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Performed spell check across the entire documentation (#872)
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@@ -12,7 +12,7 @@ description: Leveraging memory systems in the crewAI framework to enhance agent
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| Component | Description |
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| :------------------- | :----------------------------------------------------------- |
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| **Short-Term Memory**| Temporarily stores recent interactions and outcomes, enabling agents to recall and utilize information relevant to their current context during the current executions. |
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| **Long-Term Memory** | Preserves valuable insights and learnings from past executions, allowing agents to build and refine their knowledge over time. So Agents can remeber what they did right and wrong across multiple executions |
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| **Long-Term Memory** | Preserves valuable insights and learnings from past executions, allowing agents to build and refine their knowledge over time. So Agents can remember what they did right and wrong across multiple executions |
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| **Entity Memory** | Captures and organizes information about entities (people, places, concepts) encountered during tasks, facilitating deeper understanding and relationship mapping. |
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| **Contextual Memory**| Maintains the context of interactions by combining `ShortTermMemory`, `LongTermMemory`, and `EntityMemory`, aiding in the coherence and relevance of agent responses over a sequence of tasks or a conversation. |
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@@ -51,7 +51,7 @@ To optimize tool performance with caching, define custom caching strategies usin
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@tool("Tool with Caching")
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def cached_tool(argument: str) -> str:
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"""Tool functionality description."""
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return "Cachable result"
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return "Cacheable result"
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def my_cache_strategy(arguments: dict, result: str) -> bool:
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# Define custom caching logic
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@@ -79,5 +79,4 @@ manager = Agent(
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1. `allow_code_execution`: Enable or disable code execution capabilities for the agent (default is False).
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2. `max_execution_time`: Set a maximum execution time (in seconds) for the agent to complete a task.
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3. `function_calling_llm`: Specify a separate language model for function calling.
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4
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3. `function_calling_llm`: Specify a separate language model for function calling.
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@@ -31,7 +31,7 @@ tool = TXTSearchTool(txt='path/to/text/file.txt')
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```
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## Arguments
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- `txt` (str): **Optinal**. The path to the text file you want to search. This argument is only required if the tool was not initialized with a specific text file; otherwise, the search will be conducted within the initially provided text file.
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- `txt` (str): **Optional**. The path to the text file you want to search. This argument is only required if the tool was not initialized with a specific text file; otherwise, the search will be conducted within the initially provided text file.
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## Custom model and embeddings
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