docs: reorganize observability docs and update titles

Merge pull request #2463 from ayulockin/main
docs: Add documentation for W&B Weave
2025-12-23 07:48:30 +00:00 · 2025-03-25 11:03:46 -04:00 · 2025-03-25 09:48:09 -04:00 · 2025-03-25 19:05:58 +05:30 · 2025-03-25 19:04:51 +05:30 · 2025-03-25 19:04:14 +05:30
25 changed files with 977 additions and 219 deletions
--- a/docs/changelog.mdx
+++ b/docs/changelog.mdx
@@ -4,7 +4,7 @@ description: View the latest updates and changes to CrewAI
 icon: timeline
 ---

-<Update label="2024-03-17" description="v0.108.0">
+<Update label="2025-03-17" description="v0.108.0">
  **Features**
  - Converted tabs to spaces in `crew.py` template
  - Enhanced LLM Streaming Response Handling and Event System
@@ -24,7 +24,7 @@ icon: timeline
  - Added documentation for `ApifyActorsTool`
 </Update>

-<Update label="2024-03-10" description="v0.105.0">
+<Update label="2025-03-10" description="v0.105.0">
  **Core Improvements & Fixes**
  - Fixed issues with missing template variables and user memory configuration
  - Improved async flow support and addressed agent response formatting
@@ -45,7 +45,7 @@ icon: timeline
  - Fixed typos in prompts and updated Amazon Bedrock model listings
 </Update>

-<Update label="2024-02-12" description="v0.102.0">
+<Update label="2025-02-12" description="v0.102.0">
  **Core Improvements & Fixes**
  - Enhanced LLM Support: Improved structured LLM output, parameter handling, and formatting for Anthropic models
  - Crew & Agent Stability: Fixed issues with cloning agents/crews using knowledge sources, multiple task outputs in conditional tasks, and ignored Crew task callbacks
@@ -65,7 +65,7 @@ icon: timeline
  - Fixed Various Typos & Formatting Issues
 </Update>

-<Update label="2024-01-28" description="v0.100.0">
+<Update label="2025-01-28" description="v0.100.0">
  **Features**
  - Add Composio docs
  - Add SageMaker as a LLM provider
@@ -80,7 +80,7 @@ icon: timeline
  - Improve formatting and clarity in CLI and Composio Tool docs
 </Update>

-<Update label="2024-01-20" description="v0.98.0">
+<Update label="2025-01-20" description="v0.98.0">
  **Features**
  - Conversation crew v1
  - Add unique ID to flow states
@@ -101,7 +101,7 @@ icon: timeline
  - Fixed typos, nested pydantic model issue, and docling issues
 </Update>

-<Update label="2024-01-04" description="v0.95.0">
+<Update label="2025-01-04" description="v0.95.0">
  **New Features**
  - Adding Multimodal Abilities to Crew
  - Programatic Guardrails
@@ -131,7 +131,7 @@ icon: timeline
  - Suppressed userWarnings from litellm pydantic issues
 </Update>

-<Update label="2023-12-05" description="v0.86.0">
+<Update label="2024-12-05" description="v0.86.0">
  **Changes**
  - Remove all references to pipeline and pipeline router
  - Add Nvidia NIM as provider in Custom LLM
@@ -141,7 +141,7 @@ icon: timeline
  - Simplify template crew
 </Update>

-<Update label="2023-12-04" description="v0.85.0">
+<Update label="2024-12-04" description="v0.85.0">
  **Features**
  - Added knowledge to agent level
  - Feat/remove langchain
@@ -161,7 +161,7 @@ icon: timeline
  - Improvements to LLM Configuration and Usage
 </Update>

-<Update label="2023-11-25" description="v0.83.0">
+<Update label="2024-11-25" description="v0.83.0">
  **New Features**
  - New before_kickoff and after_kickoff crew callbacks
  - Support to pre-seed agents with Knowledge
@@ -178,7 +178,7 @@ icon: timeline
  - Update Docs
 </Update>

-<Update label="2023-11-13" description="v0.80.0">
+<Update label="2024-11-13" description="v0.80.0">
  **Fixes**
  - Fixing Tokens callback replacement bug
  - Fixing Step callback issue
--- a/docs/concepts/event-listener.mdx
+++ b/docs/concepts/event-listener.mdx
@@ -1,6 +1,7 @@
 ---
 title: 'Event Listeners'
 description: 'Tap into CrewAI events to build custom integrations and monitoring'
+icon: spinner
 ---

 # Event Listeners
--- a/docs/concepts/llms.mdx
+++ b/docs/concepts/llms.mdx
@@ -59,7 +59,7 @@ There are three ways to configure LLMs in CrewAI. Choose the method that best fi
        goal: Conduct comprehensive research and analysis
        backstory: A dedicated research professional with years of experience
        verbose: true
-        llm: openai/gpt-4o-mini # your model here 
+        llm: openai/gpt-4o-mini # your model here
        # (see provider configuration examples below for more)
    ```

@@ -111,7 +111,7 @@ There are three ways to configure LLMs in CrewAI. Choose the method that best fi
 ## Provider Configuration Examples


-CrewAI supports a multitude of LLM providers, each offering unique features, authentication methods, and model capabilities. 
+CrewAI supports a multitude of LLM providers, each offering unique features, authentication methods, and model capabilities.
 In this section, you'll find detailed examples that help you select, configure, and optimize the LLM that best fits your project's needs.

 <AccordionGroup>
@@ -121,7 +121,7 @@ In this section, you'll find detailed examples that help you select, configure,
    ```toml Code
    # Required
    OPENAI_API_KEY=sk-...
-    
+
    # Optional
    OPENAI_API_BASE=<custom-base-url>
    OPENAI_ORGANIZATION=<your-org-id>
@@ -226,7 +226,7 @@ In this section, you'll find detailed examples that help you select, configure,
    AZURE_API_KEY=<your-api-key>
    AZURE_API_BASE=<your-resource-url>
    AZURE_API_VERSION=<api-version>
-    
+
    # Optional
    AZURE_AD_TOKEN=<your-azure-ad-token>
    AZURE_API_TYPE=<your-azure-api-type>
@@ -289,7 +289,7 @@ In this section, you'll find detailed examples that help you select, configure,
    | Mistral 8x7B Instruct   | Up to 32k tokens     | An MOE LLM that follows instructions, completes requests, and generates creative text. |

  </Accordion>
-  
+
  <Accordion title="Amazon SageMaker">
    ```toml Code
    AWS_ACCESS_KEY_ID=<your-access-key>
@@ -474,7 +474,7 @@ In this section, you'll find detailed examples that help you select, configure,
    WATSONX_URL=<your-url>
    WATSONX_APIKEY=<your-apikey>
    WATSONX_PROJECT_ID=<your-project-id>
-    
+
    # Optional
    WATSONX_TOKEN=<your-token>
    WATSONX_DEPLOYMENT_SPACE_ID=<your-space-id>
@@ -491,7 +491,7 @@ In this section, you'll find detailed examples that help you select, configure,

  <Accordion title="Ollama (Local LLMs)">
    1. Install Ollama: [ollama.ai](https://ollama.ai/)
-    2. Run a model: `ollama run llama2`
+    2. Run a model: `ollama run llama3`
    3. Configure:

