108 lines
3.5 KiB
Markdown
108 lines
3.5 KiB
Markdown
|
|
# Documentation
|
|
- Class name: SimpleChat
|
|
- Category: SALT/Language Toolkit/Agents
|
|
- Output node: False
|
|
|
|
SimpleChat节点提供了一个简单直接的文本聊天界面，用于两个代理之间的一对一对话。它抽象了启动、管理和总结聊天互动的复杂性，为进行对话提供了一个无缝的接口。
|
|
|
|
# Input types
|
|
## Required
|
|
- initiator
|
|
- 代表发起聊天的代理，为对话的背景和动态设定基调。
|
|
- Comfy dtype: AGENT
|
|
- Python dtype: ConversableAgent
|
|
- recipient
|
|
- 表示接收聊天发起的代理，通过回应发起者的消息在对话中扮演关键角色。
|
|
- Comfy dtype: AGENT
|
|
- Python dtype: ConversableAgent
|
|
- summary_method
|
|
- 指定用于总结聊天对话的方法，影响对话的整体理解和要点提取。
|
|
- Comfy dtype: COMBO[STRING]
|
|
- Python dtype: str
|
|
- clear_history
|
|
- 决定是否在开始新对话前清除聊天历史，影响互动的连续性和上下文。
|
|
- Comfy dtype: BOOLEAN
|
|
- Python dtype: bool
|
|
## Optional
|
|
- init_message
|
|
- 可选的初始消息，用于设定对话的基调和主题。
|
|
- Comfy dtype: STRING
|
|
- Python dtype: str
|
|
- max_turns
|
|
- 限制代理之间的交互次数，控制对话的长度。
|
|
- Comfy dtype: INT
|
|
- Python dtype: int
|
|
|
|
# Output types
|
|
- chat_history
|
|
- Comfy dtype: STRING
|
|
- 提供详细的聊天对话记录，捕捉代理之间的消息交换。
|
|
- Python dtype: str
|
|
- summary
|
|
- Comfy dtype: STRING
|
|
- 提供聊天的简明摘要，突出对话的关键点和结果。
|
|
- Python dtype: str
|
|
- initiator
|
|
- Comfy dtype: AGENT
|
|
- 返回发起聊天的代理，反映其在聊天会话中的角色和贡献。
|
|
- Python dtype: ConversableAgent
|
|
- recipient
|
|
- Comfy dtype: AGENT
|
|
- 返回接收聊天的代理，展示其在聊天中的回应和参与。
|
|
- Python dtype: ConversableAgent
|
|
|
|
|
|
## Usage tips
|
|
- Infra type: `CPU`
|
|
- Common nodes: unknown
|
|
|
|
|
|
## Source code
|
|
```python
|
|
class SimpleChat:
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
return {
|
|
"required": {
|
|
"initiator": ("AGENT",),
|
|
"recipient": ("AGENT",),
|
|
"summary_method": ([
|
|
"last_msg",
|
|
"reflection_with_llm",
|
|
],),
|
|
# whether to clear the chat history with the agent
|
|
"clear_history": ("BOOLEAN", {"default": True},),
|
|
},
|
|
"optional": {
|
|
"init_message": ("STRING", {"multiline": True, "dynamicPrompts": False}),
|
|
"max_turns": ("INT", {"default": 10}),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("STRING", "STRING", "AGENT", "AGENT",)
|
|
RETURN_NAMES = ("chat_history", "summary", "initiator", "recipient",)
|
|
|
|
FUNCTION = "start_chat"
|
|
CATEGORY = f"{MENU_NAME}/{SUB_MENU_NAME}/Agents"
|
|
|
|
def start_chat(self, initiator, recipient, summary_method, clear_history, init_message=None, max_turns=None):
|
|
initiator = clone_conversable_agent(initiator)
|
|
recipient = clone_conversable_agent(recipient)
|
|
|
|
chat_result = initiator.initiate_chat(
|
|
recipient,
|
|
message=init_message,
|
|
max_turns=max_turns,
|
|
summary_method=summary_method,
|
|
clear_history=clear_history,
|
|
)
|
|
summary = chat_result.summary
|
|
chat_history = ""
|
|
for message in chat_result.chat_history:
|
|
if message["content"] is not None:
|
|
chat_history += "- " + message["content"] + "\n\n"
|
|
return (chat_history, summary, initiator, recipient,)
|
|
|
|
```
|