重新问答接口实现

src/controller/api.py

@@ -13,10 +13,10 @@ from langchain.prompts import PromptTemplate
 from src.controller.request import (
     RegisterRequest,
     LoginRequest,
-    ChatCreateRequest,
     ChatQaRequest,
     ChatDetailRequest,
-    ChatDeleteRequest
+    ChatDeleteRequest,
+    ChatReQA
 )
 from src.config.consts import (
     CHAT_DB_USER,
@@ -84,8 +84,7 @@ async def login(request: LoginRequest):
 
 
 @app.post("/lae/chat/create", response_model=Response)
-async def create(request: ChatCreateRequest, token: str = Header(None)):
-    print(request)
+async def create(token: str = Header(None)):
     print(token)
     user_id = token.replace('*', '')
     crud = CRUD(_db=c_db)
@@ -99,6 +98,7 @@ async def create(request: ChatCreateRequest, token: str = Header(None)):
     }
     return ReturnData(200, '会话创建成功', dict(data)).get_data()
 
+
 @app.post("/lae/chat/delete", response_model=Response)
 async def delete(request: ChatDeleteRequest, token: str = Header(None)):
     print(request)
@@ -116,13 +116,14 @@ async def delete(request: ChatDeleteRequest, token: str = Header(None)):
     }
     return ReturnData(200, '会话删除成功', dict(data)).get_data()
 
+
 @app.post("/lae/chat/qa", response_model=Response)
 async def qa(request: ChatQaRequest, token: str = Header(None)):
     print(request)
     print(token)
     user_id = token.replace('*', '')
     chat_id = request.chat_id
-    question = request.query
+    question = request.question
     crud = CRUD(_db=c_db)
     if not crud.chat_exist_chatid_userid(_chat_id=chat_id, _user_id=user_id):
         return ReturnData(40000, "该会话不存在（用户无法访问非本人创建的对话）", {}).get_data()
@@ -144,7 +145,8 @@ async def qa(request: ChatQaRequest, token: str = Header(None)):
     data = {
         "answer": answer
     }
-    return ReturnData(200, '会话创建成功', dict(data)).get_data()
+    return ReturnData(200, '模型问答成功', dict(data)).get_data()
+
 
 @app.get("/lae/chat/detail", response_model=Response)
 async def detail(request: ChatDetailRequest, token: str = Header(None)):
@@ -175,5 +177,35 @@ async def clist(token: str = Header(None)):
     return ReturnData(200, "会话列表获取成功", dict(data)).get_data()
 
 
+@app.post("/lae/chat/reqa", response_model=Response)
+async def reqa(request: ChatReQA, token: str = Header(None)):
+    print(request)
+    print(token)
+    chat_id = request.chat_id
+    user_id = token.replace('*', '')
+    crud = CRUD(_db=c_db)
+    if not crud.chat_exist_chatid_userid(_chat_id=chat_id, _user_id=user_id):
+        return ReturnData(40000, "该会话不存在（用户无法访问非本人创建的对话）", {}).get_data()
+    question = crud.get_last_question(_chat_id=chat_id)
+    vecstore_faiss = VectorStore_FAISS(
+        embedding_model_name=EMBEEDING_MODEL_PATH,
+        store_path=FAISS_STORE_PATH,
+        index_name=INDEX_NAME,
+        info={"port": VEC_DB_PORT, "host": VEC_DB_HOST, "dbname": VEC_DB_DBNAME, "username": VEC_DB_USER,
+              "password": VEC_DB_PASSWORD},
+        show_number=SIMILARITY_SHOW_NUMBER,
+        reset=False)
+    base_llm = ChatERNIESerLLM(
+        chat_completion=ChatCompletion(ak="pT7sV1smp4AeDl0LjyZuHBV9", sk="b3N0ibo1IKTLZlSs7weZc8jdR0oHjyMu"))
+    my_chat = QA(PromptTemplate(input_variables=["context", "question"], template=prompt1), base_llm,
+                 {"temperature": 0.9}, ['context', 'question'], _db=c_db, _chat_id=chat_id,
+                 _faiss_db=vecstore_faiss)
+    answer = my_chat.chat(question)
+    my_chat.update_history()
+    data = {
+        "answer": answer
+    }
+    return ReturnData(200, '模型重新问答成功', dict(data)).get_data()
+
 if __name__ == "__main__":
     uvicorn.run(app, host='localhost', port=8889)

