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from pydantic import BaseModel
from fastapi.middleware.cors import CORSMiddleware
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
from langchain_google_genai import (
ChatGoogleGenerativeAI,
HarmBlockThreshold,
HarmCategory,
)
from TextGen import app
class Generate(BaseModel):
text:str
def generate_text(prompt: str):
if prompt == "":
return {"detail": "Please provide a prompt."}
else:
prompt = PromptTemplate(template=prompt, input_variables=['Prompt'])
# Initialize the LLM
llm = ChatGoogleGenerativeAI(
model="gemini-pro",
safety_settings={
HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
},
)
llmchain = LLMChain(
prompt=prompt,
llm=llm
)
llm_response = llmchain.run({"Prompt": prompt})
return Generate(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=Generate)
def inference(input_prompt: str):
return generate_text(prompt=input_prompt) |