diff --git a/.gitignore b/.gitignore index 07218a0..ad63a9f 100644 --- a/.gitignore +++ b/.gitignore @@ -89,6 +89,13 @@ docker-compose.override.yml screenshots/ test-results/ +# Node.js / Frontend +node_modules/ +frontend/dist/ +frontend/build/ +frontend/*.log +frontend/coverage/ + # Project-specific docs/*.pdf *.tmp diff --git a/backend/requirements.txt b/backend/requirements.txt new file mode 100644 index 0000000..ed5acaf --- /dev/null +++ b/backend/requirements.txt @@ -0,0 +1,14 @@ +# FastAPI and ASGI server +fastapi==0.104.1 +uvicorn[standard]==0.24.0 +python-multipart==0.0.6 +pydantic==2.5.0 + +# CORS and middleware +python-json-logger==2.0.7 + +# Testing +pytest==7.4.3 +pytest-asyncio==0.21.1 +httpx==0.25.1 +testcontainers==3.7.1 diff --git a/backend/src/__init__.py b/backend/src/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/src/api/__init__.py b/backend/src/api/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/src/api/main.py b/backend/src/api/main.py new file mode 100644 index 0000000..cdb1549 --- /dev/null +++ b/backend/src/api/main.py @@ -0,0 +1,200 @@ +""" +Smart Support Operator Web Interface - FastAPI Application + +This module provides the FastAPI application factory with CORS middleware, +error handlers, and app lifecycle management. + +Constitution Compliance: +- Principle I: Modular Architecture (wraps existing modules without modification) +- Principle IV: API-First Integration (OpenAPI auto-generation) +""" + +from contextlib import asynccontextmanager +from fastapi import FastAPI, Request, status +from fastapi.middleware.cors import CORSMiddleware +from fastapi.responses import JSONResponse +from fastapi.exceptions import RequestValidationError +from pydantic import ValidationError +import logging + +from backend.src.api.routes import classification, retrieval, health + +# Configure logging +logging.basicConfig( + level=logging.INFO, + format='%(asctime)s - %(name)s - %(levelname)s - %(message)s' +) +logger = logging.getLogger(__name__) + + +@asynccontextmanager +async def lifespan(app: FastAPI): + """Application lifecycle management.""" + logger.info("Smart Support Operator Interface starting up...") + + # Startup: Initialize retrieval module with pre-stored embeddings + try: + logger.info("Initializing retrieval module from stored embeddings...") + import os + import time + from backend.src.api.routes import retrieval + from src.retrieval.embeddings import EmbeddingsClient + from src.retrieval.cache import EmbeddingCache + from src.retrieval.retriever import TemplateRetriever + from src.retrieval.storage.sqlite_backend import SQLiteBackend + + start_time = time.time() + + # Path to pre-stored embeddings database + # Get project root (4 levels up from this file) + project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) + embeddings_db_path = os.path.join(project_root, "data", "embeddings.db") + + logger.info(f"Loading embeddings from: {embeddings_db_path}") + + # Check if embeddings database exists + if not os.path.exists(embeddings_db_path): + raise FileNotFoundError( + f"Embeddings database not found at: {embeddings_db_path}\n" + "Please run embedding precomputation first." + ) + + # Initialize SQLite storage backend + storage = SQLiteBackend(db_path=embeddings_db_path) + storage.connect() + + # Create cache and load embeddings from storage + cache = EmbeddingCache(storage_backend=storage) + + if not cache.is_ready: + raise RuntimeError( + f"Failed to load embeddings from {embeddings_db_path}. " + "Database may be empty or corrupted." + ) + + # Initialize embeddings client (needed for query embedding) + embeddings_client = EmbeddingsClient() + + # Create retriever with loaded cache + retriever = TemplateRetriever( + embeddings_client=embeddings_client, + cache=cache + ) + + # Set global retriever instance for API routes + retrieval.set_retriever(retriever) + + elapsed = time.time() - start_time + stats = cache.stats + + logger.info( + f"✓ Retrieval module initialized in {elapsed:.2f}s " + f"({stats['total_templates']} templates from storage)" + ) + + except FileNotFoundError as e: + logger.error(f"Embeddings database not found: {e}") + logger.warning("API will start but retrieval endpoint will return 503") + # Don't fail startup - allow API to run without retrieval + + except Exception as e: + logger.error(f"Failed to initialize retrieval module: {e}", exc_info=True) + logger.warning("API will start but retrieval endpoint will return 503") + # Don't fail startup - allow API to run without retrieval + + yield + + # Shutdown: Cleanup + logger.info("Smart Support Operator Interface shutting down...") + + +# Create FastAPI application +app = FastAPI( + title="Smart Support Operator API", + description="REST API for operator interface to classify inquiries and retrieve template responses", + version="1.0.0", + lifespan=lifespan, +) + +# Configure CORS +app.add_middleware( + CORSMiddleware, + allow_origins=[ + "http://localhost:5173", # Vite dev server + "http://localhost:3000", # Alternative port + "http://localhost:8080", # Docker deployment + ], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +# Global exception handlers +@app.exception_handler(RequestValidationError) +async def validation_exception_handler(request: Request, exc: RequestValidationError): + """Handle Pydantic validation errors with user-friendly messages.""" + logger.warning(f"Validation error: {exc}") + + # Extract first error for user message + first_error = exc.errors()[0] if exc.errors() else {} + field = first_error.get('loc', ['unknown'])[-1] + msg = first_error.get('msg', 'Validation failed') + + # Map to user-friendly message + if 'cyrillic' in msg.lower() or field == 'text': + error_message = "Please enter inquiry in Russian (at least 5 characters)" + elif 'min_length' in msg.lower(): + error_message = "Inquiry must be at least 5 characters" + elif 'max_length' in msg.lower(): + error_message = "Inquiry must not exceed 5000 characters" + else: + error_message = f"Invalid input: {msg}" + + return JSONResponse( + status_code=status.HTTP_400_BAD_REQUEST, + content={ + "error": error_message, + "error_type": "validation", + "timestamp": "2025-10-15T00:00:00Z", # TODO: Use actual timestamp + } + ) + + +@app.exception_handler(Exception) +async def general_exception_handler(request: Request, exc: Exception): + """Handle unexpected errors with generic user message.""" + logger.error(f"Unexpected error: {exc}", exc_info=True) + + return JSONResponse( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + content={ + "error": "An unexpected error occurred. Please try again or contact support.", + "error_type": "unknown", + "details": str(exc), # For logging, not shown to user + "timestamp": "2025-10-15T00:00:00Z", # TODO: Use actual timestamp + } + ) + + +# Include routers +app.include_router(health.router, prefix="/api", tags=["health"]) +app.include_router(classification.router, prefix="/api", tags=["classification"]) +app.include_router(retrieval.router, prefix="/api", tags=["retrieval"]) + + +# Root endpoint +@app.get("/") +async def root(): + """Root endpoint - redirect to docs.""" + return { + "message": "Smart Support Operator API", + "version": "1.0.0", + "docs": "/docs", + "health": "/api/health" + } + + +if __name__ == "__main__": + import uvicorn + uvicorn.run(app, host="0.0.0.0", port=8000, reload=True) diff --git a/backend/src/api/middleware.py b/backend/src/api/middleware.py new file mode 100644 index 0000000..fbd7dc7 --- /dev/null +++ b/backend/src/api/middleware.py @@ -0,0 +1,180 @@ +""" +Middleware for Smart Support Operator API + +Provides request/response logging, performance monitoring, and error handling utilities. + +Constitution Compliance: +- Principle II: User-Centric Design (user-friendly error messages) +- Principle IV: API-First Integration (request/response tracking) +""" + +import time +import logging +from typing import Callable +from fastapi import Request, Response +from starlette.middleware.base import BaseHTTPMiddleware +from starlette.types import ASGIApp + +logger = logging.getLogger(__name__) + + +class RequestLoggingMiddleware(BaseHTTPMiddleware): + """ + Logs all incoming requests and outgoing responses with performance metrics. + + Tracks: + - HTTP method and path + - Response status code + - Processing time in milliseconds + - Client IP address + """ + + async def dispatch(self, request: Request, call_next: Callable) -> Response: + """Process request and log metrics.""" + start_time = time.time() + + # Log incoming request + logger.info( + f"Incoming request: {request.method} {request.url.path} " + f"from {request.client.host if request.client else 'unknown'}" + ) + + # Process request + try: + response = await call_next(request) + processing_time_ms = (time.time() - start_time) * 1000 + + # Log response with timing + logger.info( + f"Completed: {request.method} {request.url.path} " + f"status={response.status_code} time={processing_time_ms:.2f}ms" + ) + + # Add custom header with processing time + response.headers["X-Processing-Time-Ms"] = f"{processing_time_ms:.2f}" + + return response + + except Exception as e: + processing_time_ms = (time.time() - start_time) * 1000 + logger.error( + f"Request failed: {request.method} {request.url.path} " + f"time={processing_time_ms:.2f}ms error={str(e)}", + exc_info=True + ) + raise + + +class PerformanceMonitoringMiddleware(BaseHTTPMiddleware): + """ + Monitors API performance and logs slow requests. + + Logs warnings for requests exceeding thresholds: + - Classification: 2000ms (FR-005: must respond in <2s) + - Retrieval: 1000ms (FR-010: must retrieve in <1s) + - Other endpoints: 500ms + """ + + THRESHOLDS = { + "/api/classify": 2000, # Classification threshold + "/api/retrieve": 1000, # Retrieval threshold + "default": 500 # Default for other endpoints + } + + async def dispatch(self, request: Request, call_next: Callable) -> Response: + """Monitor request performance.""" + start_time = time.time() + response = await call_next(request) + processing_time_ms = (time.time() - start_time) * 1000 + + # Get threshold for this endpoint + threshold = self.THRESHOLDS.get( + request.url.path, + self.THRESHOLDS["default"] + ) + + # Log warning if threshold exceeded + if processing_time_ms > threshold: + logger.warning( + f"SLOW REQUEST: {request.method} {request.url.path} " + f"took {processing_time_ms:.2f}ms (threshold: {threshold}ms)" + ) + + return response + + +def format_validation_error(error_detail: list) -> str: + """ + Format Pydantic validation errors into user-friendly messages. + + Args: + error_detail: List of error dictionaries from Pydantic ValidationError + + Returns: + User-friendly error message (no technical jargon) + """ + if not error_detail: + return "Validation failed" + + # Get first error + first_error = error_detail[0] + field = first_error.get('loc', ['unknown'])[-1] + msg = first_error.get('msg', 'Validation failed') + error_type = first_error.get('type', '') + + # Map to user-friendly messages based on field and error type + user_messages = { + 'inquiry': { + 'string_too_short': "Inquiry must be at least 5 characters", + 'string_too_long': "Inquiry must not exceed 5000 characters", + 'value_error': "Please enter inquiry in Russian (at least 5 characters)", + }, + 'query': { + 'string_too_short': "Query must be at least 5 characters", + 'string_too_long': "Query must not exceed 5000 characters", + 'value_error': "Query must contain Russian text", + }, + 'category': { + 'string_too_short': "Category is required", + }, + 'subcategory': { + 'string_too_short': "Subcategory is required", + }, + 'top_k': { + 'greater_than_equal': "Number of results must be at least 1", + 'less_than_equal': "Number of results must not exceed 10", + } + } + + # Check if we have a specific user-friendly message + if field in user_messages and error_type in user_messages[field]: + return user_messages[field][error_type] + + # Check for Cyrillic validation errors + if 'cyrillic' in msg.lower() or 'Cyrillic' in msg: + return "Please enter text in Russian (Cyrillic characters required)" + + # Default fallback + return f"Invalid {field}: {msg}" + + +def get_error_type(exception: Exception) -> str: + """ + Classify exception into error_type for ErrorResponse model. + + Args: + exception: The exception that occurred + + Returns: + Error type string: validation|api_error|timeout|unknown + """ + exception_name = exception.__class__.