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reply func renaming

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Qingyun Wu 2023-09-11 10:30:24 -04:00
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website/docs/Use-Cases/agent_chat.md
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@ -26,7 +26,7 @@ We have designed a generic `ConversableAgent` class for Agents that are capable
- The `UserProxyAgent` is conceptually a proxy agent for humans, soliciting human input as the agent's reply at each interaction turn by default and also having the capability to execute code and call functions. The `UserProxyAgent` triggers code execution automatically when it detects an executable code block in the received message and no human user input is provided. Code execution can be disabled by setting `code_execution_config` to False. LLM-based response is disabled by default. It can be enabled by setting `llm_config` to a dict corresponding to the [inference](/docs/Use-Cases/enhanced_inference) configuration. When `llm_config` is set to a dict, `UserProxyAgent` can generate replies using an LLM when code execution is not performed. When `llm_config` is set to a dict, `UserProxyAgent` can generate replies using an LLM when code execution is not performed.
The auto-reply capability of `ConversableAgent` allows for more autonomous multi-agent communication while retaining the possibility of human intervention.
One can also easily extend it by registering auto_reply functions with the `register_reply()` method.
One can also easily extend it by registering reply functions with the `register_reply()` method.
In the following code, we create an `AssistantAgent` named "assistant" to serve as the assistant and a `UserProxyAgent` named "user_proxy" to serve as a proxy for the human user. We will later employ these two agents to solve a task.