    ```python Code
@@ -600,7 +600,7 @@ In this section, you'll find detailed examples that help you select, configure,
    ```toml Code
    OPENROUTER_API_KEY=<your-api-key>
    ```
-    
+
    Example usage in your CrewAI project:
    ```python Code
    llm = LLM(
@@ -723,7 +723,7 @@ Learn how to get the most out of your LLM configuration:
        - Small tasks (up to 4K tokens): Standard models
        - Medium tasks (between 4K-32K): Enhanced models
        - Large tasks (over 32K): Large context models
-        
+
        ```python
        # Configure model with appropriate settings
        llm = LLM(
@@ -760,11 +760,11 @@ Learn how to get the most out of your LLM configuration:
    <Warning>
      Most authentication issues can be resolved by checking API key format and environment variable names.
    </Warning>
-    
+
    ```bash
    # OpenAI
    OPENAI_API_KEY=sk-...
-    
+
    # Anthropic
    ANTHROPIC_API_KEY=sk-ant-...
    ```
@@ -773,11 +773,11 @@ Learn how to get the most out of your LLM configuration:
    <Check>
      Always include the provider prefix in model names
    </Check>
-    
+
    ```python
    # Correct
    llm = LLM(model="openai/gpt-4")
-    
+
    # Incorrect
    llm = LLM(model="gpt-4")
    ```
@@ -786,5 +786,10 @@ Learn how to get the most out of your LLM configuration:
    <Tip>
      Use larger context models for extensive tasks
    </Tip>
+    
+    ```python
+    # Large context model
+    llm = LLM(model="openai/gpt-4o")  # 128K tokens
+    ```
  </Tab>
 </Tabs>
--- a/docs/docs.json
+++ b/docs/docs.json
@@ -97,13 +97,19 @@
              "how-to/kickoff-async",
              "how-to/kickoff-for-each",
              "how-to/replay-tasks-from-latest-crew-kickoff",
-              "how-to/conditional-tasks",
+              "how-to/conditional-tasks"
+            ]
+          },
+          {
+            "group": "Agent Monitoring & Observability",
+            "pages": [
+              "how-to/weave-integration",
              "how-to/agentops-observability",
+              "how-to/langfuse-observability",
              "how-to/langtrace-observability",
              "how-to/mlflow-observability",
              "how-to/openlit-observability",
-              "how-to/portkey-observability",
-              "how-to/langfuse-observability"
+              "how-to/portkey-observability"
            ]
          },
          {
@@ -111,6 +117,8 @@
            "pages": [
              "tools/aimindtool",
              "tools/apifyactorstool",
+              "tools/bedrockinvokeagenttool",
+              "tools/bedrockkbretriever",
              "tools/bravesearchtool",
              "tools/browserbaseloadtool",
              "tools/codedocssearchtool",
--- a/docs/how-to/agentops-observability.mdx
+++ b/docs/how-to/agentops-observability.mdx
@@ -1,5 +1,5 @@
 ---
-title: Agent Monitoring with AgentOps
+title: AgentOps Integration
 description: Understanding and logging your agent performance with AgentOps.
 icon: paperclip
 ---
--- a/docs/how-to/kickoff-for-each.mdx
+++ b/docs/how-to/kickoff-for-each.mdx
@@ -39,8 +39,7 @@ analysis_crew = Crew(
    agents=[coding_agent],
    tasks=[data_analysis_task],
    verbose=True,
-    memory=False,
-    respect_context_window=True  # enable by default
+    memory=False
 )

 datasets = [
--- a/docs/how-to/langfuse-observability.mdx
+++ b/docs/how-to/langfuse-observability.mdx
@@ -1,7 +1,7 @@
 ---
-title: Agent Monitoring with Langfuse
+title: Langfuse Integration
 description: Learn how to integrate Langfuse with CrewAI via OpenTelemetry using OpenLit
-icon: magnifying-glass-chart
+icon: vials
 ---

 # Integrate Langfuse with CrewAI
--- a/docs/how-to/langtrace-observability.mdx
+++ b/docs/how-to/langtrace-observability.mdx
@@ -1,5 +1,5 @@
 ---
-title: Agent Monitoring with Langtrace
+title: Langtrace Integration
 description: How to monitor cost, latency, and performance of CrewAI Agents using Langtrace, an external observability tool.
 icon: chart-line
 ---
--- a/docs/how-to/mlflow-observability.mdx
+++ b/docs/how-to/mlflow-observability.mdx
@@ -1,5 +1,5 @@
 ---
-title: Agent Monitoring with MLflow
+title: MLflow Integration
 description: Quickly start monitoring your Agents with MLflow.
 icon: bars-staggered
 ---
--- a/docs/how-to/openlit-observability.mdx
+++ b/docs/how-to/openlit-observability.mdx
@@ -1,5 +1,5 @@
 ---
-title: Agent Monitoring with OpenLIT
+title: OpenLIT Integration
 description: Quickly start monitoring your Agents in just a single line of code with OpenTelemetry.
 icon: magnifying-glass-chart
 ---
--- a/docs/how-to/portkey-observability.mdx
+++ b/docs/how-to/portkey-observability.mdx
@@ -1,5 +1,5 @@
 ---
-title: Agent Monitoring with Portkey
+title: Portkey Integration
 description: How to use Portkey with CrewAI
 icon: key
 ---
--- a/docs/how-to/weave-integration.mdx
+++ b/docs/how-to/weave-integration.mdx
@@ -0,0 +1,124 @@
+---
+title: Weave Integration
+description: Learn how to use Weights & Biases (W&B) Weave to track, experiment with, evaluate, and improve your CrewAI applications.
+icon: radar
+---
+
+# Weave Overview
+
+[Weights & Biases (W&B) Weave](https://weave-docs.wandb.ai/) is a framework for tracking, experimenting with, evaluating, deploying, and improving LLM-based applications. 
+
+![Overview of W&B Weave CrewAI tracing usage](/images/weave-tracing.gif)
+
+Weave provides comprehensive support for every stage of your CrewAI application development:
+
+- **Tracing & Monitoring**: Automatically track LLM calls and application logic to debug and analyze production systems
+- **Systematic Iteration**: Refine and iterate on prompts, datasets, and models
+- **Evaluation**: Use custom or pre-built scorers to systematically assess and enhance agent performance
+- **Guardrails**: Protect your agents with pre- and post-safeguards for content moderation and prompt safety
+
+Weave automatically captures traces for your CrewAI applications, enabling you to monitor and analyze your agents' performance, interactions, and execution flow. This helps you build better evaluation datasets and optimize your agent workflows.
+
+## Setup Instructions
+
+<Steps>
+    <Step title="Install required packages">
+      ```shell
+      pip install crewai weave
+      ```
+    </Step>
+    <Step title="Set up W&B Account">
+      Sign up for a [Weights & Biases account](https://wandb.ai) if you haven't already. You'll need this to view your traces and metrics.
+    </Step>
+    <Step title="Initialize Weave in Your Application">
+      Add the following code to your application:
+
+      ```python
+      import weave
+
+      # Initialize Weave with your project name
+      weave.init(project_name="crewai_demo")
+      ```
+      
+      After initialization, Weave will provide a URL where you can view your traces and metrics.
+    </Step>
+    <Step title="Create your Crews/Flows">
+      ```python
+      from crewai import Agent, Task, Crew, LLM, Process
+
+      # Create an LLM with a temperature of 0 to ensure deterministic outputs
+      llm = LLM(model="gpt-4o", temperature=0)
+
+      # Create agents
+      researcher = Agent(
+          role='Research Analyst',
+          goal='Find and analyze the best investment opportunities',
+          backstory='Expert in financial analysis and market research',
+          llm=llm,
+          verbose=True,
+          allow_delegation=False,
+      )
+
+      writer = Agent(
+          role='Report Writer',
+          goal='Write clear and concise investment reports',
+          backstory='Experienced in creating detailed financial reports',
+          llm=llm,
+          verbose=True,
+          allow_delegation=False,
+      )
+
+      # Create tasks
+      research_task = Task(
+          description='Deep research on the {topic}',
+          expected_output='Comprehensive market data including key players, market size, and growth trends.',
+          agent=researcher
+      )
+
+      writing_task = Task(
+          description='Write a detailed report based on the research',
+          expected_output='The report should be easy to read and understand. Use bullet points where applicable.',
+          agent=writer
+      )
+
+      # Create a crew
+      crew = Crew(
+          agents=[researcher, writer],
+          tasks=[research_task, writing_task],
+          verbose=True,
+          process=Process.sequential,
+      )
+
+      # Run the crew
+      result = crew.kickoff(inputs={"topic": "AI in material science"})
+      print(result)
+      ```
+    </Step>
+    <Step title="View Traces in Weave">
+      After running your CrewAI application, visit the Weave URL provided during initialization to view:
+      - LLM calls and their metadata
+      - Agent interactions and task execution flow
+      - Performance metrics like latency and token usage
+      - Any errors or issues that occurred during execution
+
+      <Frame caption="Weave Tracing Dashboard">
+        <img src="/images/weave-tracing.png" alt="Weave tracing example with CrewAI" />
+      </Frame>
+    </Step>
+</Steps>
+
+## Features
+
+- Weave automatically captures all CrewAI operations: agent interactions and task executions; LLM calls with metadata and token usage; tool usage and results.
+- The integration supports all CrewAI execution methods: `kickoff()`, `kickoff_for_each()`, `kickoff_async()`, and `kickoff_for_each_async()`.
+- Automatic tracing of all [crewAI-tools](https://github.com/crewAIInc/crewAI-tools).
+- Flow feature support with decorator patching (`@start`, `@listen`, `@router`, `@or_`, `@and_`).
+- Track custom guardrails passed to CrewAI `Task` with `@weave.op()`.
+
+For detailed information on what's supported, visit the [Weave CrewAI documentation](https://weave-docs.wandb.ai/guides/integrations/crewai/#getting-started-with-flow).
+
+## Resources
+
+- [📘 Weave Documentation](https://weave-docs.wandb.ai)
+- [📊 Example Weave x CrewAI dashboard](https://wandb.ai/ayut/crewai_demo/weave/traces?cols=%7B%22wb_run_id%22%3Afalse%2C%22attributes.weave.client_version%22%3Afalse%2C%22attributes.weave.os_name%22%3Afalse%2C%22attributes.weave.os_release%22%3Afalse%2C%22attributes.weave.os_version%22%3Afalse%2C%22attributes.weave.source%22%3Afalse%2C%22attributes.weave.sys_version%22%3Afalse%7D&peekPath=%2Fayut%2Fcrewai_demo%2Fcalls%2F0195c838-38cb-71a2-8a15-651ecddf9d89)
+- [🐦 X](https://x.com/weave_wb)
--- a/docs/images/weave-tracing.gif
+++ b/docs/images/weave-tracing.gif
--- a/docs/images/weave-tracing.png
+++ b/docs/images/weave-tracing.png
--- a/docs/tools/bedrockinvokeagenttool.mdx
+++ b/docs/tools/bedrockinvokeagenttool.mdx
@@ -0,0 +1,187 @@
+---
+title: Bedrock Invoke Agent Tool
+description: Enables CrewAI agents to invoke Amazon Bedrock Agents and leverage their capabilities within your workflows
+icon: aws
+---
+
+# `BedrockInvokeAgentTool`
+
+The `BedrockInvokeAgentTool` enables CrewAI agents to invoke Amazon Bedrock Agents and leverage their capabilities within your workflows.
+
+## Installation
+
+```bash
+uv pip install 'crewai[tools]'
+```
+
+## Requirements
+
+- AWS credentials configured (either through environment variables or AWS CLI)
+- `boto3` and `python-dotenv` packages
+- Access to Amazon Bedrock Agents
+
+## Usage
+
+Here's how to use the tool with a CrewAI agent:
+
+```python {2, 4-8}
+from crewai import Agent, Task, Crew
+from crewai_tools.aws.bedrock.agents.invoke_agent_tool import BedrockInvokeAgentTool
+
+# Initialize the tool
+agent_tool = BedrockInvokeAgentTool(
+    agent_id="your-agent-id",
+    agent_alias_id="your-agent-alias-id"
+)
+
+# Create a CrewAI agent that uses the tool
+aws_expert = Agent(
+    role='AWS Service Expert',
+    goal='Help users understand AWS services and quotas',
+    backstory='I am an expert in AWS services and can provide detailed information about them.',
+    tools=[agent_tool],
+    verbose=True
+)
+
+# Create a task for the agent
+quota_task = Task(
+    description="Find out the current service quotas for EC2 in us-west-2 and explain any recent changes.",
+    agent=aws_expert
+)
+
+# Create a crew with the agent
+crew = Crew(
+    agents=[aws_expert],
+    tasks=[quota_task],
+    verbose=2
+)
+
+# Run the crew
