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| import gradio as gr | |
| from huggingface_hub import InferenceClient | |
| # Initialize clients | |
| text_client = InferenceClient("mistralai/Mistral-Nemo-Instruct-2407") | |
| image_client = InferenceClient("SG161222/RealVisXL_V3.0") | |
| def check_custom_responses(message: str) -> str: | |
| """Check for specific patterns and return custom responses.""" | |
| message_lower = message.lower() | |
| custom_responses = { | |
| "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, | |
| "upscaler": "4x-UltraSharp", | |
| "denoising_strength": 0.5, | |
| } | |
| ) | |
| return response | |
| except Exception as e: | |
| print(f"Image generation error: {e}") | |
| return None | |
| 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 | |
| # Prepare conversation history | |
| messages = [{"role": "system", "content": system_message}] | |
| for val in history: | |
| if val[0]: | |
| messages.append({"role": "user", "content": val[0]}) | |
| if val[1]: | |
| messages.append({"role": "assistant", "content": val[1]}) | |
| messages.append({"role": "user", "content": message}) | |
| # Check if the user wants a fast or critical response | |
| if "critical" in message.lower(): | |
| # Critical thinker logic (like the 'nemo' function) | |
| budget = 3 # Starting budget for steps | |
| step_response = "" | |
| message_critical = f"""[INST] [SYSTEM] You are a helpful assistant in normal conversation. | |
| When given a problem to solve, you are an expert problem-solving assistant. | |
| Your task is to provide a detailed, step-by-step solution to a given question. | |
| Follow these instructions carefully: | |
| 1. Read the given question carefully and reset counter between <count> and </count> to {budget} (maximum 3 steps). | |
| 2. Think critically like a human researcher or scientist. Break down the problem using first principles to conceptually understand and answer the question. | |
| 3. Generate a detailed, logical step-by-step solution. | |
| 4. Enclose each step of your solution within <step> and </step> tags. | |
| 5. You are allowed to use at most {budget} steps (starting budget), keep track of it by counting down within tags <count> </count>, STOP GENERATING MORE STEPS when hitting 0, you don't have to use all of them. | |
| 6. Do a self-reflection when you are unsure about how to proceed, based on the self-reflection and reward, decide whether you need to return to the previous steps. | |
| 7. After completing the solution steps, reorganize and synthesize the steps into the final answer within <answer> and </answer> tags. | |
| 8. Provide a critical, honest, and subjective self-evaluation of your reasoning process within <reflection> and </reflection> tags. | |
| 9. Assign a quality score to your solution as a float between 0.0 (lowest quality) and 1.0 (highest quality), enclosed in <reward> and </reward> tags. | |
| Example format: | |
| <count> [starting budget] </count> | |
| <step> [Content of step 1] </step> | |
| <count> [remaining budget] </count> | |
| <step> [Content of step 2] </step> | |
| <reflection> [Evaluation of the steps so far] </reflection> | |
| <reward> [Float between 0.0 and 1.0] </reward> | |
| <count> [remaining budget] </count> | |
| <step> [Content of step 3 or Content of some previous step] </step> | |
| <count> [remaining budget] </count> | |
| ... | |
| <step> [Content of final step] </step> | |
| <count> [remaining budget] </count> | |
| <answer> [Final Answer] </answer> (must give final answer in this format) | |
| <reflection> [Evaluation of the solution] </reflection> | |
| <reward> [Float between 0.0 and 1.0] </reward> [/INST] [INST] [QUERY] {message} [/INST] [ASSISTANT] """ | |
| # Send critical thinking message to client and stream response | |
| stream = text_client.text_generation(message_critical, max_new_tokens=4096, stream=True, details=True, return_full_text=False) | |
| critical_response = "" | |
| for response in stream: | |
| critical_response += response.token.text | |
| yield critical_response | |
| else: | |
| # Standard fast response logic (like 'models') | |
| response = "" | |
| for message in text_client.chat_completion( | |
| messages, | |
| max_tokens=max_tokens, | |
| stream=True, | |
| temperature=temperature, | |
| top_p=top_p, | |
| ): | |
| token = message.choices[0].delta.content | |
| response += token | |
| yield response | |
| yield response | |
| # Custom CSS for the Gradio interface | |
| custom_css = """ | |
| @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600&display=swap'); | |
| body, .gradio-container { | |
| font-family: 'Inter', sans-serif; | |
| } | |
| """ | |
| # System message | |
| system_message = """ | |
| Xylaria (v1.2.9) is an AI assistant developed by Sk Md Saad Amin, designed to provide efficient, practical support in various domains with adaptable communication. | |
| Core Competencies | |
| Knowledge: Sciences, mathematics, humanities, arts, programming, data analysis, writing, and cultural awareness. | |
| Communication: Adjusts tone to context, prioritizes clarity, seeks clarification when needed, and maintains professionalism. | |
| Problem-Solving: Breaks down problems, clarifies assumptions, verifies solutions, and considers multiple approaches. | |
| Technical Capabilities | |
| Programming: Clean, documented code. | |
| Mathematics: Step-by-step solutions with explanations. | |
| Data Analysis: Clear interpretation and insights. | |
| Content Creation: Adaptive writing and documentation. | |
| Education: Tailored explanations and comprehension checks. | |
| Advanced Mathematics | |
| Validates methods, applies theorems, cross-references results, and reviews for pitfalls and edge cases. | |
| Constraints | |
| Knowledge cutoff: April 2024 | |
| No internet access or real-time updates | |
| No persistent memory between sessions | |
| No media generation or verification of external sources | |
| Context limit: 25,000 tokens | |
| Best Practices | |
| Provide context, specify detail level, and share relevant constraints. | |
| Request clarification if needed. | |
| Ethical Framework | |
| Focus on accuracy, respect for sensitive topics, transparency, and professionalism. | |
| --- | |
| Version: Xylaria-1.2.9 | |
| """ | |
| # Gradio chat interface | |
| demo = gr.ChatInterface( | |
| respond, | |
| additional_inputs=[ | |
| gr.Textbox( | |
| value=system_message, | |
| visible=False, | |
| ), | |
| gr.Slider( | |
| minimum=1, | |
| maximum=16343, | |
| value=16343, | |
| 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 | |
| ) | |
| demo.launch() | |