__name__ + + if exception_name in ['ValidationError', 'RequestValidationError']: + return 'validation' + elif exception_name in ['TimeoutError', 'asyncio.TimeoutError']: + return 'timeout' + elif exception_name in ['HTTPException', 'APIError']: + return 'api_error' + else: + return 'unknown' diff --git a/backend/src/api/models.py b/backend/src/api/models.py new file mode 100644 index 0000000..3b0df7a --- /dev/null +++ b/backend/src/api/models.py @@ -0,0 +1,232 @@ +""" +Pydantic Request/Response Models for Operator Web Interface API + +Mirrors the existing classification and retrieval module models for type-safe +API contracts. These models are used for FastAPI request validation and +response serialization. + +Constitution Compliance: +- Principle I: Modular Architecture (mirrors existing models without modification) +- Principle IV: API-First Integration (enables OpenAPI auto-generation) +""" + +from datetime import datetime +from typing import List, Optional +from pydantic import BaseModel, Field, field_validator +import re + + +# ============================================================================ +# Classification Models (mirror src/classification/models.py) +# ============================================================================ + +class ClassificationRequest(BaseModel): + """ + Request model for POST /api/classify endpoint. + + Validates customer inquiry text for classification. + """ + inquiry: str = Field( + ..., + min_length=5, + max_length=5000, + description="Customer inquiry text in Russian" + ) + + @field_validator('inquiry') + @classmethod + def validate_cyrillic(cls, v: str) -> str: + """Ensure inquiry contains at least one Cyrillic character (Russian).""" + v = v.strip() + if len(v) < 5: + raise ValueError("Inquiry text must be at least 5 characters") + if not re.search(r'[а-яА-ЯёЁ]', v): + raise ValueError("Inquiry must contain at least one Cyrillic character") + return v + + +class ClassificationResult(BaseModel): + """ + Response model for POST /api/classify endpoint. + + Contains classification results with category, subcategory, and confidence. + """ + inquiry: str = Field(..., description="Original inquiry text (echoed back)") + category: str = Field(..., description="Top-level product category") + subcategory: str = Field(..., description="Second-level classification") + confidence: float = Field(..., ge=0.0, le=1.0, description="Classification confidence (0.0-1.0)") + processing_time_ms: int = Field(..., gt=0, description="Processing time in milliseconds") + timestamp: str = Field( + default_factory=lambda: datetime.utcnow().isoformat() + "Z", + description="When classification was performed (ISO 8601 UTC)" + ) + + +# ============================================================================ +# Retrieval Models (mirror src/retrieval/models.py) +# ============================================================================ + +class RetrievalRequest(BaseModel): + """ + Request model for POST /api/retrieve endpoint. + + Constructed from ClassificationResult on frontend. + """ + query: str = Field( + ..., + min_length=5, + max_length=5000, + description="Customer inquiry text (must match classified inquiry)" + ) + category: str = Field(..., min_length=1, description="Category from classification") + subcategory: str = Field(..., min_length=1, description="Subcategory from classification") + classification_confidence: Optional[float] = Field( + None, + ge=0.0, + le=1.0, + description="Confidence score from classification (optional)" + ) + top_k: int = Field( + default=5, + ge=1, + le=10, + description="Number of templates to return" + ) + use_historical_weighting: bool = Field( + default=False, + description="Enable weighted scoring (not used in MVP)" + ) + + @field_validator('query') + @classmethod + def validate_cyrillic(cls, v: str) -> str: + """Ensure query contains at least one Cyrillic character.""" + if not re.search(r'[а-яА-ЯёЁ]', v): + raise ValueError("Query must contain at least one Cyrillic character") + return v + + +class TemplateResult(BaseModel): + """ + Single retrieved template with ranking metadata. + + Denormalized for UI display (includes question, answer, scores). + """ + template_id: str = Field(..., description="Unique template identifier") + template_question: str = Field(..., description="FAQ question text") + template_answer: str = Field(..., description="FAQ answer text (for copy-to-clipboard)") + category: str = Field(..., description="Template category") + subcategory: str = Field(..., description="Template subcategory") + similarity_score: float = Field( + ..., + ge=0.0, + le=1.0, + description="Cosine similarity (0.0-1.0)" + ) + combined_score: float = Field( + ..., + ge=0.0, + le=1.0, + description="Final ranking score" + ) + rank: int = Field(..., ge=1, description="Position in result list (1=best)") + + +class RetrievalResponse(BaseModel): + """ + Response model for POST /api/retrieve endpoint. + + Contains ranked template results with metadata and warnings. + """ + query: str = Field(..., description="Original inquiry (echoed back)") + category: str = Field(..., description="Category used for filtering") + subcategory: str = Field(..., description="Subcategory used for filtering") + results: List[TemplateResult] = Field( + ..., + max_length=10, + description="Ranked template results" + ) + total_candidates: int = Field( + ..., + ge=0, + description="Number of templates in category before ranking" + ) + processing_time_ms: float = Field( + ..., + ge=0.0, + description="Time to embed query + rank (ms)" + ) + timestamp: str = Field( + default_factory=lambda: datetime.utcnow().isoformat() + "Z", + description="When retrieval completed (ISO 8601 UTC)" + ) + warnings: List[str] = Field( + default_factory=list, + description="Warnings (e.g., low confidence, no templates)" + ) + + @field_validator('results') + @classmethod + def validate_ranking(cls, results: List[TemplateResult]) -> List[TemplateResult]: + """Ensure results are sorted by rank ascending (1, 2, 3, ...).""" + for i, result in enumerate(results): + expected_rank = i + 1 + if result.rank != expected_rank: + raise ValueError( + f"Result at index {i} has incorrect rank {result.rank}, expected {expected_rank}" + ) + return results + + +# ============================================================================ +# Error Response Model +# ============================================================================ + +class ErrorResponse(BaseModel): + """ + Standardized error response format for all API failures. + + Used for validation errors (400), service errors (503), timeouts (504). + """ + error: str = Field( + ..., + description="User-friendly, actionable error message (no technical jargon)" + ) + error_type: str = Field( + ..., + pattern="^(validation|api_error|timeout|unknown)$", + description="Error category for frontend handling" + ) + details: Optional[str] = Field( + None, + description="Technical details for logging (not shown to user)" + ) + timestamp: str = Field( + default_factory=lambda: datetime.utcnow().isoformat() + "Z", + description="When error occurred (ISO 8601 UTC)" + ) + + +# ============================================================================ +# Health Check Model +# ============================================================================ + +class HealthResponse(BaseModel): + """ + Health check response for GET /api/health endpoint. + + Used by frontend to detect service availability. + """ + status: str = Field(..., description="Overall health status (healthy/unhealthy)") + classification_available: bool = Field( + ..., + description="Whether classification service can handle requests" + ) + retrieval_available: bool = Field( + ..., + description="Whether retrieval service can handle requests" + ) + embeddings_count: int = Field( + ..., + description="Number of FAQ templates in embeddings database" + ) diff --git a/backend/src/api/routes/__init__.py b/backend/src/api/routes/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/src/api/routes/classification.py b/backend/src/api/routes/classification.py new file mode 100644 index 0000000..da534e1 --- /dev/null +++ b/backend/src/api/routes/classification.py @@ -0,0 +1,144 @@ +""" +Classification Endpoint for Smart Support Operator API + +Provides customer inquiry classification into categories and subcategories. + +Constitution Compliance: +- Principle I: Modular Architecture (wraps classification module) +- Principle IV: API-First Integration (REST endpoint for classification) +""" + +from fastapi import APIRouter, status, HTTPException +from backend.src.api.models import ( + ClassificationRequest, + ClassificationResult, + ErrorResponse +) +import logging +from src.classification.classifier import classify, ClassificationError + +logger = logging.getLogger(__name__) + +router = APIRouter() + + +@router.post( + "/classify", + response_model=ClassificationResult, + status_code=status.HTTP_200_OK, + summary="Classify customer inquiry", + description="Analyze inquiry text and determine product category and subcategory", + responses={ + 200: { + "description": "Successful classification", + "model": ClassificationResult + }, + 400: { + "description": "Validation error (invalid input)", + "model": ErrorResponse + }, + 503: { + "description": "Classification service unavailable", + "model": ErrorResponse + }, + 504: { + "description": "Classification timeout (>2s)", + "model": ErrorResponse + } + } +) +async def classify_inquiry(request: ClassificationRequest) -> ClassificationResult: + """ + Classify customer inquiry into category and subcategory. + + This endpoint wraps the existing classification module and provides + a REST API interface for the operator web interface. + + **Performance**: Must complete in < 2 seconds (FR-005) + + **Input Requirements**: + - Inquiry must be 5-5000 characters + - Must contain at least one Cyrillic character (Russian text) + + **Output**: + - Category: Top-level product category + - Subcategory: Second-level classification + - Confidence: Classification confidence score (0.0-1.0) + - Processing time: Time taken in milliseconds + + Args: + request: ClassificationRequest with inquiry text + + Returns: + ClassificationResult with category, subcategory, and confidence + + Raises: + HTTPException: If classification service unavailable or fails + """ + try: + logger.info(f"Classifying inquiry: {request.inquiry[:50]}...") + + # Call existing classification module + result = classify(request.inquiry) + + logger.info( + f"Classification successful: category={result.category}, " + f"subcategory={result.subcategory}, confidence={result.confidence:.2f}, " + f"time={result.processing_time_ms}ms" + ) + + return result + + except ClassificationError as e: + # Classification module error (validation, API errors, etc.) + logger.error(f"Classification error: {str(e)}") + + # Determine appropriate HTTP status code + error_message = str(e) + + if "API" in error_message or "service" in error_message.lower(): + # Service unavailable + raise HTTPException( + status_code=status.HTTP_503_SERVICE_UNAVAILABLE, + detail={ + "error": "Classification service is temporarily unavailable. Please try again.", + "error_type": "api_error", + "details": str(e), + "timestamp": __import__('datetime').datetime.utcnow().isoformat() + "Z" + } + ) + elif "timeout" in error_message.lower(): + # Timeout + raise HTTPException( + status_code=status.HTTP_504_GATEWAY_TIMEOUT, + detail={ + "error": "Classification took too long to complete. Please try again.", + "error_type": "timeout", + "details": str(e), + "timestamp": __import__('datetime').datetime.utcnow().isoformat() + "Z" + } + ) + else: + # Generic error + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={ + "error": str(e), + "error_type": "validation", + "details": str(e), + "timestamp": __import__('datetime').datetime.utcnow().isoformat() + "Z" + } + ) + + except Exception as e: + # Unexpected error + logger.error(f"Unexpected error during classification: {str(e)}", exc_info=True) + + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail={ + "error": "An unexpected error occurred. Please try again or contact support.", + "error_type": "unknown", + "details": str(e) + } + ) diff --git a/backend/src/api/routes/health.py b/backend/src/api/routes/health.py new file mode 100644 index 0000000..e581bad --- /dev/null +++ b/backend/src/api/routes/health.py @@ -0,0 +1,81 @@ +""" +Health Check Endpoint for Smart Support Operator API + +Provides service availability status for frontend health monitoring. + +Constitution Compliance: +- Principle I: Modular Architecture (checks module availability without tight coupling) +- Principle IV: API-First Integration (standard health endpoint pattern) +""" + +from fastapi import APIRouter, status +from backend.src.api.models import HealthResponse +import logging + +logger = logging.getLogger(__name__) + +router = APIRouter() + + +@router.get( + "/health", + response_model=HealthResponse, + status_code=status.HTTP_200_OK, + summary="Health check", + description="Check API and service availability status", +) +async def health_check() -> HealthResponse: + """ + Health check endpoint. + + Returns: + HealthResponse with service availability status + + Checks: + - Classification module: Always available (uses Scibox API) + - Retrieval module: Available if embeddings precomputed + - Embeddings count: Number of templates in cache + """ + # Check classification availability (always available via Scibox API) + classification_available = True + + # Check retrieval availability + retrieval_available = False + embeddings_count = 0 + + try: + from backend.src.api.routes.retrieval import get_retriever + + retriever = get_retriever() + + if retriever.is_ready(): + retrieval_available = True + stats = retriever.get_cache_stats() + embeddings_count = stats.get('total_templates', 0) + + except Exception as e: + # Retriever not initialized or not ready + logger.debug(f"Retrieval module not available: {e}") + + # Determine overall health status + # System is healthy if both modules are available + if classification_available and retrieval_available: + overall_status = "healthy" + elif classification_available: + overall_status = "degraded" # Classification works but retrieval doesn't + else: + overall_status = "unhealthy" + + logger.info( + f"Health check: status={overall_status}, " + f"classification={classification_available}, " + f"retrieval={retrieval_available}, " + f"embeddings={embeddings_count}" + ) + + return HealthResponse( + status=overall_status, + classification_available=classification_available, + retrieval_available=retrieval_available, + embeddings_count=embeddings_count, + ) diff --git a/backend/src/api/routes/retrieval.py b/backend/src/api/routes/retrieval.py new file mode 100644 index 0000000..0020e8f --- /dev/null +++ b/backend/src/api/routes/retrieval.py @@ -0,0 +1,212 @@ +""" +Retrieval Endpoint for Smart Support Operator API + +Provides template response retrieval based on classified inquiry. + +Constitution Compliance: +- Principle I: Modular Architecture (wraps retrieval module) +- Principle IV: API-First Integration (REST endpoint for retrieval) +""" + +from fastapi import APIRouter, status, HTTPException +from backend.src.api.models import ( + RetrievalRequest, + RetrievalResponse, + ErrorResponse +) +import logging +from typing import Optional + +# Import will happen after retriever is initialized in main.py +from src.retrieval.retriever import TemplateRetriever + +logger = logging.getLogger(__name__) + +router = APIRouter() + +# Global retriever instance (will be set in main.py lifespan) +_retriever: Optional[TemplateRetriever] = None + + +def set_retriever(retriever: TemplateRetriever): + """ + Set global retriever instance (called from main.py lifespan). + + Args: + retriever: Initialized TemplateRetriever instance + """ + global _retriever + _retriever = retriever + logger.info("Retriever instance registered with API") + + +def get_retriever() -> TemplateRetriever: + """ + Get global retriever instance. + + Returns: + TemplateRetriever instance + + Raises: + HTTPException: If retriever not initialized + """ + if _retriever is None: + raise HTTPException( + status_code=status.HTTP_503_SERVICE_UNAVAILABLE, + detail={ + "error": "Retrieval service is not initialized. System is starting up.", + "error_type": "api_error", + "details": "Retriever not initialized" + } + ) + return _retriever + + +@router.post( + "/retrieve", + response_model=RetrievalResponse, + status_code=status.HTTP_200_OK, + summary="Retrieve template responses", + description="Find and rank relevant template responses for classified inquiry", + responses={ + 200: { + "description": "Successful retrieval", + "model": RetrievalResponse + }, + 400: { + "description": "Validation error (invalid input)", + "model": ErrorResponse + }, + 503: { + "description": "Retrieval service unavailable", + "model": ErrorResponse + }, + 504: { + "description": "Retrieval timeout (>1s)", + "model": ErrorResponse + } + } +) +async def retrieve_templates(request: RetrievalRequest) -> RetrievalResponse: + """ + Retrieve and rank template responses for inquiry. + + This endpoint wraps the existing retrieval module and provides + a REST API interface for the operator web interface. + + **Performance**: Must complete in < 1 second (FR-010) + + **Input Requirements**: + - Query must be 5-5000 characters with Russian text + - Category and subcategory from classification + - top_k: 1-10 templates (default: 5) + + **Output**: + - Ranked template results (sorted by relevance) + - Each template includes question, answer, scores + - Processing time and warnings + + Args: + request: RetrievalRequest with query, category, subcategory + + Returns: + RetrievalResponse with ranked template results + + Raises: + HTTPException: If retrieval service unavailable or fails + """ + try: + # Get retriever instance + retriever = get_retriever() + + logger.info( + f"Retrieving templates: query={request.query[:50]}..., " + f"category={request.category}, subcategory={request.subcategory}, " + f"top_k={request.top_k}" + ) + + # Convert API model to retrieval model + from src.retrieval.models import RetrievalRequest as SrcRetrievalRequest + + src_request = SrcRetrievalRequest( + query=request.query, + category=request.category, + subcategory=request.subcategory, + classification_confidence=request.classification_confidence or 0.0, + top_k=request.top_k or 5, + use_historical_weighting=request.use_historical_weighting or False + ) + + # Call retrieval module + src_response = retriever.retrieve(src_request) + + logger.info( + f"Retrieval successful: found {len(src_response.results)} templates, " + f"time={src_response.processing_time_ms:.1f}ms" + ) + + # Convert retrieval model to API model + from backend.src.api.models import TemplateResult + + api_results = [ + TemplateResult( + template_id=r.template_id, + template_question=r.template_question, + template_answer=r.template_answer, + category=r.category, + subcategory=r.subcategory, + similarity_score=r.similarity_score, + combined_score=r.combined_score, + rank=r.rank + ) + for r in src_response.results + ] + + return RetrievalResponse( + query=src_response.query, + category=src_response.category, + subcategory=src_response.subcategory, + results=api_results, + total_candidates=src_response.total_candidates, + processing_time_ms=src_response.processing_time_ms, + warnings=src_response.warnings + ) + + except HTTPException: + # Re-raise HTTP exceptions (like 503 from get_retriever) + raise + + except Exception as e: + # Unexpected error + logger.error(f"Unexpected error during retrieval: {str(e)}", exc_info=True) + + # Determine error type + error_message = str(e).lower() + + if "timeout" in error_message: + raise HTTPException( + status_code=status.HTTP_504_GATEWAY_TIMEOUT, + detail={ + "error": "Retrieval took too long to complete. Please try again.", + "error_type": "timeout", + "details": str(e) + } + ) + elif "embeddings" in error_message or "api" in error_message: + raise HTTPException( + status_code=status.HTTP_503_SERVICE_UNAVAILABLE, + detail={ + "error": "Retrieval service is temporarily unavailable. Please try again.", + "error_type": "api_error", + "details": str(e) + } + ) + else: + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail={ + "error": "An unexpected error occurred. Please try again or contact support.", + "error_type": "unknown", + "details": str(e) + } + ) diff --git a/backend/tests/__init__.py b/backend/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/tests/integration/__init__.py b/backend/tests/integration/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/tests/integration/test_classification_api.py b/backend/tests/integration/test_classification_api.py new file mode 100644 index 0000000..cd54a94 --- /dev/null +++ b/backend/tests/integration/test_classification_api.py @@ -0,0 +1,246 @@ +""" +Integration Tests for POST /api/classify Endpoint + +Tests the classification API endpoint with various inputs and validates: +- Request/response model validation +- Performance requirements (FR-005: <2s response time) +- Error handling for invalid inputs +- Cyrillic text validation + +Constitution Compliance: +- Principle III: Data-Driven Validation (tests against real classification requirements) +- Principle II: User-Centric Design (validates user-friendly error messages) +""" + +import pytest +from fastapi.testclient import TestClient +from backend.src.api.main import app +import time + +client = TestClient(app) + + +class TestClassifyEndpoint: + """Test suite for POST /api/classify endpoint.""" + + def test_classify_valid_russian_inquiry(self): + """Test successful classification of valid Russian inquiry.""" + # Arrange + request_data = { + "inquiry": "Как открыть счет в банке?" # "How to open a bank account?" + } + + # Act + start_time = time.time() + response = client.post("/api/classify", json=request_data) + duration_ms = (time.time() - start_time) * 1000 + + # Assert + assert response.status_code == 200, f"Expected 200, got {response.status_code}: {response.text}" + + data = response.json() + + # Validate response structure (ClassificationResult model) + assert "inquiry" in data, "Response missing 'inquiry' field" + assert "category" in data, "Response missing 'category' field" + assert "subcategory" in data, "Response missing 'subcategory' field" + assert "confidence" in data, "Response missing 'confidence' field" + assert "processing_time_ms" in data, "Response missing 'processing_time_ms' field" + assert "timestamp" in data, "Response missing 'timestamp' field" + + # Validate field types and constraints + assert data["inquiry"] == request_data["inquiry"], "Inquiry not echoed back correctly" + assert isinstance(data["category"], str), "Category must be string" + assert len(data["category"]) > 0, "Category must not be empty" + assert isinstance(data["subcategory"], str), "Subcategory must be string" + assert len(data["subcategory"]) > 0, "Subcategory must not be empty" + assert isinstance(data["confidence"], (int, float)), "Confidence must be numeric" + assert 0.0 <= data["confidence"] <= 1.0, "Confidence must be in range [0.0, 1.0]" + assert isinstance(data["processing_time_ms"], int), "Processing time must be integer" + assert data["processing_time_ms"] > 0, "Processing time must be positive" + + # Validate performance (FR-005: must respond in <2s) + assert duration_ms < 2000, f"Classification took {duration_ms:.2f}ms (expected <2000ms)" + + # Validate timestamp format (ISO 8601 UTC) + assert data["timestamp"].endswith("Z"), "Timestamp must be in UTC (end with Z)" + + def test_classify_multiple_valid_inquiries(self): + """Test classification with various valid Russian inquiries.""" + test_cases = [ + "Забыл пароль от мобильного приложения", # Forgot mobile app password + "Как получить кредит на покупку квартиры?", # How to get mortgage credit? + "Почему не работает интернет-банкинг?", # Why isn't internet banking working? + "Хочу открыть депозит", # Want to open deposit + "Где найти реквизиты моей карты?", # Where to find my card details? + ] + + for inquiry in test_cases: + request_data = {"inquiry": inquiry} + response = client.post("/api/classify", json=request_data) + + assert response.status_code == 200, f"Failed for inquiry: {inquiry}" + data = response.json() + assert data["inquiry"] == inquiry + assert len(data["category"]) > 0 + assert len(data["subcategory"]) > 0 + assert 0.0 <= data["confidence"] <= 1.0 + + def test_classify_validation_too_short(self): + """Test validation error for inquiry that's too short.""" + request_data = {"inquiry": "Hi"} # Only 2 characters, min is 5 + + response = client.post("/api/classify", json=request_data) + + # Should return 400 Bad Request with ErrorResponse + assert response.status_code == 400 + data = response.json() + + assert "error" in data, "Error response missing 'error' field" + assert "error_type" in data, "Error response missing 'error_type' field" + assert data["error_type"] == "validation" + + # Error message should be user-friendly (no technical jargon) + assert "5 characters" in data["error"] or "at least 5" in data["error"] + + def test_classify_validation_too_long(self): + """Test validation error for inquiry that's too long.""" + request_data = {"inquiry": "а" * 5001} # 5001 Cyrillic characters, max is 5000 + + response = client.post("/api/classify", json=request_data) + + assert response.status_code == 400 + data = response.json() + + assert data["error_type"] == "validation" + assert "5000" in data["error"] or "exceed" in data["error"].lower() + + def test_classify_validation_no_cyrillic(self): + """Test validation error for inquiry without Cyrillic characters.""" + request_data = {"inquiry": "Hello, how are you today?"} # English only + + response = client.post("/api/classify", json=request_data) + + assert response.status_code == 400 + data = response.json() + + assert data["error_type"] == "validation" + # Error should mention Russian/Cyrillic requirement + error_lower = data["error"].lower() + assert "russian" in error_lower or "cyrillic" in error_lower + + def test_classify_validation_missing_inquiry(self): + """Test validation error for missing inquiry field.""" + request_data = {} # Missing required 'inquiry' field + + response = client.post("/api/classify", json=request_data) + + assert response.status_code == 422 # FastAPI returns 422 for missing required fields + + def test_classify_validation_whitespace_only(self): + """Test validation error for whitespace-only inquiry.""" + request_data = {"inquiry": " "} # Only whitespace + + response = client.post("/api/classify", json=request_data) + + # After trimming, this is < 5 characters + assert response.status_code == 400 + + def test_classify_mixed_text_with_cyrillic(self): + """Test that inquiry with mixed text but containing Cyrillic is accepted.""" + request_data = { + "inquiry": "Вопрос about credit cards and loans" # Mixed Russian + English + } + + response = client.post("/api/classify", json=request_data) + + # Should succeed because it contains at least one Cyrillic character + assert response.status_code == 200 + data = response.json() + assert data["inquiry"] == request_data["inquiry"] + + def test_classify_performance_benchmark(self): + """Benchmark classification performance for FR-005 requirement.""" + request_data = { + "inquiry": "Как узнать баланс моей карты через мобильное приложение?" + } + + durations = [] + iterations = 5 + + for _ in range(iterations): + start_time = time.time() + response = client.post("/api/classify", json=request_data) + duration_ms = (time.time() - start_time) * 1000 + durations.append(duration_ms) + + assert response.status_code == 200 + + avg_duration = sum(durations) / len(durations) + max_duration = max(durations) + min_duration = min(durations) + + print(f"\nClassification Performance ({iterations} iterations):") + print(f" Average: {avg_duration:.2f}ms") + print(f" Min: {min_duration:.2f}ms") + print(f" Max: {max_duration:.2f}ms") + + # FR-005: Classification must complete in <2 seconds + assert max_duration < 2000, f"Max duration {max_duration:.2f}ms exceeds 2000ms threshold" + + def test_classify_concurrent_requests(self): + """Test that multiple concurrent requests are handled correctly.""" + import concurrent.futures + + inquiries = [ + "Как открыть счет?", + "Забыл пароль", + "Хочу взять кредит", + "Проблемы с картой", + "Где мои реквизиты?", + ] + + def make_request(inquiry): + response = client.post("/api/classify", json={"inquiry": inquiry}) + return response.status_code, response.json() if response.status_code == 200 else None + + with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor: + futures = [executor.submit(make_request, inq) for inq in inquiries] + results = [f.result() for f in concurrent.futures.as_completed(futures)] + + # All requests should succeed + assert all(status == 200 for status, _ in results), "Some concurrent requests failed" + assert all(data is not None for _, data in results), "Some responses missing data" + + +class TestClassifyEdgeCases: + """Test edge cases and special characters.""" + + def test_classify_special_characters(self): + """Test inquiry with special characters.""" + request_data = { + "inquiry": "Как открыть счёт? Нужна помощь!!!" # Contains ё and punctuation + } + + response = client.post("/api/classify", json=request_data) + assert response.status_code == 200 + + def test_classify_numbers_and_cyrillic(self): + """Test inquiry with numbers and Cyrillic text.""" + request_data = { + "inquiry": "Карта 5555-1234-5678-9012 заблокирована" # Card number + Russian + } + + response = client.post("/api/classify", json=request_data) + assert response.status_code == 200 + + def test_classify_newlines_and_tabs(self): + """Test inquiry with newlines and tabs.""" + request_data = { + "inquiry": "Вопрос:\n\nКак\tоткрыть\tсчет?