Update security.md

update policy for better readability

.github/workflows/linter.yml

@@ -5,29 +5,12 @@ on: [pull_request]
 jobs:
   lint:
     runs-on: ubuntu-latest
-    env:
-      TARGET_BRANCH: ${{ github.event.pull_request.base.ref }}
     steps:
       - uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
 
-      - name: Fetch Target Branch
-        run: git fetch origin $TARGET_BRANCH --depth=1
-
-      - name: Install Ruff
-        run: pip install ruff
-
-      - name: Get Changed Python Files
-        id: changed-files
+      - name: Install Requirements
         run: |
-          merge_base=$(git merge-base origin/"$TARGET_BRANCH" HEAD)
-          changed_files=$(git diff --name-only --diff-filter=ACMRTUB "$merge_base" | grep '\.py$' || true)
-          echo "files<<EOF" >> $GITHUB_OUTPUT
-          echo "$changed_files" >> $GITHUB_OUTPUT
-          echo "EOF" >> $GITHUB_OUTPUT
+          pip install ruff
 
-      - name: Run Ruff on Changed Files
-        if: ${{ steps.changed-files.outputs.files != '' }}
-        run: |
-          echo "${{ steps.changed-files.outputs.files }}" | tr " " "\n" | xargs -I{} ruff check "{}"
+      - name: Run Ruff Linter
+        run: ruff check

.ruff.toml

@@ -2,3 +2,8 @@ exclude = [
     "templates",
     "__init__.py",
 ]
+
+[lint]
+select = [
+    "I", # isort rules
+]

docs/concepts/cli.mdx

@@ -110,8 +110,6 @@ crewai reset-memories [OPTIONS]
 - `-s, --short`: Reset SHORT TERM memory
 - `-e, --entities`: Reset ENTITIES memory
 - `-k, --kickoff-outputs`: Reset LATEST KICKOFF TASK OUTPUTS
-- `-kn, --knowledge`: Reset KNOWLEDGE storage
-- `-akn, --agent-knowledge`: Reset AGENT KNOWLEDGE storage
 - `-a, --all`: Reset ALL memories
 
 Example:

docs/concepts/flows.mdx

@@ -75,12 +75,11 @@ class ExampleFlow(Flow):
 
 
 flow = ExampleFlow()
-flow.plot()
 result = flow.kickoff()
 
 print(f"Generated fun fact: {result}")
 ```
-![Flow Visual image](/images/crewai-flow-1.png)
+
 In the above example, we have created a simple Flow that generates a random city using OpenAI and then generates a fun fact about that city. The Flow consists of two tasks: `generate_city` and `generate_fun_fact`. The `generate_city` task is the starting point of the Flow, and the `generate_fun_fact` task listens for the output of the `generate_city` task.
 
 Each Flow instance automatically receives a unique identifier (UUID) in its state, which helps track and manage flow executions. The state can also store additional data (like the generated city and fun fact) that persists throughout the flow's execution.
@@ -147,7 +146,6 @@ class OutputExampleFlow(Flow):
 
 
 flow = OutputExampleFlow()
-flow.plot("my_flow_plot")
 final_output = flow.kickoff()
 
 print("---- Final Output ----")
@@ -160,10 +158,9 @@ Second method received: Output from first_method
 ```
 
 </CodeGroup>
-![Flow Visual image](/images/crewai-flow-2.png)
 
 In this example, the `second_method` is the last method to complete, so its output will be the final output of the Flow.
-The `kickoff()` method will return the final output, which is then printed to the console. The `plot()` method will generate the HTML file, which will help you understand the flow.
+The `kickoff()` method will return the final output, which is then printed to the console.
 
 #### Accessing and Updating State
 
@@ -195,7 +192,6 @@ class StateExampleFlow(Flow[ExampleState]):
         return self.state.message
 
 flow = StateExampleFlow()
-flow.plot("my_flow_plot")
 final_output = flow.kickoff()
 print(f"Final Output: {final_output}")
 print("Final State:")
@@ -210,8 +206,6 @@ counter=2 message='Hello from first_method - updated by second_method'
 
 </CodeGroup>
 
-![Flow Visual image](/images/crewai-flow-2.png)
-
 In this example, the state is updated by both `first_method` and `second_method`.
 After the Flow has run, you can access the final state to see the updates made by these methods.
 
@@ -255,12 +249,9 @@ class UnstructuredExampleFlow(Flow):
 
 
 flow = UnstructuredExampleFlow()
-flow.plot("my_flow_plot")
 flow.kickoff()
 ```
 
-![Flow Visual image](/images/crewai-flow-3.png)
-
 **Note:** The `id` field is automatically generated and preserved throughout the flow's execution. You don't need to manage or set it manually, and it will be maintained even when updating the state with new data.
 
 **Key Points:**
@@ -311,8 +302,6 @@ flow = StructuredExampleFlow()
 flow.kickoff()
 ```
 
-![Flow Visual image](/images/crewai-flow-3.png)
-
 **Key Points:**
 
 - **Defined Schema:** `ExampleState` clearly outlines the state structure, enhancing code readability and maintainability.
@@ -447,7 +436,6 @@ class OrExampleFlow(Flow):
 
 
 flow = OrExampleFlow()
-flow.plot("my_flow_plot")
 flow.kickoff()
 ```
 
@@ -458,8 +446,6 @@ Logger: Hello from the second method
 
 </CodeGroup>
 
-![Flow Visual image](/images/crewai-flow-4.png)
-
 When you run this Flow, the `logger` method will be triggered by the output of either the `start_method` or the `second_method`.
 The `or_` function is used to listen to multiple methods and trigger the listener method when any of the specified methods emit an output.
 
@@ -488,7 +474,6 @@ class AndExampleFlow(Flow):
         print(self.state)
 
 flow = AndExampleFlow()
-flow.plot()
 flow.kickoff()
 ```
 
@@ -499,8 +484,6 @@ flow.kickoff()
 
 </CodeGroup>
 
-![Flow Visual image](/images/crewai-flow-5.png)
-
 When you run this Flow, the `logger` method will be triggered only when both the `start_method` and the `second_method` emit an output.
 The `and_` function is used to listen to multiple methods and trigger the listener method only when all the specified methods emit an output.
 
@@ -544,7 +527,6 @@ class RouterFlow(Flow[ExampleState]):
 
 
 flow = RouterFlow()
-flow.plot("my_flow_plot")
 flow.kickoff()
 ```
 
@@ -556,8 +538,6 @@ Fourth method running
 
 </CodeGroup>
 
-![Flow Visual image](/images/crewai-flow-6.png)
-
 In the above example, the `start_method` generates a random boolean value and sets it in the state.
 The `second_method` uses the `@router()` decorator to define conditional routing logic based on the value of the boolean.
 If the boolean is `True`, the method returns `"success"`, and if it is `False`, the method returns `"failed"`.
@@ -661,7 +641,6 @@ class MarketResearchFlow(Flow[MarketResearchState]):
 # Usage example
 async def run_flow():
     flow = MarketResearchFlow()
-    flow.plot("MarketResearchFlowPlot")
     result = await flow.kickoff_async(inputs={"product": "AI-powered chatbots"})
     return result
 
@@ -671,8 +650,6 @@ if __name__ == "__main__":
     asyncio.run(run_flow())
 ```
 
-![Flow Visual image](/images/crewai-flow-7.png)
-
 This example demonstrates several key features of using Agents in flows:
 
 1. **Structured Output**: Using Pydantic models to define the expected output format (`MarketAnalysis`) ensures type safety and structured data throughout the flow.
@@ -769,16 +746,13 @@ def kickoff():
 
 def plot():
     poem_flow = PoemFlow()
-    poem_flow.plot("PoemFlowPlot")
+    poem_flow.plot()
 
 if __name__ == "__main__":
     kickoff()
-    plot()
 ```
 
-In this example, the `PoemFlow` class defines a flow that generates a sentence count, uses the `PoemCrew` to generate a poem, and then saves the poem to a file. The flow is kicked off by calling the `kickoff()` method. The PoemFlowPlot will be generated by `plot()` method.
-
-![Flow Visual image](/images/crewai-flow-8.png)
+In this example, the `PoemFlow` class defines a flow that generates a sentence count, uses the `PoemCrew` to generate a poem, and then saves the poem to a file. The flow is kicked off by calling the `kickoff()` method.
 
 ### Running the Flow
 

docs/concepts/knowledge.mdx

@@ -497,13 +497,6 @@ crew = Crew(
 result = crew.kickoff(
     inputs={"question": "What is the storage capacity of the XPS 13?"}
 )
-
-# Resetting the agent specific knowledge via crew object
-crew.reset_memories(command_type = 'agent_knowledge')
-
-# Resetting the agent specific knowledge via CLI
-crewai reset-memories --agent-knowledge 
-crewai reset-memories -akn
 ```
 
