Spaces:
Runtime error
Runtime error
| # app/main.py | |
| import uvicorn | |
| from fastapi import FastAPI, HTTPException, File, UploadFile | |
| from pydantic import BaseModel | |
| from app import models, openai_integration | |
| app = FastAPI(title="Materials AI Extraction API") | |
| # Pydantic models for request/response bodies | |
| class ExtractionRequest(BaseModel): | |
| text: str | |
| class QueryRequest(BaseModel): | |
| query: str | |
| class SummarizeRequest(BaseModel): | |
| text: str | |
| async def extract_data(request: ExtractionRequest): | |
| try: | |
| # Use our domain-specific model (e.g. MatSciBERT or BatteryBERT) for token classification | |
| extracted = models.extract_entities(request.text) | |
| return {"entities": extracted} | |
| except Exception as e: | |
| raise HTTPException(status_code=500, detail=str(e)) | |
| async def query_data(request: QueryRequest): | |
| try: | |
| # This endpoint performs a Q&A on the provided query using the domain models | |
| answer = models.answer_question(request.query) | |
| return {"answer": answer} | |
| except Exception as e: | |
| raise HTTPException(status_code=500, detail=str(e)) | |
| async def summarize(request: SummarizeRequest): | |
| try: | |
| summary = openai_integration.generate_summary(request.text) | |
| return {"summary": summary} | |
| except Exception as e: | |
| raise HTTPException(status_code=500, detail=str(e)) | |
| if __name__ == "__main__": | |
| uvicorn.run(app, host="0.0.0.0", port=8000) | |