+result = crew.kickoff()
+print(result)
+```
+
+## Tool Arguments
+
+| Argument | Type | Required | Default | Description |
+|:---------|:-----|:---------|:--------|:------------|
+| **agent_id** | `str` | Yes | None | The unique identifier of the Bedrock agent |
+| **agent_alias_id** | `str` | Yes | None | The unique identifier of the agent alias |
+| **session_id** | `str` | No | timestamp | The unique identifier of the session |
+| **enable_trace** | `bool` | No | False | Whether to enable trace for debugging |
+| **end_session** | `bool` | No | False | Whether to end the session after invocation |
+| **description** | `str` | No | None | Custom description for the tool |
+
+## Environment Variables
+
+```bash
+BEDROCK_AGENT_ID=your-agent-id           # Alternative to passing agent_id
+BEDROCK_AGENT_ALIAS_ID=your-agent-alias-id # Alternative to passing agent_alias_id
+AWS_REGION=your-aws-region               # Defaults to us-west-2
+AWS_ACCESS_KEY_ID=your-access-key        # Required for AWS authentication
+AWS_SECRET_ACCESS_KEY=your-secret-key    # Required for AWS authentication
+```
+
+## Advanced Usage
+
+### Multi-Agent Workflow with Session Management
+
+```python {2, 4-22}
+from crewai import Agent, Task, Crew, Process
+from crewai_tools.aws.bedrock.agents.invoke_agent_tool import BedrockInvokeAgentTool
+
+# Initialize tools with session management
+initial_tool = BedrockInvokeAgentTool(
+    agent_id="your-agent-id",
+    agent_alias_id="your-agent-alias-id",
+    session_id="custom-session-id"
+)
+
+followup_tool = BedrockInvokeAgentTool(
+    agent_id="your-agent-id",
+    agent_alias_id="your-agent-alias-id",
+    session_id="custom-session-id"
+)
+
+final_tool = BedrockInvokeAgentTool(
+    agent_id="your-agent-id",
+    agent_alias_id="your-agent-alias-id",
+    session_id="custom-session-id",
+    end_session=True
+)
+
+# Create agents for different stages
+researcher = Agent(
+    role='AWS Service Researcher',
+    goal='Gather information about AWS services',
+    backstory='I am specialized in finding detailed AWS service information.',
+    tools=[initial_tool]
+)
+
+analyst = Agent(
+    role='Service Compatibility Analyst',
+    goal='Analyze service compatibility and requirements',
+    backstory='I analyze AWS services for compatibility and integration possibilities.',
+    tools=[followup_tool]
+)
+
+summarizer = Agent(
+    role='Technical Documentation Writer',
+    goal='Create clear technical summaries',
+    backstory='I specialize in creating clear, concise technical documentation.',
+    tools=[final_tool]
+)
+
+# Create tasks
+research_task = Task(
+    description="Find all available AWS services in us-west-2 region.",
+    agent=researcher
+)
+
+analysis_task = Task(
+    description="Analyze which services support IPv6 and their implementation requirements.",
+    agent=analyst
+)
+
+summary_task = Task(
+    description="Create a summary of IPv6-compatible services and their key features.",
+    agent=summarizer
+)
+
+# Create a crew with the agents and tasks
+crew = Crew(
+    agents=[researcher, analyst, summarizer],
+    tasks=[research_task, analysis_task, summary_task],
+    process=Process.sequential,
+    verbose=2
+)
+
+# Run the crew
+result = crew.kickoff()
+```
+
+## Use Cases
+
+### Hybrid Multi-Agent Collaborations
+- Create workflows where CrewAI agents collaborate with managed Bedrock agents running as services in AWS
+- Enable scenarios where sensitive data processing happens within your AWS environment while other agents operate externally
+- Bridge on-premises CrewAI agents with cloud-based Bedrock agents for distributed intelligence workflows
+
+### Data Sovereignty and Compliance
+- Keep data-sensitive agentic workflows within your AWS environment while allowing external CrewAI agents to orchestrate tasks
+- Maintain compliance with data residency requirements by processing sensitive information only within your AWS account
+- Enable secure multi-agent collaborations where some agents cannot access your organization's private data
+
+### Seamless AWS Service Integration
+- Access any AWS service through Amazon Bedrock Actions without writing complex integration code
+- Enable CrewAI agents to interact with AWS services through natural language requests
+- Leverage pre-built Bedrock agent capabilities to interact with AWS services like Bedrock Knowledge Bases, Lambda, and more
+
+### Scalable Hybrid Agent Architectures
+- Offload computationally intensive tasks to managed Bedrock agents while lightweight tasks run in CrewAI
+- Scale agent processing by distributing workloads between local CrewAI agents and cloud-based Bedrock agents
+
+### Cross-Organizational Agent Collaboration
+- Enable secure collaboration between your organization's CrewAI agents and partner organizations' Bedrock agents
+- Create workflows where external expertise from Bedrock agents can be incorporated without exposing sensitive data
+- Build agent ecosystems that span organizational boundaries while maintaining security and data control
--- a/docs/tools/bedrockkbretriever.mdx
+++ b/docs/tools/bedrockkbretriever.mdx
@@ -0,0 +1,165 @@
+---
+title: 'Bedrock Knowledge Base Retriever'
+description: 'Retrieve information from Amazon Bedrock Knowledge Bases using natural language queries'
+icon: aws
+---
+
+# `BedrockKBRetrieverTool`
+
+The `BedrockKBRetrieverTool` enables CrewAI agents to retrieve information from Amazon Bedrock Knowledge Bases using natural language queries.
+
+## Installation
+
+```bash
+uv pip install 'crewai[tools]'
+```
+
+## Requirements
+
+- AWS credentials configured (either through environment variables or AWS CLI)
+- `boto3` and `python-dotenv` packages
+- Access to Amazon Bedrock Knowledge Base
+
+## Usage
+
+Here's how to use the tool with a CrewAI agent:
+
+```python {2, 4-17}
+from crewai import Agent, Task, Crew
+from crewai_tools.aws.bedrock.knowledge_base.retriever_tool import BedrockKBRetrieverTool
+
+# Initialize the tool
+kb_tool = BedrockKBRetrieverTool(
+    knowledge_base_id="your-kb-id",
+    number_of_results=5
+)
+
+# Create a CrewAI agent that uses the tool
+researcher = Agent(
+    role='Knowledge Base Researcher',
+    goal='Find information about company policies',
+    backstory='I am a researcher specialized in retrieving and analyzing company documentation.',
+    tools=[kb_tool],
+    verbose=True
+)
+
+# Create a task for the agent
+research_task = Task(
+    description="Find our company's remote work policy and summarize the key points.",
+    agent=researcher
+)
+
+# Create a crew with the agent
+crew = Crew(
+    agents=[researcher],
+    tasks=[research_task],
+    verbose=2
+)
+
+# Run the crew
+result = crew.kickoff()
+print(result)   
+```
+
+## Tool Arguments
+
+| Argument | Type | Required | Default | Description |
+|:---------|:-----|:---------|:---------|:-------------|
+| **knowledge_base_id** | `str` | Yes | None | The unique identifier of the knowledge base (0-10 alphanumeric characters) |
+| **number_of_results** | `int` | No | 5 | Maximum number of results to return |
+| **retrieval_configuration** | `dict` | No | None | Custom configurations for the knowledge base query |
+| **guardrail_configuration** | `dict` | No | None | Content filtering settings |
+| **next_token** | `str` | No | None | Token for pagination |
+
+## Environment Variables
+
+```bash
+BEDROCK_KB_ID=your-knowledge-base-id  # Alternative to passing knowledge_base_id
+AWS_REGION=your-aws-region            # Defaults to us-east-1
+AWS_ACCESS_KEY_ID=your-access-key     # Required for AWS authentication
+AWS_SECRET_ACCESS_KEY=your-secret-key # Required for AWS authentication
+```
+
+## Response Format
+
+The tool returns results in JSON format:
+
+```json
+{
+  "results": [
+    {
+      "content": "Retrieved text content",
+      "content_type": "text",
+      "source_type": "S3",
+      "source_uri": "s3://bucket/document.pdf",
+      "score": 0.95,
+      "metadata": {
+        "additional": "metadata"
+      }
+    }
+  ],
+  "nextToken": "pagination-token",
+  "guardrailAction": "NONE"
+}
+```
+
+## Advanced Usage
+
+### Custom Retrieval Configuration
+
+```python
+kb_tool = BedrockKBRetrieverTool(
+    knowledge_base_id="your-kb-id",
+    retrieval_configuration={
+        "vectorSearchConfiguration": {
+            "numberOfResults": 10,
+            "overrideSearchType": "HYBRID"
+        }
+    }
+)
+
+policy_expert = Agent(
+    role='Policy Expert',
+    goal='Analyze company policies in detail',
+    backstory='I am an expert in corporate policy analysis with deep knowledge of regulatory requirements.',
+    tools=[kb_tool]
+)
+```
+
+## Supported Data Sources
+
+- Amazon S3
+- Confluence
+- Salesforce
+- SharePoint
+- Web pages
+- Custom document locations
+- Amazon Kendra
+- SQL databases    
+
+## Use Cases
+
+### Enterprise Knowledge Integration
+- Enable CrewAI agents to access your organization's proprietary knowledge without exposing sensitive data
+- Allow agents to make decisions based on your company's specific policies, procedures, and documentation
+- Create agents that can answer questions based on your internal documentation while maintaining data security
+
+### Specialized Domain Knowledge
+- Connect CrewAI agents to domain-specific knowledge bases (legal, medical, technical) without retraining models
+- Leverage existing knowledge repositories that are already maintained in your AWS environment
+- Combine CrewAI's reasoning with domain-specific information from your knowledge bases
+
+### Data-Driven Decision Making
+- Ground CrewAI agent responses in your actual company data rather than general knowledge
+- Ensure agents provide recommendations based on your specific business context and documentation
+- Reduce hallucinations by retrieving factual information from your knowledge bases
+
+### Scalable Information Access
+- Access terabytes of organizational knowledge without embedding it all into your models
+- Dynamically query only the relevant information needed for specific tasks
+- Leverage AWS's scalable infrastructure to handle large knowledge bases efficiently
+
+### Compliance and Governance
+- Ensure CrewAI agents provide responses that align with your company's approved documentation
+- Create auditable trails of information sources used by your agents
+- Maintain control over what information sources your agents can access
--- a/src/crewai/agents/agent_builder/base_agent.py
+++ b/src/crewai/agents/agent_builder/base_agent.py
@@ -25,6 +25,7 @@ from crewai.tools.base_tool import BaseTool, Tool
 from crewai.utilities import I18N, Logger, RPMController
 from crewai.utilities.config import process_config
 from crewai.utilities.converter import Converter
+from crewai.utilities.string_utils import interpolate_only

 T = TypeVar("T", bound="BaseAgent")

@@ -333,9 +334,15 @@ class BaseAgent(ABC, BaseModel):
            self._original_backstory = self.backstory

        if inputs:
-            self.role = self._original_role.format(**inputs)
-            self.goal = self._original_goal.format(**inputs)
-            self.backstory = self._original_backstory.format(**inputs)
+            self.role = interpolate_only(
+                input_string=self._original_role, inputs=inputs
+            )
+            self.goal = interpolate_only(
+                input_string=self._original_goal, inputs=inputs
+            )
+            self.backstory = interpolate_only(
+                input_string=self._original_backstory, inputs=inputs
+            )

    def set_cache_handler(self, cache_handler: CacheHandler) -> None:
        """Set the cache handler for the agent.
--- a/src/crewai/llm.py
+++ b/src/crewai/llm.py
@@ -114,6 +114,60 @@ LLM_CONTEXT_WINDOW_SIZES = {
    "Llama-3.2-11B-Vision-Instruct": 16384,
    "Meta-Llama-3.2-3B-Instruct": 4096,
    "Meta-Llama-3.2-1B-Instruct": 16384,
+    # bedrock
+    "us.amazon.nova-pro-v1:0": 300000,
+    "us.amazon.nova-micro-v1:0": 128000,
+    "us.amazon.nova-lite-v1:0": 300000,
+    "us.anthropic.claude-3-5-sonnet-20240620-v1:0": 200000,
+    "us.anthropic.claude-3-5-haiku-20241022-v1:0": 200000,
+    "us.anthropic.claude-3-5-sonnet-20241022-v2:0": 200000,
