from fastapi import FastAPI,Query
from pydantic import BaseModel
from transformers import pipeline
app = FastAPI()

@app.get("/")
def greet_json():
    return {"status": "Its working built by Fayaz"}

# Initialize the text generation pipeline
pipe = pipeline("text2text-generation", model="google/flan-t5-small")
# checking for ofingpt
# ofintech/FinGPT_0.1.3
# pipe = pipeline("text2text-generation", model="MudassirFayaz/llama-2-7b_career_0.6.0", trust_remote_code=True)
# Initialize the text generation pipeline
# model = AutoModelForSeq2SeqLM.from_pretrained("ofintech/FinGPT_0.1.3")
# pipe = pipeline("text2text-generation", model="MudassirFayaz/llama-2-7b_career_0.6.0", tokenizer=tokenizer)

@app.get("/")
def home():
    return {"message": "Hello World"}

# Define a request model
class TextRequest(BaseModel):
    text: str

# Define a function to handle the POST request at `/generate`
@app.post("/generate")
def generate(request: TextRequest):
    # Use the pipeline to generate text from given input text
    output = pipe(request.text)

    # Return the generated text in JSON response
    return {"output": output[0]['generated_text']}