Spaces:
Runtime error
Runtime error
| # indictrans2-3 | |
| # --- 1. CLEAN UP AND CLONE THE REPOSITORY --- | |
| print("Cleaning up old directories and cloning the repository...") | |
| print("✅ Repository cloned successfully.") | |
| # --- 2. INSTALL CORE LIBRARIES --- | |
| print("Installing core libraries...") | |
| print("✅ Core libraries installed.") | |
| # --- 3. SET UP THE SYSTEM PATH (THE OFFICIAL METHOD) --- | |
| # This is the crucial step from the official notebook. | |
| # It tells Python where to find the IndicTransToolkit module without installation. | |
| import sys | |
| sys.path.insert(0, '/content/IndicTrans2/src') | |
| print("✅ System path configured for IndicTransToolkit.") | |
| # --- 4. IMPORT ALL PACKAGES --- | |
| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| from IndicTransToolkit.processor import IndicProcessor | |
| import torch | |
| print("✅ All packages imported successfully.") | |
| # --- 5. LOAD THE MODEL, TOKENIZER, AND PROCESSOR --- | |
| model_name = "ai4bharat/indictrans2-indic-en-dist-200M" # Using the CPU-friendly model | |
| print("Loading the model and other components...") | |
| device = torch.device("cpu") | |
| tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) | |
| model = AutoModelForSeq2SeqLM.from_pretrained(model_name, trust_remote_code=True).to(device) | |
| ip = IndicProcessor(inference=True) | |
| print("✅ Model, Tokenizer, and IndicProcessor are ready!") | |
| # --- 6. DEFINE THE TRANSLATION FUNCTION (Using the correct workflow) --- | |
| SUPPORTED_LANGUAGES = { | |
| "Hindi": "hin_Deva", "Bengali": "ben_Beng", "Tamil": "tam_Taml", | |
| "Telugu": "tel_Telu", "Kannada": "kan_Knda", "Malayalam": "mal_Mlym", | |
| "Gujarati": "guj_Gujr", "Punjabi": "pan_Guru", "Marathi": "mar_Deva", | |
| "Urdu": "urd_Arab", "Assamese": "asm_Beng", "Oriya": "ory_Orya", | |
| "Nepali": "npi_Deva" | |
| } | |
| def translate_correctly(native_text, source_language_name): | |
| try: | |
| if not native_text or not native_text.strip(): | |
| return "Please enter text to translate." | |
| src_lang = SUPPORTED_LANGUAGES[source_language_name] | |
| tgt_lang = "eng_Latn" | |
| # 1. Preprocess the text using IndicProcessor | |
| processed_text = ip.preprocess_batch([native_text], src_lang=src_lang, tgt_lang=tgt_lang) | |
| # 2. Tokenize the preprocessed text | |
| inputs = tokenizer(processed_text, return_tensors="pt", padding=True).to(device) | |
| # 3. Generate translation | |
| with torch.no_grad(): | |
| translated_tokens = model.generate(**inputs, num_beams=5, max_length=256) | |
| # 4. Decode the tokens | |
| decoded_translation = tokenizer.batch_decode(translated_tokens, skip_special_tokens=True) | |
| # 5. Postprocess the translation | |
| final_translation = ip.postprocess_batch(decoded_translation, lang=src_lang) | |
| return final_translation[0] | |
| except Exception as e: | |
| return f"An error occurred: {str(e)}" | |
| print("✅ Correct translation function is ready.") | |
| # --- 7. CREATE AND LAUNCH THE GRADIO APP --- | |
| iface_final = gr.Interface( | |
| fn=translate_correctly, | |
| inputs=[ | |
| gr.Textbox(lines=5, label="Native Indian Language Text", placeholder="यहाँ अपना पाठ दर्ज करें..."), | |
| gr.Dropdown(choices=list(SUPPORTED_LANGUAGES.keys()), label="Select Source Language", value="Hindi") | |
| ], | |
| outputs=gr.Textbox(label="English Translation"), | |
| title="IndicTrans2 Translator (Official Workflow)", | |
| description="Translate from 13 Indian languages to English using the official AI4Bharat workflow and IndicProcessor.", | |
| examples=[ | |
| ["नमस्ते, आप कैसे हैं?", "Hindi"], | |
| ["வணக்கம், நீங்கள் எப்படி இருக்கிறீர்கள்?", "Tamil"], | |
| ["হ্যালো, আপনি কেমন আছেন?", "Bengali"] | |
| ] | |
| ) | |
| print("🚀 Launching the final, corrected Gradio app...") | |
| iface_final.launch(share=True) | |
| # --- Step 1: Clean up and clone the repository --- | |
| # This ensures we have a fresh and correct copy. | |
| import os | |
| # --- Step 2: Verify that the 'src' directory exists --- | |
| src_path = '/content/IndicTrans2/src' | |
| if os.path.isdir(src_path): | |
| print(f"✅ SUCCESS: The directory '{src_path}' exists.") | |
| # --- Step 3: Check for the 'IndicTransToolkit' within 'src' --- | |
| toolkit_path = os.path.join(src_path, 'IndicTransToolkit') | |
| if os.path.isdir(toolkit_path): | |
| print(f"✅ SUCCESS: The 'IndicTransToolkit' directory was found inside 'src'.") | |
| else: | |
| print(f"⚠️ WARNING: The 'IndicTransToolkit' directory was NOT found directly inside 'src'. The structure might have changed.") | |
| # --- Step 4: Attempt to import the processor --- | |
| import sys | |
| # Add the src directory to Python's path | |
| sys.path.insert(0, src_path) | |
| try: | |
| from IndicTransToolkit.processor import IndicProcessor | |
| print("✅ SUCCESS: Successfully imported 'IndicProcessor' from 'IndicTransToolkit'.") | |
| print("\n🎉 Your environment is set up correctly!") | |
| except ImportError as e: | |
| print(f"❌ ERROR: Failed to import 'IndicProcessor'. Python returned the following error: {e}") | |
| print("This means the Python path is likely correct, but the module name or structure is wrong.") | |
| else: | |
| print(f"❌ ERROR: The directory '{src_path}' does not exist.") | |
| print("This means the 'git clone' command likely failed or cloned to a different location.") | |