+    "us.anthropic.claude-3-7-sonnet-20250219-v1:0": 200000,
+    "us.anthropic.claude-3-sonnet-20240229-v1:0": 200000,
+    "us.anthropic.claude-3-opus-20240229-v1:0": 200000,
+    "us.anthropic.claude-3-haiku-20240307-v1:0": 200000,
+    "us.meta.llama3-2-11b-instruct-v1:0": 128000,
+    "us.meta.llama3-2-3b-instruct-v1:0": 131000,
+    "us.meta.llama3-2-90b-instruct-v1:0": 128000,
+    "us.meta.llama3-2-1b-instruct-v1:0": 131000,
+    "us.meta.llama3-1-8b-instruct-v1:0": 128000,
+    "us.meta.llama3-1-70b-instruct-v1:0": 128000,
+    "us.meta.llama3-3-70b-instruct-v1:0": 128000,
+    "us.meta.llama3-1-405b-instruct-v1:0": 128000,
+    "eu.anthropic.claude-3-5-sonnet-20240620-v1:0": 200000,
+    "eu.anthropic.claude-3-sonnet-20240229-v1:0": 200000,
+    "eu.anthropic.claude-3-haiku-20240307-v1:0": 200000,
+    "eu.meta.llama3-2-3b-instruct-v1:0": 131000,
+    "eu.meta.llama3-2-1b-instruct-v1:0": 131000,
+    "apac.anthropic.claude-3-5-sonnet-20240620-v1:0": 200000,
+    "apac.anthropic.claude-3-5-sonnet-20241022-v2:0": 200000,
+    "apac.anthropic.claude-3-sonnet-20240229-v1:0": 200000,
+    "apac.anthropic.claude-3-haiku-20240307-v1:0": 200000,
+    "amazon.nova-pro-v1:0": 300000,
+    "amazon.nova-micro-v1:0": 128000,
+    "amazon.nova-lite-v1:0": 300000,
+    "anthropic.claude-3-5-sonnet-20240620-v1:0": 200000,
+    "anthropic.claude-3-5-haiku-20241022-v1:0": 200000,
+    "anthropic.claude-3-5-sonnet-20241022-v2:0": 200000,
+    "anthropic.claude-3-7-sonnet-20250219-v1:0": 200000,
+    "anthropic.claude-3-sonnet-20240229-v1:0": 200000,
+    "anthropic.claude-3-opus-20240229-v1:0": 200000,
+    "anthropic.claude-3-haiku-20240307-v1:0": 200000,
+    "anthropic.claude-v2:1": 200000,
+    "anthropic.claude-v2": 100000,
+    "anthropic.claude-instant-v1": 100000,
+    "meta.llama3-1-405b-instruct-v1:0": 128000,
+    "meta.llama3-1-70b-instruct-v1:0": 128000,
+    "meta.llama3-1-8b-instruct-v1:0": 128000,
+    "meta.llama3-70b-instruct-v1:0": 8000,
+    "meta.llama3-8b-instruct-v1:0": 8000,
+    "amazon.titan-text-lite-v1": 4000,
+    "amazon.titan-text-express-v1": 8000,
+    "cohere.command-text-v14": 4000,
+    "ai21.j2-mid-v1": 8191,
+    "ai21.j2-ultra-v1": 8191,
+    "ai21.jamba-instruct-v1:0": 256000,
+    "mistral.mistral-7b-instruct-v0:2": 32000,
+    "mistral.mixtral-8x7b-instruct-v0:1": 32000,
    # mistral
    "mistral-tiny": 32768,
    "mistral-small-latest": 32768,
--- a/src/crewai/task.py
+++ b/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
@@ -49,6 +50,7 @@ from crewai.utilities.events import (
 from crewai.utilities.events.crewai_event_bus import crewai_event_bus
 from crewai.utilities.i18n import I18N
 from crewai.utilities.printer import Printer
+from crewai.utilities.string_utils import interpolate_only


 class Task(BaseModel):
@@ -507,7 +509,9 @@ class Task(BaseModel):
            return

        try:
-            self.description = self._original_description.format(**inputs)
+            self.description = interpolate_only(
+                input_string=self._original_description, inputs=inputs
+            )
        except KeyError as e:
            raise ValueError(
                f"Missing required template variable '{e.args[0]}' in description"
@@ -516,7 +520,7 @@ class Task(BaseModel):
            raise ValueError(f"Error interpolating description: {str(e)}") from e

        try:
-            self.expected_output = self.interpolate_only(
+            self.expected_output = interpolate_only(
                input_string=self._original_expected_output, inputs=inputs
            )
        except (KeyError, ValueError) as e:
@@ -524,7 +528,7 @@ class Task(BaseModel):

        if self.output_file is not None:
            try:
-                self.output_file = self.interpolate_only(
+                self.output_file = interpolate_only(
                    input_string=self._original_output_file, inputs=inputs
                )
            except (KeyError, ValueError) as e:
@@ -555,72 +559,6 @@ class Task(BaseModel):
                f"\n\n{conversation_instruction}\n\n{conversation_history}"
            )

-    def interpolate_only(
-        self,
-        input_string: Optional[str],
-        inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]],
-    ) -> 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, floats, and dicts/lists
-                   containing only these types and other nested dicts/lists.
-
-        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 value contains unsupported types
-        """
-
-        # Validation function for recursive type checking
-        def validate_type(value: Any) -> None:
-            if value is None:
-                return
-            if isinstance(value, (str, int, float, bool)):
-                return
-            if isinstance(value, (dict, list)):
-                for item in value.values() if isinstance(value, dict) else value:
-                    validate_type(item)
-                return
-            raise ValueError(
-                f"Unsupported type {type(value).__name__} in inputs. "
-                "Only str, int, float, bool, dict, and list are allowed."
-            )
-
-        # Validate all input values
-        for key, value in inputs.items():
-            try:
-                validate_type(value)
-            except ValueError as e:
-                raise ValueError(f"Invalid value for key '{key}': {str(e)}") from e
-
-        if input_string is None or not input_string:
-            return ""
-        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"
-            )
-        try:
-            escaped_string = input_string.replace("{", "{{").replace("}", "}}")
-
-            for key in inputs.keys():
-                escaped_string = escaped_string.replace(f"{{{{{key}}}}}", f"{{{key}}}")
-
-            return escaped_string.format(**inputs)
-        except KeyError as 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
-
    def increment_tools_errors(self) -> None:
        """Increment the tools errors counter."""
        self.tools_errors += 1
--- a/src/crewai/tools/tool_usage.py
+++ b/src/crewai/tools/tool_usage.py
@@ -455,7 +455,7 @@ class ToolUsage:

        # Attempt 4: Repair JSON
        try:
-            repaired_input = repair_json(tool_input)
+            repaired_input = repair_json(tool_input, skip_json_loads=True)
            self._printer.print(
                content=f"Repaired JSON: {repaired_input}", color="blue"
            )
--- a/src/crewai/utilities/formatter.py
+++ b/src/crewai/utilities/formatter.py
@@ -1,10 +1,12 @@
-from typing import List
+import re
+from typing import TYPE_CHECKING, List

-from crewai.task import Task
-from crewai.tasks.task_output import TaskOutput
+if TYPE_CHECKING:
+    from crewai.task import Task
+    from crewai.tasks.task_output import TaskOutput


-def aggregate_raw_outputs_from_task_outputs(task_outputs: List[TaskOutput]) -> str:
+def aggregate_raw_outputs_from_task_outputs(task_outputs: List["TaskOutput"]) -> str:
    """Generate string context from the task outputs."""
    dividers = "\n\n----------\n\n"

@@ -13,7 +15,7 @@ def aggregate_raw_outputs_from_task_outputs(task_outputs: List[TaskOutput]) -> s
    return context


-def aggregate_raw_outputs_from_tasks(tasks: List[Task]) -> str:
+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]

--- a/src/crewai/utilities/string_utils.py
+++ b/src/crewai/utilities/string_utils.py
@@ -0,0 +1,82 @@
+import re
+from typing import Any, Dict, List, Optional, Union
+
+
+def interpolate_only(
+    input_string: Optional[str],
+    inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]],
+) -> str:
+    """Interpolate placeholders (e.g., {key}) in a string while leaving JSON untouched.
+    Only interpolates placeholders that follow the pattern {variable_name} where
+    variable_name starts with a letter/underscore and contains only letters, numbers, and underscores.
+
+    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, floats, and dicts/lists
+               containing only these types and other nested dicts/lists.
+
+    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 value contains unsupported types or a template variable is missing
+    """
+
+    # Validation function for recursive type checking
+    def validate_type(value: Any) -> None:
+        if value is None:
+            return
+        if isinstance(value, (str, int, float, bool)):
+            return
+        if isinstance(value, (dict, list)):
+            for item in value.values() if isinstance(value, dict) else value:
+                validate_type(item)
+            return
+        raise ValueError(
+            f"Unsupported type {type(value).__name__} in inputs. "
+            "Only str, int, float, bool, dict, and list are allowed."
+        )
+
+    # Validate all input values
+    for key, value in inputs.items():
+        try:
+            validate_type(value)
+        except ValueError as e:
+            raise ValueError(f"Invalid value for key '{key}': {str(e)}") from e
+
+    if input_string is None or not input_string:
+        return ""
+    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"
+        )
+
+    # 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_]*)\}"
+
+    # Find all matching variables in the input string
+    variables = re.findall(pattern, input_string)
+    result = input_string
+
+    # Check if all variables exist in inputs
+    missing_vars = [var for var in variables if var not in inputs]
+    if missing_vars:
+        raise KeyError(
+            f"Template variable '{missing_vars[0]}' not found in inputs dictionary"
+        )
+
+    # Replace each variable with its value
+    for var in variables:
+        if var in inputs:
+            placeholder = "{" + var + "}"
+            value = str(inputs[var])
+            result = result.replace(placeholder, value)
+
+    return result
--- a/tests/task_test.py
+++ b/tests/task_test.py
@@ -15,6 +15,7 @@ from crewai import Agent, Crew, Process, Task
 from crewai.tasks.conditional_task import ConditionalTask
 from crewai.tasks.task_output import TaskOutput
 from crewai.utilities.converter import Converter
+from crewai.utilities.string_utils import interpolate_only


 def test_task_tool_reflect_agent_tools():
@@ -822,7 +823,7 @@ def test_interpolate_only():

    # Test JSON structure preservation
    json_string = '{"info": "Look at {placeholder}", "nested": {"val": "{nestedVal}"}}'
-    result = task.interpolate_only(
+    result = interpolate_only(
        input_string=json_string,
        inputs={"placeholder": "the data", "nestedVal": "something else"},
    )
@@ -833,20 +834,18 @@ def test_interpolate_only():

    # Test normal string interpolation
    normal_string = "Hello {name}, welcome to {place}!"
-    result = task.interpolate_only(
+    result = interpolate_only(
        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 = 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"}
-    )
+    result = interpolate_only(input_string=no_placeholders, inputs={"unused": "value"})
    assert result == no_placeholders


@@ -858,7 +857,7 @@ def test_interpolate_only_with_dict_inside_expected_output():
    )

    json_string = '{"questions": {"main_question": "What is the user\'s name?", "secondary_question": "What is the user\'s age?"}}'
-    result = task.interpolate_only(
+    result = interpolate_only(
        input_string=json_string,
        inputs={
            "questions": {
@@ -872,18 +871,16 @@ def test_interpolate_only_with_dict_inside_expected_output():
    assert result == json_string

    normal_string = "Hello {name}, welcome to {place}!"
-    result = task.interpolate_only(
+    result = interpolate_only(
        input_string=normal_string, inputs={"name": "John", "place": "CrewAI"}
    )
    assert result == "Hello John, welcome to CrewAI!"

-    result = task.interpolate_only(input_string="", inputs={"unused": "value"})
+    result = interpolate_only(input_string="", inputs={"unused": "value"})
    assert result == ""

    no_placeholders = "Hello, this is a test"
-    result = task.interpolate_only(
-        input_string=no_placeholders, inputs={"unused": "value"}
-    )
