# api/main.py from fastapi import FastAPI, HTTPException import sentence_transformers from huggingface_hub import hf_hub_download, login import pandas as pd from src.processor import send_to_dataset,search_and_retrieve,generate_tech from typing import List, Dict from pydantic import BaseModel from datasets import load_dataset import os login(token=os.getenv("HF_TOKEN")) # This is the main application object that Uvicorn will run app = FastAPI( title="My Standalone API", description="An API hosted on Hugging Face Spaces", version="1.0.0" ) model = sentence_transformers.SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2') dataset = load_dataset("heymenn/Technologies", streaming=True, split="train") class SearchInput(BaseModel): title: str class SearchOutput(BaseModel): title: str purpose: str score: float top5: List[Dict] class GenerateInput(BaseModel): title: str instructions: str force: bool = False class GenerateOutput(BaseModel): name: str purpose: str problem_types_solved: str advantages: str limitations: str domain_tags: str @app.post("/search-technologies", response_model=SearchOutput) def post_search(payload: SearchInput): """ Endpoint that returns a search result. """ config = {"dataset": dataset, "model": model} res = search_and_retrieve(payload.title, config) return res @app.post("/generate-technology", response_model=GenerateOutput) def post_generate_and_push(payload: GenerateInput): """ Endpoint to generate a technology and push it to the dataset """ config = {"dataset": dataset, "model": model} res = search_and_retrieve(payload.title, config) if res["score"] >= 0.7 and not payload.force: raise HTTPException(status_code=500, detail=f"Cannot generate the technology a high score of {res['score']} have been found for the technology : {res['title']}") json_response = generate_tech(payload.title, payload.instructions) send_to_dataset(json_response, model) return json_response