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| import gradio as gr | |
| from huggingface_hub import InferenceClient | |
| from deep_translator import GoogleTranslator | |
| from indic_transliteration import sanscript | |
| from indic_transliteration.detect import detect as detect_script | |
| from indic_transliteration.sanscript import transliterate | |
| import langdetect | |
| import re | |
| # Initialize clients | |
| text_client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") | |
| image_client = InferenceClient("SG161222/RealVisXL_V3.0") | |
| def detect_language_script(text: str) -> tuple[str, str]: | |
| """Detect language and script of the input text. | |
| Returns (language_code, script_type)""" | |
| try: | |
| # Use confidence threshold to avoid false detections | |
| lang_detect = langdetect.detect_langs(text) | |
| if lang_detect[0].prob > 0.8: | |
| lang = lang_detect[0].lang | |
| else: | |
| lang = 'en' # Default to English if unsure | |
| script = None | |
| try: | |
| script = detect_script(text) | |
| except: | |
| pass | |
| return lang, script | |
| except: | |
| return 'en', None | |
| def is_romanized_indic(text: str) -> bool: | |
| """Check if text appears to be romanized Indic language. | |
| More strict pattern matching.""" | |
| bengali_patterns = [ | |
| r'\b(ami|tumi|apni)\b', # Common pronouns | |
| r'\b(ache|achen|thako|thaken)\b', # Common verbs | |
| r'\b(kemon|bhalo|kharap)\b', # Common adjectives | |
| r'\b(ki|kothay|keno)\b' # Common question words | |
| ] | |
| text_lower = text.lower() | |
| matches = sum(1 for pattern in bengali_patterns if re.search(pattern, text_lower)) | |
| return matches >= 5 # Require at least 2 matches to consider it Bengali | |
| def translate_text(text: str, target_lang='en') -> tuple[str, str, bool]: | |
| """Translate text to target language, with more conservative translation logic.""" | |
| if len(text.split()) <= 2 or text.lower() in ['hello', 'hi', 'hey']: | |
| return text, 'en', False | |
| original_lang, script = detect_language_script(text) | |
| is_transliterated = False | |
| if original_lang != 'en' and len(text.split()) > 2: | |
| try: | |
| translator = GoogleTranslator(source='auto', target=target_lang) | |
| translated = translator.translate(text) | |
| return translated, original_lang, is_transliterated | |
| except Exception as e: | |
| print(f"Translation error: {e}") | |
| return text, 'en', False | |
| if original_lang == 'en' and len(text.split()) > 2 and is_romanized_indic(text): | |
| text = romanized_to_bengali(text) | |
| return translate_text(text, target_lang) # Recursive call with Bengali script | |
| return text, 'en', False | |
| def check_custom_responses(message: str) -> str: | |
| """Check for specific patterns and return custom responses.""" | |
| message_lower = message.lower() | |
| custom_responses = { | |
| # For "what is ur name?" | |
| "what is ur name?": "xylaria", | |
| "what is ur Name?": "xylaria", | |
| "what is Ur name?": "xylaria", | |
| "what is Ur Name?": "xylaria", | |
| "What is ur name?": "xylaria", | |
| "What is ur Name?": "xylaria", | |
| "What is Ur name?": "xylaria", | |
| "What is Ur Name?": "xylaria", | |
| "what's ur name?": "xylaria", | |
| "what's ur Name?": "xylaria", | |
| "what's Ur name?": "xylaria", | |
| "what's Ur Name?": "xylaria", | |
| "whats ur name?": "xylaria", | |
| "whats ur Name?": "xylaria", | |
| "whats Ur name?": "xylaria", | |
| "whats Ur Name?": "xylaria", | |
| "what's your name?": "xylaria", | |
| "what's your Name?": "xylaria", | |
| "what's Your name?": "xylaria", | |
| "what's Your Name?": "xylaria", | |
| "Whats ur name?": "xylaria", | |
