128 lines
No EOL
4.1 KiB
Python
128 lines
No EOL
4.1 KiB
Python
from fastapi import APIRouter, HTTPException
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import json
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from datetime import datetime
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from typing import Dict, List
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from app.config import GOOGLE_API_KEY, GOOGLE_FACT_CHECK_BASE_URL
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from app.models.fact_check_models import (
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GoogleFactCheckRequest as FactCheckRequest,
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GoogleFactCheckResponse as FactCheckResponse,
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Claim,
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ErrorResponse,
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TokenUsage
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)
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from app.websites.fact_checker_website import fetch_fact_checks, get_all_sources
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fact_check_router = APIRouter()
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class CustomJSONEncoder(json.JSONEncoder):
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def default(self, obj):
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if isinstance(obj, datetime):
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return obj.isoformat()
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return super().default(obj)
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@fact_check_router.post(
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"/check-facts",
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response_model=FactCheckResponse,
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responses={
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400: {"model": ErrorResponse},
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404: {"model": ErrorResponse},
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500: {"model": ErrorResponse},
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503: {"model": ErrorResponse}
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}
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)
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async def check_facts(request: FactCheckRequest) -> FactCheckResponse:
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"""
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Check facts using multiple fact-checking sources
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"""
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all_results = []
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verified_results = []
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# Validate configuration
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if not GOOGLE_API_KEY or not GOOGLE_FACT_CHECK_BASE_URL:
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raise HTTPException(
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status_code=500,
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detail=ErrorResponse(
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detail="API configuration is missing",
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error_code="CONFIGURATION_ERROR",
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path="/check-facts"
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).dict()
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)
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# Get all sources in priority order
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all_sources = get_all_sources()
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all_sources_list = [] # To store source URLs
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contexts_used = [] # To store context snippets
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for source in all_sources:
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try:
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result = await fetch_fact_checks(
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GOOGLE_API_KEY,
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GOOGLE_FACT_CHECK_BASE_URL,
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request.content,
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source
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)
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if "claims" in result:
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# Validate each claim through Pydantic
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for claim in result["claims"]:
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validated_claim = Claim(**claim).dict()
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all_results.append(validated_claim)
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# Extract source and context information
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if "claimReview" in validated_claim:
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review = validated_claim["claimReview"][0]
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if "publisher" in review and "site" in review["publisher"]:
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all_sources_list.append(review["publisher"]["site"])
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if "textualRating" in review:
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contexts_used.append(review["textualRating"])
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except HTTPException:
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raise
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except Exception as e:
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# Log the error but continue with other sources
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print(f"Error processing {source.domain}: {str(e)}")
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continue
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if not all_results:
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raise HTTPException(
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status_code=404,
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detail=ErrorResponse(
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detail="No fact check results found",
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error_code="NO_RESULTS_FOUND",
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path="/check-facts"
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).dict()
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)
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# Prepare the verification result
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verification_result = {
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"verdict": "Insufficient Information", # Default verdict
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"confidence": "Low",
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"evidence": contexts_used,
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"reasoning": "Based on available fact checks",
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"missing_info": "Additional verification may be needed"
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}
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# Create token usage information
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token_usage = TokenUsage(
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prompt_tokens=0,
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completion_tokens=0,
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total_tokens=0
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)
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# Create the response using Pydantic model with all required fields
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response = FactCheckResponse(
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query=request.content,
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total_claims_found=len(all_results),
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results=all_results,
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verification_result=verification_result,
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sources=list(set(all_sources_list)),
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context_used=contexts_used,
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token_usage=token_usage,
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summary={
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"total_sources": len(set(all_sources_list)),
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"fact_checking_sites_queried": len(all_sources)
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}
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)
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return response |