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44c7978 4a50f91 44c7978 | 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 | from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from langchain.llms import OpenAI
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
import openai
from dotenv import load_dotenv
import os
# Load environment variables from .env file
load_dotenv()
# Configure OpenAI for Azure
openai.api_type = "azure"
openai.api_base = "https://amplifai-openai.openai.azure.com/"
openai.api_version = "2023-07-01-preview"
openai.api_key = os.getenv("OPENAI_API_KEY")
app = FastAPI()
class Prompt(BaseModel):
text: str
class GenerateResponse(BaseModel):
text: str
def generate_text(prompt: str):
if prompt == "":
return {"detail": "Please provide a prompt."}
else:
prompt_template = PromptTemplate(template=prompt, input_variables=['Prompt'])
llm = OpenAI(api_key=openai.api_key)
llmchain = LLMChain(
prompt=prompt_template,
llm=llm
)
llm_response = llmchain.run(
{"Prompt": prompt},
temperature=0.7,
max_tokens=750,
top_p=1.0,
frequency_penalty=0.0,
presence_penalty=0.0
)
return GenerateResponse(text=llm_response)
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.get("/", tags=["Home"])
def api_home():
return {'detail': 'Welcome to FastAPI TextGen Tutorial!'}
@app.post("/api/generate", summary="Generate text from prompt", tags=["Generate"], response_model=GenerateResponse)
def inference(input_prompt: Prompt):
return generate_text(prompt=input_prompt.text)
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