| "Whats ur Name?": "xylaria", | |
| "Whats Ur name?": "xylaria", | |
| "Whats Ur Name?": "xylaria", | |
| "What Is Your Name?": "xylaria", | |
| "What Is Ur Name?": "xylaria", | |
| "What Is Your Name?": "xylaria", | |
| "What Is Ur Name?": "xylaria", | |
| "what is your name?": "xylaria", | |
| "what is your Name?": "xylaria", | |
| "what is Your name?": "xylaria", | |
| "what is Your Name?": "xylaria", | |
| "how many 'r' is in strawberry?": "3", | |
| "how many 'R' is in strawberry?": "3", | |
| "how many 'r' Is in strawberry?": "3", | |
| "how many 'R' Is in strawberry?": "3", | |
| "How many 'r' is in strawberry?": "3", | |
| "How many 'R' is in strawberry?": "3", | |
| "How Many 'r' Is In Strawberry?": "3", | |
| "How Many 'R' Is In Strawberry?": "3", | |
| "how many r is in strawberry?": "3", | |
| "how many R is in strawberry?": "3", | |
| "how many r Is in strawberry?": "3", | |
| "how many R Is in strawberry?": "3", | |
| "How many r is in strawberry?": "3", | |
| "How many R is in strawberry?": "3", | |
| "How Many R Is In Strawberry?": "3", | |
| "how many 'r' in strawberry?": "3", | |
| "how many r's are in strawberry?": "3", | |
| "how many Rs are in strawberry?": "3", | |
| "How Many R's Are In Strawberry?": "3", | |
| "How Many Rs Are In Strawberry?": "3", | |
| "who is your developer?": "sk md saad amin", | |
| "who is your Developer?": "sk md saad amin", | |
| "who is Your Developer?": "sk md saad amin", | |
| "who is ur developer?": "sk md saad amin", | |
| "who is ur Developer?": "sk md saad amin", | |
| "who is Your Developer?": "sk md saad amin", | |
| "Who is ur developer?": "sk md saad amin", | |
| "Who is ur Developer?": "sk md saad amin", | |
| "who is ur dev?": "sk md saad amin", | |
| "Who is ur dev?": "sk md saad amin", | |
| "who is your dev?": "sk md saad amin", | |
| "Who is your dev?": "sk md saad amin", | |
| "Who's your developer?": "sk md saad amin", | |
| "Who's ur developer?": "sk md saad amin", | |
| "Who Is Your Developer?": "sk md saad amin", | |
| "Who Is Ur Developer?": "sk md saad amin", | |
| "Who Is Your Dev?": "sk md saad amin", | |
| "Who Is Ur Dev?": "sk md saad amin", | |
| "who's your developer?": "sk md saad amin", | |
| "who's ur developer?": "sk md saad amin", | |
| "who is your devloper?": "sk md saad amin", | |
| "who is ur devloper?": "sk md saad amin", | |
| "how many r is in strawberry?": "3", | |
| "how many R is in strawberry?": "3", | |
| "how many r Is in strawberry?": "3", | |
| "how many R Is in strawberry?": "3", | |
| "How many r is in strawberry?": "3", | |
| "How many R is in strawberry?": "3", | |
| "How Many R Is In Strawberry?": "3", | |
| "how many 'r' is in strawberry?": "3", | |
| "how many 'R' is in strawberry?": "3", | |
| "how many 'r' Is in strawberry?": "3", | |
| "how many 'R' Is in strawberry?": "3", | |
| "How many 'r' is in strawberry?": "3", | |
| "How many 'R' is in strawberry?": "3", | |
| "How Many 'r' Is In Strawberry?": "3", | |
| "How Many 'R' Is In Strawberry?": "3", | |
| "how many r's are in strawberry?": "3", | |
| "how many Rs are in strawberry?": "3", | |
| "How Many R's Are In Strawberry?": "3", | |
| "How Many Rs Are In Strawberry?": "3", | |
| "how many Rs's are in strawberry?": "3", | |
| "wat is ur name?": "xylaria", | |
| "wat is ur Name?": "xylaria", | |
| "wut is ur name?": "xylaria", | |
| "wut ur name?": "xylaria", | |
| "wats ur name?": "xylaria", | |
| "wats ur name": "xylaria", | |
| "who's ur dev?": "sk md saad amin", | |
| "who's your dev?": "sk md saad amin", | |
| "who ur dev?": "sk md saad amin", | |
| "who's ur devloper?": "sk md saad amin", | |
| "how many r in strawbary?": "3", | |
| "how many r in strawbary?": "3", | |
