-
Notifications
You must be signed in to change notification settings - Fork 0
/
answer_eval_server.py
55 lines (43 loc) · 1.63 KB
/
answer_eval_server.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
#!/usr/bin/env python
from typing import List
from fastapi.staticfiles import StaticFiles
from langserve import add_routes
from fastapi import FastAPI, Form, Request
from fastapi.templating import Jinja2Templates
from langchain_community.chat_models import ChatOpenAI
from langchain.prompts import ChatPromptTemplate
from langchain_core.runnables.base import RunnableSequence
from fastapi.responses import HTMLResponse, JSONResponse
from answer_eval import Evaluation, CriteriaScore, get_answer_eval_chain
import langchain
langchain.debug = True
app = FastAPI(
title="AnswerEvallm",
version="1.0",
description="An API for evaluating the quality of the answer to a question",
)
add_routes(
app,
get_answer_eval_chain(),
path="/answer_eval",
output_type=Evaluation,
)
app.mount("/static", StaticFiles(directory="static"), name="static")
templates = Jinja2Templates(directory="templates")
@app.get("/qa", response_class=HTMLResponse)
async def qa_form(request: Request):
return templates.TemplateResponse("qa_form.html", {"request": request})
@app.post("/qa", response_class=HTMLResponse)
async def qa_form_evaluate(request: Request,
question: str = Form(...),
answer: str = Form(...)):
inputs = {
'question': question,
'answer': answer,
}
evaluation: Evaluation = get_answer_eval_chain().invoke(inputs)
response_data = {"request": request, **inputs, "evaluation": evaluation}
return templates.TemplateResponse("qa_form.html", response_data)
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="localhost", port=8000)