
-]
-
 [[package]]
 name = "vcrpy"
 version = "5.1.0"
@@ -5610,25 +5430,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/fd/84/fd2ba7aafacbad3c4201d395674fc6348826569da3c0937e75505ead3528/wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859", size = 34166 },
 ]
 
-[[package]]
-name = "weaviate-client"
-version = "4.9.6"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "authlib" },
-    { name = "grpcio" },
-    { name = "grpcio-health-checking" },
-    { name = "grpcio-tools" },
-    { name = "httpx" },
-    { name = "pydantic" },
-    { name = "requests" },
-    { name = "validators" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/5d/7d/3894d12065d006743271b0b6bcc3bf911910473e91179d5966966816d694/weaviate_client-4.9.6.tar.gz", hash = "sha256:56d67c40fc94b0d53e81e0aa4477baaebbf3646fbec26551df66e396a72adcb6", size = 696813 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/2f/40/e3550e743b92ddd8dc69ebfd69cceb6de45b7d9a1cd439995454b499e9a3/weaviate_client-4.9.6-py3-none-any.whl", hash = "sha256:1d3b551939c0f7314f25e417cbcf4cf34e7adf942627993eef36ae6b4a044673", size = 386998 },
-]
-
 [[package]]
 name = "webencodings"
 version = "0.5.1"
@@ -5766,64 +5567,64 @@ wheels = [
 
 [[package]]
 name = "yarl"
-version = "1.18.3"
+version = "1.16.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "idna" },
     { name = "multidict" },
     { name = "propcache" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/b7/9d/4b94a8e6d2b51b599516a5cb88e5bc99b4d8d4583e468057eaa29d5f0918/yarl-1.18.3.tar.gz", hash = "sha256:ac1801c45cbf77b6c99242eeff4fffb5e4e73a800b5c4ad4fc0be5def634d2e1", size = 181062 }
+sdist = { url = "https://files.pythonhosted.org/packages/23/52/e9766cc6c2eab7dd1e9749c52c9879317500b46fb97d4105223f86679f93/yarl-1.16.0.tar.gz", hash = "sha256:b6f687ced5510a9a2474bbae96a4352e5ace5fa34dc44a217b0537fec1db00b4", size = 176548 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/d2/98/e005bc608765a8a5569f58e650961314873c8469c333616eb40bff19ae97/yarl-1.18.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7df647e8edd71f000a5208fe6ff8c382a1de8edfbccdbbfe649d263de07d8c34", size = 141458 },
-    { url = "https://files.pythonhosted.org/packages/df/5d/f8106b263b8ae8a866b46d9be869ac01f9b3fb7f2325f3ecb3df8003f796/yarl-1.18.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c69697d3adff5aa4f874b19c0e4ed65180ceed6318ec856ebc423aa5850d84f7", size = 94365 },
-    { url = "https://files.pythonhosted.org/packages/56/3e/d8637ddb9ba69bf851f765a3ee288676f7cf64fb3be13760c18cbc9d10bd/yarl-1.18.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:602d98f2c2d929f8e697ed274fbadc09902c4025c5a9963bf4e9edfc3ab6f7ed", size = 92181 },
-    { url = "https://files.pythonhosted.org/packages/76/f9/d616a5c2daae281171de10fba41e1c0e2d8207166fc3547252f7d469b4e1/yarl-1.18.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c654d5207c78e0bd6d749f6dae1dcbbfde3403ad3a4b11f3c5544d9906969dde", size = 315349 },
-    { url = "https://files.pythonhosted.org/packages/bb/b4/3ea5e7b6f08f698b3769a06054783e434f6d59857181b5c4e145de83f59b/yarl-1.18.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5094d9206c64181d0f6e76ebd8fb2f8fe274950a63890ee9e0ebfd58bf9d787b", size = 330494 },
-    { url = "https://files.pythonhosted.org/packages/55/f1/e0fc810554877b1b67420568afff51b967baed5b53bcc983ab164eebf9c9/yarl-1.18.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:35098b24e0327fc4ebdc8ffe336cee0a87a700c24ffed13161af80124b7dc8e5", size = 326927 },
