Module ai_contract_diff 

Pillars: [Contracts][AI]

AI-powered contract diff analysis

This module provides intelligent contract diff analysis that compares front-end requests against backend API contract specifications, detects mismatches, and generates AI-powered recommendations and correction proposals.

Features

• Structural Diff Analysis: Detects mismatches between requests and contract specs
• AI-Powered Recommendations: Uses LLM to generate contextual recommendations
• Correction Proposals: Generates JSON Patch files for schema corrections
• Confidence Scoring: Provides confidence scores for all suggestions

Example Usage

use mockforge_core::ai_contract_diff::{
    ContractDiffAnalyzer, ContractDiffConfig, CapturedRequest,
};
use mockforge_core::openapi::OpenApiSpec;

async fn example() -> mockforge_core::Result<()> {
    // Load contract specification
    let spec = OpenApiSpec::from_file("api.yaml").await?;

// Configure contract diff
let config = ContractDiffConfig {
    enabled: true,
    llm_provider: "openai".to_string(),
    llm_model: "gpt-4".to_string(),
    confidence_threshold: 0.5,
    ..Default::default()
};

// Create analyzer
let analyzer = ContractDiffAnalyzer::new(config)?;

// Capture a request
let request = CapturedRequest::new("POST", "/api/users", "browser_extension")
    .with_body(serde_json::json!({"name": "Alice", "email": "alice@example.com"}));

// Analyze request against contract
let result = analyzer.analyze(request, &spec).await?;

// Check results
if !result.matches {
    println!("Found {} mismatches", result.mismatches.len());
    for mismatch in &result.mismatches {
        println!("  - {}: {}", mismatch.path, mismatch.description);
    }

    // Generate recommendations
    for recommendation in &result.recommendations {
        println!("  Recommendation: {}", recommendation.recommendation);
    }

    // Generate correction proposals
    for correction in &result.corrections {
        println!("  Correction: {}", correction.description);
    }
    }
    Ok(())
}

Re-exports

pub use confidence_scorer::ConfidenceScorer;

pub use confidence_scorer::ScoringContext;

pub use correction_proposer::CorrectionProposer;

pub use diff_analyzer::DiffAnalyzer;

pub use recommendation_engine::RecommendationEngine;

pub use recommendation_engine::RequestContext;

pub use semantic_analyzer::SemanticAnalyzer;

Modules

confidence_scorer

Confidence scoring system for AI contract diff recommendations

correction_proposer

Schema correction proposal generator

diff_analyzer

Core diff analysis engine for contract comparison

recommendation_engine

AI-powered recommendation engine for contract diff analysis

semantic_analyzer

Semantic drift analysis for contract diffs

types

Re-exported from mockforge_foundation::contract_diff_types (Phase 6 / A5).

Structs

CapturedRequest

Captured request for contract analysis

ContractDiffAnalyzer

Main contract diff analyzer that orchestrates all components

ContractDiffConfig

Configuration for contract diff analysis

ContractDiffResult

Result of contract diff analysis between a request and a contract specification

CorrectionProposal

Correction proposal with patch operations

DiffMetadata

Metadata about the diff analysis

Mismatch

A detected mismatch between request and contract

Recommendation

AI-generated recommendation for fixing a mismatch

SemanticDriftResult

Semantic drift analysis result

Enums

ConfidenceLevel

Confidence level categories for visual indicators

MismatchSeverity

Severity levels for mismatches

MismatchType

Types of mismatches that can be detected

PatchOperation

JSON Patch operation types (RFC 6902)

SemanticChangeType

Type of semantic change