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Text Processing API Router
Provides endpoints for multilingual text processing with support for Urdu and Roman Urdu
"""
from fastapi import APIRouter, HTTPException, Request
from pydantic import BaseModel
from typing import Optional, Dict, Any
import logging
from src.text_processor.language_config import get_all_languages
from src.text_processor.models import TextProcessRequest, TextProcessResponse
from src.text_processor.translator import TextTranslator
from src.text_processor.clarifier import TextClarifier
from src.text_processor.rag_client import RAGClient
from src.config.translations import get_translation, is_rtl_language, get_supported_languages as get_translation_supported_languages
router = APIRouter(prefix="/text", tags=["text-processing"])
logger = logging.getLogger(__name__)
class MultilingualTextRequest(BaseModel):
"""Request model for multilingual text processing."""
text: str
target_language: str = "en"
source_language: Optional[str] = None
use_rag: bool = False
operation: str = "translate" # translate, clarify, both
class MultilingualTextResponse(BaseModel):
"""Response model for multilingual text processing."""
original_text: str
processed_text: str
source_language: str
target_language: str
is_rtl: bool
operation: str
confidence: Optional[float] = None
metadata: Optional[Dict[str, Any]] = None
@router.post("/process", response_model=MultilingualTextResponse)
async def process_multilingual_text(request: MultilingualTextRequest) -> MultilingualTextResponse:
"""
Process text with multilingual support for Urdu and Roman Urdu.
Args:
request: Text processing request with language specifications
Returns:
Processed text with language metadata
"""
try:
# Validate language codes against supported languages
supported_langs = get_translation_supported_languages()
if request.target_language not in supported_langs:
raise HTTPException(
status_code=400,
detail=f"Language '{request.target_language}' is not supported. Supported languages: {list(supported_langs.keys())}"
)
# Determine operation
if request.operation not in ["translate", "clarify", "both"]:
raise HTTPException(
status_code=400,
detail="Operation must be 'translate', 'clarify', or 'both'"
)
# Initialize components
translator = TextTranslator()
clarifier = TextClarifier()
processed_text = request.text
source_lang = request.source_language or "auto" # In a real implementation, we'd detect the source language
if request.operation in ["clarify", "both"]:
processed_text = await clarifier.clarify(processed_text)
if request.operation in ["translate", "both"] and request.target_language != "en":
processed_text = await translator.translate(processed_text, request.target_language)
# Determine if target language is right-to-left
is_rtl = is_rtl_language(request.target_language)
response = MultilingualTextResponse(
original_text=request.text,
processed_text=processed_text,
source_language=source_lang,
target_language=request.target_language,
is_rtl=is_rtl,
operation=request.operation,
confidence=0.95, # Placeholder confidence score
metadata={
"character_count_original": len(request.text),
"character_count_processed": len(processed_text),
"word_count_original": len(request.text.split()),
"word_count_processed": len(processed_text.split()),
}
)
logger.info(f"Processed text in {request.target_language}: {len(request.text)} -> {len(processed_text)} chars")
return response
except HTTPException:
# Re-raise HTTP exceptions as-is
raise
except Exception as e:
logger.error(f"Text processing failed: {str(e)}")
raise HTTPException(
status_code=500,
detail=f"Text processing failed: {str(e)}"
)
@router.post("/translate", response_model=MultilingualTextResponse)
async def translate_text_endpoint(request: MultilingualTextRequest) -> MultilingualTextResponse:
"""
Translate text to target language with special support for Urdu and Roman Urdu.
Args:
request: Translation request with text and target language
Returns:
Translated text with language metadata
"""
try:
# Override operation to translate
request.operation = "translate"
# Validate language codes against supported languages
supported_langs = get_translation_supported_languages()
if request.target_language not in supported_langs:
raise HTTPException(
status_code=400,
detail=f"Language '{request.target_language}' is not supported. Supported languages: {list(supported_langs.keys())}"
)
translator = TextTranslator()
translated_text = await translator.translate(request.text, request.target_language)
# Determine if target language is right-to-left
is_rtl = is_rtl_language(request.target_language)
response = MultilingualTextResponse(
original_text=request.text,
processed_text=translated_text,
source_language=request.source_language or "auto",
target_language=request.target_language,
is_rtl=is_rtl,
operation="translate",
confidence=0.90, # Placeholder confidence score
metadata={
"character_count_original": len(request.text),
"character_count_translated": len(translated_text),
"word_count_original": len(request.text.split()),
"word_count_translated": len(translated_text.split()),
}
)
logger.info(f"Translated text to {request.target_language}: {len(request.text)} -> {len(translated_text)} chars")
return response
except HTTPException:
# Re-raise HTTP exceptions as-is
raise
except Exception as e:
logger.error(f"Translation failed: {str(e)}")
raise HTTPException(
status_code=500,
detail=f"Translation failed: {str(e)}"
)
@router.post("/clarify", response_model=MultilingualTextResponse)
async def clarify_text_endpoint(request: MultilingualTextRequest) -> MultilingualTextResponse:
"""
Clarify text to make it clearer and more concise, preserving the original language.