 <Info>
@@ -707,11 +700,4 @@ recent_news = SpaceNewsKnowledgeSource(
     - Configure appropriate embedding models
     - Consider using local embedding providers for faster processing
   </Accordion>
-
-  <Accordion title="One Time Knowledge">
-    - With the typical file structure provided by CrewAI, knowledge sources are embedded every time the kickoff is triggered.
-    - If the knowledge sources are large, this leads to inefficiency and increased latency, as the same data is embedded each time.
-    - To resolve this, directly initialize the knowledge parameter instead of the knowledge_sources parameter.
-    - Link to the issue to get complete idea [Github Issue](https://github.com/crewAIInc/crewAI/issues/2755)
-  </Accordion>  
 </AccordionGroup>

docs/concepts/llms.mdx

@@ -169,55 +169,19 @@ In this section, you'll find detailed examples that help you select, configure,
     ```
   </Accordion>
 
-  <Accordion title="Google (Gemini API)">
-    Set your API key in your `.env` file. If you need a key, or need to find an
-    existing key, check [AI Studio](https://aistudio.google.com/apikey).
+  <Accordion title="Google">
+    Set the following environment variables in your `.env` file:
 
-    ```toml .env
+    ```toml Code
+    # Option 1: Gemini accessed with an API key.
     # https://ai.google.dev/gemini-api/docs/api-key
     GEMINI_API_KEY=<your-api-key>
+
+    # Option 2: Vertex AI IAM credentials for Gemini, Anthropic, and Model Garden.
+    # https://cloud.google.com/vertex-ai/generative-ai/docs/overview
     ```
 
-    Example usage in your CrewAI project:
-    ```python Code
-    from crewai import LLM
-
-    llm = LLM(
-        model="gemini/gemini-2.0-flash",
-        temperature=0.7,
-    )
-    ```
-
-    ### Gemini models
-
-    Google offers a range of powerful models optimized for different use cases.
-
-    | Model                          | Context Window | Best For                                                          |
-    |--------------------------------|----------------|-------------------------------------------------------------------|
-    | gemini-2.5-flash-preview-04-17 | 1M tokens      | Adaptive thinking, cost efficiency                                |
-    | gemini-2.5-pro-preview-05-06   | 1M tokens      | Enhanced thinking and reasoning, multimodal understanding, advanced coding, and more |
-    | gemini-2.0-flash               | 1M tokens      | Next generation features, speed, thinking, and realtime streaming |
-    | gemini-2.0-flash-lite          | 1M tokens      | Cost efficiency and low latency                                   |
-    | gemini-1.5-flash               | 1M tokens      | Balanced multimodal model, good for most tasks                    |
-    | gemini-1.5-flash-8B            | 1M tokens      | Fastest, most cost-efficient, good for high-frequency tasks       |
-    | gemini-1.5-pro                 | 2M tokens      | Best performing, wide variety of reasoning tasks including logical reasoning, coding, and creative collaboration |
-
-    The full list of models is available in the [Gemini model docs](https://ai.google.dev/gemini-api/docs/models).
-
-    ### Gemma
-
-    The Gemini API also allows you to use your API key to access [Gemma models](https://ai.google.dev/gemma/docs) hosted on Google infrastructure.
-
-    | Model          | Context Window |
-    |----------------|----------------|
-    | gemma-3-1b-it  | 32k tokens     |
-    | gemma-3-4b-it  | 32k tokens     |
-    | gemma-3-12b-it | 32k tokens     |
-    | gemma-3-27b-it | 128k tokens    |
-
-  </Accordion>
-  <Accordion title="Google (Vertex AI)">
-    Get credentials from your Google Cloud Console and save it to a JSON file, then load it with the following code:
+    Get credentials from your Google Cloud Console and save it to a JSON file with the following code:
     ```python Code
     import json
 
@@ -241,18 +205,14 @@ In this section, you'll find detailed examples that help you select, configure,
         vertex_credentials=vertex_credentials_json
     )
     ```
-
     Google offers a range of powerful models optimized for different use cases:
 
-    | Model                          | Context Window | Best For                                                          |
-    |--------------------------------|----------------|-------------------------------------------------------------------|
-    | gemini-2.5-flash-preview-04-17 | 1M tokens      | Adaptive thinking, cost efficiency                                |
-    | gemini-2.5-pro-preview-05-06   | 1M tokens      | Enhanced thinking and reasoning, multimodal understanding, advanced coding, and more |
-    | gemini-2.0-flash               | 1M tokens      | Next generation features, speed, thinking, and realtime streaming |
-    | gemini-2.0-flash-lite          | 1M tokens      | Cost efficiency and low latency                                   |
-    | gemini-1.5-flash               | 1M tokens      | Balanced multimodal model, good for most tasks                    |
-    | gemini-1.5-flash-8B            | 1M tokens      | Fastest, most cost-efficient, good for high-frequency tasks       |
-    | gemini-1.5-pro                 | 2M tokens      | Best performing, wide variety of reasoning tasks including logical reasoning, coding, and creative collaboration |
+    | Model                  | Context Window | Best For                                                          |
+    |-----------------------|----------------|------------------------------------------------------------------|
+    | gemini-2.0-flash-exp  | 1M tokens      | Higher quality at faster speed, multimodal model, good for most tasks |
+    | gemini-1.5-flash      | 1M tokens      | Balanced multimodal model, good for most tasks                    |
+    | gemini-1.5-flash-8B   | 1M tokens      | Fastest, most cost-efficient, good for high-frequency tasks       |
+    | gemini-1.5-pro        | 2M tokens      | Best performing, wide variety of reasoning tasks including logical reasoning, coding, and creative collaboration |
   </Accordion>
 
   <Accordion title="Azure">

docs/concepts/memory.mdx

@@ -679,7 +679,6 @@ crewai reset-memories [OPTIONS]
 | `-e`, `--entities` | Reset ENTITIES memory.           | Flag (boolean) | False   |
 | `-k`, `--kickoff-outputs` | Reset LATEST KICKOFF TASK OUTPUTS. | Flag (boolean) | False   |
 | `-kn`, `--knowledge` | Reset KNOWLEDEGE storage | Flag (boolean) | False   |
-| `-akn`, `--agent-knowledge` | Reset AGENT KNOWLEDGE storage | Flag (boolean) | False   |
 | `-a`, `--all`      | Reset ALL memories.              | Flag (boolean) | False   |
 
 Note: To use the cli command you need to have your crew in a file called crew.py in the same directory.
@@ -717,11 +716,9 @@ my_crew.reset_memories(command_type = 'all') # Resets all the memory
 | `entities`         | Reset ENTITIES memory.           | 
 | `kickoff_outputs`  | Reset LATEST KICKOFF TASK OUTPUTS. |
 | `knowledge`        | Reset KNOWLEDGE memory.          |
-| `agent_knowledge`  | Reset AGENT KNOWLEDGE memory.    |
 | `all`              | Reset ALL memories.              |
 
 
-
 ## Benefits of Using CrewAI's Memory System
 
 - 🦾 **Adaptive Learning:** Crews become more efficient over time, adapting to new information and refining their approach to tasks.

