FactCheckerAI/backend.py at main · Rasbon99/FactCheckerAI · GitHub

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from fastapi import FastAPI
from pydantic import BaseModel

from WebScraper.scraper import Scraper
from Preprocessor.preprocessing_pipeline import Preprocessing_Pipeline
from Database.data_entities import Claim, Answer
from Database.sqldb import Database
from GraphRAG.rag_pipeline import RAG_Pipeline

backend_app = FastAPI()

db = Database()

class InputText(BaseModel):
    text: str

@backend_app.post("/run_pipeline")
def process_text(input_text: InputText):
    text = input_text.text

    preprocessor = Preprocessing_Pipeline()
    claim_title, claim_summary = preprocessor.run_claim_pipe(text)
    claim = Claim(text, claim_title, claim_summary)

    scraper = Scraper()
    sources = scraper.search_and_extract(claim_title, num_results=10)
    preprocessed_sources = preprocessor.run_sources_pipe(sources)
    claim.add_sources(preprocessed_sources)

    rag = RAG_Pipeline()
    query_result, graphs_folder = rag.run_pipeline(preprocessed_sources, claim.summary, claim.id)

    answer = Answer(claim.id, query_result, graphs_folder)

    return {"claim_title": claim_title, "claim_summary": claim_summary, "sources": preprocessed_sources, "query_result": query_result, "graphs_folder": graphs_folder}

@backend_app.post("/delete_db")
def delete_database():
    db.delete_all_conversations()

@backend_app.get("/get_history")
def delete_database():
    history = db.get_history()
    return history