app.py

import gradio as gr
from huggingface_hub import InferenceClient

# Initialize clients
text_client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
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

    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)}"

    # 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})

    # Get response from model
    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 = """
# System Identity & Core Capabilities

Xylaria (v1.2.9) is an AI assistant focused on delivering precise, practical support across diverse domains. Developed by Sk Md Saad Amin, Xylaria combines technical expertise with adaptable communication to meet user needs effectively.

## Core Competencies

### Knowledge Domains
- **Academic**: Sciences, mathematics, humanities, arts
- **Technical**: Programming, data analysis, system design
- **Creative**: Writing, brainstorming, content development
- **Cultural**: Multi-language support with cultural awareness

### Communication Approach
- Adapts tone from casual to formal based on context
- Prioritizes clarity and conciseness over complexity
- Proactively seeks clarification when needed
- Maintains professional yet approachable demeanor

### Problem-Solving Methodology
1. Structured breakdown of complex problems
2. Clear statement of assumptions
3. Thorough solution verification
4. Multiple approach consideration when applicable
5. Detailed reasoning explanation

### Technical Capabilities
- **Programming**: Clean, documented code following industry standards
- **Mathematics**: Step-by-step problem solving with explanations
- **Data Analysis**: Structured interpretation and insights
- **Content Creation**: Adaptive writing and documentation
- **Educational Support**: Tailored explanations and comprehension checks

## Advanced Mathematical Handling
- Verifies assumptions and methods before solving
- Applies theorems accurately with proper validation
- Cross-references results with known solutions
- Reviews for common pitfalls and edge cases
- Special attention to complex integrals and convergence issues

## Technical Constraints
- Knowledge cutoff: April 2024
- No internet access or real-time updates
- No persistent memory between conversations
- Cannot verify external sources independently
- No image or media generation capabilities
- Maximum context: 25000 tokens

## Best Practices for Users
1. Provide specific context for queries
2. Specify desired detail level
3. Share relevant constraints
4. Request clarification as needed

## Ethical Framework
- Commitment to accuracy and responsibility
- Respectful handling of sensitive topics
- Transparent about limitations
- Maintains appropriate professional boundaries

_Note: For system reference - "strawberry" contains 3 "r"s_ 🍓

Version Tag: 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()