docs/how-to/arize-phoenix-observability.mdx

@@ -68,13 +68,7 @@ We'll create a CrewAI application where two agents collaborate to research and w
 ```python
 from crewai import Agent, Crew, Process, Task
 from crewai_tools import SerperDevTool
-from openinference.instrumentation.crewai import CrewAIInstrumentor
-from phoenix.otel import register
 
-# setup monitoring for your crew
-tracer_provider = register(
-    endpoint="http://localhost:6006/v1/traces")
-CrewAIInstrumentor().instrument(skip_dep_check=True, tracer_provider=tracer_provider)
 search_tool = SerperDevTool()
 
 # Define your agents with roles and goals

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.120.0"
+version = "0.119.0"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<3.13"
@@ -45,7 +45,7 @@ Documentation = "https://docs.crewai.com"
 Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
-tools = ["crewai-tools~=0.45.0"]
+tools = ["crewai-tools~=0.44.0"]
 embeddings = [
     "tiktoken~=0.7.0"
 ]

src/crewai/__init__.py

@@ -17,7 +17,7 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.120.0"
+__version__ = "0.119.0"
 __all__ = [
     "Agent",
     "Crew",

src/crewai/agent.py

@@ -20,7 +20,6 @@ from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.utilities import Converter, Prompts
 from crewai.utilities.agent_utils import (
     get_tool_names,
-    load_agent_from_repository,
     parse_tools,
     render_text_description_and_args,
 )
@@ -135,16 +134,6 @@ class Agent(BaseAgent):
         default=None,
         description="Knowledge search query for the agent dynamically generated by the agent.",
     )
-    from_repository: Optional[str] = Field(
-        default=None,
-        description="The Agent's role to be used from your repository.",
-    )
-
-    @model_validator(mode="before")
-    def validate_from_repository(cls, v):
-        if v is not None and (from_repository := v.get("from_repository")):
-            return load_agent_from_repository(from_repository) | v
-        return v
 
     @model_validator(mode="after")
     def post_init_setup(self):

src/crewai/cli/authentication/token.py

@@ -5,5 +5,5 @@ def get_auth_token() -> str:
     """Get the authentication token."""
     access_token = TokenManager().get_token()
     if not access_token:
-        raise Exception("No token found, make sure you are logged in")
+        raise Exception()
     return access_token

src/crewai/cli/cli.py

@@ -1,5 +1,6 @@
+import os
 from importlib.metadata import version as get_version
-from typing import Optional
+from typing import Optional, Tuple
 
 import click
 
@@ -137,8 +138,12 @@ def log_tasks_outputs() -> None:
 @click.option("-s", "--short", is_flag=True, help="Reset SHORT TERM memory")
 @click.option("-e", "--entities", is_flag=True, help="Reset ENTITIES memory")
 @click.option("-kn", "--knowledge", is_flag=True, help="Reset KNOWLEDGE storage")
-@click.option("-akn", "--agent-knowledge", is_flag=True, help="Reset AGENT KNOWLEDGE storage")
-@click.option("-k","--kickoff-outputs",is_flag=True,help="Reset LATEST KICKOFF TASK OUTPUTS")
+@click.option(
+    "-k",
+    "--kickoff-outputs",
+    is_flag=True,
+    help="Reset LATEST KICKOFF TASK OUTPUTS",
+)
 @click.option("-a", "--all", is_flag=True, help="Reset ALL memories")
 def reset_memories(
     long: bool,
@@ -146,20 +151,18 @@ def reset_memories(
     entities: bool,
     knowledge: bool,
     kickoff_outputs: bool,
-    agent_knowledge: bool,
     all: bool,
 ) -> None:
     """
-    Reset the crew memories (long, short, entity, latest_crew_kickoff_ouputs, knowledge, agent_knowledge). This will delete all the data saved.
+    Reset the crew memories (long, short, entity, latest_crew_kickoff_ouputs). This will delete all the data saved.
     """
     try:
-        memory_types = [long, short, entities, knowledge, agent_knowledge, kickoff_outputs, all]
-        if not any(memory_types):
+        if not all and not (long or short or entities or knowledge or kickoff_outputs):
             click.echo(
                 "Please specify at least one memory type to reset using the appropriate flags."
             )
             return
-        reset_memories_command(long, short, entities, knowledge, agent_knowledge, kickoff_outputs, all)
+        reset_memories_command(long, short, entities, knowledge, kickoff_outputs, all)
     except Exception as e:
         click.echo(f"An error occurred while resetting memories: {e}", err=True)
 

src/crewai/cli/constants.py

@@ -13,7 +13,7 @@ ENV_VARS = {
     ],
     "gemini": [
         {
-            "prompt": "Enter your GEMINI API key from https://ai.dev/apikey (press Enter to skip)",
+            "prompt": "Enter your GEMINI API key (press Enter to skip)",
             "key_name": "GEMINI_API_KEY",
         }
     ],

src/crewai/cli/plus_api.py

@@ -14,7 +14,6 @@ class PlusAPI:
 
     TOOLS_RESOURCE = "/crewai_plus/api/v1/tools"
     CREWS_RESOURCE = "/crewai_plus/api/v1/crews"
-    AGENTS_RESOURCE = "/crewai_plus/api/v1/agents"
 
     def __init__(self, api_key: str) -> None:
         self.api_key = api_key
@@ -38,9 +37,6 @@ class PlusAPI:
     def get_tool(self, handle: str):
         return self._make_request("GET", f"{self.TOOLS_RESOURCE}/{handle}")
 
-    def get_agent(self, handle: str):
-        return self._make_request("GET", f"{self.AGENTS_RESOURCE}/{handle}")
-
     def publish_tool(
         self,
         handle: str,

src/crewai/cli/reset_memories_command.py

@@ -10,7 +10,6 @@ def reset_memories_command(
     short,
     entity,
     knowledge,
-    agent_knowledge,
     kickoff_outputs,
     all,
 ) -> None:
@@ -24,11 +23,10 @@ def reset_memories_command(
       kickoff_outputs (bool): Whether to reset the latest kickoff task outputs.
       all (bool): Whether to reset all memories.
       knowledge (bool): Whether to reset the knowledge.
-      agent_knowledge (bool): Whether to reset the agents knowledge.
     """
 
     try:
-        if not any([long, short, entity, kickoff_outputs, knowledge, agent_knowledge, all]):
+        if not any([long, short, entity, kickoff_outputs, knowledge, all]):
             click.echo(
                 "No memory type specified. Please specify at least one type to reset."
             )
@@ -69,11 +67,6 @@ def reset_memories_command(
                 click.echo(
                     f"[Crew ({crew.name if crew.name else crew.id})] Knowledge has been reset."
                 )
-            if agent_knowledge:
-                crew.reset_memories(command_type="agent_knowledge")
-                click.echo(
-                    f"[Crew ({crew.name if crew.name else crew.id})] Agents knowledge has been reset."
-                )
 
     except subprocess.CalledProcessError as e:
         click.echo(f"An error occurred while resetting the memories: {e}", err=True)

src/crewai/cli/templates/crew/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.13"
 dependencies = [
-    "crewai[tools]>=0.120.0,<1.0.0"
+    "crewai[tools]>=0.119.0,<1.0.0"
 ]
 
 [project.scripts]

src/crewai/cli/templates/flow/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.13"
 dependencies = [
-    "crewai[tools]>=0.120.0,<1.0.0",
+    "crewai[tools]>=0.119.0,<1.0.0",
 ]
 
 [project.scripts]

src/crewai/cli/templates/tool/pyproject.toml

@@ -5,7 +5,7 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<3.13"
 dependencies = [
-    "crewai[tools]>=0.120.0"
+    "crewai[tools]>=0.119.0"
 ]
 
 [tool.crewai]

src/crewai/crew.py

@@ -52,7 +52,7 @@ from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.tools.base_tool import BaseTool, Tool
 from crewai.types.usage_metrics import UsageMetrics
 from crewai.utilities import I18N, FileHandler, Logger, RPMController
-from crewai.utilities.constants import NOT_SPECIFIED, TRAINING_DATA_FILE
+from crewai.utilities.constants import TRAINING_DATA_FILE
 from crewai.utilities.evaluators.crew_evaluator_handler import CrewEvaluator
 from crewai.utilities.evaluators.task_evaluator import TaskEvaluator
 from crewai.utilities.events.crew_events import (
@@ -478,7 +478,7 @@ class Crew(FlowTrackable, BaseModel):
         separated by a synchronous task.
         """
         for i, task in enumerate(self.tasks):
-            if task.async_execution and isinstance(task.context, list):
+            if task.async_execution and task.context:
                 for context_task in task.context:
                     if context_task.async_execution:
                         for j in range(i - 1, -1, -1):
