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from fastapi import FastAPI
from langgraph.agents.summarize_agent.graph import graph
from langgraph.agents.rag_agent.graph import graph as rag_graph
from fastapi import Request
from fastapi.middleware.cors import CORSMiddleware
from langchain_core.documents import Document
from utils.create_vectordb import create_chroma_db_and_document,query_chroma_db
app = FastAPI()
# cors
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.get("/")
def greet_json():
return {"Hello": "World!"}
@app.post("/summarize")
async def summarize(request: Request):
data = await request.json()
urls = data.get("urls")
codes = data.get("codes")
notes = data.get("notes")
return graph.invoke({"urls": urls, "codes": codes, "notes": notes})
@app.post("/save_summary")
async def save_summary(request: Request):
data = await request.json()
summary = data.get("summary", "")
post_id = data.get("post_id", None)
title = data.get("title", "")
category = data.get("category", "")
tags = data.get("tags", [])
references = data.get("references", [])
page_content = f"""
Title: {title}
Category: {category}
Tags: {', '.join(tags)}
Summary: {summary}
"""
document = Document(
page_content=page_content,
id = str(post_id)
)
is_added = create_chroma_db_and_document(document)
if not is_added:
return {"error": "Failed to save summary to the database." , "status": "error"}
return {"message": "Summary saved successfully." , "status": "success"}
@app.post("/summaries")
async def get_summaries(request: Request):
data = await request.json()
print(data)
query = data.get("query" , "")
print(f"Query received: {query}")
results = query_chroma_db(query=query)
return results
@app.post("/chat")
async def chat(request: Request):
data = await request.json()
print(f"Chat request data: {data}")
user_input = data.get("message", "")
chat_history = data.get("chat_history", [])
print(f"User input: {user_input}")
print(f"Chat history: {chat_history}")
# Invoke the RAG chatbot graph
result = rag_graph.invoke({
"user_input": user_input,
"chat_history": chat_history
})
return {
"response": result["response"],
"chat_history": result["chat_history"]
}
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