Spaces:
Sleeping
Sleeping
File size: 1,271 Bytes
7110ce1 f10e9d4 7110ce1 |
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 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
import os
from dotenv import load_dotenv
from langchain_groq import ChatGroq
from langchain_core.prompts import ChatPromptTemplate
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
load_dotenv()
groq_api_key = os.getenv('GROQ_API_KEY')
llm_model = ChatGroq(
groq_api_key=groq_api_key,
model_name="Llama3-8b-8192"
)
app = FastAPI()
origins = ["*"]
app.add_middleware(
CORSMiddleware,
allow_origins=origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
class textFromFrontendModel(BaseModel):
textFromNextJSFrontend: str
@app.get('/')
def welcome():
return {
'success': True,
'message': 'server of "fitbites is up and running successfully '
}
@app.post('/generateanswer')
async def predict(incomingTextFromFrontend: textFromFrontendModel):
prompt_text = incomingTextFromFrontend.textFromNextJSFrontend
prompt_template = ChatPromptTemplate.from_template(
"""
{text}
"""
)
chain = prompt_template | llm_model
response_from_model = chain.invoke({"text": prompt_text})
return {
'success': True,
'response_from_model': response_from_model
}
|