@@ -496,7 +496,7 @@ class Crew(FlowTrackable, BaseModel):
         task_indices = {id(task): i for i, task in enumerate(self.tasks)}
 
         for task in self.tasks:
-            if isinstance(task.context, list):
+            if task.context:
                 for context_task in task.context:
                     if id(context_task) not in task_indices:
                         continue  # Skip context tasks not in the main tasks list
@@ -1034,14 +1034,11 @@ class Crew(FlowTrackable, BaseModel):
                 )
         return cast(List[BaseTool], tools)
 
-    def _get_context(self, task: Task, task_outputs: List[TaskOutput]) -> str:
-        if not task.context:
-            return ""
-
+    def _get_context(self, task: Task, task_outputs: List[TaskOutput]):
         context = (
-            aggregate_raw_outputs_from_task_outputs(task_outputs)
-            if task.context is NOT_SPECIFIED
-            else aggregate_raw_outputs_from_tasks(task.context)
+            aggregate_raw_outputs_from_tasks(task.context)
+            if task.context
+            else aggregate_raw_outputs_from_task_outputs(task_outputs)
         )
         return context
 
@@ -1229,7 +1226,7 @@ class Crew(FlowTrackable, BaseModel):
             task_mapping[task.key] = cloned_task
 
         for cloned_task, original_task in zip(cloned_tasks, self.tasks):
-            if isinstance(original_task.context, list):
+            if original_task.context:
                 cloned_context = [
                     task_mapping[context_task.key]
                     for context_task in original_task.context
@@ -1356,7 +1353,7 @@ class Crew(FlowTrackable, BaseModel):
 
         Args:
             command_type: Type of memory to reset.
-                Valid options: 'long', 'short', 'entity', 'knowledge', 'agent_knowledge'
+                Valid options: 'long', 'short', 'entity', 'knowledge',
                 'kickoff_outputs', or 'all'
 
         Raises:
@@ -1369,7 +1366,6 @@ class Crew(FlowTrackable, BaseModel):
                 "short",
                 "entity",
                 "knowledge",
-                "agent_knowledge",
                 "kickoff_outputs",
                 "all",
                 "external",
@@ -1394,14 +1390,19 @@ class Crew(FlowTrackable, BaseModel):
 
     def _reset_all_memories(self) -> None:
         """Reset all available memory systems."""
-        memory_systems = self._get_memory_systems()
+        memory_systems = [
+            ("short term", getattr(self, "_short_term_memory", None)),
+            ("entity", getattr(self, "_entity_memory", None)),
+            ("external", getattr(self, "_external_memory", None)),
+            ("long term", getattr(self, "_long_term_memory", None)),
+            ("task output", getattr(self, "_task_output_handler", None)),
+            ("knowledge", getattr(self, "knowledge", None)),
+        ]
 
-        for memory_type, config in memory_systems.items():
-            if (system := config.get('system')) is not None:
-                name = config.get('name')
+        for name, system in memory_systems:
+            if system is not None:
                 try:
-                    reset_fn: Callable = cast(Callable, config.get('reset'))
-                    reset_fn(system)
+                    system.reset()
                     self._logger.log(
                         "info",
                         f"[Crew ({self.name if self.name else self.id})] {name} memory has been reset",
@@ -1420,17 +1421,24 @@ class Crew(FlowTrackable, BaseModel):
         Raises:
             RuntimeError: If the specified memory system fails to reset
         """
-        memory_systems = self._get_memory_systems()
-        config = memory_systems[memory_type]
-        system = config.get('system')
-        name = config.get('name')
+        reset_functions = {
+            "long": (getattr(self, "_long_term_memory", None), "long term"),
+            "short": (getattr(self, "_short_term_memory", None), "short term"),
+            "entity": (getattr(self, "_entity_memory", None), "entity"),
+            "knowledge": (getattr(self, "knowledge", None), "knowledge"),
+            "kickoff_outputs": (
+                getattr(self, "_task_output_handler", None),
+                "task output",
+            ),
+            "external": (getattr(self, "_external_memory", None), "external"),
+        }
 
-        if system is None:
+        memory_system, name = reset_functions[memory_type]
+        if memory_system is None:
             raise RuntimeError(f"{name} memory system is not initialized")
-        
+
         try:
-            reset_fn: Callable = cast(Callable, config.get('reset'))
-            reset_fn(system)
+            memory_system.reset()
             self._logger.log(
                 "info",
                 f"[Crew ({self.name if self.name else self.id})] {name} memory has been reset",
@@ -1439,64 +1447,3 @@ class Crew(FlowTrackable, BaseModel):
             raise RuntimeError(
                 f"[Crew ({self.name if self.name else self.id})] Failed to reset {name} memory: {str(e)}"
             ) from e
-
-    def _get_memory_systems(self):
-        """Get all available memory systems with their configuration.
-        
-        Returns:
-            Dict containing all memory systems with their reset functions and display names.
-        """
-        def default_reset(memory):
-            return memory.reset()
-        def knowledge_reset(memory):
-            return self.reset_knowledge(memory)
-        
-        # Get knowledge for agents 
-        agent_knowledges = [getattr(agent, "knowledge", None) for agent in self.agents 
-                                    if getattr(agent, "knowledge", None) is not None]
-        # Get knowledge for crew and agents
-        crew_knowledge = getattr(self, "knowledge", None)
-        crew_and_agent_knowledges = ([crew_knowledge] if crew_knowledge is not None else []) + agent_knowledges
-
-        return {
-            'short': {
-                'system': getattr(self, "_short_term_memory", None),
-                'reset': default_reset,
-                'name': 'Short Term'
-            },
-            'entity': {
-                'system': getattr(self, "_entity_memory", None),
-                'reset': default_reset,
-                'name': 'Entity'
-            },
-            'external': {
-                'system': getattr(self, "_external_memory", None),
-                'reset': default_reset,
-                'name': 'External'
-            },
-            'long': {
-                'system': getattr(self, "_long_term_memory", None),
-                'reset': default_reset,
-                'name': 'Long Term'
-            },
-            'kickoff_outputs': {
-                'system': getattr(self, "_task_output_handler", None),
-                'reset': default_reset,
-                'name': 'Task Output'
-            },
-            'knowledge': {
-                'system': crew_and_agent_knowledges if crew_and_agent_knowledges else None,
-                'reset': knowledge_reset,
-                'name': 'Crew Knowledge and Agent Knowledge'
-            },
-            'agent_knowledge': {
-                'system': agent_knowledges if agent_knowledges else None,
-                'reset': knowledge_reset,
-                'name': 'Agent Knowledge'
-            }
-        }
-
-    def reset_knowledge(self, knowledges: List[Knowledge]) -> None:
-        """Reset crew and agent knowledge storage."""
-        for ks in knowledges:
-            ks.reset()

src/crewai/llm.py

@@ -5,7 +5,8 @@ import sys
 import threading
 import warnings
 from collections import defaultdict
-from contextlib import contextmanager, redirect_stderr, redirect_stdout
+from contextlib import contextmanager
+from types import SimpleNamespace
 from typing import (
     Any,
     DefaultDict,
@@ -30,6 +31,7 @@ from crewai.utilities.events.llm_events import (
     LLMCallType,
     LLMStreamChunkEvent,
 )
+from crewai.utilities.events.tool_usage_events import ToolExecutionErrorEvent
 
 with warnings.catch_warnings():
     warnings.simplefilter("ignore", UserWarning)
@@ -43,9 +45,6 @@ with warnings.catch_warnings():
     from litellm.utils import supports_response_schema
 
 
-import io
-from typing import TextIO
-
 from crewai.llms.base_llm import BaseLLM
 from crewai.utilities.events import crewai_event_bus