+    result = interpolate_only(input_string=no_placeholders, inputs={"unused": "value"})
    assert result == no_placeholders


@@ -1085,12 +1082,12 @@ def test_interpolate_with_list_of_strings():
    # Test simple list of strings
    input_str = "Available items: {items}"
    inputs = {"items": ["apple", "banana", "cherry"]}
-    result = task.interpolate_only(input_str, inputs)
+    result = interpolate_only(input_str, inputs)
    assert result == f"Available items: {inputs['items']}"

    # Test empty list
    empty_list_input = {"items": []}
-    result = task.interpolate_only(input_str, empty_list_input)
+    result = interpolate_only(input_str, empty_list_input)
    assert result == "Available items: []"


@@ -1106,7 +1103,7 @@ def test_interpolate_with_list_of_dicts():
            {"name": "Bob", "age": 25, "skills": ["Java", "Cloud"]},
        ]
    }
-    result = task.interpolate_only("{people}", input_data)
+    result = interpolate_only("{people}", input_data)

    parsed_result = eval(result)
    assert isinstance(parsed_result, list)
@@ -1138,7 +1135,7 @@ def test_interpolate_with_nested_structures():
            ],
        }
    }
-    result = task.interpolate_only("{company}", input_data)
+    result = interpolate_only("{company}", input_data)
    parsed = eval(result)

    assert parsed["name"] == "TechCorp"
@@ -1161,7 +1158,7 @@ def test_interpolate_with_special_characters():
            "empty": "",
        }
    }
-    result = task.interpolate_only("{special_data}", input_data)
+    result = interpolate_only("{special_data}", input_data)
    parsed = eval(result)

    assert parsed["quotes"] == """This has "double" and 'single' quotes"""
@@ -1188,7 +1185,7 @@ def test_interpolate_mixed_types():
            },
        }
    }
-    result = task.interpolate_only("{data}", input_data)
+    result = interpolate_only("{data}", input_data)
    parsed = eval(result)

    assert parsed["name"] == "Test Dataset"
@@ -1216,7 +1213,7 @@ def test_interpolate_complex_combination():
            },
        ]
    }
-    result = task.interpolate_only("{report}", input_data)
+    result = interpolate_only("{report}", input_data)
    parsed = eval(result)

    assert len(parsed) == 2
@@ -1233,7 +1230,7 @@ def test_interpolate_invalid_type_validation():

    # Test with invalid top-level type
    with pytest.raises(ValueError) as excinfo:
-        task.interpolate_only("{data}", {"data": set()})  # type: ignore we are purposely testing this failure
+        interpolate_only("{data}", {"data": set()})  # type: ignore we are purposely testing this failure

    assert "Unsupported type set" in str(excinfo.value)

@@ -1246,7 +1243,7 @@ def test_interpolate_invalid_type_validation():
        }
    }
    with pytest.raises(ValueError) as excinfo:
-        task.interpolate_only("{data}", {"data": invalid_nested})
+        interpolate_only("{data}", {"data": invalid_nested})
    assert "Unsupported type set" in str(excinfo.value)


@@ -1265,24 +1262,22 @@ def test_interpolate_custom_object_validation():

    # Test with custom object at top level
    with pytest.raises(ValueError) as excinfo:
-        task.interpolate_only("{obj}", {"obj": CustomObject(5)})  # type: ignore we are purposely testing this failure
+        interpolate_only("{obj}", {"obj": CustomObject(5)})  # type: ignore we are purposely testing this failure
    assert "Unsupported type CustomObject" in str(excinfo.value)

    # Test with nested custom object in dictionary
    with pytest.raises(ValueError) as excinfo:
-        task.interpolate_only(
-            "{data}", {"data": {"valid": 1, "invalid": CustomObject(5)}}
-        )
+        interpolate_only("{data}", {"data": {"valid": 1, "invalid": CustomObject(5)}})
    assert "Unsupported type CustomObject" in str(excinfo.value)

    # Test with nested custom object in list
    with pytest.raises(ValueError) as excinfo:
-        task.interpolate_only("{data}", {"data": [1, "valid", CustomObject(5)]})
+        interpolate_only("{data}", {"data": [1, "valid", CustomObject(5)]})
    assert "Unsupported type CustomObject" in str(excinfo.value)

    # Test with deeply nested custom object
    with pytest.raises(ValueError) as excinfo:
-        task.interpolate_only(
+        interpolate_only(
            "{data}", {"data": {"level1": {"level2": [{"level3": CustomObject(5)}]}}}
        )
    assert "Unsupported type CustomObject" in str(excinfo.value)
@@ -1306,7 +1301,7 @@ def test_interpolate_valid_complex_types():
    }

    # Should not raise any errors
-    result = task.interpolate_only("{data}", {"data": valid_data})
+    result = interpolate_only("{data}", {"data": valid_data})
    parsed = eval(result)
    assert parsed["name"] == "Valid Dataset"
    assert parsed["stats"]["nested"]["deeper"]["b"] == 2.5
@@ -1319,16 +1314,16 @@ def test_interpolate_edge_cases():
    )

    # Test empty dict and list
-    assert task.interpolate_only("{}", {"data": {}}) == "{}"
-    assert task.interpolate_only("[]", {"data": []}) == "[]"
+    assert interpolate_only("{}", {"data": {}}) == "{}"
+    assert interpolate_only("[]", {"data": []}) == "[]"

    # Test numeric types
-    assert task.interpolate_only("{num}", {"num": 42}) == "42"
-    assert task.interpolate_only("{num}", {"num": 3.14}) == "3.14"
+    assert interpolate_only("{num}", {"num": 42}) == "42"
+    assert interpolate_only("{num}", {"num": 3.14}) == "3.14"

    # Test boolean values (valid JSON types)
-    assert task.interpolate_only("{flag}", {"flag": True}) == "True"
-    assert task.interpolate_only("{flag}", {"flag": False}) == "False"
+    assert interpolate_only("{flag}", {"flag": True}) == "True"
+    assert interpolate_only("{flag}", {"flag": False}) == "False"


 def test_interpolate_valid_types():
@@ -1346,7 +1341,7 @@ def test_interpolate_valid_types():
        "nested": {"flag": True, "empty": None},
    }

-    result = task.interpolate_only("{data}", {"data": valid_data})
+    result = interpolate_only("{data}", {"data": valid_data})
    parsed = eval(result)

    assert parsed["active"] is True
--- a/tests/utilities/test_string_utils.py
+++ b/tests/utilities/test_string_utils.py
@@ -0,0 +1,187 @@
+from typing import Any, Dict, List, Union
+
+import pytest
+
+from crewai.utilities.string_utils import interpolate_only
+
+
+class TestInterpolateOnly:
+    """Tests for the interpolate_only function in string_utils.py."""
+
+    def test_basic_variable_interpolation(self):
+        """Test basic variable interpolation works correctly."""
+        template = "Hello, {name}! Welcome to {company}."
+        inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
+            "name": "Alice",
+            "company": "CrewAI",
+        }
+
+        result = interpolate_only(template, inputs)
+
+        assert result == "Hello, Alice! Welcome to CrewAI."
+
+    def test_multiple_occurrences_of_same_variable(self):
+        """Test that multiple occurrences of the same variable are replaced."""
+        template = "{name} is using {name}'s account."
+        inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
+            "name": "Bob"
+        }
+
+        result = interpolate_only(template, inputs)
+
+        assert result == "Bob is using Bob's account."
+
+    def test_json_structure_preservation(self):
+        """Test that JSON structures are preserved and not interpolated incorrectly."""
+        template = """
+        Instructions for {agent}:
+
+        Please return the following object:
+
+        {"name": "person's name", "age": 25, "skills": ["coding", "testing"]}
+        """
+        inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
+            "agent": "DevAgent"
+        }
+
+        result = interpolate_only(template, inputs)
+
+        assert "Instructions for DevAgent:" in result
+        assert (
+            '{"name": "person\'s name", "age": 25, "skills": ["coding", "testing"]}'
+            in result
+        )
+
+    def test_complex_nested_json(self):
+        """Test with complex JSON structures containing curly braces."""
+        template = """
+        {agent} needs to process:
+        {
+          "config": {
+            "nested": {
+              "value": 42
+            },
+            "arrays": [1, 2, {"inner": "value"}]
+          }
+        }
+        """
+        inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
+            "agent": "DataProcessor"
+        }
+
+        result = interpolate_only(template, inputs)
+
+        assert "DataProcessor needs to process:" in result
+        assert '"nested": {' in result
+        assert '"value": 42' in result
+        assert '[1, 2, {"inner": "value"}]' in result
+
+    def test_missing_variable(self):
+        """Test that an error is raised when a required variable is missing."""
+        template = "Hello, {name}!"
+        inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
+            "not_name": "Alice"
+        }
+
+        with pytest.raises(KeyError) as excinfo:
+            interpolate_only(template, inputs)
+
+        assert "template variable" in str(excinfo.value).lower()
+        assert "name" in str(excinfo.value)
+
+    def test_invalid_input_types(self):
+        """Test that an error is raised with invalid input types."""
+        template = "Hello, {name}!"
+        # Using Any for this test since we're intentionally testing an invalid type
+        inputs: Dict[str, Any] = {"name": object()}  # Object is not a valid input type
+
+        with pytest.raises(ValueError) as excinfo:
+            interpolate_only(template, inputs)
+
+        assert "unsupported type" in str(excinfo.value).lower()
+
+    def test_empty_input_string(self):
+        """Test handling of empty or None input string."""
+        inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
+            "name": "Alice"
+        }
+
+        assert interpolate_only("", inputs) == ""
+        assert interpolate_only(None, inputs) == ""
+
+    def test_no_variables_in_template(self):
+        """Test a template with no variables to replace."""
+        template = "This is a static string with no variables."
+        inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
+            "name": "Alice"
+        }
+
+        result = interpolate_only(template, inputs)
+
+        assert result == template
+
+    def test_variable_name_starting_with_underscore(self):
+        """Test variables starting with underscore are replaced correctly."""
+        template = "Variable: {_special_var}"
+        inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
+            "_special_var": "Special Value"
+        }
+
+        result = interpolate_only(template, inputs)
+
+        assert result == "Variable: Special Value"
+
+    def test_preserves_non_matching_braces(self):
+        """Test that non-matching braces patterns are preserved."""
+        template = (
+            "This {123} and {!var} should not be replaced but {valid_var} should."
+        )
+        inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
+            "valid_var": "works"
+        }
+
+        result = interpolate_only(template, inputs)
+
+        assert (
+            result == "This {123} and {!var} should not be replaced but works should."
+        )
+
+    def test_complex_mixed_scenario(self):
+        """Test a complex scenario with both valid variables and JSON structures."""
+        template = """
+        {agent_name} is working on task {task_id}.
+        
+        Instructions:
+        1. Process the data
+        2. Return results as:
+        
+        {
+          "taskId": "{task_id}",
+          "results": {
+            "processed_by": "agent_name",
+            "status": "complete",
+            "values": [1, 2, 3]
+          }
+        }
+        """
+        inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
+            "agent_name": "AnalyticsAgent",
+            "task_id": "T-12345",
+        }
+
+        result = interpolate_only(template, inputs)
+
+        assert "AnalyticsAgent is working on task T-12345" in result
+        assert '"taskId": "T-12345"' in result
+        assert '"processed_by": "agent_name"' in result  # This shouldn't be replaced