\n" + } + + response = client.post("/api/classify", json=request_data) + assert response.status_code == 200 + # Inquiry should be preserved as-is + assert response.json()["inquiry"] == request_data["inquiry"] diff --git a/backend/tests/integration/test_performance_benchmarks.py b/backend/tests/integration/test_performance_benchmarks.py new file mode 100644 index 0000000..410df7b --- /dev/null +++ b/backend/tests/integration/test_performance_benchmarks.py @@ -0,0 +1,504 @@ +""" +Performance Benchmark Tests for Smart Support Operator API + +Validates all performance requirements across the system: +- FR-005: Classification must complete in < 2 seconds +- FR-010: Retrieval must complete in < 1 second +- FR-015: Total workflow must complete in < 10 seconds + +Tests include: +- Single request performance +- Concurrent request performance +- Statistical analysis (min/max/mean/p95) +- Performance degradation under load + +Constitution Compliance: +- Principle III: Data-Driven Validation (quantifiable performance metrics) +- Principle II: User-Centric Design (operator workflow efficiency) +""" + +import pytest +from fastapi.testclient import TestClient +from backend.src.api.main import app +import time +import statistics +import concurrent.futures + +client = TestClient(app) + + +def calculate_percentile(data, percentile): + """Calculate percentile value from list of numbers.""" + sorted_data = sorted(data) + index = int((percentile / 100.0) * len(sorted_data)) + if index >= len(sorted_data): + index = len(sorted_data) - 1 + return sorted_data[index] + + +class TestClassificationPerformance: + """Performance benchmarks for classification endpoint.""" + + def test_classification_performance_single_request(self): + """Test classification performance for single request (FR-005: <2s).""" + request_data = { + "inquiry": "Как заблокировать банковскую карту?" + } + + durations = [] + iterations = 10 + + for _ in range(iterations): + start_time = time.time() + response = client.post("/api/classify", json=request_data) + duration_ms = (time.time() - start_time) * 1000 + durations.append(duration_ms) + + assert response.status_code == 200 + + # Calculate statistics + min_duration = min(durations) + max_duration = max(durations) + mean_duration = statistics.mean(durations) + p95_duration = calculate_percentile(durations, 95) + p99_duration = calculate_percentile(durations, 99) + + print(f"\nClassification Performance ({iterations} iterations):") + print(f" Min: {min_duration:.2f}ms") + print(f" Max: {max_duration:.2f}ms") + print(f" Mean: {mean_duration:.2f}ms") + print(f" P95: {p95_duration:.2f}ms") + print(f" P99: {p99_duration:.2f}ms") + + # FR-005: All requests must complete in < 2 seconds + assert max_duration < 2000, f"Max duration {max_duration:.2f}ms exceeds 2000ms" + assert p95_duration < 2000, f"P95 duration {p95_duration:.2f}ms exceeds 2000ms" + + def test_classification_performance_various_lengths(self): + """Test classification performance with different inquiry lengths.""" + test_cases = [ + ("Short", "Как открыть счет?"), # ~17 characters + ("Medium", "Как получить кредит на покупку автомобиля в вашем банке?"), # ~60 characters + ("Long", "Я хочу открыть депозитный счет на длительный срок, какие условия предлагает ваш банк для физических лиц, какие процентные ставки действуют на текущий момент?" * 3), # ~450 characters + ] + + for label, inquiry in test_cases: + durations = [] + iterations = 5 + + for _ in range(iterations): + start_time = time.time() + response = client.post("/api/classify", json={"inquiry": inquiry}) + duration_ms = (time.time() - start_time) * 1000 + durations.append(duration_ms) + + assert response.status_code == 200 + + avg_duration = statistics.mean(durations) + print(f"{label} inquiry ({len(inquiry)} chars): {avg_duration:.2f}ms avg") + + assert max(durations) < 2000, f"{label} inquiry exceeded 2000ms" + + def test_classification_concurrent_requests(self): + """Test classification performance under concurrent load.""" + inquiries = [ + "Как открыть счет в банке?", + "Забыл пароль от мобильного приложения", + "Хочу получить кредит на покупку квартиры", + "Почему не работает интернет-банкинг?", + "Как заблокировать карту?", + ] + + def make_request(inquiry): + start_time = time.time() + response = client.post("/api/classify", json={"inquiry": inquiry}) + duration_ms = (time.time() - start_time) * 1000 + return duration_ms, response.status_code + + # Test with 5 concurrent workers + with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor: + futures = [executor.submit(make_request, inq) for inq in inquiries] + results = [f.result() for f in concurrent.futures.as_completed(futures)] + + durations = [r[0] for r in results] + statuses = [r[1] for r in results] + + # All should succeed + assert all(s == 200 for s in statuses), "Some concurrent requests failed" + + # Performance should not degrade significantly + max_duration = max(durations) + mean_duration = statistics.mean(durations) + + print(f"\nConcurrent classification (5 parallel):") + print(f" Max: {max_duration:.2f}ms") + print(f" Mean: {mean_duration:.2f}ms") + + # Even under concurrent load, should meet <2s requirement + assert max_duration < 2000, f"Concurrent max {max_duration:.2f}ms exceeds 2000ms" + + +class TestRetrievalPerformance: + """Performance benchmarks for retrieval endpoint.""" + + def test_retrieval_performance_single_request(self): + """Test retrieval performance for single request (FR-010: <1s).""" + # First classify to get category/subcategory + classify_response = client.post("/api/classify", json={ + "inquiry": "Как узнать баланс карты?" + }) + assert classify_response.status_code == 200 + classification = classify_response.json() + + request_data = { + "query": "Как узнать баланс карты?", + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": 5 + } + + durations = [] + iterations = 10 + + for _ in range(iterations): + start_time = time.time() + response = client.post("/api/retrieve", json=request_data) + duration_ms = (time.time() - start_time) * 1000 + durations.append(duration_ms) + + assert response.status_code == 200 + + # Calculate statistics + min_duration = min(durations) + max_duration = max(durations) + mean_duration = statistics.mean(durations) + p95_duration = calculate_percentile(durations, 95) + p99_duration = calculate_percentile(durations, 99) + + print(f"\nRetrieval Performance ({iterations} iterations):") + print(f" Min: {min_duration:.2f}ms") + print(f" Max: {max_duration:.2f}ms") + print(f" Mean: {mean_duration:.2f}ms") + print(f" P95: {p95_duration:.2f}ms") + print(f" P99: {p99_duration:.2f}ms") + + # FR-010: All requests must complete in < 1 second + assert max_duration < 1000, f"Max duration {max_duration:.2f}ms exceeds 1000ms" + assert p95_duration < 1000, f"P95 duration {p95_duration:.2f}ms exceeds 1000ms" + + def test_retrieval_performance_different_top_k(self): + """Test retrieval performance with different top_k values.""" + # Classify first + classify_response = client.post("/api/classify", json={ + "inquiry": "Вопрос о кредитах" + }) + classification = classify_response.json() + + for top_k in [1, 3, 5, 10]: + request_data = { + "query": "Вопрос о кредитах", + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": top_k + } + + durations = [] + iterations = 5 + + for _ in range(iterations): + start_time = time.time() + response = client.post("/api/retrieve", json=request_data) + duration_ms = (time.time() - start_time) * 1000 + durations.append(duration_ms) + + assert response.status_code == 200 + + avg_duration = statistics.mean(durations) + print(f"top_k={top_k}: {avg_duration:.2f}ms avg") + + assert max(durations) < 1000, f"top_k={top_k} exceeded 1000ms" + + def test_retrieval_concurrent_requests(self): + """Test retrieval performance under concurrent load.""" + # Classify different inquiries + inquiries_and_categories = [] + + test_inquiries = [ + "Как открыть счет?", + "Забыл пароль", + "Нужен кредит", + "Проблема с картой", + "Хочу депозит", + ] + + for inquiry in test_inquiries: + classify_response = client.post("/api/classify", json={"inquiry": inquiry}) + assert classify_response.status_code == 200 + classification = classify_response.json() + inquiries_and_categories.append({ + "query": inquiry, + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": 5 + }) + + def make_request(request_data): + start_time = time.time() + response = client.post("/api/retrieve", json=request_data) + duration_ms = (time.time() - start_time) * 1000 + return duration_ms, response.status_code + + # Test with 5 concurrent workers + with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor: + futures = [executor.submit(make_request, req) for req in inquiries_and_categories] + results = [f.result() for f in concurrent.futures.as_completed(futures)] + + durations = [r[0] for r in results] + statuses = [r[1] for r in results] + + # All should succeed + assert all(s == 200 for s in statuses), "Some concurrent requests failed" + + max_duration = max(durations) + mean_duration = statistics.mean(durations) + + print(f"\nConcurrent retrieval (5 parallel):") + print(f" Max: {max_duration:.2f}ms") + print(f" Mean: {mean_duration:.2f}ms") + + # Even under concurrent load, should meet <1s requirement + assert max_duration < 1000, f"Concurrent max {max_duration:.2f}ms exceeds 1000ms" + + +class TestEndToEndWorkflowPerformance: + """Performance benchmarks for complete User Story 1 workflow.""" + + def test_workflow_performance_comprehensive(self): + """Test complete workflow performance (FR-015: <10s total).""" + test_inquiries = [ + "Как заблокировать банковскую карту?", + "Забыл пароль от мобильного приложения", + "Как получить кредит на покупку автомобиля?", + "Почему не приходят SMS с кодами?", + "Как открыть депозит в банке?", + ] + + all_classify_durations = [] + all_retrieval_durations = [] + all_workflow_durations = [] + + for inquiry in test_inquiries: + workflow_start = time.time() + + # Classify + classify_start = time.time() + classify_response = client.post("/api/classify", json={"inquiry": inquiry}) + classify_duration = (time.time() - classify_start) * 1000 + all_classify_durations.append(classify_duration) + + assert classify_response.status_code == 200 + classification = classify_response.json() + + # Retrieve + retrieval_start = time.time() + retrieval_response = client.post("/api/retrieve", json={ + "query": inquiry, + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": 5 + }) + retrieval_duration = (time.time() - retrieval_start) * 1000 + all_retrieval_durations.append(retrieval_duration) + + assert retrieval_response.status_code == 200 + + workflow_duration = (time.time() - workflow_start) * 1000 + all_workflow_durations.append(workflow_duration) + + # Calculate statistics + print(f"\nWorkflow Performance ({len(test_inquiries)} workflows):") + print("\nClassification:") + print(f" Min: {min(all_classify_durations):.2f}ms") + print(f" Max: {max(all_classify_durations):.2f}ms") + print(f" Mean: {statistics.mean(all_classify_durations):.2f}ms") + + print("\nRetrieval:") + print(f" Min: {min(all_retrieval_durations):.2f}ms") + print(f" Max: {max(all_retrieval_durations):.2f}ms") + print(f" Mean: {statistics.mean(all_retrieval_durations):.2f}ms") + + print("\nTotal Workflow:") + print(f" Min: {min(all_workflow_durations):.2f}ms") + print(f" Max: {max(all_workflow_durations):.2f}ms") + print(f" Mean: {statistics.mean(all_workflow_durations):.2f}ms") + + # Validate performance requirements + assert max(all_classify_durations) < 2000, "Classification exceeded 2s" + assert max(all_retrieval_durations) < 1000, "Retrieval exceeded 1s" + assert max(all_workflow_durations) < 10000, "Workflow exceeded 10s" + + def test_workflow_performance_stress(self): + """Stress test: Run workflow 20 times and validate performance consistency.""" + inquiry = "Как узнать баланс моей карты?" + iterations = 20 + + workflow_durations = [] + classify_durations = [] + retrieval_durations = [] + + for i in range(iterations): + workflow_start = time.time() + + # Classify + classify_start = time.time() + classify_response = client.post("/api/classify", json={"inquiry": inquiry}) + classify_duration = (time.time() - classify_start) * 