Merge branch 'main' into bugfix/restrict-python-version-compatibility

2026-01-25 08:08:14 +00:00 · 2024-12-09 13:50:19 -05:00
parent cf39d73e64 6b87d22a70
commit 97b85e1830
10 changed files with 92 additions and 26 deletions
--- a/docs/concepts/knowledge.mdx
+++ b/docs/concepts/knowledge.mdx
@@ -8,8 +8,8 @@ icon: book

 ## What is Knowledge?

-Knowledge in CrewAI is a powerful system that allows AI agents to access and utilize external information sources during their tasks. 
-Think of it as giving your agents a reference library they can consult while working. 
+Knowledge in CrewAI is a powerful system that allows AI agents to access and utilize external information sources during their tasks.
+Think of it as giving your agents a reference library they can consult while working.

 <Info>
  Key benefits of using Knowledge:
@@ -47,7 +47,7 @@ from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSourc
 # Create a knowledge source
 content = "Users name is John. He is 30 years old and lives in San Francisco."
 string_source = StringKnowledgeSource(
-    content=content, 
+    content=content,
 )

 # Create an LLM with a temperature of 0 to ensure deterministic outputs
@@ -122,7 +122,6 @@ crewai reset-memories --knowledge

 This is useful when you've updated your knowledge sources and want to ensure that the agents are using the most recent information.

-
 ## Custom Knowledge Sources

 CrewAI allows you to create custom knowledge sources for any type of data by extending the `BaseKnowledgeSource` class. Let's create a practical example that fetches and processes space news articles.
@@ -141,10 +140,10 @@ from pydantic import BaseModel, Field

 class SpaceNewsKnowledgeSource(BaseKnowledgeSource):
    """Knowledge source that fetches data from Space News API."""
-    
+
    api_endpoint: str = Field(description="API endpoint URL")
    limit: int = Field(default=10, description="Number of articles to fetch")
-    
+
    def load_content(self) -> Dict[Any, str]:
        """Fetch and format space news articles."""
        try:
@@ -152,15 +151,15 @@ class SpaceNewsKnowledgeSource(BaseKnowledgeSource):
                f"{self.api_endpoint}?limit={self.limit}"
            )
            response.raise_for_status()
-            
+
            data = response.json()
            articles = data.get('results', [])
-            
+
            formatted_data = self._format_articles(articles)
            return {self.api_endpoint: formatted_data}
        except Exception as e:
            raise ValueError(f"Failed to fetch space news: {str(e)}")
-    
+
    def _format_articles(self, articles: list) -> str:
        """Format articles into readable text."""
        formatted = "Space News Articles:\n\n"
@@ -180,7 +179,7 @@ class SpaceNewsKnowledgeSource(BaseKnowledgeSource):
        for _, text in content.items():
            chunks = self._chunk_text(text)
            self.chunks.extend(chunks)
-        
+
        self._save_documents()

 # Create knowledge source
@@ -193,7 +192,7 @@ recent_news = SpaceNewsKnowledgeSource(
 space_analyst = Agent(
    role="Space News Analyst",
    goal="Answer questions about space news accurately and comprehensively",
-    backstory="""You are a space industry analyst with expertise in space exploration, 
+    backstory="""You are a space industry analyst with expertise in space exploration,
    satellite technology, and space industry trends. You excel at answering questions
    about space news and providing detailed, accurate information.""",
    knowledge_sources=[recent_news],
@@ -220,13 +219,14 @@ result = crew.kickoff(
    inputs={"user_question": "What are the latest developments in space exploration?"}
 )
 ```
+
 ```output Output
 # Agent: Space News Analyst
 ## Task: Answer this question about space news: What are the latest developments in space exploration?


 # Agent: Space News Analyst
-## Final Answer: 
+## Final Answer:
 The latest developments in space exploration, based on recent space news articles, include the following:

 1. SpaceX has received the final regulatory approvals to proceed with the second integrated Starship/Super Heavy launch, scheduled for as soon as the morning of Nov. 17, 2023. This is a significant step in SpaceX's ambitious plans for space exploration and colonization. [Source: SpaceNews](https://spacenews.com/starship-cleared-for-nov-17-launch/)
@@ -242,11 +242,13 @@ The latest developments in space exploration, based on recent space news article
 6. The National Natural Science Foundation of China has outlined a five-year project for researchers to study the assembly of ultra-large spacecraft. This could lead to significant advancements in spacecraft technology and space exploration capabilities. [Source: SpaceNews](https://spacenews.com/china-researching-challenges-of-kilometer-scale-ultra-large-spacecraft/)

