feat:ichat 修改大模型接口

apps/ichat/serializers.py

@@ -0,0 +1,4 @@
+from rest_framework import serializers
+
+class CustomLLMrequestSerializer(serializers.Serializer):
+    prompt = serializers.CharField()

apps/ichat/urls.py

@@ -0,0 +1,12 @@
+from apps.ichat.views import QueryLLMview
+from django.urls import path, include
+from rest_framework.routers import DefaultRouter
+
+API_BASE_URL = 'api/hrm/'
+HTML_BASE_URL = 'dhtml/hrm/'
+
+router = DefaultRouter()
+router.register('llm/query/', QueryLLMview, basename='llm_query')
+urlpatterns = [
+    path(API_BASE_URL, include(router.urls)),
+]

apps/ichat/views.py

@@ -4,11 +4,20 @@ from langchain_core.language_models import LLM
 from langchain_core.outputs import LLMResult, Generation
 from langchain_experimental.sql import SQLDatabaseChain
 from langchain_community.utilities import SQLDatabase
+from server.conf import DATABASES
+from serializers import CustomLLMrequestSerializer
+from rest_framework.views import APIView
+from urllib.parse import quote_plus
 # fastapi
 from fastapi import FastAPI
 from pydantic import BaseModel
 
-db = SQLDatabase.from_uri("postgresql+pg8000://postgres:zcDsj%402024@127.0.0.1:5432/factory", include_tables=["enm_mpoint", "enm_mpointstat"])
+
+db_conf = DATABASES['default']
+# 密码需要 URL 编码（因为有特殊字符如 @）
+password_encodeed = quote_plus(db_conf['password'])
+
+db = SQLDatabase.from_uri(f"postgresql+psycopg2://{db_conf['user']}:{password_encodeed}@{db_conf['host']}/{db_conf['name']}", include_tables=["enm_mpoint", "enm_mpointstat"])
 # model_url = "http://14.22.88.72:11025/v1/chat/completions"
 model_url = "http://139.159.180.64:11434/v1/chat/completions"
 
@@ -59,17 +68,12 @@ class CustomLLM(LLM):
         return "custom_llm"
     
 
-# 实例化
+class QueryLLMview(APIView):
-app = FastAPI()
+    def post(self, request):
-
+        serializer = CustomLLMrequestSerializer(data=request.data)
-class CustomLLMRequest(BaseModel):
+        serializer.is_valid(raise_exception=True)
-    prompt: str
+        prompt = serializer.validated_data['prompt']
-
+        llm = CustomLLM(model_url=model_url)
-@app.post("/llm/query/")
+        chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)
-def query(custom_llm_request: CustomLLMRequest):
+        result = chain.invoke(prompt)
-    prompt = custom_llm_request.prompt
+        return result
-    llm = CustomLLM(model_url=model_url)
-    db_chain = SQLDatabaseChain.from_llm(llm, db, verbose=True)
-    result = db_chain.invoke(prompt)
-    print('result--', result, prompt)
-    return {"result": result}