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
@@ -55,17 +54,12 @@ from crewai.utilities.exceptions.context_window_exceeding_exception import (
 load_dotenv()
 
 
-class FilteredStream(io.TextIOBase):
-    _lock = None
-
-    def __init__(self, original_stream: TextIO):
+class FilteredStream:
+    def __init__(self, original_stream):
         self._original_stream = original_stream
         self._lock = threading.Lock()
 
-    def write(self, s: str) -> int:
-        if not self._lock:
-            self._lock = threading.Lock()
-
+    def write(self, s) -> int:
         with self._lock:
             # Filter out extraneous messages from LiteLLM
             if (
@@ -220,11 +214,15 @@ def suppress_warnings():
         )
 
         # Redirect stdout and stderr
-        with (
-            redirect_stdout(FilteredStream(sys.stdout)),
-            redirect_stderr(FilteredStream(sys.stderr)),
-        ):
+        old_stdout = sys.stdout
+        old_stderr = sys.stderr
+        sys.stdout = FilteredStream(old_stdout)
+        sys.stderr = FilteredStream(old_stderr)
+        try:
             yield
+        finally:
+            sys.stdout = old_stdout
+            sys.stderr = old_stderr
 
 
 class Delta(TypedDict):

src/crewai/task.py

@@ -2,6 +2,7 @@ import datetime
 import inspect
 import json
 import logging
+import re
 import threading
 import uuid
 from concurrent.futures import Future
@@ -40,7 +41,6 @@ from crewai.tasks.output_format import OutputFormat
 from crewai.tasks.task_output import TaskOutput
 from crewai.tools.base_tool import BaseTool
 from crewai.utilities.config import process_config
-from crewai.utilities.constants import NOT_SPECIFIED
 from crewai.utilities.converter import Converter, convert_to_model
 from crewai.utilities.events import (
     TaskCompletedEvent,
@@ -97,7 +97,7 @@ class Task(BaseModel):
     )
     context: Optional[List["Task"]] = Field(
         description="Other tasks that will have their output used as context for this task.",
-        default=NOT_SPECIFIED,
+        default=None,
     )
     async_execution: Optional[bool] = Field(
         description="Whether the task should be executed asynchronously or not.",
@@ -643,7 +643,7 @@ class Task(BaseModel):
 
         cloned_context = (
             [task_mapping[context_task.key] for context_task in self.context]
-            if isinstance(self.context, list)
+            if self.context
             else None
         )
 

src/crewai/telemetry/telemetry.py

@@ -10,18 +10,6 @@ from contextlib import contextmanager
 from importlib.metadata import version
 from typing import TYPE_CHECKING, Any, Optional
 
-from opentelemetry import trace
-from opentelemetry.exporter.otlp.proto.http.trace_exporter import (
-    OTLPSpanExporter,
-)
-from opentelemetry.sdk.resources import SERVICE_NAME, Resource
-from opentelemetry.sdk.trace import TracerProvider
-from opentelemetry.sdk.trace.export import (
-    BatchSpanProcessor,
-    SpanExportResult,
-)
-from opentelemetry.trace import Span, Status, StatusCode
-
 from crewai.telemetry.constants import (
     CREWAI_TELEMETRY_BASE_URL,
     CREWAI_TELEMETRY_SERVICE_NAME,
@@ -37,6 +25,18 @@ def suppress_warnings():
         yield
 
 
+from opentelemetry import trace  # noqa: E402
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import (
+    OTLPSpanExporter,  # noqa: E402
+)
+from opentelemetry.sdk.resources import SERVICE_NAME, Resource  # noqa: E402
+from opentelemetry.sdk.trace import TracerProvider  # noqa: E402
+from opentelemetry.sdk.trace.export import (  # noqa: E402
+    BatchSpanProcessor,
+    SpanExportResult,
+)
+from opentelemetry.trace import Span, Status, StatusCode  # noqa: E402
+
 if TYPE_CHECKING:
     from crewai.crew import Crew
     from crewai.task import Task
@@ -232,7 +232,7 @@ class Telemetry:
                                 "agent_key": task.agent.key if task.agent else None,
                                 "context": (
                                     [task.description for task in task.context]
-                                    if isinstance(task.context, list)
+                                    if task.context
                                     else None
                                 ),
                                 "tools_names": [
@@ -748,7 +748,7 @@ class Telemetry:
                             "agent_key": task.agent.key if task.agent else None,
                             "context": (
                                 [task.description for task in task.context]
-                                if isinstance(task.context, list)
+                                if task.context
                                 else None
                             ),
                             "tools_names": [

src/crewai/utilities/agent_utils.py

@@ -16,7 +16,6 @@ from crewai.tools.base_tool import BaseTool
 from crewai.tools.structured_tool import CrewStructuredTool
 from crewai.tools.tool_types import ToolResult
 from crewai.utilities import I18N, Printer
-from crewai.utilities.errors import AgentRepositoryError
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededException,
 )
@@ -429,41 +428,3 @@ def show_agent_logs(
             printer.print(
                 content=f"\033[95m## Final Answer:\033[00m \033[92m\n{formatted_answer.output}\033[00m\n\n"
             )
-
-
-def load_agent_from_repository(from_repository: str) -> Dict[str, Any]:
-    attributes: Dict[str, Any] = {}
-    if from_repository:
-        import importlib
-
-        from crewai.cli.authentication.token import get_auth_token
-        from crewai.cli.plus_api import PlusAPI
-
-        client = PlusAPI(api_key=get_auth_token())
-        response = client.get_agent(from_repository)
-        if response.status_code == 404:
-            raise AgentRepositoryError(
-                f"Agent {from_repository} does not exist, make sure the name is correct or the agent is available on your organization"
-            )
-
-        if response.status_code != 200:
-            raise AgentRepositoryError(
-                f"Agent {from_repository} could not be loaded: {response.text}"
-            )
-
-        agent = response.json()
-        for key, value in agent.items():
-            if key == "tools":
-                attributes[key] = []
-                for tool in value:
-                    try:
-                        module = importlib.import_module("crewai_tools")
-                        tool_class = getattr(module, tool["name"])
-                        attributes[key].append(tool_class())
-                    except Exception as e:
-                        raise AgentRepositoryError(
-                            f"Tool {tool['name']} could not be loaded: {e}"
-                        ) from e
-            else:
-                attributes[key] = value
-    return attributes

src/crewai/utilities/constants.py

@@ -5,14 +5,3 @@ KNOWLEDGE_DIRECTORY = "knowledge"
 MAX_LLM_RETRY = 3
 MAX_FILE_NAME_LENGTH = 255
 EMITTER_COLOR = "bold_blue"
-
-
-class _NotSpecified:
-    def __repr__(self):
-        return "NOT_SPECIFIED"
-
-
-# Sentinel value used to detect when no value has been explicitly provided.
-# Unlike `None`, which might be a valid value from the user, `NOT_SPECIFIED` allows
-# us to distinguish between "not passed at all" and "explicitly passed None" or "[]".
-NOT_SPECIFIED = _NotSpecified()

src/crewai/utilities/errors.py

@@ -1,5 +1,4 @@
 """Error message definitions for CrewAI database operations."""
-
 from typing import Optional
 
 
@@ -38,9 +37,3 @@ class DatabaseError:
             The formatted error message
         """
         return template.format(str(error))
-
-
-class AgentRepositoryError(Exception):
-    """Exception raised when an agent repository is not found."""
-
-    ...

src/crewai/utilities/formatter.py

@@ -1,6 +1,6 @@
+import re
 from typing import TYPE_CHECKING, List
 
-
 if TYPE_CHECKING:
     from crewai.task import Task
     from crewai.tasks.task_output import TaskOutput
@@ -17,11 +17,6 @@ def aggregate_raw_outputs_from_task_outputs(task_outputs: List["TaskOutput"]) ->
 
 def aggregate_raw_outputs_from_tasks(tasks: List["Task"]) -> str:
     """Generate string context from the tasks."""
-
-    task_outputs = (
-        [task.output for task in tasks if task.output is not None]
-        if isinstance(tasks, list)
-        else []
-    )
+    task_outputs = [task.output for task in tasks if task.output is not None]
 
