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Enhance knowledge management in CrewAI
- Added `KnowledgeConfig` class to configure knowledge retrieval parameters such as `limit` and `score_threshold`. - Updated `Agent` and `Crew` classes to utilize the new knowledge configuration for querying knowledge sources. - Enhanced documentation to clarify the addition of knowledge sources at both agent and crew levels. - Introduced new tips in documentation to guide users on knowledge source management and configuration.
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@@ -42,6 +42,16 @@ CrewAI supports various types of knowledge sources out of the box:
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| `collection_name` | **str** | No | Name of the collection where the knowledge will be stored. Used to identify different sets of knowledge. Defaults to "knowledge" if not provided. |
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| `storage` | **Optional[KnowledgeStorage]** | No | Custom storage configuration for managing how the knowledge is stored and retrieved. If not provided, a default storage will be created. |
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<Tip>
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Unlike retrieval from a vector database using a tool, agents preloaded with knowledge will not need a retrieval persona or task.
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Simply add the relevant knowledge sources your agent or crew needs to function.
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Knowledge sources can be added at the agent or crew level.
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Crew level knowledge sources will be used by **all agents** in the crew.
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Agent level knowledge sources will be used by the **specific agent** that is preloaded with the knowledge.
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</Tip>
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## Quickstart Example
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<Tip>
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@@ -146,6 +156,26 @@ result = crew.kickoff(
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)
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```
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## Knowledge Configuration
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You can configure the knowledge configuration for the crew or agent.
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```python Code
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from crewai.knowledge.knowledge_config import KnowledgeConfig
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knowledge_config = KnowledgeConfig(limit=10, score_threshold=0.5)
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agent = Agent(
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...
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knowledge_config=knowledge_config
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)
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```
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<Tip>
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limit: is the number of relevant documents to return. Default is 3.
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score_threshold: is the minimum score for a document to be considered relevant. Default is 0.35.
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</Tip>
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## More Examples
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Here are examples of how to use different types of knowledge sources:
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