Merge pull request #59 from ant-xuexiao/fix_chat_history

feat: add chat history

lui/src/Chat/index.tsx

@@ -61,7 +61,13 @@ const Chat: FC<ChatProps> = memo(({ helloMessage }) => {
           return [];
         }}
         request={async (messages) => {
-          const response = await streamChat(messages);
+          const newMessages = messages.map((message) => {
+            return {
+              role: message.role,
+              content: message.content as string,
+            };
+          });
+          const response = await streamChat(newMessages);
           return handleStream(response);
         }}
         inputAreaProps={{ className: 'userInputBox h-24 !important' }}

lui/src/services/ChatController.ts

@@ -1,12 +1,10 @@
-import { ChatMessage } from '@ant-design/pro-chat';
+import { IPrompt } from 'lui/interface';
 
 /**
  * Chat api
  * @param message IPrompt
  */
-export async function streamChat(
-  messages: ChatMessage<Record<string, any>>[],
-): Promise<Response> {
+export async function streamChat(messages: IPrompt[]): Promise<Response> {
   return fetch('http://127.0.0.1:8000/api/chat/stream', {
     method: 'POST',
     headers: {
@@ -15,7 +13,8 @@ export async function streamChat(
       'keep-alive': 'timeout=5',
     },
     body: JSON.stringify({
-      input_data: messages[0].content,
+      messages: messages,
+      prompt: '',
     }),
   });
 }

server/agent/stream.py

@@ -1,14 +1,16 @@
-from typing import Any, AsyncIterator, List, Literal
-from langchain.agents import AgentExecutor, tool
+from typing import AsyncIterator
+from langchain.agents import AgentExecutor
+from data_class import ChatData, Message
 from langchain.agents.format_scratchpad.openai_tools import (
     format_to_openai_tool_messages,
 )
 from langchain.agents.output_parsers.openai_tools import OpenAIToolsAgentOutputParser
 from langchain.prompts import MessagesPlaceholder
-from langchain_community.tools.convert_to_openai import format_tool_to_openai_tool
+from langchain_core.utils.function_calling import convert_to_openai_tool
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_openai import ChatOpenAI
 from tools import issue
+from langchain_core.messages import AIMessage, FunctionMessage, HumanMessage
 
 
 prompt = ChatPromptTemplate.from_messages(
@@ -19,13 +21,13 @@
             "1. Talk with the user as normal. "
             "2. If they ask you about issues, use a tool",
         ),
+        MessagesPlaceholder(variable_name="chat_history"),
         ("user", "{input}"),
         MessagesPlaceholder(variable_name="agent_scratchpad"),
     ]
 )
 
 
-
 TOOL_MAPPING = {
     "create_issue": issue.create_issue,
     "get_issues_list": issue.get_issues_list,
@@ -46,7 +48,7 @@ def _create_agent_with_tools(openai_api_key: str ) -> AgentExecutor:
 
     if tools:
         llm_with_tools = llm.bind(
-            tools=[format_tool_to_openai_tool(tool) for tool in tools]
+            tools=[convert_to_openai_tool(tool) for tool in tools]
         )
     else:
         llm_with_tools = llm
@@ -57,6 +59,7 @@ def _create_agent_with_tools(openai_api_key: str ) -> AgentExecutor:
             "agent_scratchpad": lambda x: format_to_openai_tool_messages(
                 x["intermediate_steps"]
             ),
+            "chat_history": lambda x: x["chat_history"],
         }
         | prompt
         | llm_with_tools
@@ -68,43 +71,51 @@ def _create_agent_with_tools(openai_api_key: str ) -> AgentExecutor:
     return agent_executor
 
 
+def chat_history_transform(messages: list[Message]):
+    transformed_messages = []
+    for message in messages:
+        print('meaage', message)
+        if message.role == "user":
+            transformed_messages.append(HumanMessage(content=message.content))
+        elif message.role == "assistant":
+           transformed_messages.append(AIMessage(content=message.content))
+        else:
+            transformed_messages.append(FunctionMessage(content=message.content))
+    return transformed_messages
+
 
-async def agent_chat(input_data: str, openai_api_key) -> AsyncIterator[str]:
+async def agent_chat(input_data: ChatData, openai_api_key) -> AsyncIterator[str]:
     try:
+        messages = input_data.messages
         agent_executor = _create_agent_with_tools(openai_api_key)
+        print(chat_history_transform(messages))
         async for event in agent_executor.astream_events(
             {
-                "input": input_data,
+                "input": messages[len(messages) - 1].content,
+                "chat_history": chat_history_transform(messages),
             },
             version="v1",
         ):
             kind = event["event"]
             if kind == "on_chain_start":
                 if (
                     event["name"] == "agent"
-                ):  # matches `.with_config({"run_name": "Agent"})` in agent_executor
-                    yield "\n"
-                    yield (
+                ): 
+                    print(
                         f"Starting agent: {event['name']} "
                         f"with input: {event['data'].get('input')}"
                     )
-                    yield "\n"
             elif kind == "on_chain_end":
                 if (
                     event["name"] == "agent"
-                ):  # matches `.with_config({"run_name": "Agent"})` in agent_executor
-                    yield "\n"
-                    yield (
+                ): 
+                    print (
                         f"Done agent: {event['name']} "
                         f"with output: {event['data'].get('output')['output']}"
                     )
-                    yield "\n"
             if kind == "on_chat_model_stream":
                 content = event["data"]["chunk"].content
                 if content:
-                    # Empty content in the context of OpenAI means
-                    # that the model is asking for a tool to be invoked.
-                    # So we only print non-empty content
                     yield f"{content}"
             elif kind == "on_tool_start":
                 yield "\n"

server/data_class.py

@@ -13,6 +13,3 @@ class Message(BaseModel):
 class ChatData(BaseModel):
     messages: list[Message] = []
     prompt: str = None
-
-class DataItem(BaseModel):
-    input_data: str

server/main.py

@@ -2,7 +2,7 @@
 from fastapi import FastAPI
 from fastapi.responses import StreamingResponse
 from fastapi.middleware.cors import CORSMiddleware
-from data_class import DalleData, ChatData, DataItem
+from data_class import DalleData, ChatData
 from openai_api import dalle
 from langchain_api import chat
 from agent import stream
@@ -40,6 +40,6 @@ def run_langchain_chat(input_data: ChatData):
 
 
 @app.post("/api/chat/stream", response_class=StreamingResponse)
-async def run_agent_chat(input_data: DataItem):
+async def run_agent_chat(input_data: ChatData):
     result = stream.agent_chat(input_data, open_api_key)
     return StreamingResponse(result, media_type="text/event-stream")