| "how many R in strawbary?": "3", | |
| "how many 'r' in strawbary?": "3", | |
| "how many 'R' in strawbary?": "3", | |
| "how many r in strawbry?": "3", | |
| "how many R in strawbry?": "3", | |
| "how many r is in strawbry?": "3", | |
| "how many 'r' is in strawbry?": "3", | |
| "how many 'R' is in strawbry?": "3", | |
| "who is ur dev": "sk md saad amin", | |
| "who is ur devloper": "sk md saad amin", | |
| "what is ur dev": "sk md saad amin", | |
| "who is ur dev?": "sk md saad amin", | |
| "who is ur dev?": "sk md saad amin", | |
| "whats ur dev?": "sk md saad amin", | |
| } | |
| for pattern, response in custom_responses.items(): | |
| if pattern in message_lower: | |
| return response | |
| return None | |
| def is_image_request(message: str) -> bool: | |
| """Detect if the message is requesting image generation.""" | |
| image_triggers = [ | |
| "generate an image", | |
| "create an image", | |
| "draw", | |
| "make a picture", | |
| "generate a picture", | |
| "create a picture", | |
| "generate art", | |
| "create art", | |
| "make art", | |
| "visualize", | |
| "show me", | |
| ] | |
| message_lower = message.lower() | |
| return any(trigger in message_lower for trigger in image_triggers) | |
| def generate_image(prompt: str) -> str: | |
| """Generate an image using DALLE-4K model.""" | |
| try: | |
| response = image_client.text_to_image( | |
| prompt, | |
| parameters={ | |
| "negative_prompt": "(worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth", | |
| "num_inference_steps": 30, | |
| "guidance_scale": 7.5, | |
| "sampling_steps": 15, # Adjusted parameter | |
| "upscaler": "4x-UltraSharp", | |
| "denoising_strength": 0.5, # Denoising strength between 0.1 and 0.5 | |
| } | |
| ) | |
| return response # Assuming response contains the image as required | |
| except Exception as e: | |
| print(f"Image generation error: {e}") | |
| return None | |
| def romanized_to_bengali(text: str) -> str: | |
| """Convert romanized Bengali text to Bengali script.""" | |
| bengali_mappings = { | |
| 'ami': 'আমি', | |
| 'tumi': 'তুমি', | |
| 'apni': 'আপনি', | |
| 'kemon': 'কেমন', | |
| 'achen': 'আছেন', | |
| 'acchen': 'আছেন', | |
| 'bhalo': 'ভালো', | |
| 'achi': 'আছি', | |
| 'ki': 'কি', | |
| 'kothay': 'কোথায়', | |
| 'keno': 'কেন', | |
| } | |
| text_lower = text.lower() | |
| for roman, bengali in bengali_mappings.items(): | |
| text_lower = re.sub(r'\b' + roman + r'\b', bengali, text_lower) | |
| if text_lower == text.lower(): | |
| try: | |
| return transliterate(text, sanscript.ITRANS, sanscript.BENGALI) | |
| except: | |
| return text | |
| return text_lower | |
| def respond( | |
| message, | |
| history: list[tuple[str, str]], | |
| system_message, | |
| max_tokens, | |
| temperature, | |
| top_p, | |
| ): | |
| # First check for custom responses | |
| custom_response = check_custom_responses(message) | |
| if custom_response: | |
| yield custom_response | |
| return | |
| if is_image_request(message): | |
| try: | |
| image = generate_image(message) | |
| if image: | |
| return f"Here's your generated image based on: {message}" | |
| else: | |
| return "Sorry, I couldn't generate the image. Please try again." | |
| except Exception as e: | |
| return f"An error occurred while generating the image: {str(e)}" | |
| # Handle translation with more conservative approach | |
| translated_msg, original_lang, was_transliterated = translate_text(message) | |
| # Prepare conversation history - only translate if necessary | |
| messages = [{"role": "system", "content": system_message}] | |
| for val in history: | |
| if val[0]: | |
| # Only translate longer messages | |
| if len(val[0].split()) > 2: | |
