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| from fastapi import FastAPI, UploadFile, File | |
| from pydantic import BaseModel | |
| from utils import * | |
| from io import BytesIO | |
| document_data = {} | |
| app = FastAPI() | |
| class Q(BaseModel): | |
| question: str | |
| from utils import * | |
| async def upload_document(file: UploadFile = File()): | |
| content = await file.read() | |
| file = BytesIO(content) | |
| text, tables = textprocessing(file) | |
| text_embds = embed_query(text) | |
| table_texts = ["-".join(["|".join(row) for row in table]) for table in tables] | |
| table_embds = embed_query(table_texts) | |
| vectordb = setvecdb(text_embds, table_embds, text, table_texts) | |
| document_data["vectordb"] = vectordb | |
| return {"message": "Document uploaded and processed successfully"} | |
| async def processquestion(question: Q): | |
| query_text = question.question | |
| vectordb = document_data.get("vectordb") | |
| if vectordb is None: | |
| return {"error": "No document uploaded"} | |
| search_results = retriever(vectordb, query_text) | |
| context = "\n".join(search_results['content'].sum()) | |
| answer = generate_answer(query_text, context) | |
| return {"answer": answer} |