 7. The Center for AEroSpace Autonomy Research (CAESAR) at Stanford University is focusing on spacecraft autonomy. The center held a kickoff event on May 22, 2024, to highlight the industry, academia, and government collaboration it seeks to foster. This could lead to significant advancements in autonomous spacecraft technology. [Source: SpaceNews](https://spacenews.com/stanford-center-focuses-on-spacecraft-autonomy/)
-``` 
+```
+
 </CodeGroup>
 #### Key Components Explained

 1. **Custom Knowledge Source (`SpaceNewsKnowledgeSource`)**:
+
   - Extends `BaseKnowledgeSource` for integration with CrewAI
   - Configurable API endpoint and article limit
   - Implements three key methods:
@@ -255,10 +257,12 @@ The latest developments in space exploration, based on recent space news article
     - `add()`: Processes and stores the content

 2. **Agent Configuration**:
+
   - Specialized role as a Space News Analyst
   - Uses the knowledge source to access space news

 3. **Task Setup**:
+
   - Takes a user question as input through `{user_question}`
   - Designed to provide detailed answers based on the knowledge source

@@ -267,6 +271,7 @@ The latest developments in space exploration, based on recent space news article
   - Handles input/output through the kickoff method

 This example demonstrates how to:
+
 - Create a custom knowledge source that fetches real-time data
 - Process and format external data for AI consumption
 - Use the knowledge source to answer specific user questions
@@ -274,13 +279,15 @@ This example demonstrates how to:

 #### About the Spaceflight News API

-The example uses the [Spaceflight News API](https://api.spaceflightnewsapi.net/v4/documentation), which:
+The example uses the [Spaceflight News API](https://api.spaceflightnewsapi.net/v4/docs/), which:
+
 - Provides free access to space-related news articles
 - Requires no authentication
 - Returns structured data about space news
 - Supports pagination and filtering

 You can customize the API query by modifying the endpoint URL:
+
 ```python
 # Fetch more articles
 recent_news = SpaceNewsKnowledgeSource(
@@ -303,9 +310,9 @@ recent_news = SpaceNewsKnowledgeSource(
    - Consider content overlap for context preservation
    - Organize related information into separate knowledge sources
  </Accordion>
-  
+
  <Accordion title="Performance Tips">
-    - Adjust chunk sizes based on content complexity
+    - Adjust chunk sizes based on content complexity 
    - Configure appropriate embedding models
    - Consider using local embedding providers for faster processing
  </Accordion>
--- a/docs/concepts/tools.mdx
+++ b/docs/concepts/tools.mdx
@@ -172,6 +172,48 @@ def my_tool(question: str) -> str:
    return "Result from your custom tool"
 ```

+### Structured Tools
+
+The `StructuredTool` class wraps functions as tools, providing flexibility and validation while reducing boilerplate. It supports custom schemas and dynamic logic for seamless integration of complex functionalities.
+
+#### Example:
+Using `StructuredTool.from_function`, you can wrap a function that interacts with an external API or system, providing a structured interface. This enables robust validation and consistent execution, making it easier to integrate complex functionalities into your applications as demonstrated in the following example:
+
+```python
+from crewai.tools.structured_tool import CrewStructuredTool
+from pydantic import BaseModel
+
+# Define the schema for the tool's input using Pydantic
+class APICallInput(BaseModel):
+    endpoint: str
+    parameters: dict
+
+# Wrapper function to execute the API call
+def tool_wrapper(*args, **kwargs):
+    # Here, you would typically call the API using the parameters
+    # For demonstration, we'll return a placeholder string
+    return f"Call the API at {kwargs['endpoint']} with parameters {kwargs['parameters']}"
+
+# Create and return the structured tool
+def create_structured_tool():
+    return CrewStructuredTool.from_function(
+        name='Wrapper API',
+        description="A tool to wrap API calls with structured input.",
+        args_schema=APICallInput,
+        func=tool_wrapper,
+    )
+
+# Example usage
+structured_tool = create_structured_tool()
+
+# Execute the tool with structured input
+result = structured_tool._run(**{
+    "endpoint": "https://example.com/api",
+    "parameters": {"key1": "value1", "key2": "value2"}
+})
+print(result)  # Output: Call the API at https://example.com/api with parameters {'key1': 'value1', 'key2': 'value2'}
+```
+
 ### Custom Caching Mechanism

 <Tip>