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)