Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

added retrieve_docs endpoint for external RAG agent integration #1053

Open
wants to merge 1 commit into
base: dev
Choose a base branch
from
Open

added retrieve_docs endpoint for external RAG agent integration #1053

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
26 changes: 24 additions & 2 deletions backend/score.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@
import asyncio
import base64
from langserve import add_routes
from langchain_core.messages import HumanMessage, AIMessage
from langchain_google_vertexai import ChatVertexAI
from src.api_response import create_api_response
from src.graphDB_dataAccess import graphDBdataAccess
Expand Down Expand Up @@ -375,7 +376,28 @@ async def post_processing(uri=Form(), userName=Form(), password=Form(), database

finally:
gc.collect()


@app.post('/retrieve_docs')
async def retrieve_docs(uri=Form(),model=Form(None),userName=Form(), password=Form(), database=Form(), document_names=Form(None), mode=Form(None), question=Form(None)):
if mode == "graph":
graph = Neo4jGraph( url=uri,username=userName,password=password,database=database,sanitize = True, refresh_schema=True)
else:
graph = create_graph_database_connection(uri, userName, password, database)

chat_mode_settings = get_chat_mode_settings(mode=mode)

messages = [HumanMessage(question)]

try:
llm, doc_retriever, model_version = setup_chat(model, graph, document_names, chat_mode_settings)
docs, transformed_question = retrieve_documents(doc_retriever, messages)
return {
'docs': docs,
'transformed_question': transformed_question
}
except Exception as e:
return {'docs': [], 'transformed_question': None}

@app.post("/chat_bot")
async def chat_bot(uri=Form(),model=Form(None),userName=Form(), password=Form(), database=Form(),question=Form(None), document_names=Form(None),session_id=Form(None),mode=Form(None),email=Form()):
logging.info(f"QA_RAG called at {datetime.now()}")
Expand Down Expand Up @@ -1053,4 +1075,4 @@ async def get_schema_visualization(uri=Form(), userName=Form(), password=Form(),
gc.collect()

if __name__ == "__main__":
uvicorn.run(app)
uvicorn.run(app)