1000 + classify_durations.append(classify_duration) + + assert classify_response.status_code == 200 + classification = classify_response.json() + + # Retrieve + retrieval_start = time.time() + retrieval_response = client.post("/api/retrieve", json={ + "query": inquiry, + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": 5 + }) + retrieval_duration = (time.time() - retrieval_start) * 1000 + retrieval_durations.append(retrieval_duration) + + assert retrieval_response.status_code == 200 + + workflow_duration = (time.time() - workflow_start) * 1000 + workflow_durations.append(workflow_duration) + + # Calculate comprehensive statistics + classify_stats = { + 'min': min(classify_durations), + 'max': max(classify_durations), + 'mean': statistics.mean(classify_durations), + 'median': statistics.median(classify_durations), + 'stdev': statistics.stdev(classify_durations) if len(classify_durations) > 1 else 0, + 'p95': calculate_percentile(classify_durations, 95), + } + + retrieval_stats = { + 'min': min(retrieval_durations), + 'max': max(retrieval_durations), + 'mean': statistics.mean(retrieval_durations), + 'median': statistics.median(retrieval_durations), + 'stdev': statistics.stdev(retrieval_durations) if len(retrieval_durations) > 1 else 0, + 'p95': calculate_percentile(retrieval_durations, 95), + } + + workflow_stats = { + 'min': min(workflow_durations), + 'max': max(workflow_durations), + 'mean': statistics.mean(workflow_durations), + 'median': statistics.median(workflow_durations), + 'stdev': statistics.stdev(workflow_durations) if len(workflow_durations) > 1 else 0, + 'p95': calculate_percentile(workflow_durations, 95), + } + + print(f"\nStress Test ({iterations} iterations):") + print("\nClassification:") + for key, value in classify_stats.items(): + print(f" {key.upper():6s}: {value:.2f}ms") + + print("\nRetrieval:") + for key, value in retrieval_stats.items(): + print(f" {key.upper():6s}: {value:.2f}ms") + + print("\nTotal Workflow:") + for key, value in workflow_stats.items(): + print(f" {key.upper():6s}: {value:.2f}ms") + + # Validate all requirements met + assert classify_stats['p95'] < 2000, f"Classification P95 {classify_stats['p95']:.2f}ms exceeds 2000ms" + assert retrieval_stats['p95'] < 1000, f"Retrieval P95 {retrieval_stats['p95']:.2f}ms exceeds 1000ms" + assert workflow_stats['p95'] < 10000, f"Workflow P95 {workflow_stats['p95']:.2f}ms exceeds 10000ms" + + # Performance should be consistent (stdev < 50% of mean) + assert classify_stats['stdev'] < classify_stats['mean'] * 0.5, \ + "Classification performance too inconsistent" + assert retrieval_stats['stdev'] < retrieval_stats['mean'] * 0.5, \ + "Retrieval performance too inconsistent" + + +class TestPerformanceRequirementsSummary: + """Summary test validating all performance requirements together.""" + + def test_all_performance_requirements(self): + """Comprehensive test of all performance requirements.""" + inquiry = "Как открыть счет в банке для получения зарплаты?" + + print("\n" + "=" * 70) + print("PERFORMANCE REQUIREMENTS VALIDATION") + print("=" * 70) + + # Run workflow multiple times + iterations = 10 + results = { + 'classify': [], + 'retrieval': [], + 'workflow': [] + } + + for _ in range(iterations): + workflow_start = time.time() + + # Classify + classify_start = time.time() + classify_response = client.post("/api/classify", json={"inquiry": inquiry}) + classify_duration = (time.time() - classify_start) * 1000 + results['classify'].append(classify_duration) + + assert classify_response.status_code == 200 + classification = classify_response.json() + + # Retrieve + retrieval_start = time.time() + retrieval_response = client.post("/api/retrieve", json={ + "query": inquiry, + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": 5 + }) + retrieval_duration = (time.time() - retrieval_start) * 1000 + results['retrieval'].append(retrieval_duration) + + assert retrieval_response.status_code == 200 + + workflow_duration = (time.time() - workflow_start) * 1000 + results['workflow'].append(workflow_duration) + + # Print summary + print(f"\nResults ({iterations} iterations):\n") + + for operation, requirement in [ + ('classify', 2000), + ('retrieval', 1000), + ('workflow', 10000) + ]: + durations = results[operation] + max_val = max(durations) + mean_val = statistics.mean(durations) + p95_val = calculate_percentile(durations, 95) + + status = "✓ PASS" if max_val < requirement else "✗ FAIL" + + print(f"{operation.upper():12s} (requirement: <{requirement}ms)") + print(f" Max: {max_val:7.2f}ms {status}") + print(f" Mean: {mean_val:7.2f}ms") + print(f" P95: {p95_val:7.2f}ms") + print() + + # Assert requirements + assert max_val < requirement, \ + f"{operation} max {max_val:.2f}ms exceeds requirement {requirement}ms" + + print("=" * 70) + print("ALL PERFORMANCE REQUIREMENTS MET ✓") + print("=" * 70) diff --git a/backend/tests/integration/test_retrieval_api.py b/backend/tests/integration/test_retrieval_api.py new file mode 100644 index 0000000..653bce7 --- /dev/null +++ b/backend/tests/integration/test_retrieval_api.py @@ -0,0 +1,371 @@ +""" +Integration Tests for POST /api/retrieve Endpoint + +Tests the retrieval API endpoint with various inputs and validates: +- Request/response model validation +- Performance requirements (FR-010: <1s retrieval time) +- Ranking and filtering logic +- Top-k result limiting + +Constitution Compliance: +- Principle III: Data-Driven Validation (tests against real retrieval requirements) +- Principle VI: Knowledge Base Integration (validates template retrieval) +""" + +import pytest +from fastapi.testclient import TestClient +from backend.src.api.main import app +import time + +client = TestClient(app) + + +class TestRetrieveEndpoint: + """Test suite for POST /api/retrieve endpoint.""" + + def test_retrieve_valid_request(self): + """Test successful template retrieval with valid request.""" + # Arrange + request_data = { + "query": "Как открыть счет в банке?", + "category": "Счета", + "subcategory": "Открытие счета", + "classification_confidence": 0.85, + "top_k": 5 + } + + # Act + start_time = time.time() + response = client.post("/api/retrieve", json=request_data) + duration_ms = (time.time() - start_time) * 1000 + + # Assert + assert response.status_code == 200, f"Expected 200, got {response.status_code}: {response.text}" + + data = response.json() + + # Validate response structure (RetrievalResponse model) + assert "query" in data, "Response missing 'query' field" + assert "category" in data, "Response missing 'category' field" + assert "subcategory" in data, "Response missing 'subcategory' field" + assert "results" in data, "Response missing 'results' field" + assert "total_candidates" in data, "Response missing 'total_candidates' field" + assert "processing_time_ms" in data, "Response missing 'processing_time_ms' field" + assert "timestamp" in data, "Response missing 'timestamp' field" + assert "warnings" in data, "Response missing 'warnings' field" + + # Validate echoed fields + assert data["query"] == request_data["query"] + assert data["category"] == request_data["category"] + assert data["subcategory"] == request_data["subcategory"] + + # Validate results array + assert isinstance(data["results"], list), "Results must be a list" + assert len(data["results"]) <= request_data["top_k"], f"Results exceed top_k={request_data['top_k']}" + + # Validate total_candidates + assert isinstance(data["total_candidates"], int) + assert data["total_candidates"] >= 0 + + # Validate processing time + assert isinstance(data["processing_time_ms"], (int, float)) + assert data["processing_time_ms"] >= 0 + + # FR-010: Retrieval must complete in <1 second + assert duration_ms < 1000, f"Retrieval took {duration_ms:.2f}ms (expected <1000ms)" + + # Validate warnings array + assert isinstance(data["warnings"], list) + + def test_retrieve_result_structure(self): + """Test that each TemplateResult has correct structure.""" + request_data = { + "query": "Забыл пароль от приложения", + "category": "Мобильное приложение", + "subcategory": "Вход и авторизация", + "top_k": 3 + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 200 + + data = response.json() + + for i, result in enumerate(data["results"]): + # Validate required fields + assert "template_id" in result, f"Result {i} missing 'template_id'" + assert "template_question" in result, f"Result {i} missing 'template_question'" + assert "template_answer" in result, f"Result {i} missing 'template_answer'" + assert "category" in result, f"Result {i} missing 'category'" + assert "subcategory" in result, f"Result {i} missing 'subcategory'" + assert "similarity_score" in result, f"Result {i} missing 'similarity_score'" + assert "combined_score" in result, f"Result {i} missing 'combined_score'" + assert "rank" in result, f"Result {i} missing 'rank'" + + # Validate field types and constraints + assert isinstance(result["template_id"], str) + assert len(result["template_id"]) > 0 + assert isinstance(result["template_question"], str) + assert len(result["template_question"]) > 0 + assert isinstance(result["template_answer"], str) + assert len(result["template_answer"]) > 0 + + # Validate scores are in [0.0, 1.0] + assert 0.0 <= result["similarity_score"] <= 1.0, \ + f"similarity_score {result['similarity_score']} out of range" + assert 0.0 <= result["combined_score"] <= 1.0, \ + f"combined_score {result['combined_score']} out of range" + + # Validate rank + assert isinstance(result["rank"], int) + assert result["rank"] >= 1 + + def test_retrieve_ranking_order(self): + """Test that results are properly ranked (1, 2, 3, ...).""" + request_data = { + "query": "Как получить кредит?", + "category": "Кредиты", + "subcategory": "Потребительский кредит", + "top_k": 5 + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 200 + + data = response.json() + results = data["results"] + + if len(results) > 0: + # Ranks should be sequential: 1, 2, 3, ... + for i, result in enumerate(results): + expected_rank = i + 1 + assert result["rank"] == expected_rank, \ + f"Result at index {i} has rank {result['rank']}, expected {expected_rank}" + + # Combined scores should be in descending order (best first) + if len(results) > 1: + for i in range(len(results) - 1): + assert results[i]["combined_score"] >= results[i + 1]["combined_score"], \ + f"Results not sorted by combined_score descending" + + def test_retrieve_top_k_limiting(self): + """Test that top_k parameter correctly limits results.""" + for top_k in [1, 3, 5, 10]: + request_data = { + "query": "Вопрос о депозитах", + "category": "Депозиты", + "subcategory": "Открытие депозита", + "top_k": top_k + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 200 + + data = response.json() + assert len(data["results"]) <= top_k, \ + f"Results count {len(data['results'])} exceeds top_k={top_k}" + + def test_retrieve_default_top_k(self): + """Test that default top_k=5 is used when not specified.""" + request_data = { + "query": "Вопрос о картах", + "category": "Карты", + "subcategory": "Дебетовые карты" + # top_k not specified, should default to 5 + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 200 + + data = response.json() + # Should return at most 5 results (default) + assert len(data["results"]) <= 5 + + def test_retrieve_validation_missing_query(self): + """Test validation error for missing query field.""" + request_data = { + "category": "Карты", + "subcategory": "Блокировка карты" + # Missing required 'query' field + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 422 # Missing required field + + def test_retrieve_validation_missing_category(self): + """Test validation error for missing category field.""" + request_data = { + "query": "Как заблокировать карту?", + "subcategory": "Блокировка карты" + # Missing required 'category' field + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 422 + + def test_retrieve_validation_missing_subcategory(self): + """Test validation error for missing subcategory field.""" + request_data = { + "query": "Как заблокировать карту?", + "category": "Карты" + # Missing required 'subcategory' field + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 422 + + def test_retrieve_validation_invalid_top_k(self): + """Test validation error for invalid top_k values.""" + # Test top_k < 1 + request_data = { + "query": "Вопрос о кредите", + "category": "Кредиты", + "subcategory": "Ипотека", + "top_k": 0 + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 422 or response.status_code == 400 + + # Test top_k > 10 + request_data["top_k"] = 11 + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 422 or response.status_code == 400 + + def test_retrieve_validation_query_too_short(self): + """Test validation error for query that's too short.""" + request_data = { + "query": "Как", # Only 3 characters, min is 5 + "category": "Карты", + "subcategory": "Общие вопросы" + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 400 + + def test_retrieve_validation_query_too_long(self): + """Test validation error for query that's too long.""" + request_data = { + "query": "а" * 5001, # 5001 characters, max is 5000 + "category": "Карты", + "subcategory": "Общие вопросы" + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 400 or response.status_code == 422 + + def test_retrieve_validation_no_cyrillic_query(self): + """Test validation error for query without Cyrillic characters.""" + request_data = { + "query": "Hello, how are you today?", # English only + "category": "Карты", + "subcategory": "Общие вопросы" + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 400 + + def test_retrieve_performance_benchmark(self): + """Benchmark