-    { url = "https://files.pythonhosted.org/packages/a9/42/b1753949b327b36f210899f2dd0a0947c0c74e42a32de3f8eb5c7d93edca/yarl-1.18.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3236da9272872443f81fedc389bace88408f64f89f75d1bdb2256069a8730ccc", size = 319703 },
-    { url = "https://files.pythonhosted.org/packages/f0/6d/e87c62dc9635daefb064b56f5c97df55a2e9cc947a2b3afd4fd2f3b841c7/yarl-1.18.3-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e2c08cc9b16f4f4bc522771d96734c7901e7ebef70c6c5c35dd0f10845270bcd", size = 310246 },
-    { url = "https://files.pythonhosted.org/packages/e3/ef/e2e8d1785cdcbd986f7622d7f0098205f3644546da7919c24b95790ec65a/yarl-1.18.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:80316a8bd5109320d38eef8833ccf5f89608c9107d02d2a7f985f98ed6876990", size = 319730 },
-    { url = "https://files.pythonhosted.org/packages/fc/15/8723e22345bc160dfde68c4b3ae8b236e868f9963c74015f1bc8a614101c/yarl-1.18.3-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:c1e1cc06da1491e6734f0ea1e6294ce00792193c463350626571c287c9a704db", size = 321681 },
-    { url = "https://files.pythonhosted.org/packages/86/09/bf764e974f1516efa0ae2801494a5951e959f1610dd41edbfc07e5e0f978/yarl-1.18.3-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:fea09ca13323376a2fdfb353a5fa2e59f90cd18d7ca4eaa1fd31f0a8b4f91e62", size = 324812 },
-    { url = "https://files.pythonhosted.org/packages/f6/4c/20a0187e3b903c97d857cf0272d687c1b08b03438968ae8ffc50fe78b0d6/yarl-1.18.3-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:e3b9fd71836999aad54084906f8663dffcd2a7fb5cdafd6c37713b2e72be1760", size = 337011 },
-    { url = "https://files.pythonhosted.org/packages/c9/71/6244599a6e1cc4c9f73254a627234e0dad3883ece40cc33dce6265977461/yarl-1.18.3-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:757e81cae69244257d125ff31663249b3013b5dc0a8520d73694aed497fb195b", size = 338132 },
-    { url = "https://files.pythonhosted.org/packages/af/f5/e0c3efaf74566c4b4a41cb76d27097df424052a064216beccae8d303c90f/yarl-1.18.3-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:b1771de9944d875f1b98a745bc547e684b863abf8f8287da8466cf470ef52690", size = 331849 },
-    { url = "https://files.pythonhosted.org/packages/8a/b8/3d16209c2014c2f98a8f658850a57b716efb97930aebf1ca0d9325933731/yarl-1.18.3-cp310-cp310-win32.whl", hash = "sha256:8874027a53e3aea659a6d62751800cf6e63314c160fd607489ba5c2edd753cf6", size = 84309 },
-    { url = "https://files.pythonhosted.org/packages/fd/b7/2e9a5b18eb0fe24c3a0e8bae994e812ed9852ab4fd067c0107fadde0d5f0/yarl-1.18.3-cp310-cp310-win_amd64.whl", hash = "sha256:93b2e109287f93db79210f86deb6b9bbb81ac32fc97236b16f7433db7fc437d8", size = 90484 },
-    { url = "https://files.pythonhosted.org/packages/40/93/282b5f4898d8e8efaf0790ba6d10e2245d2c9f30e199d1a85cae9356098c/yarl-1.18.3-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8503ad47387b8ebd39cbbbdf0bf113e17330ffd339ba1144074da24c545f0069", size = 141555 },
-    { url = "https://files.pythonhosted.org/packages/6d/9c/0a49af78df099c283ca3444560f10718fadb8a18dc8b3edf8c7bd9fd7d89/yarl-1.18.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:02ddb6756f8f4517a2d5e99d8b2f272488e18dd0bfbc802f31c16c6c20f22193", size = 94351 },
-    { url = "https://files.pythonhosted.org/packages/5a/a1/205ab51e148fdcedad189ca8dd587794c6f119882437d04c33c01a75dece/yarl-1.18.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:67a283dd2882ac98cc6318384f565bffc751ab564605959df4752d42483ad889", size = 92286 },