     return aggregate_raw_outputs_from_task_outputs(task_outputs)

src/crewai/utilities/string_utils.py

@@ -59,7 +59,7 @@ def interpolate_only(
     # The regex pattern to find valid variable placeholders
     # Matches {variable_name} where variable_name starts with a letter/underscore
     # and contains only letters, numbers, and underscores
-    pattern = r"\{([A-Za-z_][A-Za-z0-9_\-]*)\}"
+    pattern = r"\{([A-Za-z_][A-Za-z0-9_]*)\}"
 
     # Find all matching variables in the input string
     variables = re.findall(pattern, input_string)

tests/agent_test.py

@@ -2,7 +2,7 @@
 
 import os
 from unittest import mock
-from unittest.mock import MagicMock, patch
+from unittest.mock import patch
 
 import pytest
 
@@ -18,7 +18,6 @@ from crewai.tools import tool
 from crewai.tools.tool_calling import InstructorToolCalling
 from crewai.tools.tool_usage import ToolUsage
 from crewai.utilities import RPMController
-from crewai.utilities.errors import AgentRepositoryError
 from crewai.utilities.events import crewai_event_bus
 from crewai.utilities.events.tool_usage_events import ToolUsageFinishedEvent
 
@@ -309,7 +308,9 @@ def test_cache_hitting():
     def handle_tool_end(source, event):
         received_events.append(event)
 
-    with (patch.object(CacheHandler, "read") as read,):
+    with (
+        patch.object(CacheHandler, "read") as read,
+    ):
         read.return_value = "0"
         task = Task(
             description="What is 2 times 6? Ignore correctness and just return the result of the multiplication tool, you must use the tool.",
@@ -1039,7 +1040,7 @@ def test_agent_human_input():
             CrewAgentExecutor,
             "_invoke_loop",
             return_value=AgentFinish(output="Hello", thought="", text=""),
-        ),
+        ) as mock_invoke_loop,
     ):
         # Execute the task
         output = agent.execute_task(task)
@@ -2024,99 +2025,3 @@ def test_get_knowledge_search_query():
                 },
             ]
         )
-
-
-@pytest.fixture
-def mock_get_auth_token():
-    with patch(
-        "crewai.cli.authentication.token.get_auth_token", return_value="test_token"
-    ):
-        yield
-
-
-@patch("crewai.cli.plus_api.PlusAPI.get_agent")
-def test_agent_from_repository(mock_get_agent, mock_get_auth_token):
-    from crewai_tools import SerperDevTool
-
-    mock_get_response = MagicMock()
-    mock_get_response.status_code = 200
-    mock_get_response.json.return_value = {
-        "role": "test role",
-        "goal": "test goal",
-        "backstory": "test backstory",
-        "tools": [{"name": "SerperDevTool"}],
-    }
-    mock_get_agent.return_value = mock_get_response
-    agent = Agent(from_repository="test_agent")
-
-    assert agent.role == "test role"
-    assert agent.goal == "test goal"
-    assert agent.backstory == "test backstory"
-    assert len(agent.tools) == 1
-    assert isinstance(agent.tools[0], SerperDevTool)
-
-
-@patch("crewai.cli.plus_api.PlusAPI.get_agent")
-def test_agent_from_repository_override_attributes(mock_get_agent, mock_get_auth_token):
-    from crewai_tools import SerperDevTool
-
-    mock_get_response = MagicMock()
-    mock_get_response.status_code = 200
-    mock_get_response.json.return_value = {
-        "role": "test role",
-        "goal": "test goal",
-        "backstory": "test backstory",
-        "tools": [{"name": "SerperDevTool"}],
-    }
-    mock_get_agent.return_value = mock_get_response
-    agent = Agent(from_repository="test_agent", role="Custom Role")
-
-    assert agent.role == "Custom Role"
-    assert agent.goal == "test goal"
-    assert agent.backstory == "test backstory"
-    assert len(agent.tools) == 1
-    assert isinstance(agent.tools[0], SerperDevTool)
-
-
-@patch("crewai.cli.plus_api.PlusAPI.get_agent")
-def test_agent_from_repository_with_invalid_tools(mock_get_agent, mock_get_auth_token):
-    mock_get_response = MagicMock()
-    mock_get_response.status_code = 200
-    mock_get_response.json.return_value = {
-        "role": "test role",
-        "goal": "test goal",
-        "backstory": "test backstory",
-        "tools": [{"name": "DoesNotExist"}],
-    }
-    mock_get_agent.return_value = mock_get_response
-    with pytest.raises(
-        AgentRepositoryError,
-        match="Tool DoesNotExist could not be loaded: module 'crewai_tools' has no attribute 'DoesNotExist'",
-    ):
-        Agent(from_repository="test_agent")
-
-
-@patch("crewai.cli.plus_api.PlusAPI.get_agent")
-def test_agent_from_repository_internal_error(mock_get_agent, mock_get_auth_token):
-    mock_get_response = MagicMock()
-    mock_get_response.status_code = 500
-    mock_get_response.text = "Internal server error"
-    mock_get_agent.return_value = mock_get_response
-    with pytest.raises(
-        AgentRepositoryError,
-        match="Agent test_agent could not be loaded: Internal server error",
-    ):
-        Agent(from_repository="test_agent")
-
-
-@patch("crewai.cli.plus_api.PlusAPI.get_agent")
-def test_agent_from_repository_agent_not_found(mock_get_agent, mock_get_auth_token):
-    mock_get_response = MagicMock()
-    mock_get_response.status_code = 404
-    mock_get_response.text = "Agent not found"
-    mock_get_agent.return_value = mock_get_response
-    with pytest.raises(
-        AgentRepositoryError,
-        match="Agent test_agent does not exist, make sure the name is correct or the agent is available on your organization",
-    ):
-        Agent(from_repository="test_agent")

tests/cassettes/test_task_interpolation_with_hyphens.yaml

@@ -1,121 +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: be an assistant that responds
-      with say hello world\nTo give my best complete final answer to the task respond
-      using 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: be an assistant that responds
-      with say hello world\n\nThis is the expected criteria for your final answer:
-      The response should be addressing: say hello world\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:"]}'
-    headers:
-      accept:
-      - application/json
-      accept-encoding:
-      - gzip, deflate, zstd
-      connection:
-      - keep-alive
-      content-length:
-      - '1108'
-      content-type:
-      - application/json
-      host:
-      - api.openai.com
-      user-agent:
-      - OpenAI/Python 1.68.2
-      x-stainless-arch:
-      - arm64
-      x-stainless-async:
-      - 'false'
-      x-stainless-lang:
-      - python
-      x-stainless-os:
-      - MacOS
-      x-stainless-package-version:
-      - 1.68.2
-      x-stainless-raw-response:
-      - 'true'
-      x-stainless-read-timeout:
-      - '600.0'
-      x-stainless-retry-count:
-      - '0'
-      x-stainless-runtime:
-      - CPython
-      x-stainless-runtime-version:
-      - 3.12.9
-    method: POST
-    uri: https://api.openai.com/v1/chat/completions
-  response:
-    body:
-      string: !!binary |
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tests/cli/cli_test.py

@@ -162,18 +162,8 @@ def test_reset_knowledge(mock_get_crews, runner):
     assert call_count == 1, "reset_memories should have been called once"
 
 
-def test_reset_agent_knowledge(mock_get_crews, runner):
-    result = runner.invoke(reset_memories, ["--agent-knowledge"])
-    call_count = 0
-    for crew in mock_get_crews.return_value:
-        crew.reset_memories.assert_called_once_with(command_type="agent_knowledge")
-        assert f"[Crew ({crew.name})] Agents knowledge has been reset." in result.output
-        call_count += 1
-
-    assert call_count == 1, "reset_memories should have been called once"
-
-
 def test_reset_memory_from_many_crews(mock_get_crews, runner):
+
     crews = []
     for crew_id in ["id-1234", "id-5678"]:
         mock_crew = mock.Mock(spec=Crew)

tests/crew_test.py

@@ -2,19 +2,22 @@
 
 import hashlib
 import json
+import os
+import tempfile
 from concurrent.futures import Future
 from unittest import mock
-from unittest.mock import ANY, MagicMock, patch
+from unittest.mock import MagicMock, patch
 
 import pydantic_core
 import pytest
 
 from crewai.agent import Agent
 from crewai.agents import CacheHandler
+from crewai.agents.cache import CacheHandler
+from crewai.agents.crew_agent_executor import CrewAgentExecutor
 from crewai.crew import Crew
 from crewai.crews.crew_output import CrewOutput
-from crewai.flow import Flow, start
-from crewai.knowledge.knowledge import Knowledge
+from crewai.flow import Flow, listen, start