retrieval performance for FR-010 requirement.""" + request_data = { + "query": "Как узнать баланс карты?", + "category": "Карты", + "subcategory": "Проверка баланса", + "top_k": 5 + } + + durations = [] + iterations = 5 + + for _ in range(iterations): + start_time = time.time() + response = client.post("/api/retrieve", json=request_data) + duration_ms = (time.time() - start_time) * 1000 + durations.append(duration_ms) + + assert response.status_code == 200 + + avg_duration = sum(durations) / len(durations) + max_duration = max(durations) + min_duration = min(durations) + + print(f"\nRetrieval Performance ({iterations} iterations):") + print(f" Average: {avg_duration:.2f}ms") + print(f" Min: {min_duration:.2f}ms") + print(f" Max: {max_duration:.2f}ms") + + # FR-010: Retrieval must complete in <1 second + assert max_duration < 1000, f"Max duration {max_duration:.2f}ms exceeds 1000ms threshold" + + def test_retrieve_optional_classification_confidence(self): + """Test that classification_confidence is optional.""" + # Without classification_confidence + request_data = { + "query": "Вопрос о переводах", + "category": "Переводы", + "subcategory": "Внутренние переводы" + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 200 + + # With classification_confidence + request_data["classification_confidence"] = 0.92 + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 200 + + def test_retrieve_optional_use_historical_weighting(self): + """Test that use_historical_weighting is optional (MVP: not used).""" + request_data = { + "query": "Вопрос о вкладах", + "category": "Вклады", + "subcategory": "Процентные ставки", + "use_historical_weighting": False + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 200 + + # Note: In MVP, this parameter is ignored, but should not cause errors + request_data["use_historical_weighting"] = True + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 200 + + +class TestRetrieveWarnings: + """Test warning generation in retrieval responses.""" + + def test_retrieve_warns_on_low_confidence(self): + """Test that warnings are generated for low classification confidence.""" + request_data = { + "query": "Непонятный вопрос", + "category": "Общие", + "subcategory": "Прочее", + "classification_confidence": 0.3 # Low confidence + } + + response = client.post("/api/retrieve", json=request_data) + assert response.status_code == 200 + + data = response.json() + # Implementation may add warning about low confidence + # This is implementation-specific, so we just check warnings field exists + assert isinstance(data["warnings"], list) + + def test_retrieve_empty_results_warning(self): + """Test behavior when no templates found in category.""" + # Using a potentially non-existent category + request_data = { + "query": "Вопрос о чём-то странном", + "category": "Несуществующая категория", + "subcategory": "Несуществующая подкатегория" + } + + response = client.post("/api/retrieve", json=request_data) + # Should still return 200, but with empty results or warning + assert response.status_code == 200 + + data = response.json() + # Either results are empty, or there's a warning + if len(data["results"]) == 0: + assert data["total_candidates"] == 0 diff --git a/backend/tests/integration/test_user_story_1_e2e.py b/backend/tests/integration/test_user_story_1_e2e.py new file mode 100644 index 0000000..038db64 --- /dev/null +++ b/backend/tests/integration/test_user_story_1_e2e.py @@ -0,0 +1,429 @@ +""" +End-to-End Tests for User Story 1: Core Operator Workflow + +User Story 1: As an operator, I need to submit a customer inquiry and receive +ranked template responses, so I can quickly respond to customer questions. + +Workflow: +1. Operator submits Russian customer inquiry +2. System classifies inquiry → category + subcategory (< 2s) +3. System retrieves top 5 relevant templates (< 1s) +4. Operator can copy template answer to clipboard +5. Total workflow completes in < 10 seconds + +Acceptance Criteria: +- AC-001: Operator can submit Russian text inquiry (5-5000 characters) +- AC-002: Classification returns category, subcategory, confidence within 2 seconds +- AC-003: System retrieves exactly 5 ranked template responses within 1 second +- AC-004: Each template includes question, answer, and similarity score +- AC-005: Templates are ranked by relevance (best first) +- AC-006: Total end-to-end workflow completes in < 10 seconds + +Constitution Compliance: +- Principle II: User-Centric Design (validates operator workflow efficiency) +- Principle III: Data-Driven Validation (validates performance requirements) +""" + +import pytest +from fastapi.testclient import TestClient +from backend.src.api.main import app +import time + +client = TestClient(app) + + +class TestUserStory1EndToEnd: + """End-to-end tests for User Story 1 complete workflow.""" + + def test_complete_workflow_success(self): + """ + Test complete User Story 1 workflow from inquiry to template retrieval. + + This test validates the entire operator workflow: + 1. Submit inquiry → classification + 2. Use classification result → retrieval + 3. Verify total time < 10s + """ + # === STEP 1: Operator submits inquiry === + inquiry = "Как заблокировать банковскую карту, если она утеряна?" + + workflow_start = time.time() + + # === STEP 2: System classifies inquiry === + classify_request = {"inquiry": inquiry} + + classify_start = time.time() + classify_response = client.post("/api/classify", json=classify_request) + classify_duration_ms = (time.time() - classify_start) * 1000 + + # Validate classification response + assert classify_response.status_code == 200, \ + f"Classification failed: {classify_response.status_code} - {classify_response.text}" + + classification_result = classify_response.json() + + # AC-002: Classification returns category, subcategory, confidence within 2s + assert "category" in classification_result + assert "subcategory" in classification_result + assert "confidence" in classification_result + assert classification_result["inquiry"] == inquiry + assert 0.0 <= classification_result["confidence"] <= 1.0 + assert classify_duration_ms < 2000, \ + f"Classification took {classify_duration_ms:.2f}ms (expected <2000ms)" + + print(f"\n✓ Classification completed in {classify_duration_ms:.2f}ms") + print(f" Category: {classification_result['category']}") + print(f" Subcategory: {classification_result['subcategory']}") + print(f" Confidence: {classification_result['confidence']:.2f}") + + # === STEP 3: System retrieves relevant templates === + retrieval_request = { + "query": inquiry, + "category": classification_result["category"], + "subcategory": classification_result["subcategory"], + "classification_confidence": classification_result["confidence"], + "top_k": 5 # AC-003: Retrieve exactly 5 templates + } + + retrieval_start = time.time() + retrieval_response = client.post("/api/retrieve", json=retrieval_request) + retrieval_duration_ms = (time.time() - retrieval_start) * 1000 + + # Validate retrieval response + assert retrieval_response.status_code == 200, \ + f"Retrieval failed: {retrieval_response.status_code} - {retrieval_response.text}" + + retrieval_result = retrieval_response.json() + + # AC-003: Retrieval completes within 1 second + assert retrieval_duration_ms < 1000, \ + f"Retrieval took {retrieval_duration_ms:.2f}ms (expected <1000ms)" + + # AC-003: System returns up to 5 ranked templates + assert "results" in retrieval_result + assert isinstance(retrieval_result["results"], list) + assert len(retrieval_result["results"]) <= 5 + + print(f"✓ Retrieval completed in {retrieval_duration_ms:.2f}ms") + print(f" Found {len(retrieval_result['results'])} templates") + + # === STEP 4: Validate template structure === + for i, template in enumerate(retrieval_result["results"]): + # AC-004: Each template includes question, answer, and similarity score + assert "template_id" in template + assert "template_question" in template + assert "template_answer" in template + assert "similarity_score" in template + assert "combined_score" in template + assert "rank" in template + + # Validate template content is not empty + assert len(template["template_question"]) > 0, f"Template {i} has empty question" + assert len(template["template_answer"]) > 0, f"Template {i} has empty answer" + + # AC-005: Templates ranked by relevance (validate rank order) + expected_rank = i + 1 + assert template["rank"] == expected_rank, \ + f"Template at index {i} has rank {template['rank']}, expected {expected_rank}" + + # Validate scores are valid + assert 0.0 <= template["similarity_score"] <= 1.0 + assert 0.0 <= template["combined_score"] <= 1.0 + + print(f" [{template['rank']}] {template['template_question'][:60]}... (score: {template['combined_score']:.2f})") + + # AC-005: Verify templates are sorted by combined_score descending + if len(retrieval_result["results"]) > 1: + for i in range(len(retrieval_result["results"]) - 1): + current_score = retrieval_result["results"][i]["combined_score"] + next_score = retrieval_result["results"][i + 1]["combined_score"] + assert current_score >= next_score, \ + f"Templates not sorted: rank {i+1} score {current_score} < rank {i+2} score {next_score}" + + # === STEP 5: Validate total workflow time === + total_duration_ms = (time.time() - workflow_start) * 1000 + + # AC-006: Total workflow completes in < 10 seconds + assert total_duration_ms < 10000, \ + f"Total workflow took {total_duration_ms:.2f}ms (expected <10000ms)" + + print(f"✓ Total workflow completed in {total_duration_ms:.2f}ms") + print(f" Classification: {classify_duration_ms:.2f}ms") + print(f" Retrieval: {retrieval_duration_ms:.2f}ms") + print(f" Total: {total_duration_ms:.2f}ms") + + # === SUCCESS === + print("\n✓ User Story 1 workflow completed successfully!") + + def test_workflow_with_various_inquiries(self): + """Test workflow with different types of customer inquiries.""" + test_inquiries = [ + "Забыл пароль от мобильного приложения, как восстановить?", + "Хочу открыть вклад на 1 год, какие условия?", + "Как получить кредит на покупку автомобиля?", + "Почему не работает интернет-банкинг?", + "Где посмотреть реквизиты моей карты?", + ] + + for inquiry in test_inquiries: + # Classify + classify_response = client.post("/api/classify", json={"inquiry": inquiry}) + assert classify_response.status_code == 200, f"Failed to classify: {inquiry}" + + classification = classify_response.json() + + # Retrieve + retrieval_request = { + "query": inquiry, + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": 5 + } + + retrieval_response = client.post("/api/retrieve", json=retrieval_request) + assert retrieval_response.status_code == 200, f"Failed to retrieve for: {inquiry}" + + retrieval = retrieval_response.json() + assert len(retrieval["results"]) <= 5 + + print(f"✓ Workflow successful for: {inquiry[:50]}...") + + def test_workflow_performance_multiple_runs(self): + """Test workflow performance consistency across multiple runs.""" + inquiry = "Как узнать баланс моей карты через мобильное приложение?" + iterations = 3 + + workflow_durations = [] + classify_durations = [] + retrieval_durations = [] + + for i in range(iterations): + workflow_start = time.time() + + # Classify + classify_start = time.time() + classify_response = client.post("/api/classify", json={"inquiry": inquiry}) + classify_duration = (time.time() - classify_start) * 1000 + classify_durations.append(classify_duration) + + assert classify_response.status_code == 200 + classification = classify_response.json() + + # Retrieve + retrieval_start = time.time() + retrieval_response = client.post("/api/retrieve", json={ + "query": inquiry, + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": 5 + }) + retrieval_duration = (time.time() - retrieval_start) * 1000 + retrieval_durations.append(retrieval_duration) + + assert retrieval_response.status_code == 200 + + workflow_duration = (time.time() - workflow_start) * 1000 + workflow_durations.append(workflow_duration) + + print(f"\nRun {i+1}: Total {workflow_duration:.2f}ms (classify: {classify_duration:.2f}ms, retrieve: {retrieval_duration:.2f}ms)") + + # Validate all runs meet performance requirements + assert all(d < 2000 for d in classify_durations), \ + f"Some classification runs exceeded 2s: {classify_durations}" + assert all(d < 1000 for d in retrieval_durations), \ + f"Some retrieval runs exceeded 1s: {retrieval_durations}" + assert all(d < 10000 for d in workflow_durations), \ + f"Some workflows exceeded 10s: {workflow_durations}" + + avg_workflow = sum(workflow_durations) / len(workflow_durations) + print(f"\n✓ Average workflow time: {avg_workflow:.2f}ms ({iterations} runs)") + + def test_workflow_with_low_confidence_classification(self): + """Test workflow behavior when classification confidence is low.""" + # Intentionally ambiguous inquiry + inquiry = "Помогите пожалуйста с проблемой" + + # Classify + classify_response = client.post("/api/classify", json={"inquiry": inquiry}) + assert classify_response.status_code == 200 + + classification = classify_response.json() + + # Even with low confidence, workflow should complete + retrieval_response = client.post("/api/retrieve", json={ + "query": inquiry, + "category": classification["category"], + "subcategory": classification["subcategory"], + "classification_confidence": classification["confidence"], + "top_k": 5 + }) + + assert retrieval_response.status_code == 200 + retrieval = retrieval_response.json() + + # May have warning about low confidence + if classification["confidence"] < 0.5: + # Low confidence is acceptable, but workflow should still work + print(f"Low confidence: {classification['confidence']:.2f}") + print(f"Warnings: {retrieval.get('warnings', [])}") + + def test_workflow_error_handling(self): + """Test workflow error handling for invalid inputs.""" + # Invalid inquiry (too short) + classify_response = client.post("/api/classify", json={"inquiry": "Hi"}) + assert classify_response.status_code == 400 # Validation error + + error_data = classify_response.json() + assert "error" in error_data + assert error_data["error_type"] == "validation" + + # Invalid retrieval (missing category) + retrieval_response = client.post("/api/retrieve", json={ + "query": "Как открыть счет?", + "subcategory": "Открытие счета" + # Missing category + }) + assert retrieval_response.status_code == 422 # Missing required field + + +class TestUserStory1AcceptanceCriteria: + """Test each acceptance criterion individually.""" + + def test_ac_001_russian_text_inquiry(self): + """AC-001: Operator can submit Russian text inquiry (5-5000 characters).""" + # Valid Russian inquiry + inquiry = "Как заблокировать карту?" + response = client.post("/api/classify", json={"inquiry": inquiry}) + assert response.status_code == 200 + + # Too short (< 5 characters) + response = client.post("/api/classify", json={"inquiry": "Как"}) + assert response.status_code == 400 + + # Too long (> 5000 characters) + response = client.post("/api/classify", json={"inquiry": "а" * 5001}) + assert response.status_code == 400 + + # Not Russian (no Cyrillic) + response = client.post("/api/classify", json={"inquiry": "Hello world"}) + assert response.status_code == 400 + + def test_ac_002_classification_within_2_seconds(self): + """AC-002: Classification returns category, subcategory, confidence within 2 seconds.""" + inquiry = "Как открыть депозит в банке?" + + start_time = time.time() + response = client.post("/api/classify", json={"inquiry": inquiry}) + duration_ms = (time.time() - start_time) * 1000 + + assert response.status_code == 200 + data = response.json() + + assert "category" in data + assert "subcategory" in data + assert "confidence" in data + assert duration_ms < 2000 + + def test_ac_003_retrieve_5_templates_within_1_second(self): + """AC-003: System retrieves exactly 5 ranked template responses within 1 second.""" + # First classify to get category/subcategory + classify_response = client.post("/api/classify", json={ + "inquiry": "Как перевести деньги на другой счет?" + }) + assert classify_response.status_code == 200 + classification = classify_response.json() + + # Then retrieve + start_time = time.time() + retrieval_response = client.post("/api/retrieve", json={ + "query": "Как перевести деньги на другой счет?", + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": 5 + }) + duration_ms = (time.time() - start_time) * 1000 + + assert retrieval_response.status_code == 200 + data = retrieval_response.json() + + # Should return up to 5 results + assert len(data["results"]) <= 5 + # Performance: < 1 second + assert duration_ms < 1000 + + def test_ac_004_template_structure(self): + """AC-004: Each template includes question, answer, and similarity score.""" + # Classify then retrieve + classify_response = client.post("/api/classify", json={ + "inquiry": "Вопрос о кредитах" + }) + classification = classify_response.json() + + retrieval_response = client.post("/api/retrieve", json={ + "query": "Вопрос о кредитах", + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": 5 + }) + + data = retrieval_response.json() + + for template in data["results"]: + assert "template_question" in template + assert "template_answer" in template + assert "similarity_score" in template + assert len(template["template_question"]) > 0 + assert len(template["template_answer"]) > 0 + assert 0.0 <= template["similarity_score"] <= 1.0 + + def test_ac_005_templates_ranked_by_relevance(self): + """AC-005: Templates are ranked by relevance (best first).""" + # Classify then retrieve + classify_response = client.post("/api/classify", json={ + "inquiry": "Как получить выписку по счету?" + }) + classification = classify_response.json() + + retrieval_response = client.post("/api/retrieve", json={ + "query": "Как получить выписку по счету?", + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": 5 + }) + + data = retrieval_response.json() + results = data["results"] + + # Verify ranks are sequential: 1, 2, 3, 4, 5 + for i, template in enumerate(results): + assert template["rank"] == i + 1 + + # Verify sorted by combined_score descending + if len(results) > 1: + for i in range(len(results) - 1): + assert results[i]["combined_score"] >= results[i + 1]["combined_score"] + + def test_ac_006_total_workflow_under_10_seconds(self): + """AC-006: Total end-to-end workflow completes in < 10 seconds.""" + inquiry = "Как активировать новую карту?" + + start_time = time.time() + + # Classify + classify_response = client.post("/api/classify", json={"inquiry": inquiry}) + assert classify_response.status_code == 200 + classification = classify_response.json() + + # Retrieve + retrieval_response = client.post("/api/retrieve", json={ + "query": inquiry, + "category": classification["category"], + "subcategory": classification["subcategory"], + "top_k": 5 + }) + assert retrieval_response.status_code == 200 + + total_duration_ms = (time.time() - start_time) * 1000 + + # Must complete in < 10 seconds + assert total_duration_ms < 10000 diff --git a/backend/tests/unit/__init__.py b/backend/tests/unit/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/frontend/.gitignore b/frontend/.gitignore new file mode 100644 index 0000000..a547bf3 --- /dev/null +++ b/frontend/.gitignore @@ -0,0 +1,24 @@ +# Logs +logs +*.log +npm-debug.log* +yarn-debug.log* +yarn-error.log* +pnpm-debug.log* +lerna-debug.log* + +node_modules +dist +dist-ssr +*.local + +# Editor directories and files +.vscode/* +!.vscode/extensions.json +.idea +.DS_Store +*.suo +*.ntvs* +*.njsproj +*.sln +*.sw? diff --git a/frontend/README.md b/frontend/README.md new file mode 100644 index 0000000..d2e7761 --- /dev/null +++ b/frontend/README.md @@ -0,0 +1,73 @@ +# React + TypeScript + Vite + +This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules. + +Currently, two official plugins are available: + +- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react) uses [Babel](https://babeljs.io/) (or [oxc](https://oxc.rs) when used in [rolldown-vite](https://vite.dev/guide/rolldown)) for Fast Refresh +- [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react-swc) uses [SWC](https://swc.rs/) for Fast Refresh + +## React Compiler + +The React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see [this documentation](https://react.dev/learn/react-compiler/installation). + +## Expanding the ESLint configuration + +If you are developing a production application, we recommend updating the configuration to enable type-aware lint rules: + +```js +export default defineConfig([ + globalIgnores(['dist']), + { + files: ['**/*.{ts,tsx}'], + extends: [ + // Other configs... + + // Remove tseslint.configs.recommended and replace with this + tseslint.configs.recommendedTypeChecked, + // Alternatively, use this for stricter rules + tseslint.configs.strictTypeChecked, + // Optionally, add this for stylistic rules + tseslint.configs.stylisticTypeChecked, + + // Other configs... + ], + languageOptions: { + parserOptions: { + project: ['./tsconfig.node.json', './tsconfig.app.json'], + tsconfigRootDir: import.meta.dirname, + }, + // other options... + }, + }, +]) +``` + +You can also install [eslint-plugin-react-x](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-x) and [eslint-plugin-react-dom](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-dom) for React-specific lint rules: + +```js +// eslint.config.js +import reactX from 'eslint-plugin-react-x' +import reactDom from 'eslint-plugin-react-dom' + +export default defineConfig([ + globalIgnores(['dist']), + { + files: ['**/*.{ts,tsx}'], + extends: [ + // Other configs... + // Enable lint rules for React + reactX.configs['recommended-typescript'], + // Enable lint rules for React DOM + reactDom.configs.recommended, + ], + languageOptions: { + parserOptions: { + project: ['./tsconfig.node.json', './tsconfig.app.json'], + tsconfigRootDir: import.meta.dirname, + }, + // other options... + }, + }, +]) +``` diff --git a/frontend/eslint.config.js b/frontend/eslint.config.js new file mode 100644 index 0000000..b19330b --- /dev/null +++ b/frontend/eslint.config.js @@ -0,0 +1,23 @@ +import js from '@eslint/js' +import globals from 'globals' +import reactHooks from 'eslint-plugin-react-hooks' +import reactRefresh from 'eslint-plugin-react-refresh' +import tseslint from 'typescript-eslint' +import { defineConfig, globalIgnores } from 'eslint/config' + +export default defineConfig([ + globalIgnores(['dist']), + { + files: ['**/*.{ts,tsx}'], + extends: [ + js.configs.recommended, + tseslint.configs.recommended, + reactHooks.configs['recommended-latest'], + reactRefresh.configs.vite, + ], + languageOptions: { + ecmaVersion: 2020, + globals: globals.browser, + }, + }, +]) diff --git a/frontend/index.html b/frontend/index.html new file mode 100644 index 0000000..072a57e --- /dev/null +++ b/frontend/index.html @@ -0,0 +1,13 @@ + + + + + + + frontend + + +
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+ "tailwindcss": "^3.4.18", + "typescript": "~5.9.3", + "typescript-eslint": "^8.45.0", + "vite": "^7.1.7" + } +} diff --git a/frontend/postcss.config.js b/frontend/postcss.config.js new file mode 100644 index 0000000..2e7af2b --- /dev/null +++ b/frontend/postcss.config.js @@ -0,0 +1,6 @@ +export default { + plugins: { + tailwindcss: {}, + autoprefixer: {}, + }, +} diff --git a/frontend/public/vite.svg b/frontend/public/vite.svg new file mode 100644 index 0000000..e7b8dfb --- /dev/null +++ b/frontend/public/vite.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/frontend/src/App.css b/frontend/src/App.css new file mode 100644 index 0000000..b9d355d --- /dev/null +++ b/frontend/src/App.css @@ -0,0 +1,42 @@ +#root { + max-width: 1280px; + margin: 0 auto; + padding: 2rem; + text-align: center; +} + +.logo { + height: 6em; + padding: 1.5em; + will-change: filter; + transition: filter 300ms; +} +.logo:hover { + filter: drop-shadow(0 0 2em #646cffaa); +} +.logo.react:hover { + filter: drop-shadow(0 0 2em #61dafbaa); +} + +@keyframes logo-spin { + from { + transform: rotate(0deg); + } + to { + transform: rotate(360deg); + } +} + +@media (prefers-reduced-motion: no-preference) { + a:nth-of-type(2) .logo { + animation: logo-spin infinite 20s linear; + } +} + +.card { + padding: 2em; +} + +.read-the-docs { + color: #888; +} diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx new file mode 100644 index 0000000..e9fba69 --- /dev/null +++ b/frontend/src/App.tsx @@ -0,0 +1,230 @@ +/** + * Smart Support Operator Interface - Main App + * + * Complete operator workflow: + * 1. Operator submits customer inquiry + * 2. System classifies inquiry → category + subcategory + * 3. System retrieves top 5 relevant templates + * 4. Operator can copy template answer to clipboard + * + * Performance requirements: + * - Classification: <2s (FR-005) + * - Retrieval: <1s (FR-010) + * - Total workflow: <10s (FR-015) + */ + +import { useState } from 'react'; +import { InquiryInput } from './components/InquiryInput'; +import { ClassificationDisplay } from './components/ClassificationDisplay'; +import { TemplateList } from './components/TemplateList'; +import { ErrorDisplay } from './components/ErrorDisplay'; +import { useClassify } from './hooks/useClassify'; +import { useRetrieve } from './hooks/useRetrieve'; +import { useHealth } from './hooks/useHealth'; +import type { ClassificationResult, ErrorResponse } from './types/classification'; +import type { RetrievalResponse } from './types/retrieval'; + +function App() { + // State + const [classificationResult, setClassificationResult] = useState(null); + const [retrievalResponse, setRetrievalResponse] = useState(null); + const [currentError, setCurrentError] = useState(null); + + // React Query hooks + const classifyMutation = useClassify(); + const retrieveMutation = useRetrieve(); + const { data: healthData } = useHealth({ refetchInterval: 30000 }); // Poll every 30s + + // Handle inquiry submission + const handleInquirySubmit = async (inquiry: string) => { + // Reset previous results and errors + setClassificationResult(null); + setRetrievalResponse(null); + setCurrentError(null); + + try { + // Step 1: Classify inquiry + const classificationData = await classifyMutation.mutateAsync(inquiry); + setClassificationResult(classificationData); + + // Step 2: Retrieve templates + const retrievalData = await retrieveMutation.mutateAsync({ + query: inquiry, + category: classificationData.category, + subcategory: classificationData.subcategory, + classification_confidence: classificationData.confidence, + top_k: 5, + }); + setRetrievalResponse(retrievalData); + } catch (error) { + // Error is already transformed by Axios interceptor to ErrorResponse + setCurrentError(error as ErrorResponse); + } + }; + + // Handle retry + const handleRetry = () => { + setCurrentError(null); + // Trigger re-submission if there was a classification result + if (classificationResult) { + handleInquirySubmit(classificationResult.inquiry); + } + }; + + // Determine loading states + const isClassifying = classifyMutation.isPending; + const isRetrieving = retrieveMutation.isPending; + const isProcessing = isClassifying || isRetrieving; + + // Check health status + const isHealthy = healthData?.status === 'healthy'; + const isRetrievalAvailable = healthData?.retrieval_available ?? false; + + return ( +
+ {/* Header */} +
+
+
+
+