-    { url = "https://files.pythonhosted.org/packages/ed/fe/88b690b30f3f59275fb674f5f93ddd4a3ae796c2b62e5bb9ece8a4914b83/yarl-1.18.3-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d980e0325b6eddc81331d3f4551e2a333999fb176fd153e075c6d1c2530aa8a8", size = 340649 },
-    { url = "https://files.pythonhosted.org/packages/07/eb/3b65499b568e01f36e847cebdc8d7ccb51fff716dbda1ae83c3cbb8ca1c9/yarl-1.18.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b643562c12680b01e17239be267bc306bbc6aac1f34f6444d1bded0c5ce438ca", size = 356623 },
-    { url = "https://files.pythonhosted.org/packages/33/46/f559dc184280b745fc76ec6b1954de2c55595f0ec0a7614238b9ebf69618/yarl-1.18.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c017a3b6df3a1bd45b9fa49a0f54005e53fbcad16633870104b66fa1a30a29d8", size = 354007 },
-    { url = "https://files.pythonhosted.org/packages/af/ba/1865d85212351ad160f19fb99808acf23aab9a0f8ff31c8c9f1b4d671fc9/yarl-1.18.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75674776d96d7b851b6498f17824ba17849d790a44d282929c42dbb77d4f17ae", size = 344145 },
-    { url = "https://files.pythonhosted.org/packages/94/cb/5c3e975d77755d7b3d5193e92056b19d83752ea2da7ab394e22260a7b824/yarl-1.18.3-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ccaa3a4b521b780a7e771cc336a2dba389a0861592bbce09a476190bb0c8b4b3", size = 336133 },
-    { url = "https://files.pythonhosted.org/packages/19/89/b77d3fd249ab52a5c40859815765d35c91425b6bb82e7427ab2f78f5ff55/yarl-1.18.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2d06d3005e668744e11ed80812e61efd77d70bb7f03e33c1598c301eea20efbb", size = 347967 },
-    { url = "https://files.pythonhosted.org/packages/35/bd/f6b7630ba2cc06c319c3235634c582a6ab014d52311e7d7c22f9518189b5/yarl-1.18.3-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:9d41beda9dc97ca9ab0b9888cb71f7539124bc05df02c0cff6e5acc5a19dcc6e", size = 346397 },
-    { url = "https://files.pythonhosted.org/packages/18/1a/0b4e367d5a72d1f095318344848e93ea70da728118221f84f1bf6c1e39e7/yarl-1.18.3-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:ba23302c0c61a9999784e73809427c9dbedd79f66a13d84ad1b1943802eaaf59", size = 350206 },
-    { url = "https://files.pythonhosted.org/packages/b5/cf/320fff4367341fb77809a2d8d7fe75b5d323a8e1b35710aafe41fdbf327b/yarl-1.18.3-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:6748dbf9bfa5ba1afcc7556b71cda0d7ce5f24768043a02a58846e4a443d808d", size = 362089 },
-    { url = "https://files.pythonhosted.org/packages/57/cf/aadba261d8b920253204085268bad5e8cdd86b50162fcb1b10c10834885a/yarl-1.18.3-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:0b0cad37311123211dc91eadcb322ef4d4a66008d3e1bdc404808992260e1a0e", size = 366267 },
-    { url = "https://files.pythonhosted.org/packages/54/58/fb4cadd81acdee6dafe14abeb258f876e4dd410518099ae9a35c88d8097c/yarl-1.18.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:0fb2171a4486bb075316ee754c6d8382ea6eb8b399d4ec62fde2b591f879778a", size = 359141 },
-    { url = "https://files.pythonhosted.org/packages/9a/7a/4c571597589da4cd5c14ed2a0b17ac56ec9ee7ee615013f74653169e702d/yarl-1.18.3-cp311-cp311-win32.whl", hash = "sha256:61b1a825a13bef4a5f10b1885245377d3cd0bf87cba068e1d9a88c2ae36880e1", size = 84402 },
-    { url = "https://files.pythonhosted.org/packages/ae/7b/8600250b3d89b625f1121d897062f629883c2f45339623b69b1747ec65fa/yarl-1.18.3-cp311-cp311-win_amd64.whl", hash = "sha256:b9d60031cf568c627d028239693fd718025719c02c9f55df0a53e587aab951b5", size = 91030 },