 from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
 from crewai.llm import LLM
 from crewai.memory.contextual.contextual_memory import ContextualMemory
@@ -3138,30 +3141,6 @@ def test_replay_with_context():
         assert crew.tasks[1].context[0].output.raw == "context raw output"
 
 
-def test_replay_with_context_set_to_nullable():
-    agent = Agent(role="test_agent", backstory="Test Description", goal="Test Goal")
-    task1 = Task(
-        description="Context Task", expected_output="Say Task Output", agent=agent
-    )
-    task2 = Task(
-        description="Test Task", expected_output="Say Hi", agent=agent, context=[]
-    )
-    task3 = Task(
-        description="Test Task 3", expected_output="Say Hi", agent=agent, context=None
-    )
-
-    crew = Crew(agents=[agent], tasks=[task1, task2, task3], process=Process.sequential)
-    with patch("crewai.task.Task.execute_sync") as mock_execute_task:
-        mock_execute_task.return_value = TaskOutput(
-            description="Test Task Output",
-            raw="test raw output",
-            agent="test_agent",
-        )
-        crew.kickoff()
-
-    mock_execute_task.assert_called_with(agent=ANY, context="", tools=ANY)
-
-
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_replay_with_invalid_task_id():
     agent = Agent(role="test_agent", backstory="Test Description", goal="Test Goal")
@@ -4404,165 +4383,3 @@ def test_sets_parent_flow_when_inside_flow(researcher, writer):
     flow = MyFlow()
     result = flow.kickoff()
     assert result.parent_flow is flow
-
-
-def test_reset_knowledge_with_no_crew_knowledge(researcher,writer):
-    crew = Crew(
-        agents=[researcher, writer],
-        process=Process.sequential,
-        tasks=[
-            Task(description="Task 1", expected_output="output", agent=researcher),
-            Task(description="Task 2", expected_output="output", agent=writer),
-        ]
-    )
-
-    with pytest.raises(RuntimeError) as excinfo:
-        crew.reset_memories(command_type='knowledge')
-        
-        # Optionally, you can also check the error message
-    assert "Crew Knowledge and Agent Knowledge memory system is not initialized" in str(excinfo.value)  # Replace with the expected message
-
-
-def test_reset_knowledge_with_only_crew_knowledge(researcher,writer):
-    mock_ks = MagicMock(spec=Knowledge)
-
-    with patch.object(Crew,'reset_knowledge') as mock_reset_agent_knowledge:
-        crew = Crew(
-            agents=[researcher, writer],
-            process=Process.sequential,
-            tasks=[
-                Task(description="Task 1", expected_output="output", agent=researcher),
-                Task(description="Task 2", expected_output="output", agent=writer),
-            ],
-            knowledge=mock_ks
-        )
-
-        crew.reset_memories(command_type='knowledge')
-        mock_reset_agent_knowledge.assert_called_once_with([mock_ks])
-
-
-def test_reset_knowledge_with_crew_and_agent_knowledge(researcher,writer):
-    mock_ks_crew = MagicMock(spec=Knowledge)
-    mock_ks_research = MagicMock(spec=Knowledge)
-    mock_ks_writer = MagicMock(spec=Knowledge)
-
-    researcher.knowledge = mock_ks_research
-    writer.knowledge = mock_ks_writer
-
-    with patch.object(Crew,'reset_knowledge') as mock_reset_agent_knowledge:
-        crew = Crew(
-            agents=[researcher, writer],
-            process=Process.sequential,
-            tasks=[
-                Task(description="Task 1", expected_output="output", agent=researcher),
-                Task(description="Task 2", expected_output="output", agent=writer),
-            ],
-            knowledge=mock_ks_crew
-        )
-
-        crew.reset_memories(command_type='knowledge')
-        mock_reset_agent_knowledge.assert_called_once_with([mock_ks_crew,mock_ks_research,mock_ks_writer])
-
-
-def test_reset_knowledge_with_only_agent_knowledge(researcher,writer):
-    mock_ks_research = MagicMock(spec=Knowledge)
-    mock_ks_writer = MagicMock(spec=Knowledge)
-
-    researcher.knowledge = mock_ks_research
-    writer.knowledge = mock_ks_writer
-
-    with patch.object(Crew,'reset_knowledge') as mock_reset_agent_knowledge:
-        crew = Crew(
-            agents=[researcher, writer],
-            process=Process.sequential,
-            tasks=[
-                Task(description="Task 1", expected_output="output", agent=researcher),
-                Task(description="Task 2", expected_output="output", agent=writer),
-            ],
-        )
-
-        crew.reset_memories(command_type='knowledge')
-        mock_reset_agent_knowledge.assert_called_once_with([mock_ks_research,mock_ks_writer])
-
-
-def test_reset_agent_knowledge_with_no_agent_knowledge(researcher,writer):
-    crew = Crew(
-        agents=[researcher, writer],
-        process=Process.sequential,
-        tasks=[
-            Task(description="Task 1", expected_output="output", agent=researcher),
-            Task(description="Task 2", expected_output="output", agent=writer),
-        ],
-    )
-
-    with pytest.raises(RuntimeError) as excinfo:
-        crew.reset_memories(command_type='agent_knowledge')
-    
-    # Optionally, you can also check the error message
-    assert "Agent Knowledge memory system is not initialized" in str(excinfo.value)  # Replace with the expected message
-
-
-def test_reset_agent_knowledge_with_only_crew_knowledge(researcher,writer):
-    mock_ks = MagicMock(spec=Knowledge)
-
-    crew = Crew(
-        agents=[researcher, writer],
-        process=Process.sequential,
-        tasks=[
-            Task(description="Task 1", expected_output="output", agent=researcher),
-            Task(description="Task 2", expected_output="output", agent=writer),
-        ],
-        knowledge=mock_ks
-    )
-
-    with pytest.raises(RuntimeError) as excinfo:
-        crew.reset_memories(command_type='agent_knowledge')
-    
-    # Optionally, you can also check the error message
-    assert "Agent Knowledge memory system is not initialized" in str(excinfo.value)  # Replace with the expected message
-
-
-def test_reset_agent_knowledge_with_crew_and_agent_knowledge(researcher,writer):
-    mock_ks_crew = MagicMock(spec=Knowledge)
-    mock_ks_research = MagicMock(spec=Knowledge)
-    mock_ks_writer = MagicMock(spec=Knowledge)
-
-    researcher.knowledge = mock_ks_research
-    writer.knowledge = mock_ks_writer
-
-    with patch.object(Crew,'reset_knowledge') as mock_reset_agent_knowledge:
-        crew = Crew(
-            agents=[researcher, writer],
-            process=Process.sequential,
-            tasks=[
-                Task(description="Task 1", expected_output="output", agent=researcher),
-                Task(description="Task 2", expected_output="output", agent=writer),
-            ],
-            knowledge=mock_ks_crew
-        )
-
-        crew.reset_memories(command_type='agent_knowledge')
-        mock_reset_agent_knowledge.assert_called_once_with([mock_ks_research,mock_ks_writer])
-
-
-def test_reset_agent_knowledge_with_only_agent_knowledge(researcher,writer):
-    mock_ks_research = MagicMock(spec=Knowledge)
-    mock_ks_writer = MagicMock(spec=Knowledge)
-
-    researcher.knowledge = mock_ks_research
-    writer.knowledge = mock_ks_writer
-
-    with patch.object(Crew,'reset_knowledge') as mock_reset_agent_knowledge:
-        crew = Crew(
-            agents=[researcher, writer],
-            process=Process.sequential,
-            tasks=[
-                Task(description="Task 1", expected_output="output", agent=researcher),
-                Task(description="Task 2", expected_output="output", agent=writer),
-            ],
-        )
-
-        crew.reset_memories(command_type='agent_knowledge')
-        mock_reset_agent_knowledge.assert_called_once_with([mock_ks_research,mock_ks_writer])
-
-

tests/task_test.py

@@ -837,6 +837,9 @@ 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"
+    )
 
     # Test JSON structure preservation
     json_string = '{"info": "Look at {placeholder}", "nested": {"val": "{nestedVal}"}}'
@@ -868,6 +871,10 @@ def test_interpolate_only():
 
 def test_interpolate_only_with_dict_inside_expected_output():
     """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: {questions}",
+    )
 
     json_string = '{"questions": {"main_question": "What is the user\'s name?", "secondary_question": "What is the user\'s age?"}}'
     result = interpolate_only(
@@ -1087,6 +1094,11 @@ def test_task_execution_times():
 
 