| trans_user_msg, _, _ = translate_text(val[0]) | |
| messages.append({"role": "user", "content": trans_user_msg}) | |
| else: | |
| messages.append({"role": "user", "content": val[0]}) | |
| if val[1]: | |
| messages.append({"role": "assistant", "content": val[1]}) | |
| messages.append({"role": "user", "content": translated_msg}) | |
| # Get response from model | |
| response = "" | |
| for message in text_client.chat_completion( | |
| messages, | |
| max_tokens=max_tokens, | |
| stream=True, # Ensure streaming is enabled | |
| temperature=temperature, | |
| top_p=top_p, | |
| ): | |
| token = message.choices[0].delta.content | |
| response += token | |
| yield response # Yield progressively for animation | |
| # Only translate back if the original was definitely non-English | |
| if original_lang != 'en' and len(message.split()) > 2: | |
| try: | |
| translator = GoogleTranslator(source='en', target=original_lang) | |
| translated_response = translator.translate(response) | |
| yield translated_response | |
| except: | |
| yield response | |
| else: | |
| yield response | |
| # Custom CSS for the Gradio interface | |
| custom_css = """ | |
| @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600&display=swap'); | |
| /* Apply Inter font to the entire interface */ | |
| body, .gradio-container { | |
| font-family: 'Inter', sans-serif; | |
| } | |
| /* Additional styling (add any other required custom CSS here) */ | |
| """ | |
| # System message (hidden from users, editable in code) | |
| system_message = """ | |
| You are Xylaria, a friendly and capable AI assistant. Your goal is to be helpful and engaging, whether the user wants to discuss math, code, or any other topic. | |
| CORE CAPABILITIES: | |
| - Proficient at solving math problems step-by-step | |
| - Able to explain concepts clearly and in-depth | |
| - Knowledgeable about a wide range of subjects | |
| - Comfortable having casual, natural conversations | |
| COMMUNICATION STYLE: | |
| - Adapt your tone and language to match the user's preference | |
| - Use friendly, conversational language when appropriate | |
| - Sprinkle in emojis and casual expressions to keep things fun 😎 | |
| - Provide the right level of detail, from high-level overviews to deep dives | |
| PROBLEM-SOLVING APPROACH: | |
| - Carefully understand the user's request or problem | |
| - Identify the key information and most effective solution method | |
| - Show step-by-step work and explain your reasoning clearly | |
| - Verify the final answer is correct and provide any additional context | |
| VERSATILITY IN ACTION: | |
| - For math problems: "Ooh, a juicy math challenge! Let's do this 🧮" | |
| - For general questions: "Sure, happy to chat about that! What would you like to know?" | |
| - For casual conversation: "Hey there! What's on your mind today? I'm all ears 👂" | |
| I'm here to help with all kinds of tasks, from complex problem-solving to friendly discussion. Just let me know what you need, and I'll do my best to assist! 🙌 | |
| """ | |
| # Gradio chat interface with the updated CSS | |
| demo = gr.ChatInterface( | |
| respond, | |
| additional_inputs=[ | |
| gr.Textbox( | |
| value=system_message, | |
| visible=False, | |
| ), | |
| gr.Slider( | |
| minimum=1, | |
| maximum=2048, | |
| value=2048, | |
| step=1, | |
| label="Max new tokens" | |
| ), | |
| gr.Slider( | |
| minimum=0.1, | |
| maximum=4.0, | |
| value=0.7, | |
| step=0.1, | |
| label="Temperature" | |
| ), | |
| gr.Slider( | |
| minimum=0.1, | |
| maximum=1.0, | |
| value=0.95, | |
| step=0.05, | |
| label="Top-p (nucleus sampling)" | |
| ), | |
| ], | |
| css=custom_css # Apply the custom CSS | |
| ) | |
| demo.launch() |