-    { url = "https://files.pythonhosted.org/packages/33/85/bd2e2729752ff4c77338e0102914897512e92496375e079ce0150a6dc306/yarl-1.18.3-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:1dd4bdd05407ced96fed3d7f25dbbf88d2ffb045a0db60dbc247f5b3c5c25d50", size = 142644 },
-    { url = "https://files.pythonhosted.org/packages/ff/74/1178322cc0f10288d7eefa6e4a85d8d2e28187ccab13d5b844e8b5d7c88d/yarl-1.18.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7c33dd1931a95e5d9a772d0ac5e44cac8957eaf58e3c8da8c1414de7dd27c576", size = 94962 },
-    { url = "https://files.pythonhosted.org/packages/be/75/79c6acc0261e2c2ae8a1c41cf12265e91628c8c58ae91f5ff59e29c0787f/yarl-1.18.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:25b411eddcfd56a2f0cd6a384e9f4f7aa3efee14b188de13048c25b5e91f1640", size = 92795 },
-    { url = "https://files.pythonhosted.org/packages/6b/32/927b2d67a412c31199e83fefdce6e645247b4fb164aa1ecb35a0f9eb2058/yarl-1.18.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:436c4fc0a4d66b2badc6c5fc5ef4e47bb10e4fd9bf0c79524ac719a01f3607c2", size = 332368 },
-    { url = "https://files.pythonhosted.org/packages/19/e5/859fca07169d6eceeaa4fde1997c91d8abde4e9a7c018e371640c2da2b71/yarl-1.18.3-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e35ef8683211db69ffe129a25d5634319a677570ab6b2eba4afa860f54eeaf75", size = 342314 },
-    { url = "https://files.pythonhosted.org/packages/08/75/76b63ccd91c9e03ab213ef27ae6add2e3400e77e5cdddf8ed2dbc36e3f21/yarl-1.18.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:84b2deecba4a3f1a398df819151eb72d29bfeb3b69abb145a00ddc8d30094512", size = 341987 },
-    { url = "https://files.pythonhosted.org/packages/1a/e1/a097d5755d3ea8479a42856f51d97eeff7a3a7160593332d98f2709b3580/yarl-1.18.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:00e5a1fea0fd4f5bfa7440a47eff01d9822a65b4488f7cff83155a0f31a2ecba", size = 336914 },
-    { url = "https://files.pythonhosted.org/packages/0b/42/e1b4d0e396b7987feceebe565286c27bc085bf07d61a59508cdaf2d45e63/yarl-1.18.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d0e883008013c0e4aef84dcfe2a0b172c4d23c2669412cf5b3371003941f72bb", size = 325765 },
-    { url = "https://files.pythonhosted.org/packages/7e/18/03a5834ccc9177f97ca1bbb245b93c13e58e8225276f01eedc4cc98ab820/yarl-1.18.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:5a3f356548e34a70b0172d8890006c37be92995f62d95a07b4a42e90fba54272", size = 344444 },
-    { url = "https://files.pythonhosted.org/packages/c8/03/a713633bdde0640b0472aa197b5b86e90fbc4c5bc05b727b714cd8a40e6d/yarl-1.18.3-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:ccd17349166b1bee6e529b4add61727d3f55edb7babbe4069b5764c9587a8cc6", size = 340760 },
-    { url = "https://files.pythonhosted.org/packages/eb/99/f6567e3f3bbad8fd101886ea0276c68ecb86a2b58be0f64077396cd4b95e/yarl-1.18.3-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:b958ddd075ddba5b09bb0be8a6d9906d2ce933aee81100db289badbeb966f54e", size = 346484 },
-    { url = "https://files.pythonhosted.org/packages/8e/a9/84717c896b2fc6cb15bd4eecd64e34a2f0a9fd6669e69170c73a8b46795a/yarl-1.18.3-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:c7d79f7d9aabd6011004e33b22bc13056a3e3fb54794d138af57f5ee9d9032cb", size = 359864 },
-    { url = "https://files.pythonhosted.org/packages/1e/2e/d0f5f1bef7ee93ed17e739ec8dbcb47794af891f7d165fa6014517b48169/yarl-1.18.3-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:4891ed92157e5430874dad17b15eb1fda57627710756c27422200c52d8a4e393", size = 364537 },