 def test_interpolate_with_list_of_strings():
+    task = Task(
+        description="Test list interpolation",
+        expected_output="List: {items}",
+    )
+
     # Test simple list of strings
     input_str = "Available items: {items}"
     inputs = {"items": ["apple", "banana", "cherry"]}
@@ -1100,6 +1112,11 @@ def test_interpolate_with_list_of_strings():
 
 
 def test_interpolate_with_list_of_dicts():
+    task = Task(
+        description="Test list of dicts interpolation",
+        expected_output="People: {people}",
+    )
+
     input_data = {
         "people": [
             {"name": "Alice", "age": 30, "skills": ["Python", "AI"]},
@@ -1120,6 +1137,11 @@ def test_interpolate_with_list_of_dicts():
 
 
 def test_interpolate_with_nested_structures():
+    task = Task(
+        description="Test nested structures",
+        expected_output="Company: {company}",
+    )
+
     input_data = {
         "company": {
             "name": "TechCorp",
@@ -1143,6 +1165,11 @@ def test_interpolate_with_nested_structures():
 
 
 def test_interpolate_with_special_characters():
+    task = Task(
+        description="Test special characters in dicts",
+        expected_output="Data: {special_data}",
+    )
+
     input_data = {
         "special_data": {
             "quotes": """This has "double" and 'single' quotes""",
@@ -1161,6 +1188,11 @@ def test_interpolate_with_special_characters():
 
 
 def test_interpolate_mixed_types():
+    task = Task(
+        description="Test mixed type interpolation",
+        expected_output="Mixed: {data}",
+    )
+
     input_data = {
         "data": {
             "name": "Test Dataset",
@@ -1182,6 +1214,11 @@ def test_interpolate_mixed_types():
 
 
 def test_interpolate_complex_combination():
+    task = Task(
+        description="Test complex combination",
+        expected_output="Report: {report}",
+    )
+
     input_data = {
         "report": [
             {
@@ -1206,6 +1243,11 @@ def test_interpolate_complex_combination():
 
 
 def test_interpolate_invalid_type_validation():
+    task = Task(
+        description="Test invalid type validation",
+        expected_output="Should never reach here",
+    )
+
     # Test with invalid top-level type
     with pytest.raises(ValueError) as excinfo:
         interpolate_only("{data}", {"data": set()})  # type: ignore we are purposely testing this failure
@@ -1226,6 +1268,11 @@ def test_interpolate_invalid_type_validation():
 
 
 def test_interpolate_custom_object_validation():
+    task = Task(
+        description="Test custom object rejection",
+        expected_output="Should never reach here",
+    )
+
     class CustomObject:
         def __init__(self, value):
             self.value = value
@@ -1257,6 +1304,11 @@ def test_interpolate_custom_object_validation():
 
 
 def test_interpolate_valid_complex_types():
+    task = Task(
+        description="Test valid complex types",
+        expected_output="Validation should pass",
+    )
+
     # Valid complex structure
     valid_data = {
         "name": "Valid Dataset",
@@ -1276,6 +1328,11 @@ def test_interpolate_valid_complex_types():
 
 
 def test_interpolate_edge_cases():
+    task = Task(
+        description="Test edge cases",
+        expected_output="Edge case handling",
+    )
+
     # Test empty dict and list
     assert interpolate_only("{}", {"data": {}}) == "{}"
     assert interpolate_only("[]", {"data": []}) == "[]"
@@ -1290,6 +1347,11 @@ def test_interpolate_edge_cases():
 
 
 def test_interpolate_valid_types():
+    task = Task(
+        description="Test valid types including null and boolean",
+        expected_output="Should pass validation",
+    )
+
     # Test with boolean and null values (valid JSON types)
     valid_data = {
         "name": "Test",
@@ -1311,11 +1373,11 @@ def test_interpolate_valid_types():
 
 def test_task_with_no_max_execution_time():
     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,
-        max_execution_time=None,
+    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,
+    max_execution_time=None
     )
 
     task = Task(
@@ -1324,7 +1386,7 @@ def test_task_with_no_max_execution_time():
         agent=researcher,
     )
 
-    with patch.object(Agent, "_execute_without_timeout", return_value="ok") as execute:
+    with patch.object(Agent, "_execute_without_timeout", return_value = "ok") as execute:
         result = task.execute_sync(agent=researcher)
         assert result.raw == "ok"
         execute.assert_called_once()
@@ -1333,7 +1395,6 @@ def test_task_with_no_max_execution_time():
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_task_with_max_execution_time():
     from crewai.tools import tool
-
     """Test that execution raises TimeoutError when max_execution_time is exceeded."""
 
     @tool("what amazing tool", result_as_answer=True)
@@ -1351,7 +1412,7 @@ def test_task_with_max_execution_time():
         ),
         allow_delegation=False,
         tools=[my_tool],
-        max_execution_time=4,
+        max_execution_time=4
     )
 
     task = Task(
@@ -1367,7 +1428,6 @@ def test_task_with_max_execution_time():
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_task_with_max_execution_time_exceeded():
     from crewai.tools import tool
-
     """Test that execution raises TimeoutError when max_execution_time is exceeded."""
 
     @tool("what amazing tool", result_as_answer=True)
@@ -1385,7 +1445,7 @@ def test_task_with_max_execution_time_exceeded():
         ),
         allow_delegation=False,
         tools=[my_tool],
-        max_execution_time=1,
+        max_execution_time=1
     )
 
     task = Task(
@@ -1395,28 +1455,4 @@ def test_task_with_max_execution_time_exceeded():
     )
 
     with pytest.raises(TimeoutError):
-        task.execute_sync(agent=researcher)
-
-
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_task_interpolation_with_hyphens():
-    agent = Agent(
-        role="Researcher",
-        goal="be an assistant that responds with {interpolation-with-hyphens}",
-        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="be an assistant that responds with {interpolation-with-hyphens}",
-        expected_output="The response should be addressing: {interpolation-with-hyphens}",
-        agent=agent,
-    )
-    crew = Crew(
-        agents=[agent],
-        tasks=[task],
-        verbose=True,
-    )
-    result = crew.kickoff(inputs={"interpolation-with-hyphens": "say hello world"})
-    assert "say hello world" in task.prompt()
-
-    assert result.raw == "Hello, World!"
+        task.execute_sync(agent=researcher)

uv.lock

@@ -738,7 +738,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.120.0"
+version = "0.119.0"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },
@@ -828,7 +828,7 @@ 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 = "~=0.45.0" },
+    { name = "crewai-tools", marker = "extra == 'tools'", specifier = "~=0.44.0" },
     { name = "docling", marker = "extra == 'docling'", specifier = ">=2.12.0" },
     { name = "fastembed", marker = "extra == 'fastembed'", specifier = ">=0.4.1" },
     { name = "instructor", specifier = ">=1.3.3" },
@@ -879,7 +879,7 @@ dev = [
 
 [[package]]
 name = "crewai-tools"
-version = "0.45.0"
+version = "0.44.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "chromadb" },
@@ -894,9 +894,9 @@ dependencies = [
     { name = "pytube" },
     { name = "requests" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/e9/3a/7070dcacef56702c5d83ad1a87021b1666ff1850ff80b3aa7540892406e7/crewai_tools-0.45.0.tar.gz", hash = "sha256:1b2e4eff3f928ce5fac308d6e648719a0e4718a1228ae98980aa0d74fc16bfc7", size = 909723 }
+sdist = { url = "https://files.pythonhosted.org/packages/b8/1f/2977dc72628c1225bf5788ae22a65e5a53df384d19b197646d2c4760684e/crewai_tools-0.44.0.tar.gz", hash = "sha256:44e0c26079396503a326efdd9ff34bf369d410cbf95c362cc523db65b18f3c3a", size = 892004 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/6e/72/db45626973027c992df75cbc7ef391f18393d631be3bceb6388c1b9f01e1/crewai_tools-0.45.0-py3-none-any.whl", hash = "sha256:9dd34e4792c075ee7a72134aedaab268e78d0e350114fd7fe2426e691c5f52a3", size = 602659 },
+    { url = "https://files.pythonhosted.org/packages/ba/80/b91aa837d06edbb472445ea3c92d7619518894fd3049d480e5fffbf0c21b/crewai_tools-0.44.0-py3-none-any.whl", hash = "sha256:119e2365fe66ee16e18a5e8e222994b19f76bafcc8c1bb87f61609c1e39b2463", size = 583462 },
 ]
 
 [[package]]