+ Smart Support +

+

+ Интеллектуальная система поддержки операторов +

+
+ + {/* Health indicator */} + {healthData && ( +
+
+ + {isHealthy ? 'Система работает' : 'Ограниченная функциональность'} + +
+ )} +
+
+
+ + {/* Main content */} +
+
+ {/* Left column: Input and Classification */} +
+ {/* Service status warning */} + {healthData && !isRetrievalAvailable && ( +
+
+ + + +
+

Сервис поиска шаблонов недоступен

+

Классификация работает, но поиск шаблонов временно недоступен. Загружено шаблонов: {healthData.embeddings_count}

+
+
+
+ )} + + {/* Inquiry input */} +
+ +
+ + {/* Classification result */} + {classificationResult && !isClassifying && ( + + )} + + {/* Loading indicator for classification */} + {isClassifying && ( +
+ + + + +

Классификация обращения...

+
+ )} + + {/* Error display */} + {currentError && ( + setCurrentError(null)} + /> + )} +
+ + {/* Right column: Template results */} +
+
+ +
+
+
+ + {/* Performance metrics (development only) */} + {import.meta.env.DEV && (classificationResult || retrievalResponse) && ( +
+
Performance Metrics:
+
+ {classificationResult && ( +
+
Classification:
+
+ {classificationResult.processing_time_ms}ms + {classificationResult.processing_time_ms < 2000 ? ' ✓' : ' ✗ (>2s)'} +
+
+ )} + {retrievalResponse && ( +
+
Retrieval:
+
+ {retrievalResponse.processing_time_ms.toFixed(0)}ms + {retrievalResponse.processing_time_ms < 1000 ? ' ✓' : ' ✗ (>1s)'} +
+
+ )} + {classificationResult && retrievalResponse && ( +
+
Total:
+
+ {(classificationResult.processing_time_ms + retrievalResponse.processing_time_ms).toFixed(0)}ms + {(classificationResult.processing_time_ms + retrievalResponse.processing_time_ms) < 10000 ? ' ✓' : ' ✗ (>10s)'} +
+
+ )} +
+
+ )} +
+ + {/* Footer */} +
+
+

+ Smart Support © 2025 | Minsk Hackathon | Powered by Scibox AI +

+
+
+
+ ); +} + +export default App; diff --git a/frontend/src/assets/react.svg b/frontend/src/assets/react.svg new file mode 100644 index 0000000..6c87de9 --- /dev/null +++ b/frontend/src/assets/react.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/frontend/src/components/ClassificationDisplay.tsx b/frontend/src/components/ClassificationDisplay.tsx new file mode 100644 index 0000000..a01371d --- /dev/null +++ b/frontend/src/components/ClassificationDisplay.tsx @@ -0,0 +1,130 @@ +/** + * ClassificationDisplay Component + * + * Displays classification results with category, subcategory, and confidence. + * + * Features: + * - Visual confidence indicator (color-coded) + * - Processing time display + * - Expandable inquiry text + * - Clean, professional design + */ + +import type { ClassificationResult } from '../types/classification'; + +interface ClassificationDisplayProps { + /** Classification result to display */ + result: ClassificationResult; +} + +export function ClassificationDisplay({ result }: ClassificationDisplayProps) { + // Determine confidence level and color + const getConfidenceLevel = (confidence: number): { label: string; color: string; bgColor: string } => { + if (confidence >= 0.8) { + return { label: 'Высокая', color: 'text-green-700', bgColor: 'bg-green-100' }; + } else if (confidence >= 0.5) { + return { label: 'Средняя', color: 'text-yellow-700', bgColor: 'bg-yellow-100' }; + } else { + return { label: 'Низкая', color: 'text-red-700', bgColor: 'bg-red-100' }; + } + }; + + const confidenceInfo = getConfidenceLevel(result.confidence); + const confidencePercent = Math.round(result.confidence * 100); + + return ( +
+ {/* Header */} +
+

+ Результат классификации +

+ + {result.processing_time_ms}мс + +
+ + {/* Inquiry (truncated) */} +
+

+ {result.inquiry} +

+
+ + {/* Classification results */} +
+ {/* Category */} +
+ +
+

+ {result.category} +

+
+
+ + {/* Subcategory */} +
+ +
+

+ {result.subcategory} +

+
+
+
+ + {/* Confidence indicator */} +
+
+ + + {confidenceInfo.label} ({confidencePercent}%) + +
+ + {/* Progress bar */} +
+
= 0.8 + ? 'bg-green-600' + : result.confidence >= 0.5 + ? 'bg-yellow-500' + : 'bg-red-500' + }`} + style={{ width: `${confidencePercent}%` }} + /> +
+ + {/* Confidence badge */} +
+ + {confidencePercent}% уверенность + + {result.confidence < 0.5 && ( + + ⚠️ Рекомендуется проверка оператором + + )} +
+
+ + {/* Status indicator */} +
+
+ + + + Классификация выполнена успешно +
+
+
+ ); +} diff --git a/frontend/src/components/ErrorDisplay.tsx b/frontend/src/components/ErrorDisplay.tsx new file mode 100644 index 0000000..348bf62 --- /dev/null +++ b/frontend/src/components/ErrorDisplay.tsx @@ -0,0 +1,161 @@ +/** + * ErrorDisplay Component + * + * User-friendly error message display with retry functionality. + * + * Features: + * - Different error types with appropriate icons + * - Retry button for recoverable errors + * - Dismissible + * - Accessible design + */ + +import type { ErrorResponse } from '../types/classification'; + +interface ErrorDisplayProps { + /** Error to display */ + error: ErrorResponse; + /** Optional retry callback */ + onRetry?: () => void; + /** Optional dismiss callback */ + onDismiss?: () => void; +} + +export function ErrorDisplay({ error, onRetry, onDismiss }: ErrorDisplayProps) { + // Get icon and colors based on error type + const getErrorStyle = (errorType: string) => { + switch (errorType) { + case 'validation': + return { + icon: ( + + + + ), + bgColor: 'bg-yellow-50', + borderColor: 'border-yellow-300', + iconColor: 'text-yellow-600', + textColor: 'text-yellow-800', + title: 'Ошибка валидации', + }; + case 'timeout': + return { + icon: ( + + + + ), + bgColor: 'bg-orange-50', + borderColor: 'border-orange-300', + iconColor: 'text-orange-600', + textColor: 'text-orange-800', + title: 'Превышено время ожидания', + }; + case 'api_error': + return { + icon: ( + + + + ), + bgColor: 'bg-red-50', + borderColor: 'border-red-300', + iconColor: 'text-red-600', + textColor: 'text-red-800', + title: 'Ошибка сервиса', + }; + default: + return { + icon: ( + + + + ), + bgColor: 'bg-red-50', + borderColor: 'border-red-300', + iconColor: 'text-red-600', + textColor: 'text-red-800', + title: 'Произошла ошибка', + }; + } + }; + + const style = getErrorStyle(error.error_type); + const canRetry = error.error_type === 'timeout' || error.error_type === 'api_error'; + + return ( +
+
+ {/* Icon */} +
+ {style.icon} +
+ + {/* Content */} +
+

+ {style.title} +

+

+ {error.error} +

+ + {/* Technical details (collapsible) */} + {error.details && ( +
+ + Технические детали + + 
+                {error.details}
+
+
+ )} + + {/* Actions */} +
+ {/* Retry button */} + {canRetry && onRetry && ( + + )} + + {/* Dismiss button */} + {onDismiss && ( + + )} +
+
+ + {/* Close button */} + {onDismiss && ( + + )} +
+
+ ); +} diff --git a/frontend/src/components/InquiryInput.tsx b/frontend/src/components/InquiryInput.tsx new file mode 100644 index 0000000..fbdfc0d --- /dev/null +++ b/frontend/src/components/InquiryInput.tsx @@ -0,0 +1,155 @@ +/** + * InquiryInput Component + * + * Text input area for customer inquiry submission. + * Validates Russian text (Cyrillic required, 5-5000 characters). + * + * Features: + * - Multi-line textarea with character counter + * - Real-time validation feedback + * - Submit button with loading state + * - User-friendly error messages + */ + +import { useState } from 'react'; +import { validateInquiry } from '../types/classification'; + +interface InquiryInputProps { + /** Callback when valid inquiry is submitted */ + onSubmit: (inquiry: string) => void; + /** Whether classification is in progress */ + isLoading?: boolean; + /** Disabled state (e.g., when retrieval is running) */ + disabled?: boolean; +} + +export function InquiryInput({ onSubmit, isLoading = false, disabled = false }: InquiryInputProps) { + const [inquiry, setInquiry] = useState(''); + const [error, setError] = useState(null); + const [touched, setTouched] = useState(false); + + const handleSubmit = (e: React.FormEvent) => { + e.preventDefault(); + + // Validate inquiry + const validationError = validateInquiry(inquiry); + + if (validationError) { + setError(validationError); + setTouched(true); + return; + } + + // Clear error and submit + setError(null); + onSubmit(inquiry.trim()); + }; + + const handleChange = (e: React.ChangeEvent) => { + const value = e.target.value; + setInquiry(value); + + // Clear error when user starts typing + if (error && touched) { + setError(null); + } + }; + + const handleBlur = () => { + setTouched(true); + + // Validate on blur if there's text + if (inquiry.trim().length > 0) { + const validationError = validateInquiry(inquiry); + setError(validationError); + } + }; + + const characterCount = inquiry.length; + const isOverLimit = characterCount > 5000; + const isUnderLimit = characterCount > 0 && characterCount < 5; + const showError = touched && error; + + return ( +
+
+ {/* Label */} + + + {/* Textarea */} +
+