-    { url = "https://files.pythonhosted.org/packages/97/8a/568d07c5d4964da5b02621a517532adb8ec5ba181ad1687191fffeda0ab6/yarl-1.18.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:ce1af883b94304f493698b00d0f006d56aea98aeb49d75ec7d98cd4a777e9285", size = 357861 },
-    { url = "https://files.pythonhosted.org/packages/7d/e3/924c3f64b6b3077889df9a1ece1ed8947e7b61b0a933f2ec93041990a677/yarl-1.18.3-cp312-cp312-win32.whl", hash = "sha256:f91c4803173928a25e1a55b943c81f55b8872f0018be83e3ad4938adffb77dd2", size = 84097 },
-    { url = "https://files.pythonhosted.org/packages/34/45/0e055320daaabfc169b21ff6174567b2c910c45617b0d79c68d7ab349b02/yarl-1.18.3-cp312-cp312-win_amd64.whl", hash = "sha256:7e2ee16578af3b52ac2f334c3b1f92262f47e02cc6193c598502bd46f5cd1477", size = 90399 },
-    { url = "https://files.pythonhosted.org/packages/f5/4b/a06e0ec3d155924f77835ed2d167ebd3b211a7b0853da1cf8d8414d784ef/yarl-1.18.3-py3-none-any.whl", hash = "sha256:b57f4f58099328dfb26c6a771d09fb20dbbae81d20cfb66141251ea063bd101b", size = 45109 },
+    { url = "https://files.pythonhosted.org/packages/df/30/00b17348655202e4bd24f8d79cd062888e5d3bdbf2ba726615c5d21b54a5/yarl-1.16.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:32468f41242d72b87ab793a86d92f885355bcf35b3355aa650bfa846a5c60058", size = 140016 },
+    { url = "https://files.pythonhosted.org/packages/a5/15/9b7b85b72b81f180689257b2bb6e54d5d0764a399679aa06d5dec8ca6e2e/yarl-1.16.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:234f3a3032b505b90e65b5bc6652c2329ea7ea8855d8de61e1642b74b4ee65d2", size = 92953 },
+    { url = "https://files.pythonhosted.org/packages/31/41/91848bbb76789336d3b786ff144030001b5027b17729b3afa32da668f5b0/yarl-1.16.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8a0296040e5cddf074c7f5af4a60f3fc42c0237440df7bcf5183be5f6c802ed5", size = 90793 },
+    { url = "https://files.pythonhosted.org/packages/6c/99/f1ada764e350ab054e14902f3f68589a7d77469ac47fbc512aa1a78a2f35/yarl-1.16.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de6c14dd7c7c0badba48157474ea1f03ebee991530ba742d381b28d4f314d6f3", size = 313155 },
+    { url = "https://files.pythonhosted.org/packages/75/fd/998ccdb489ca97d9073d882265203a2fae4c5bff30eb9b8a0bbbed7aef2b/yarl-1.16.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b140e532fe0266003c936d017c1ac301e72ee4a3fd51784574c05f53718a55d8", size = 328624 },
+    { url = "https://files.pythonhosted.org/packages/2d/5d/395bbae1f509f64e6d26b7ffffff178d70c5480f15af735dfb0afb8f0dc5/yarl-1.16.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:019f5d58093402aa8f6661e60fd82a28746ad6d156f6c5336a70a39bd7b162b9", size = 325163 },
+    { url = "https://files.pythonhosted.org/packages/1d/25/65601d336189d122483f5ff0276b08278fa4778f833458cfcac5c6eddc87/yarl-1.16.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8c42998fd1cbeb53cd985bff0e4bc25fbe55fd6eb3a545a724c1012d69d5ec84", size = 318076 },
+    { url = "https://files.pythonhosted.org/packages/50/bb/0c9692ec457c1ed023654a9fba6d0c69a20c79b56275d972f6a24ab18547/yarl-1.16.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7c7c30fb38c300fe8140df30a046a01769105e4cf4282567a29b5cdb635b66c4", size = 309551 },
+    { url = "https://files.pythonhosted.org/packages/a5/2f/d0ced2050a203241a3f2e05c5bb86038b071f216897defd824dd85333f9e/yarl-1.16.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:e49e0fd86c295e743fd5be69b8b0712f70a686bc79a16e5268386c2defacaade", size = 317678 },
+    { url = "https://files.pythonhosted.org/packages/46/93/b7359aa2bd0567eca72491cd20059744ed6ee00f08cd58c861243f656a90/yarl-1.16.0-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:b9ca7b9147eb1365c8bab03c003baa1300599575effad765e0b07dd3501ea9af", size = 317003 },
