Base code

backend/models/hallucination_models.py

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+"""
+Pydantic models for hallucination detection API endpoints.
+"""
+
+from typing import List, Dict, Any, Optional
+from pydantic import BaseModel, Field
+from datetime import datetime
+from enum import Enum
+
+class AssessmentType(str, Enum):
+    """Assessment types for claim verification."""
+    SUPPORTED = "supported"
+    REFUTED = "refuted"
+    INSUFFICIENT_INFORMATION = "insufficient_information"
+
+class SourceDocument(BaseModel):
+    """Represents a source document used for fact-checking."""
+    title: str = Field(..., description="Title of the source document")
+    url: str = Field(..., description="URL of the source document")
+    text: str = Field(..., description="Relevant text content from the source")
+    published_date: Optional[str] = Field(None, description="Publication date of the source")
+    author: Optional[str] = Field(None, description="Author of the source")
+    score: float = Field(0.5, description="Relevance score of the source (0.0-1.0)")
+
+class Claim(BaseModel):
+    """Represents a single verifiable claim extracted from text."""
+    text: str = Field(..., description="The claim text")
+    confidence: float = Field(..., description="Confidence score for the claim assessment (0.0-1.0)")
+    assessment: AssessmentType = Field(..., description="Assessment result for the claim")
+    supporting_sources: List[SourceDocument] = Field(default_factory=list, description="Sources that support the claim")
+    refuting_sources: List[SourceDocument] = Field(default_factory=list, description="Sources that refute the claim")
+    reasoning: Optional[str] = Field(None, description="Explanation for the assessment")
+
+class HallucinationDetectionRequest(BaseModel):
+    """Request model for hallucination detection."""
+    text: str = Field(..., description="Text to analyze for factual accuracy", min_length=10, max_length=5000)
+    include_sources: bool = Field(True, description="Whether to include source documents in the response")
+    max_claims: int = Field(10, description="Maximum number of claims to extract and verify", ge=1, le=20)
+
+class HallucinationDetectionResponse(BaseModel):
+    """Response model for hallucination detection."""
+    success: bool = Field(..., description="Whether the analysis was successful")
+    claims: List[Claim] = Field(default_factory=list, description="List of extracted and verified claims")
+    overall_confidence: float = Field(..., description="Overall confidence score for the analysis (0.0-1.0)")
+    total_claims: int = Field(..., description="Total number of claims extracted")
+    supported_claims: int = Field(..., description="Number of claims that are supported by sources")
+    refuted_claims: int = Field(..., description="Number of claims that are refuted by sources")
+    insufficient_claims: int = Field(..., description="Number of claims with insufficient information")
+    timestamp: str = Field(..., description="Timestamp of the analysis")
+    processing_time_ms: Optional[int] = Field(None, description="Processing time in milliseconds")
+    error: Optional[str] = Field(None, description="Error message if analysis failed")
+
+class ClaimExtractionRequest(BaseModel):
+    """Request model for claim extraction only."""
+    text: str = Field(..., description="Text to extract claims from", min_length=10, max_length=5000)
+    max_claims: int = Field(10, description="Maximum number of claims to extract", ge=1, le=20)
+
+class ClaimExtractionResponse(BaseModel):
+    """Response model for claim extraction."""
+    success: bool = Field(..., description="Whether the extraction was successful")
+    claims: List[str] = Field(default_factory=list, description="List of extracted claim texts")
+    total_claims: int = Field(..., description="Total number of claims extracted")
+    timestamp: str = Field(..., description="Timestamp of the extraction")
+    error: Optional[str] = Field(None, description="Error message if extraction failed")
+
+class ClaimVerificationRequest(BaseModel):
+    """Request model for verifying a single claim."""
+    claim: str = Field(..., description="Claim to verify", min_length=5, max_length=500)
+    include_sources: bool = Field(True, description="Whether to include source documents in the response")
+
+class ClaimVerificationResponse(BaseModel):
+    """Response model for claim verification."""
+    success: bool = Field(..., description="Whether the verification was successful")
+    claim: Claim = Field(..., description="Verified claim with assessment results")
+    timestamp: str = Field(..., description="Timestamp of the verification")
+    processing_time_ms: Optional[int] = Field(None, description="Processing time in milliseconds")
+    error: Optional[str] = Field(None, description="Error message if verification failed")
+
+class HealthCheckResponse(BaseModel):
+    """Response model for health check."""
+    status: str = Field(..., description="Service status")
+    version: str = Field(..., description="Service version")
+    exa_api_available: bool = Field(..., description="Whether Exa API is available")
+    openai_api_available: bool = Field(..., description="Whether OpenAI API is available")
+    timestamp: str = Field(..., description="Timestamp of the health check")