+        assert '"values": [1, 2, 3]' in result
+
+    def test_empty_inputs_dictionary(self):
+        """Test that an error is raised with empty inputs dictionary."""
+        template = "Hello, {name}!"
+        inputs: Dict[str, Any] = {}
+
+        with pytest.raises(ValueError) as excinfo:
+            interpolate_only(template, inputs)
+
+        assert "inputs dictionary cannot be empty" in str(excinfo.value).lower()
--- a/uv.lock
+++ b/uv.lock
@@ -715,9 +715,9 @@ requires-dist = [
    { name = "openai", specifier = ">=1.13.3" },
    { name = "openpyxl", specifier = ">=3.1.5" },
    { name = "openpyxl", marker = "extra == 'openpyxl'", specifier = ">=3.1.5" },
-    { name = "opentelemetry-api", specifier = ">=1.22.0" },
-    { name = "opentelemetry-exporter-otlp-proto-http", specifier = ">=1.22.0" },
-    { name = "opentelemetry-sdk", specifier = ">=1.22.0" },
+    { name = "opentelemetry-api", specifier = ">=1.30.0" },
+    { name = "opentelemetry-exporter-otlp-proto-http", specifier = ">=1.30.0" },
+    { name = "opentelemetry-sdk", specifier = ">=1.30.0" },
    { name = "pandas", marker = "extra == 'pandas'", specifier = ">=2.2.3" },
    { name = "pdfplumber", specifier = ">=0.11.4" },
    { name = "pdfplumber", marker = "extra == 'pdfplumber'", specifier = ">=0.11.4" },
@@ -1617,39 +1617,42 @@ wheels = [

 [[package]]
 name = "grpcio-tools"
-version = "1.62.3"
+version = "1.67.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "grpcio" },
    { name = "protobuf" },
    { name = "setuptools" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/54/fa/b69bd8040eafc09b88bb0ec0fea59e8aacd1a801e688af087cead213b0d0/grpcio-tools-1.62.3.tar.gz", hash = "sha256:7c7136015c3d62c3eef493efabaf9e3380e3e66d24ee8e94c01cb71377f57833", size = 4538520 }
+sdist = { url = "https://files.pythonhosted.org/packages/e7/f8/62e15867651b72f6f95313e21d81f5f1c210b69a4cc664aecf52ec4c8a53/grpcio_tools-1.67.0.tar.gz", hash = "sha256:181b3d4e61b83142c182ec366f3079b0023509743986e54c9465ca38cac255f8", size = 5159163 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/ff/eb/eb0a3aa9480c3689d31fd2ad536df6a828e97a60f667c8a93d05bdf07150/grpcio_tools-1.62.3-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:2f968b049c2849540751ec2100ab05e8086c24bead769ca734fdab58698408c1", size = 5117556 },
-    { url = "https://files.pythonhosted.org/packages/f3/fb/8be3dda485f7fab906bfa02db321c3ecef953a87cdb5f6572ca08b187bcb/grpcio_tools-1.62.3-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:0a8c0c4724ae9c2181b7dbc9b186df46e4f62cb18dc184e46d06c0ebeccf569e", size = 2719330 },
-    { url = "https://files.pythonhosted.org/packages/63/de/6978f8d10066e240141cd63d1fbfc92818d96bb53427074f47a8eda921e1/grpcio_tools-1.62.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5782883a27d3fae8c425b29a9d3dcf5f47d992848a1b76970da3b5a28d424b26", size = 3070818 },
-    { url = "https://files.pythonhosted.org/packages/74/34/bb8f816893fc73fd6d830e895e8638d65d13642bb7a434f9175c5ca7da11/grpcio_tools-1.62.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f3d812daffd0c2d2794756bd45a353f89e55dc8f91eb2fc840c51b9f6be62667", size = 2804993 },
-    { url = "https://files.pythonhosted.org/packages/78/60/b2198d7db83293cdb9760fc083f077c73e4c182da06433b3b157a1567d06/grpcio_tools-1.62.3-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:b47d0dda1bdb0a0ba7a9a6de88e5a1ed61f07fad613964879954961e36d49193", size = 3684915 },
-    { url = "https://files.pythonhosted.org/packages/61/20/56dbdc4ecb14d42a03cd164ff45e6e84572bbe61ee59c50c39f4d556a8d5/grpcio_tools-1.62.3-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:ca246dffeca0498be9b4e1ee169b62e64694b0f92e6d0be2573e65522f39eea9", size = 3297482 },
-    { url = "https://files.pythonhosted.org/packages/4a/dc/e417a313c905744ce8cedf1e1edd81c41dc45ff400ae1c45080e18f26712/grpcio_tools-1.62.3-cp310-cp310-win32.whl", hash = "sha256:6a56d344b0bab30bf342a67e33d386b0b3c4e65868ffe93c341c51e1a8853ca5", size = 909793 },
-    { url = "https://files.pythonhosted.org/packages/d9/69/75e7ebfd8d755d3e7be5c6d1aa6d13220f5bba3a98965e4b50c329046777/grpcio_tools-1.62.3-cp310-cp310-win_amd64.whl", hash = "sha256:710fecf6a171dcbfa263a0a3e7070e0df65ba73158d4c539cec50978f11dad5d", size = 1052459 },
-    { url = "https://files.pythonhosted.org/packages/23/52/2dfe0a46b63f5ebcd976570aa5fc62f793d5a8b169e211c6a5aede72b7ae/grpcio_tools-1.62.3-cp311-cp311-macosx_10_10_universal2.whl", hash = "sha256:703f46e0012af83a36082b5f30341113474ed0d91e36640da713355cd0ea5d23", size = 5147623 },
-    { url = "https://files.pythonhosted.org/packages/f0/2e/29fdc6c034e058482e054b4a3c2432f84ff2e2765c1342d4f0aa8a5c5b9a/grpcio_tools-1.62.3-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:7cc83023acd8bc72cf74c2edbe85b52098501d5b74d8377bfa06f3e929803492", size = 2719538 },
-    { url = "https://files.pythonhosted.org/packages/f9/60/abe5deba32d9ec2c76cdf1a2f34e404c50787074a2fee6169568986273f1/grpcio_tools-1.62.3-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7ff7d58a45b75df67d25f8f144936a3e44aabd91afec833ee06826bd02b7fbe7", size = 3070964 },
-    { url = "https://files.pythonhosted.org/packages/bc/ad/e2b066684c75f8d9a48508cde080a3a36618064b9cadac16d019ca511444/grpcio_tools-1.62.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f2483ea232bd72d98a6dc6d7aefd97e5bc80b15cd909b9e356d6f3e326b6e43", size = 2805003 },
-    { url = "https://files.pythonhosted.org/packages/9c/3f/59bf7af786eae3f9d24ee05ce75318b87f541d0950190ecb5ffb776a1a58/grpcio_tools-1.62.3-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:962c84b4da0f3b14b3cdb10bc3837ebc5f136b67d919aea8d7bb3fd3df39528a", size = 3685154 },
-    { url = "https://files.pythonhosted.org/packages/f1/79/4dd62478b91e27084c67b35a2316ce8a967bd8b6cb8d6ed6c86c3a0df7cb/grpcio_tools-1.62.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:8ad0473af5544f89fc5a1ece8676dd03bdf160fb3230f967e05d0f4bf89620e3", size = 3297942 },
-    { url = "https://files.pythonhosted.org/packages/b8/cb/86449ecc58bea056b52c0b891f26977afc8c4464d88c738f9648da941a75/grpcio_tools-1.62.3-cp311-cp311-win32.whl", hash = "sha256:db3bc9fa39afc5e4e2767da4459df82b095ef0cab2f257707be06c44a1c2c3e5", size = 910231 },
-    { url = "https://files.pythonhosted.org/packages/45/a4/9736215e3945c30ab6843280b0c6e1bff502910156ea2414cd77fbf1738c/grpcio_tools-1.62.3-cp311-cp311-win_amd64.whl", hash = "sha256:e0898d412a434e768a0c7e365acabe13ff1558b767e400936e26b5b6ed1ee51f", size = 1052496 },
-    { url = "https://files.pythonhosted.org/packages/2a/a5/d6887eba415ce318ae5005e8dfac3fa74892400b54b6d37b79e8b4f14f5e/grpcio_tools-1.62.3-cp312-cp312-macosx_10_10_universal2.whl", hash = "sha256:d102b9b21c4e1e40af9a2ab3c6d41afba6bd29c0aa50ca013bf85c99cdc44ac5", size = 5147690 },
-    { url = "https://files.pythonhosted.org/packages/8a/7c/3cde447a045e83ceb4b570af8afe67ffc86896a2fe7f59594dc8e5d0a645/grpcio_tools-1.62.3-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:0a52cc9444df978438b8d2332c0ca99000521895229934a59f94f37ed896b133", size = 2720538 },
-    { url = "https://files.pythonhosted.org/packages/88/07/f83f2750d44ac4f06c07c37395b9c1383ef5c994745f73c6bfaf767f0944/grpcio_tools-1.62.3-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:141d028bf5762d4a97f981c501da873589df3f7e02f4c1260e1921e565b376fa", size = 3071571 },
-    { url = "https://files.pythonhosted.org/packages/37/74/40175897deb61e54aca716bc2e8919155b48f33aafec8043dda9592d8768/grpcio_tools-1.62.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47a5c093ab256dec5714a7a345f8cc89315cb57c298b276fa244f37a0ba507f0", size = 2806207 },
-    { url = "https://files.pythonhosted.org/packages/ec/ee/d8de915105a217cbcb9084d684abdc032030dcd887277f2ef167372287fe/grpcio_tools-1.62.3-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:f6831fdec2b853c9daa3358535c55eed3694325889aa714070528cf8f92d7d6d", size = 3685815 },
-    { url = "https://files.pythonhosted.org/packages/fd/d9/4360a6c12be3d7521b0b8c39e5d3801d622fbb81cc2721dbd3eee31e28c8/grpcio_tools-1.62.3-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:e02d7c1a02e3814c94ba0cfe43d93e872c758bd8fd5c2797f894d0c49b4a1dfc", size = 3298378 },
-    { url = "https://files.pythonhosted.org/packages/29/3b/7cdf4a9e5a3e0a35a528b48b111355cd14da601413a4f887aa99b6da468f/grpcio_tools-1.62.3-cp312-cp312-win32.whl", hash = "sha256:b881fd9505a84457e9f7e99362eeedd86497b659030cf57c6f0070df6d9c2b9b", size = 910416 },
-    { url = "https://files.pythonhosted.org/packages/6c/66/dd3ec249e44c1cc15e902e783747819ed41ead1336fcba72bf841f72c6e9/grpcio_tools-1.62.3-cp312-cp312-win_amd64.whl", hash = "sha256:11c625eebefd1fd40a228fc8bae385e448c7e32a6ae134e43cf13bbc23f902b7", size = 1052856 },
+    { url = "https://files.pythonhosted.org/packages/91/9d/7608eb89b41433a49dbf96f56d9c05b3a5ba08951702d54c368d370ab6aa/grpcio_tools-1.67.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:12aa38af76b5ef00a55808c7c374ed18d5dc7cc8081b717e56da3c50df1776e2", size = 2308120 },
+    { url = "https://files.pythonhosted.org/packages/93/f2/d8cbc35e63bba98e4352427d01c64801fef9e9d9cd7fc5eea0538128e0e6/grpcio_tools-1.67.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:b0b03d055127bbc7c629454804b53b5cad2cedfcf904576d159a8a04c22b8e66", size = 5500124 },
+    { url = "https://files.pythonhosted.org/packages/eb/b5/131d0eac92205d0ae3d3f7eecf655884ef7746aecac5a93520fb83d907d0/grpcio_tools-1.67.0-cp310-cp310-manylinux_2_17_aarch64.whl", hash = "sha256:02b0b50c59a8f7428326197027a2f586d216c46138c547f861533c46bff78bfe", size = 2282058 },
+    { url = "https://files.pythonhosted.org/packages/3f/3f/5e4de8d7fe38e8e42567a49a39f77d67e2905b00c69165e2e88f9d3005ac/grpcio_tools-1.67.0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b2afdfe151ed9edbd4a3fd646716f83b58010769c57f9c0aa1cf4c3bfb1240a8", size = 2617363 },
+    { url = "https://files.pythonhosted.org/packages/eb/53/3eb4eb7c178a229676d1ff0bcda640ebc0a104d12cdbd884f6796d118c56/grpcio_tools-1.67.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fc3eeb87575b2b360c5ef5aef22eb76cfdd6a255d2f628a48ab0e5a61a0039fb", size = 2416026 },
+    { url = "https://files.pythonhosted.org/packages/a6/9a/9c584d21ed1fb8f7adac6135a569c9b3b1378b6b467fba8d94d14de70606/grpcio_tools-1.67.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:ead78089c4771605a1ff8894e47f2267440693f1beeee06fd5a788aede83370f", size = 3224904 },
+    { url = "https://files.pythonhosted.org/packages/93/6a/dab92a7aa1bae0d2e0735462fbde778011916e5124d7ee9b52d214f42552/grpcio_tools-1.67.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:0671dcdccef09ca4eb415c1d6f470a857c6486733c146676f6810a3ade1d42cb", size = 2870381 },
+    { url = "https://files.pythonhosted.org/packages/49/be/3f2c958ef65161f3eeae5a1013358ca3c2eab25174ec4fc8d46b6d6146c8/grpcio_tools-1.67.0-cp310-cp310-win32.whl", hash = "sha256:a7398d90b8c7da479aec8f853d3664d5a93c209f8ac3bd41cb7ae4e8677a45c6", size = 941140 },
+    { url = "https://files.pythonhosted.org/packages/17/e9/461db9af08badc647659fa4a382ab546981ebccb413fc625e4b7c0413305/grpcio_tools-1.67.0-cp310-cp310-win_amd64.whl", hash = "sha256:f7e7d70a74df7e07be7cceaa694b7e8e5f3bef8e0299906f60885ecf7a40adb4", size = 1091151 },
+    { url = "https://files.pythonhosted.org/packages/cd/0d/88f181eecef84c9c8c009fa4d49ce812a5717539b75aacea4a7be8b9587c/grpcio_tools-1.67.0-cp311-cp311-linux_armv7l.whl", hash = "sha256:655716bf931a22a090134d87953710033640996d31e36f5f9b0106ff5f552d8e", size = 2307990 },
+    { url = "https://files.pythonhosted.org/packages/de/22/94855e18588800c96eca95af3be918249f635e4635e3e46895949b0ca27e/grpcio_tools-1.67.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:484ae782f9d3ff58e0bbb2f4cad14d5f5d9132fc701835b1dffd2c2a06f73ba6", size = 5526488 },
+    { url = "https://files.pythonhosted.org/packages/c3/c7/086f6c287fed85c2a5e19cb457a42a0eae2df9534666ed252947170daf8e/grpcio_tools-1.67.0-cp311-cp311-manylinux_2_17_aarch64.whl", hash = "sha256:f3e34de876efe1273f91e25ef241e449ed7f9411472dd9ff56d2039618017c30", size = 2282139 },
+    { url = "https://files.pythonhosted.org/packages/40/1a/d8e2171ef7b5b1fda54fa2dc82807725c9e31dd6b4878e9d68ab8f3c48b7/grpcio_tools-1.67.0-cp311-cp311-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d8301719edde2c3d388995703cdd962f558b76e9750405f772dce61402e4c3d0", size = 2617333 },