+    { url = "https://files.pythonhosted.org/packages/87/18/77ef4d45d19ecafad0f7c07d5cf13a757a90122383494bc5a3e8ee68e2f2/yarl-1.16.0-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:27e11db3f1e6a51081a981509f75617b09810529de508a181319193d320bc5c7", size = 322795 },
+    { url = "https://files.pythonhosted.org/packages/28/a9/b38880bf79665d1c8a3d4c09d6f7a686a50f8c74caf07603a2b8e5314038/yarl-1.16.0-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:8994c42f4ca25df5380ddf59f315c518c81df6a68fed5bb0c159c6cb6b92f120", size = 337022 },
+    { url = "https://files.pythonhosted.org/packages/e9/79/865788b297fc17117e3ff6ea74d5f864185085d61adc3364444732095254/yarl-1.16.0-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:542fa8e09a581bcdcbb30607c7224beff3fdfb598c798ccd28a8184ffc18b7eb", size = 338357 },
+    { url = "https://files.pythonhosted.org/packages/bd/5e/c5cba528448f73c7035c9d3c07261b54312d8caa8372eeeff5e1f07e43ec/yarl-1.16.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:2bd6a51010c7284d191b79d3b56e51a87d8e1c03b0902362945f15c3d50ed46b", size = 330470 },
+    { url = "https://files.pythonhosted.org/packages/1a/e4/90757595d81ec328ad94afa62d0724903a6c72b76e0ee9c9af9d8a399dd2/yarl-1.16.0-cp310-cp310-win32.whl", hash = "sha256:178ccb856e265174a79f59721031060f885aca428983e75c06f78aa24b91d929", size = 82967 },
+    { url = "https://files.pythonhosted.org/packages/01/5a/b82ec5e7557b0d938b9475cbb5dcbb1f98c8601101188d79e423dc215cd0/yarl-1.16.0-cp310-cp310-win_amd64.whl", hash = "sha256:fe8bba2545427418efc1929c5c42852bdb4143eb8d0a46b09de88d1fe99258e7", size = 89159 },
+    { url = "https://files.pythonhosted.org/packages/0a/00/b29affe83de95e403f8a2a669b5a33f1e7dfe686264008100052eb0b05fd/yarl-1.16.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:d8643975a0080f361639787415a038bfc32d29208a4bf6b783ab3075a20b1ef3", size = 140120 },
+    { url = "https://files.pythonhosted.org/packages/3f/22/bcc9799950281a5d4f646536854839ccdbb965e900827ef0750680f81faf/yarl-1.16.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:676d96bafc8c2d0039cea0cd3fd44cee7aa88b8185551a2bb93354668e8315c2", size = 92956 },
+    { url = "https://files.pythonhosted.org/packages/33/0f/1b76d853d9d921d68bd9991648be17d34e7ac51e2e20e7658f8ee7e2e2ad/yarl-1.16.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d9525f03269e64310416dbe6c68d3b23e5d34aaa8f47193a1c45ac568cecbc49", size = 90891 },
+    { url = "https://files.pythonhosted.org/packages/61/19/3666d990c24aae98c748e2c262adc9b3a71e38834df007ac5317f4bbd789/yarl-1.16.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8b37d5ec034e668b22cf0ce1074d6c21fd2a08b90d11b1b73139b750a8b0dd97", size = 338857 },
+    { url = "https://files.pythonhosted.org/packages/a0/3d/54acbb3cdfcfea03d6a3535cff1e060a2de23e419a4e3955c9661171b8a8/yarl-1.16.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4f32c4cb7386b41936894685f6e093c8dfaf0960124d91fe0ec29fe439e201d0", size = 354005 },
+    { url = "https://files.pythonhosted.org/packages/15/98/cd9fe3938422c88775c94578a6c145aca89ff8368ff64e6032213ac12403/yarl-1.16.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5b8e265a0545637492a7e12fd7038370d66c9375a61d88c5567d0e044ded9202", size = 351195 },
+    { url = "https://files.pythonhosted.org/packages/e2/13/b6eff6ea1667aee948ecd6b1c8fb6473234f8e48f49af97be93251869c51/yarl-1.16.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:789a3423f28a5fff46fbd04e339863c169ece97c827b44de16e1a7a42bc915d2", size = 342789 },