Args:
request: Clarification request with text
Returns:
Clarified text with metadata
"""
try:
# Override operation to clarify
request.operation = "clarify"
# Validate language codes if provided
if request.source_language:
supported_langs = get_translation_supported_languages()
if request.source_language not in supported_langs:
raise HTTPException(
status_code=400,
detail=f"Language '{request.source_language}' is not supported. Supported languages: {list(supported_langs.keys())}"
)
clarifier = TextClarifier()
clarified_text = await clarifier.clarify(request.text)
# Determine source language (this would normally be detected)
source_lang = request.source_language or "auto"
# Determine if source language is right-to-left
is_rtl = is_rtl_language(source_lang) if source_lang != "auto" else False
response = MultilingualTextResponse(
original_text=request.text,
processed_text=clarified_text,
source_language=source_lang,
target_language=source_lang,
is_rtl=is_rtl,
operation="clarify",
confidence=0.85, # Placeholder confidence score
metadata={
"character_count_original": len(request.text),
"character_count_clarified": len(clarified_text),
"word_count_original": len(request.text.split()),
"word_count_clarified": len(clarified_text.split()),
}
)
logger.info(f"Clarified text: {len(request.text)} -> {len(clarified_text)} chars")
return response
except HTTPException:
# Re-raise HTTP exceptions as-is
raise
except Exception as e:
logger.error(f"Clarification failed: {str(e)}")
raise HTTPException(
status_code=500,
detail=f"Clarification failed: {str(e)}"
)
@router.get("/languages")
async def get_supported_languages() -> Dict[str, Any]:
"""
Get list of all supported languages with their details.
Returns:
Dictionary of supported languages
"""
try:
# Get languages from the text processor config
languages = get_all_languages()
# Also get languages from translation config for completeness
translation_langs = get_translation_supported_languages()
# Format response
formatted_languages = []
for lang in languages:
formatted_languages.append({
"code": lang.code,
"name": lang.name,
"native_name": lang.native_name,
"is_rtl": is_rtl_language(lang.code),
"has_translations": lang.code in translation_langs
})
return {
"languages": formatted_languages,
"total_count": len(formatted_languages),
"rtl_languages": [lang["code"] for lang in formatted_languages if lang["is_rtl"]],
"l2r_languages": [lang["code"] for lang in formatted_languages if not lang["is_rtl"]],
"translation_support": {
"available_count": len(translation_langs),
"supported_codes": list(translation_langs.keys())
}
}
except Exception as e:
logger.error(f"Getting languages failed: {str(e)}")
raise HTTPException(
status_code=500,
detail=f"Failed to get supported languages: {str(e)}"
)
@router.get("/health")
async def text_processing_health():
"""
Health check for the text processing service.
Returns:
Health status of the text processing service
"""
supported_langs = get_translation_supported_languages()
return {
"status": "healthy",
"service": "text-processing",
"features": {
"multilingual_support": True,
"urdu_support": "ur" in supported_langs,
"roman_urdu_support": "ur-PK" in supported_langs,
"right_to_left_layout": True,
"translation": True,
"clarification": True,
"rag_integration": True,
"supported_languages_count": len(supported_langs),
"languages": list(supported_langs.keys())
}
}
@router.post("/detect-language")
async def detect_language_post(text: str) -> Dict[str, str]:
"""
Detect the language of the provided text (simplified detection).
Args:
text: Text to detect language for
Returns:
Detected language code and name
"""
# This is a simplified language detection based on character sets
# In a real implementation, we would use a more sophisticated approach
arabic_chars = sum(1 for c in text if '\u0600' <= c <= '\u06FF')
latin_chars = sum(1 for c in text if '\u0041' <= c <= '\u007A' or '\u00C0' <= c <= '\u00FF')
if arabic_chars > latin_chars:
detected_lang = "ur" # Urdu/Arabic script
elif text.encode('utf-8', errors='ignore').lower().startswith(('a', 'e', 'i', 'o', 'u')):
detected_lang = "en" # Simplified English detection
else:
detected_lang = "en" # Default to English
supported_langs = get_translation_supported_languages()
if detected_lang not in supported_langs:
detected_lang = "en" # Fall back to English if detected language not supported
return {
"detected_language": detected_lang,
"language_name": get_translation(detected_lang, "language", detected_lang),
"script_type": "RTL" if is_rtl_language(detected_lang) else "LTR",
"is_supported": detected_lang in supported_langs
}
# Add GET version for consistency
@router.get("/detect-language")
async def detect_language_get(request: Request) -> Dict[str, str]:
"""
Detect the language from the request context.
Args:
request: FastAPI request object
Returns:
Detected language code and name
"""
from .translation_middleware import get_request_language
detected_lang = get_request_language(request)
supported_langs = get_translation_supported_languages()
return {
"detected_language": detected_lang,
"language_name": get_translation(detected_lang, "language", detected_lang) if detected_lang in supported_langs else "Unknown",
"script_type": "RTL" if is_rtl_language(detected_lang) else "LTR",
"is_supported": detected_lang in supported_langs
} |