+    { url = "https://files.pythonhosted.org/packages/08/e8/e2b0a3e5890ad650d0cc9d92227f87a407784a9fc110438b85d01cf1ec71/grpcio_tools-1.67.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1629ea246044ccd473d9ac4c9f137a440d830b5e08d35225e1b354dbbb15b75d", size = 2415805 },
+    { url = "https://files.pythonhosted.org/packages/6a/43/a1731299e1662c24d89795a8ae4bb725f4a8a0c8e2dc6e12d3276eb96e14/grpcio_tools-1.67.0-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:d77a3c5cec0065267ca1a0b2589ececd1277ce25aa67f13ec50c816ee6f26f7f", size = 3224764 },
+    { url = "https://files.pythonhosted.org/packages/5d/03/968dd4b8de9ec4c6d287a8ba8b844f515a2cfcb350acefdb1fcb6f2945d9/grpcio_tools-1.67.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:c9bf992bcc7d9e6eaa20705056e1b955593092a38cec1746fef389d873ab2056", size = 2870440 },
+    { url = "https://files.pythonhosted.org/packages/9f/ea/e6bb028fec6f37aace620bd0a68e7c369bc975ece940dd3de08a2ef66edc/grpcio_tools-1.67.0-cp311-cp311-win32.whl", hash = "sha256:7e6e3db119c38629e0767cdb2ee18726ecc87e2249117d4c9e7ce06ea8c894ea", size = 940888 },
+    { url = "https://files.pythonhosted.org/packages/e5/26/b6f98fc9c1e6b8fa5b676bbb07e2bc70f388d4c513140fa38ffa9a15b934/grpcio_tools-1.67.0-cp311-cp311-win_amd64.whl", hash = "sha256:c6c27aec301a0e6cf231f9ee1c467c64002af51170fa7c0f3bb10bbfcd03fee7", size = 1091094 },
+    { url = "https://files.pythonhosted.org/packages/d6/b6/57e67c0244db8d7c0c312041293b806bfb1c9d66c26159e6faf39cc10356/grpcio_tools-1.67.0-cp312-cp312-linux_armv7l.whl", hash = "sha256:dca7f053cbdb26a587d4410ddb893877c585fb60a31f22fdd128e4f7c4dab27c", size = 2307646 },
+    { url = "https://files.pythonhosted.org/packages/52/43/837f08b85b04ac225aebe1d7da1a7a79fc313f231306c865b5112cef7dc4/grpcio_tools-1.67.0-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:de8c4f68ffa690769d84329c17c7fdd5fbe4c61b8f8a0de03f1ad8ef8bb06963", size = 5525447 },
+    { url = "https://files.pythonhosted.org/packages/3e/5f/adb8b87f5c403ba53529b6645184beddfa63abf2c524a6dabaa430e6bab3/grpcio_tools-1.67.0-cp312-cp312-manylinux_2_17_aarch64.whl", hash = "sha256:6e4ecb24c27a78f09fead45d4ed873805d6026124ccb6793b6fb93a490b78ddf", size = 2281767 },
+    { url = "https://files.pythonhosted.org/packages/6e/cd/3d6a7971e28b96cb618abb281325517443744ecfe48aa03f27a17cd5d4e1/grpcio_tools-1.67.0-cp312-cp312-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:004d6ef1b5f724480f05c0bdc904bf8c78c43d633c537d99abe51b52ce0cadeb", size = 2617363 },
+    { url = "https://files.pythonhosted.org/packages/2d/a9/b8f1eae3db0f1b6f9548bd2032f48cb6f1ec9bc6781436d52dff4b352fab/grpcio_tools-1.67.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9dd257072c86eb9b36791b3674a513a215ba76bbdd38fc228f0e8c6dc5ce3524", size = 2415322 },
+    { url = "https://files.pythonhosted.org/packages/9b/fc/0045bf2e5c97a5ffe0ff2c9a4e4a62894402e8d7094162c2084a809c9d1c/grpcio_tools-1.67.0-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:a8cca551317ed26e17d13b6ee27b2bd62f5fe9b3842b4e88389deb984f995848", size = 3225044 },
+    { url = "https://files.pythonhosted.org/packages/dc/73/eaf40958dd648dd98a0fbd30df2b51c5beb7ee24127c1f0bb99ea44fd435/grpcio_tools-1.67.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:a7ac3b4f837c693142f6688b629d1f6408f6ab250d927159b572555f5339fe25", size = 2870418 },
+    { url = "https://files.pythonhosted.org/packages/b4/77/e307e91816123444ff657bbae2269cb912f31a9390118ed371bde9d0c1f3/grpcio_tools-1.67.0-cp312-cp312-win32.whl", hash = "sha256:95feec33388e2a8f72c360a68efe6f0bfed9c771e94d21b7f2359d0010f60219", size = 940540 },
+    { url = "https://files.pythonhosted.org/packages/be/2a/0c1a64e88fbc17235b68d3178be6cf4a69aea5bd1deed683c0bbd2f5e9f9/grpcio_tools-1.67.0-cp312-cp312-win_amd64.whl", hash = "sha256:50a31d035193ebe7154181eac84734e25bdcdb36adba849d3b2adf1c3b0c382b", size = 1090427 },
 ]

 [[package]]
@@ -3116,32 +3119,32 @@ wheels = [

 [[package]]
 name = "opentelemetry-api"
-version = "1.27.0"
+version = "1.31.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "deprecated" },
    { name = "importlib-metadata" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/c9/83/93114b6de85a98963aec218a51509a52ed3f8de918fe91eb0f7299805c3f/opentelemetry_api-1.27.0.tar.gz", hash = "sha256:ed673583eaa5f81b5ce5e86ef7cdaf622f88ef65f0b9aab40b843dcae5bef342", size = 62693 }
+sdist = { url = "https://files.pythonhosted.org/packages/8a/cf/db26ab9d748bf50d6edf524fb863aa4da616ba1ce46c57a7dff1112b73fb/opentelemetry_api-1.31.1.tar.gz", hash = "sha256:137ad4b64215f02b3000a0292e077641c8611aab636414632a9b9068593b7e91", size = 64059 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/fb/1f/737dcdbc9fea2fa96c1b392ae47275165a7c641663fbb08a8d252968eed2/opentelemetry_api-1.27.0-py3-none-any.whl", hash = "sha256:953d5871815e7c30c81b56d910c707588000fff7a3ca1c73e6531911d53065e7", size = 63970 },
+    { url = "https://files.pythonhosted.org/packages/6c/c8/86557ff0da32f3817bc4face57ea35cfdc2f9d3bcefd42311ef860dcefb7/opentelemetry_api-1.31.1-py3-none-any.whl", hash = "sha256:1511a3f470c9c8a32eeea68d4ea37835880c0eed09dd1a0187acc8b1301da0a1", size = 65197 },
 ]

 [[package]]
 name = "opentelemetry-exporter-otlp-proto-common"
-version = "1.27.0"
+version = "1.31.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "opentelemetry-proto" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/cd/2e/7eaf4ba595fb5213cf639c9158dfb64aacb2e4c7d74bfa664af89fa111f4/opentelemetry_exporter_otlp_proto_common-1.27.0.tar.gz", hash = "sha256:159d27cf49f359e3798c4c3eb8da6ef4020e292571bd8c5604a2a573231dd5c8", size = 17860 }
+sdist = { url = "https://files.pythonhosted.org/packages/53/e5/48662d9821d28f05ab8350a9a986ab99d9c0e8b23f8ff391c8df82742a9c/opentelemetry_exporter_otlp_proto_common-1.31.1.tar.gz", hash = "sha256:c748e224c01f13073a2205397ba0e415dcd3be9a0f95101ba4aace5fc730e0da", size = 20627 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/41/27/4610ab3d9bb3cde4309b6505f98b3aabca04a26aa480aa18cede23149837/opentelemetry_exporter_otlp_proto_common-1.27.0-py3-none-any.whl", hash = "sha256:675db7fffcb60946f3a5c43e17d1168a3307a94a930ecf8d2ea1f286f3d4f79a", size = 17848 },
+    { url = "https://files.pythonhosted.org/packages/82/70/134282413000a3fc02e6b4e301b8c5d7127c43b50bd23cddbaf406ab33ff/opentelemetry_exporter_otlp_proto_common-1.31.1-py3-none-any.whl", hash = "sha256:7cadf89dbab12e217a33c5d757e67c76dd20ce173f8203e7370c4996f2e9efd8", size = 18823 },
 ]

 [[package]]
 name = "opentelemetry-exporter-otlp-proto-grpc"
-version = "1.27.0"
+version = "1.31.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "deprecated" },
@@ -3152,14 +3155,14 @@ dependencies = [
    { name = "opentelemetry-proto" },
    { name = "opentelemetry-sdk" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/a1/d0/c1e375b292df26e0ffebf194e82cd197e4c26cc298582bda626ce3ce74c5/opentelemetry_exporter_otlp_proto_grpc-1.27.0.tar.gz", hash = "sha256:af6f72f76bcf425dfb5ad11c1a6d6eca2863b91e63575f89bb7b4b55099d968f", size = 26244 }
+sdist = { url = "https://files.pythonhosted.org/packages/0f/37/6ce465827ac69c52543afb5534146ccc40f54283a3a8a71ef87c91eb8933/opentelemetry_exporter_otlp_proto_grpc-1.31.1.tar.gz", hash = "sha256:c7f66b4b333c52248dc89a6583506222c896c74824d5d2060b818ae55510939a", size = 26620 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/8d/80/32217460c2c64c0568cea38410124ff680a9b65f6732867bbf857c4d8626/opentelemetry_exporter_otlp_proto_grpc-1.27.0-py3-none-any.whl", hash = "sha256:56b5bbd5d61aab05e300d9d62a6b3c134827bbd28d0b12f2649c2da368006c9e", size = 18541 },
+    { url = "https://files.pythonhosted.org/packages/ee/25/9974fa3a431d7499bd9d179fb9bd7daaa3ad9eba3313f72da5226b6d02df/opentelemetry_exporter_otlp_proto_grpc-1.31.1-py3-none-any.whl", hash = "sha256:f4055ad2c9a2ea3ae00cbb927d6253233478b3b87888e197d34d095a62305fae", size = 18588 },
 ]

 [[package]]
 name = "opentelemetry-exporter-otlp-proto-http"
-version = "1.27.0"
+version = "1.31.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "deprecated" },
@@ -3170,28 +3173,29 @@ dependencies = [
    { name = "opentelemetry-sdk" },
    { name = "requests" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/31/0a/f05c55e8913bf58a033583f2580a0ec31a5f4cf2beacc9e286dcb74d6979/opentelemetry_exporter_otlp_proto_http-1.27.0.tar.gz", hash = "sha256:2103479092d8eb18f61f3fbff084f67cc7f2d4a7d37e75304b8b56c1d09ebef5", size = 15059 }
+sdist = { url = "https://files.pythonhosted.org/packages/6d/9c/d8718fce3d14042beab5a41c8e17be1864c48d2067be3a99a5652d2414a3/opentelemetry_exporter_otlp_proto_http-1.31.1.tar.gz", hash = "sha256:723bd90eb12cfb9ae24598641cb0c92ca5ba9f1762103902f6ffee3341ba048e", size = 15140 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/2d/8d/4755884afc0b1db6000527cac0ca17273063b6142c773ce4ecd307a82e72/opentelemetry_exporter_otlp_proto_http-1.27.0-py3-none-any.whl", hash = "sha256:688027575c9da42e179a69fe17e2d1eba9b14d81de8d13553a21d3114f3b4d75", size = 17203 },
+    { url = "https://files.pythonhosted.org/packages/f2/19/5041dbfdd0b2a6ab340596693759bfa7dcfa8f30b9fa7112bb7117358571/opentelemetry_exporter_otlp_proto_http-1.31.1-py3-none-any.whl", hash = "sha256:5dee1f051f096b13d99706a050c39b08e3f395905f29088bfe59e54218bd1cf4", size = 17257 },
 ]

 [[package]]
 name = "opentelemetry-instrumentation"
-version = "0.48b0"
+version = "0.52b1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "opentelemetry-api" },
-    { name = "setuptools" },
+    { name = "opentelemetry-semantic-conventions" },
+    { name = "packaging" },
    { name = "wrapt" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/04/0e/d9394839af5d55c8feb3b22cd11138b953b49739b20678ca96289e30f904/opentelemetry_instrumentation-0.48b0.tar.gz", hash = "sha256:94929685d906380743a71c3970f76b5f07476eea1834abd5dd9d17abfe23cc35", size = 24724 }
+sdist = { url = "https://files.pythonhosted.org/packages/49/c9/c52d444576b0776dbee71d2a4485be276cf46bec0123a5ba2f43f0cf7cde/opentelemetry_instrumentation-0.52b1.tar.gz", hash = "sha256:739f3bfadbbeec04dd59297479e15660a53df93c131d907bb61052e3d3c1406f", size = 28406 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/0a/7f/405c41d4f359121376c9d5117dcf68149b8122d3f6c718996d037bd4d800/opentelemetry_instrumentation-0.48b0-py3-none-any.whl", hash = "sha256:a69750dc4ba6a5c3eb67986a337185a25b739966d80479befe37b546fc870b44", size = 29449 },
+    { url = "https://files.pythonhosted.org/packages/61/dd/a2b35078170941990e7a5194b9600fa75868958a9a2196a752da0e7b97a0/opentelemetry_instrumentation-0.52b1-py3-none-any.whl", hash = "sha256:8c0059c4379d77bbd8015c8d8476020efe873c123047ec069bb335e4b8717477", size = 31036 },
 ]

 [[package]]
 name = "opentelemetry-instrumentation-asgi"
-version = "0.48b0"
+version = "0.52b1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "asgiref" },
@@ -3200,14 +3204,14 @@ dependencies = [
    { name = "opentelemetry-semantic-conventions" },
    { name = "opentelemetry-util-http" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/44/ac/fd3d40bab3234ec3f5c052a815100676baaae1832fa1067935f11e5c59c6/opentelemetry_instrumentation_asgi-0.48b0.tar.gz", hash = "sha256:04c32174b23c7fa72ddfe192dad874954968a6a924608079af9952964ecdf785", size = 23435 }
+sdist = { url = "https://files.pythonhosted.org/packages/bc/db/79bdc2344b38e60fecc7e99159a3f5b4c0e1acec8de305fba0a713cc3692/opentelemetry_instrumentation_asgi-0.52b1.tar.gz", hash = "sha256:a6dbce9cb5b2c2f45ce4817ad21f44c67fd328358ad3ab911eb46f0be67f82ec", size = 24203 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/db/74/a0e0d38622856597dd8e630f2bd793760485eb165708e11b8be1696bbb5a/opentelemetry_instrumentation_asgi-0.48b0-py3-none-any.whl", hash = "sha256:ddb1b5fc800ae66e85a4e2eca4d9ecd66367a8c7b556169d9e7b57e10676e44d", size = 15958 },
+    { url = "https://files.pythonhosted.org/packages/19/de/39ec078ae94a365d2f434b7e25886c267864aca5695b48fa5b60f80fbfb3/opentelemetry_instrumentation_asgi-0.52b1-py3-none-any.whl", hash = "sha256:f7179f477ed665ba21871972f979f21e8534edb971232e11920c8a22f4759236", size = 16338 },
 ]

 [[package]]
 name = "opentelemetry-instrumentation-fastapi"
-version = "0.48b0"
+version = "0.52b1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "opentelemetry-api" },