+    { url = "https://files.pythonhosted.org/packages/fe/05/d98e65ea74a7e44bb033b2cf5bcc16edc1d5212bdc5ca7fbb5e380d89f8e/yarl-1.16.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:f1d1f45e3e8d37c804dca99ab3cf4ab3ed2e7a62cd82542924b14c0a4f46d243", size = 336478 },
+    { url = "https://files.pythonhosted.org/packages/7d/47/43de2e94b75f36d84733a35c807d0e33aaf084e98f32e2cbc685102f4ba4/yarl-1.16.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:621280719c4c5dad4c1391160a9b88925bb8b0ff6a7d5af3224643024871675f", size = 346008 },
+    { url = "https://files.pythonhosted.org/packages/e2/de/9c2f900ec5e2f2e20329cfe7dcd9452e326d08cb5ecd098c2d4e9987b65c/yarl-1.16.0-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:ed097b26f18a1f5ff05f661dc36528c5f6735ba4ce8c9645e83b064665131349", size = 343745 },
+    { url = "https://files.pythonhosted.org/packages/56/cd/b014dce22e37b77caa37f998c6c47434fd78d01e7be07119629f369f5ee1/yarl-1.16.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:2f1fe2b2e3ee418862f5ebc0c0083c97f6f6625781382f828f6d4e9b614eba9b", size = 349705 },
+    { url = "https://files.pythonhosted.org/packages/07/17/bb191a26f7189423964e008ccb5146ce5258454ef3979f9d4c6860d282c7/yarl-1.16.0-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:87dd10bc0618991c66cee0cc65fa74a45f4ecb13bceec3c62d78ad2e42b27a16", size = 360767 },
+    { url = "https://files.pythonhosted.org/packages/19/09/7d777369e151991b708a5b35280ea7444621d65af5f0545bcdce5d840867/yarl-1.16.0-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:4199db024b58a8abb2cfcedac7b1292c3ad421684571aeb622a02f242280e8d6", size = 364755 },
+    { url = "https://files.pythonhosted.org/packages/00/32/7558997d1d2e53dab15f6db5db49fc6b412b63ede3cb8314e5dd7cff14fe/yarl-1.16.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:99a9dcd4b71dd5f5f949737ab3f356cfc058c709b4f49833aeffedc2652dac56", size = 357087 },
+    { url = "https://files.pythonhosted.org/packages/28/20/c49a95a30c57224e5fb0fc83235295684b041300ce508b71821cb042527d/yarl-1.16.0-cp311-cp311-win32.whl", hash = "sha256:a9394c65ae0ed95679717d391c862dece9afacd8fa311683fc8b4362ce8a410c", size = 83030 },
+    { url = "https://files.pythonhosted.org/packages/75/e3/2a746721d6f32886d9bafccdb80174349f180ccae0a287f25ba4312a2618/yarl-1.16.0-cp311-cp311-win_amd64.whl", hash = "sha256:5b9101f528ae0f8f65ac9d64dda2bb0627de8a50344b2f582779f32fda747c1d", size = 89616 },
+    { url = "https://files.pythonhosted.org/packages/3a/be/82f696c8ce0395c37f62b955202368086e5cc114d5bb9cb1b634cff5e01d/yarl-1.16.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:4ffb7c129707dd76ced0a4a4128ff452cecf0b0e929f2668ea05a371d9e5c104", size = 141230 },
+    { url = "https://files.pythonhosted.org/packages/38/60/45caaa748b53c4b0964f899879fcddc41faa4e0d12c6f0ae3311e8c151ff/yarl-1.16.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:1a5e9d8ce1185723419c487758d81ac2bde693711947032cce600ca7c9cda7d6", size = 93515 },
+    { url = "https://files.pythonhosted.org/packages/54/bd/33aaca2f824dc1d630729e16e313797e8b24c8f7b6803307e5394274e443/yarl-1.16.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:d743e3118b2640cef7768ea955378c3536482d95550222f908f392167fe62059", size = 91441 },
+    { url = "https://files.pythonhosted.org/packages/af/fa/1ce8ca85489925aabdb8d2e7bbeaf74e7d3e6ac069779d6d6b9c7c62a8ed/yarl-1.16.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:26768342f256e6e3c37533bf9433f5f15f3e59e3c14b2409098291b3efaceacb", size = 330871 },