src/controller/request.py

@@ -11,13 +11,9 @@ class RegisterRequest(BaseModel):
     password: str
 
 
-class ChatCreateRequest(BaseModel):
-    id: str
-
-
 class ChatQaRequest(BaseModel):
     chat_id: str = None
-    query: str
+    question: str
 
 
 class ChatDetailRequest(BaseModel):
@@ -26,3 +22,8 @@ class ChatDetailRequest(BaseModel):
 
 class ChatDeleteRequest(BaseModel):
     chat_id: str
+
+
+class ChatReQA(BaseModel):
+    chat_id: str
+    query: str

src/llm/ernie_with_sdk.py

@@ -2,8 +2,7 @@ import os
 import requests
 from typing import Dict, Optional, List, Any, Mapping, Iterator
 from pydantic import root_validator
-
-from langchain.llms.base import BaseLLM, LLM
+from langchain.llms.base import LLM
 from langchain.cache import InMemoryCache
 from langchain.callbacks.manager import CallbackManagerForLLMRun, Callbacks, AsyncCallbackManagerForLLMRun
 import qianfan

src/pgdb/chat/crud.py

@@ -132,7 +132,6 @@ class CRUD:
         self.db.execute_args(query, (_user_id,))
         return self.db.fetchall()
 
-
     def get_chatinfo_from_chatid(self, _chat_id):
         query = f'SELECT info FROM chat WHERE chat_id = (%s)'
         self.db.execute_args(query, (_chat_id,))
@@ -141,3 +140,8 @@ class CRUD:
     def delete_chat(self, _chat_id):
         query = f'UPDATE chat SET deleted = 1 WHERE chat_id = (%s)'
         self.db.execute_args(query, (_chat_id,))
+
+    def get_last_question(self, _chat_id):
+        query = f'SELECT question FROM turn_qa WHERE chat_id = (%s) AND turn_number = 1'
+        self.db.execute_args(query, (_chat_id,))
+        return self.db.fetchone()[0]

src/server/qa.py

@@ -60,7 +60,7 @@ class QA:
         return GetSimilarity(_question=_aquestion, _faiss_db=self.faiss_db).get_similarity_doc()
 
     # 一次性直接给出所有的答案
-    async def chat(self, _question):
+    def chat(self, _question):
         self.cur_oquestion = _question
         self.cur_similarity = self.get_similarity(_aquestion=self.cur_oquestion)
         self.cur_question = self.prompt.format(**{k: v for k, v in zip(self.prompt_kwargs, (self.cur_similarity, self.cur_oquestion))})

test/gradio_test.py

@@ -48,9 +48,9 @@ def main():
               "password": VEC_DB_PASSWORD},
         show_number=SIMILARITY_SHOW_NUMBER,
         reset=False)
-    # base_llm = ChatERNIESerLLM(
-    #     chat_completion=ChatCompletion(ak="pT7sV1smp4AeDl0LjyZuHBV9", sk="b3N0ibo1IKTLZlSs7weZc8jdR0oHjyMu"))
-    base_llm = ChatGLMSerLLM(url='http://192.168.22.106:8088')
+    base_llm = ChatERNIESerLLM(
+        chat_completion=ChatCompletion(ak="pT7sV1smp4AeDl0LjyZuHBV9", sk="b3N0ibo1IKTLZlSs7weZc8jdR0oHjyMu"))
+    # base_llm = ChatGLMSerLLM(url='http://192.168.22.106:8088')
 
     my_chat = QA(PROMPT1, base_llm, {"temperature": 0.9}, ['context', 'question'], _db=c_db, _chat_id='2',
                  _faiss_db=vecstore_faiss)