@@ -3216,57 +3220,57 @@ dependencies = [
    { name = "opentelemetry-semantic-conventions" },
    { name = "opentelemetry-util-http" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/58/20/43477da5850ef2cd3792715d442aecd051e885e0603b6ee5783b2104ba8f/opentelemetry_instrumentation_fastapi-0.48b0.tar.gz", hash = "sha256:21a72563ea412c0b535815aeed75fc580240f1f02ebc72381cfab672648637a2", size = 18497 }
+sdist = { url = "https://files.pythonhosted.org/packages/30/01/d159829077f2795c716445df6f8edfdd33391e82d712ba4613fb62b99dc5/opentelemetry_instrumentation_fastapi-0.52b1.tar.gz", hash = "sha256:d26ab15dc49e041301d5c2571605b8f5c3a6ee4a85b60940338f56c120221e98", size = 19247 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/ee/50/745ab075a3041b7a5f29a579d2c28eaad54f64b4589d8f9fd364c62cf0f3/opentelemetry_instrumentation_fastapi-0.48b0-py3-none-any.whl", hash = "sha256:afeb820a59e139d3e5d96619600f11ce0187658b8ae9e3480857dd790bc024f2", size = 11777 },
+    { url = "https://files.pythonhosted.org/packages/23/89/acef7f625b218523873e32584dc5243d95ffa4facba737fd8b854c049c58/opentelemetry_instrumentation_fastapi-0.52b1-py3-none-any.whl", hash = "sha256:73c8804f053c5eb2fd2c948218bff9561f1ef65e89db326a6ab0b5bf829969f4", size = 12114 },
 ]

 [[package]]
 name = "opentelemetry-proto"
-version = "1.27.0"
+version = "1.31.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "protobuf" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/9a/59/959f0beea798ae0ee9c979b90f220736fbec924eedbefc60ca581232e659/opentelemetry_proto-1.27.0.tar.gz", hash = "sha256:33c9345d91dafd8a74fc3d7576c5a38f18b7fdf8d02983ac67485386132aedd6", size = 34749 }
+sdist = { url = "https://files.pythonhosted.org/packages/5b/b0/e763f335b9b63482f1f31f46f9299c4d8388e91fc12737aa14fdb5d124ac/opentelemetry_proto-1.31.1.tar.gz", hash = "sha256:d93e9c2b444e63d1064fb50ae035bcb09e5822274f1683886970d2734208e790", size = 34363 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/94/56/3d2d826834209b19a5141eed717f7922150224d1a982385d19a9444cbf8d/opentelemetry_proto-1.27.0-py3-none-any.whl", hash = "sha256:b133873de5581a50063e1e4b29cdcf0c5e253a8c2d8dc1229add20a4c3830ace", size = 52464 },
+    { url = "https://files.pythonhosted.org/packages/b6/f1/3baee86eab4f1b59b755f3c61a9b5028f380c88250bb9b7f89340502dbba/opentelemetry_proto-1.31.1-py3-none-any.whl", hash = "sha256:1398ffc6d850c2f1549ce355744e574c8cd7c1dba3eea900d630d52c41d07178", size = 55854 },
 ]

 [[package]]
 name = "opentelemetry-sdk"
-version = "1.27.0"
+version = "1.31.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "opentelemetry-api" },
    { name = "opentelemetry-semantic-conventions" },
    { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/0d/9a/82a6ac0f06590f3d72241a587cb8b0b751bd98728e896cc4cbd4847248e6/opentelemetry_sdk-1.27.0.tar.gz", hash = "sha256:d525017dea0ccce9ba4e0245100ec46ecdc043f2d7b8315d56b19aff0904fa6f", size = 145019 }
+sdist = { url = "https://files.pythonhosted.org/packages/63/d9/4fe159908a63661e9e635e66edc0d0d816ed20cebcce886132b19ae87761/opentelemetry_sdk-1.31.1.tar.gz", hash = "sha256:c95f61e74b60769f8ff01ec6ffd3d29684743404603df34b20aa16a49dc8d903", size = 159523 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/c1/bd/a6602e71e315055d63b2ff07172bd2d012b4cba2d4e00735d74ba42fc4d6/opentelemetry_sdk-1.27.0-py3-none-any.whl", hash = "sha256:365f5e32f920faf0fd9e14fdfd92c086e317eaa5f860edba9cdc17a380d9197d", size = 110505 },
+    { url = "https://files.pythonhosted.org/packages/bc/36/758e5d3746bc86a2af20aa5e2236a7c5aa4264b501dc0e9f40efd9078ef0/opentelemetry_sdk-1.31.1-py3-none-any.whl", hash = "sha256:882d021321f223e37afaca7b4e06c1d8bbc013f9e17ff48a7aa017460a8e7dae", size = 118866 },
 ]

 [[package]]
 name = "opentelemetry-semantic-conventions"
-version = "0.48b0"
+version = "0.52b1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "deprecated" },
    { name = "opentelemetry-api" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/0a/89/1724ad69f7411772446067cdfa73b598694c8c91f7f8c922e344d96d81f9/opentelemetry_semantic_conventions-0.48b0.tar.gz", hash = "sha256:12d74983783b6878162208be57c9effcb89dc88691c64992d70bb89dc00daa1a", size = 89445 }
+sdist = { url = "https://files.pythonhosted.org/packages/06/8c/599f9f27cff097ec4d76fbe9fe6d1a74577ceec52efe1a999511e3c42ef5/opentelemetry_semantic_conventions-0.52b1.tar.gz", hash = "sha256:7b3d226ecf7523c27499758a58b542b48a0ac8d12be03c0488ff8ec60c5bae5d", size = 111275 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/b7/7a/4f0063dbb0b6c971568291a8bc19a4ca70d3c185db2d956230dd67429dfc/opentelemetry_semantic_conventions-0.48b0-py3-none-any.whl", hash = "sha256:a0de9f45c413a8669788a38569c7e0a11ce6ce97861a628cca785deecdc32a1f", size = 149685 },
+    { url = "https://files.pythonhosted.org/packages/98/be/d4ba300cfc1d4980886efbc9b48ee75242b9fcf940d9c4ccdc9ef413a7cf/opentelemetry_semantic_conventions-0.52b1-py3-none-any.whl", hash = "sha256:72b42db327e29ca8bb1b91e8082514ddf3bbf33f32ec088feb09526ade4bc77e", size = 183409 },
 ]

 [[package]]
 name = "opentelemetry-util-http"
-version = "0.48b0"
+version = "0.52b1"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/d6/d7/185c494754340e0a3928fd39fde2616ee78f2c9d66253affaad62d5b7935/opentelemetry_util_http-0.48b0.tar.gz", hash = "sha256:60312015153580cc20f322e5cdc3d3ecad80a71743235bdb77716e742814623c", size = 7863 }
+sdist = { url = "https://files.pythonhosted.org/packages/23/3f/16a4225a953bbaae7d800140ed99813f092ea3071ba7780683299a87049b/opentelemetry_util_http-0.52b1.tar.gz", hash = "sha256:c03c8c23f1b75fadf548faece7ead3aecd50761c5593a2b2831b48730eee5b31", size = 8044 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/ad/2e/36097c0a4d0115b8c7e377c90bab7783ac183bc5cb4071308f8959454311/opentelemetry_util_http-0.48b0-py3-none-any.whl", hash = "sha256:76f598af93aab50328d2a69c786beaedc8b6a7770f7a818cc307eb353debfffb", size = 6946 },
+    { url = "https://files.pythonhosted.org/packages/2c/00/1591b397c9efc0e4215d223553a1cb9090c8499888a4447f842443077d31/opentelemetry_util_http-0.52b1-py3-none-any.whl", hash = "sha256:6a6ab6bfa23fef96f4995233e874f67602adf9d224895981b4ab9d4dde23de78", size = 7305 },
 ]

 [[package]]
@@ -3628,16 +3632,16 @@ wheels = [

 [[package]]
 name = "protobuf"
-version = "4.25.5"
+version = "5.29.4"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/67/dd/48d5fdb68ec74d70fabcc252e434492e56f70944d9f17b6a15e3746d2295/protobuf-4.25.5.tar.gz", hash = "sha256:7f8249476b4a9473645db7f8ab42b02fe1488cbe5fb72fddd445e0665afd8584", size = 380315 }
+sdist = { url = "https://files.pythonhosted.org/packages/17/7d/b9dca7365f0e2c4fa7c193ff795427cfa6290147e5185ab11ece280a18e7/protobuf-5.29.4.tar.gz", hash = "sha256:4f1dfcd7997b31ef8f53ec82781ff434a28bf71d9102ddde14d076adcfc78c99", size = 424902 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/00/35/1b3c5a5e6107859c4ca902f4fbb762e48599b78129a05d20684fef4a4d04/protobuf-4.25.5-cp310-abi3-win32.whl", hash = "sha256:5e61fd921603f58d2f5acb2806a929b4675f8874ff5f330b7d6f7e2e784bbcd8", size = 392457 },
-    { url = "https://files.pythonhosted.org/packages/a7/ad/bf3f358e90b7e70bf7fb520702cb15307ef268262292d3bdb16ad8ebc815/protobuf-4.25.5-cp310-abi3-win_amd64.whl", hash = "sha256:4be0571adcbe712b282a330c6e89eae24281344429ae95c6d85e79e84780f5ea", size = 413449 },
-    { url = "https://files.pythonhosted.org/packages/51/49/d110f0a43beb365758a252203c43eaaad169fe7749da918869a8c991f726/protobuf-4.25.5-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:b2fde3d805354df675ea4c7c6338c1aecd254dfc9925e88c6d31a2bcb97eb173", size = 394248 },
-    { url = "https://files.pythonhosted.org/packages/c6/ab/0f384ca0bc6054b1a7b6009000ab75d28a5506e4459378b81280ae7fd358/protobuf-4.25.5-cp37-abi3-manylinux2014_aarch64.whl", hash = "sha256:919ad92d9b0310070f8356c24b855c98df2b8bd207ebc1c0c6fcc9ab1e007f3d", size = 293717 },
-    { url = "https://files.pythonhosted.org/packages/05/a6/094a2640be576d760baa34c902dcb8199d89bce9ed7dd7a6af74dcbbd62d/protobuf-4.25.5-cp37-abi3-manylinux2014_x86_64.whl", hash = "sha256:fe14e16c22be926d3abfcb500e60cab068baf10b542b8c858fa27e098123e331", size = 294635 },
-    { url = "https://files.pythonhosted.org/packages/33/90/f198a61df8381fb43ae0fe81b3d2718e8dcc51ae8502c7657ab9381fbc4f/protobuf-4.25.5-py3-none-any.whl", hash = "sha256:0aebecb809cae990f8129ada5ca273d9d670b76d9bfc9b1809f0a9c02b7dbf41", size = 156467 },
+    { url = "https://files.pythonhosted.org/packages/9a/b2/043a1a1a20edd134563699b0e91862726a0dc9146c090743b6c44d798e75/protobuf-5.29.4-cp310-abi3-win32.whl", hash = "sha256:13eb236f8eb9ec34e63fc8b1d6efd2777d062fa6aaa68268fb67cf77f6839ad7", size = 422709 },
+    { url = "https://files.pythonhosted.org/packages/79/fc/2474b59570daa818de6124c0a15741ee3e5d6302e9d6ce0bdfd12e98119f/protobuf-5.29.4-cp310-abi3-win_amd64.whl", hash = "sha256:bcefcdf3976233f8a502d265eb65ea740c989bacc6c30a58290ed0e519eb4b8d", size = 434506 },
+    { url = "https://files.pythonhosted.org/packages/46/de/7c126bbb06aa0f8a7b38aaf8bd746c514d70e6a2a3f6dd460b3b7aad7aae/protobuf-5.29.4-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:307ecba1d852ec237e9ba668e087326a67564ef83e45a0189a772ede9e854dd0", size = 417826 },
+    { url = "https://files.pythonhosted.org/packages/a2/b5/bade14ae31ba871a139aa45e7a8183d869efe87c34a4850c87b936963261/protobuf-5.29.4-cp38-abi3-manylinux2014_aarch64.whl", hash = "sha256:aec4962f9ea93c431d5714ed1be1c93f13e1a8618e70035ba2b0564d9e633f2e", size = 319574 },
+    { url = "https://files.pythonhosted.org/packages/46/88/b01ed2291aae68b708f7d334288ad5fb3e7aa769a9c309c91a0d55cb91b0/protobuf-5.29.4-cp38-abi3-manylinux2014_x86_64.whl", hash = "sha256:d7d3f7d1d5a66ed4942d4fefb12ac4b14a29028b209d4bfb25c68ae172059922", size = 319672 },
+    { url = "https://files.pythonhosted.org/packages/12/fb/a586e0c973c95502e054ac5f81f88394f24ccc7982dac19c515acd9e2c93/protobuf-5.29.4-py3-none-any.whl", hash = "sha256:3fde11b505e1597f71b875ef2fc52062b6a9740e5f7c8997ce878b6009145862", size = 172551 },
 ]

 [[package]]
Author	SHA1	Message	Date
Tony Kipkemboi	cb23c8da63	docs: reorganize observability docs and update titles	2025-03-25 11:03:46 -04:00
Tony Kipkemboi	35cb7fcf4d	Merge pull request #2463 from ayulockin/main docs: Add documentation for W&B Weave	2025-03-25 09:48:09 -04:00
ayulockin	d2a9a4a4e4	Revert "remove uv.lock" This reverts commit `e62e9c7401`.	2025-03-25 19:05:58 +05:30
ayulockin	e62e9c7401	remove uv.lock	2025-03-25 19:04:51 +05:30
ayulockin	3c5031e711	docs.json	2025-03-25 19:04:14 +05:30
ayulockin	82e84c0f88	features and resources	2025-03-25 16:43:14 +05:30
ayulockin	2c550dc175	add weave docs	2025-03-25 15:46:41 +05:30
Tony Kipkemboi	bdc92deade	docs: update changelog dates (#2437 ) * docs: update changelog dates * docs: add aws bedrock tools docs * docs: fix incorrect respect_context_window parameter in Crew example	2025-03-24 12:06:50 -04:00
Brandon Hancock (bhancock_ai)	ed1f009c64	Feat/improve yaml extraction (#2428 ) * Support wildcard handling in `emit()` Change `emit()` to call handlers registered for parent classes using `isinstance()`. Ensures that base event handlers receive derived events. * Fix failing test * Remove unused variable * update interpolation to work with example response types in yaml docs * make tests * fix circular deps * Fixing interpolation imports * Improve test --------- Co-authored-by: Vinicius Brasil <vini@hey.com> Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>	2025-03-21 18:59:55 -07:00
Matisse	bb3829a9ed	docs: Update model reference in LLM configuration (#2267 ) Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>	2025-03-21 15:12:26 -04:00
Fernando Galves	0a116202f0	Update the context window size for Amazon Bedrock FM- llm.py (#2304 ) Update the context window size for Amazon Bedrock Foundation Models. Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com> Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>	2025-03-21 14:48:25 -04:00
Stefano Baccianella	4daa88fa59	As explained in https://github.com/mangiucugna/json_repair?tab=readme-ov-file#performance-considerations we can skip a wasteful json.loads() here and save quite some time (#2397 ) Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com> Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>	2025-03-21 14:25:19 -04:00