+    { url = "https://files.pythonhosted.org/packages/f1/2a/a8110a225e498b87315827f8b61d24de35f86041834cf8c9c5544380c46b/yarl-1.16.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d1b0796168b953bca6600c5f97f5ed407479889a36ad7d17183366260f29a6b9", size = 340641 },
+    { url = "https://files.pythonhosted.org/packages/d0/64/20cd1cb1f60b3ff49e7d75c1a2083352e7c5939368aafa960712c9e53797/yarl-1.16.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:858728086914f3a407aa7979cab743bbda1fe2bdf39ffcd991469a370dd7414d", size = 340245 },
+    { url = "https://files.pythonhosted.org/packages/77/a8/7f38bbefb22eb925a68ad1d8193b05f51515614a6c0ebcadf26e9ae5e5ad/yarl-1.16.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5570e6d47bcb03215baf4c9ad7bf7c013e56285d9d35013541f9ac2b372593e7", size = 336054 },
+    { url = "https://files.pythonhosted.org/packages/b4/a6/ac633ea3ea0c4eb1057e6800db1d077e77493b4b3449a4a97b2fbefadef4/yarl-1.16.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:66ea8311422a7ba1fc79b4c42c2baa10566469fe5a78500d4e7754d6e6db8724", size = 324405 },
+    { url = "https://files.pythonhosted.org/packages/93/cd/4fc87ce9b0df7afb610ffb904f4aef25f59e0ad40a49da19a475facf98b7/yarl-1.16.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:649bddcedee692ee8a9b7b6e38582cb4062dc4253de9711568e5620d8707c2a3", size = 342235 },
+    { url = "https://files.pythonhosted.org/packages/9f/bc/38bae4b716da1206849d88e167d3d2c5695ae9b418a3915220947593e5ca/yarl-1.16.0-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:3a91654adb7643cb21b46f04244c5a315a440dcad63213033826549fa2435f71", size = 340835 },
+    { url = "https://files.pythonhosted.org/packages/dc/0f/b9efbc0075916a450cbad41299dff3bdd3393cb1d8378bb831c4a6a836e1/yarl-1.16.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:b439cae82034ade094526a8f692b9a2b5ee936452de5e4c5f0f6c48df23f8604", size = 344323 },
+    { url = "https://files.pythonhosted.org/packages/87/6d/dc483ea1574005f14ef4c5f5f726cf60327b07ac83bd417d98db23e5285f/yarl-1.16.0-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:571f781ae8ac463ce30bacebfaef2c6581543776d5970b2372fbe31d7bf31a07", size = 355112 },
+    { url = "https://files.pythonhosted.org/packages/10/22/3b7c3728d26b3cc295c51160ae4e2612ab7d3f9df30beece44bf72861730/yarl-1.16.0-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:aa7943f04f36d6cafc0cf53ea89824ac2c37acbdb4b316a654176ab8ffd0f968", size = 361506 },
+    { url = "https://files.pythonhosted.org/packages/ad/8d/b7b5d43cf22a020b564ddf7502d83df150d797e34f18f6bf5fe0f12cbd91/yarl-1.16.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:1a5cf32539373ff39d97723e39a9283a7277cbf1224f7aef0c56c9598b6486c3", size = 355746 },
+    { url = "https://files.pythonhosted.org/packages/d9/a6/a2098bf3f09d38eb540b2b192e180d9d41c2ff64b692783db2188f0a55e3/yarl-1.16.0-cp312-cp312-win32.whl", hash = "sha256:a5b6c09b9b4253d6a208b0f4a2f9206e511ec68dce9198e0fbec4f160137aa67", size = 82675 },
+    { url = "https://files.pythonhosted.org/packages/ed/a6/0a54b382cfc336e772b72681d6816a99222dc2d21876e649474973b8d244/yarl-1.16.0-cp312-cp312-win_amd64.whl", hash = "sha256:1208ca14eed2fda324042adf8d6c0adf4a31522fa95e0929027cd487875f0240", size = 88986 },
+    { url = "https://files.pythonhosted.org/packages/fb/f7/87a32867ddc1a9817018bfd6109ee57646a543acf0d272843d8393e575f9/yarl-1.16.0-py3-none-any.whl", hash = "sha256:e6980a558d8461230c457218bd6c92dfc1d10205548215c2c21d79dc8d0a96f3", size = 43746 },
 ]
 
 [[package]]