app.py

import streamlit as st
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image, ImageDraw
import time
from transformers import AutoModelForCausalLM, AutoTokenizer

# Constants
AVATAR_WIDTH, AVATAR_HEIGHT = 400, 600

# Set up DialoGPT model
@st.cache_resource
def load_model():
    tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
    model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
    return tokenizer, model

tokenizer, model = load_model()

# Simulated Sensor Classes
class Sensors:
    @staticmethod
    def measure_pressure(base_sensitivity, duration):
        return base_sensitivity * (1 - np.exp(-duration / 2))

    @staticmethod
    def measure_temperature(base_temp, duration):
        return base_temp + 5 * (1 - np.exp(-duration / 3))

    @staticmethod
    def measure_texture(x, y):
        textures = ["smooth", "rough", "bumpy", "silky", "grainy"]
        return textures[hash((x, y)) % len(textures)]

    @staticmethod
    def measure_em_field(x, y):
        return np.sin(x/50) * np.cos(y/50) * 10

# Create more detailed sensation map for the avatar
def create_sensation_map(width, height):
    sensation_map = np.zeros((height, width, 7))  # pain, pleasure, pressure, temp, texture, em, tickle
    for y in range(height):
        for x in range(width):
            # Head
            if 150 < x < 250 and 50 < y < 150:
                sensation_map[y, x] = [0.7, 0.5, 0.8, 0.6, 0.9, 0.9, 0.3]
            # Torso
            elif 175 < x < 225 and 150 < y < 400:
                sensation_map[y, x] = [0.5, 0.6, 0.7, 0.8, 0.6, 0.7, 0.5]
            # Arms
            elif (125 < x < 175 or 225 < x < 275) and 150 < y < 350:
                sensation_map[y, x] = [0.6, 0.5, 0.9, 0.7, 0.8, 0.6, 0.7]
            # Hands
            elif (100 < x < 150 or 250 < x < 300) and 300 < y < 350:
                sensation_map[y, x] = [0.8, 0.7, 1.0, 0.9, 1.0, 0.8, 0.9]
            # Legs
            elif 175 < x < 225 and 400 < y < 550:
                sensation_map[y, x] = [0.7, 0.4, 0.8, 0.6, 0.7, 0.5, 0.6]
            # Feet
            elif 175 < x < 225 and 550 < y < 600:
                sensation_map[y, x] = [0.9, 0.6, 1.0, 0.8, 0.9, 0.7, 1.0]
            else:
                sensation_map[y, x] = [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1]
    
    return sensation_map

avatar_sensation_map = create_sensation_map(AVATAR_WIDTH, AVATAR_HEIGHT)

# Create more detailed human-like avatar
def create_avatar():
    img = Image.new('RGB', (AVATAR_WIDTH, AVATAR_HEIGHT), color='white')
    draw = ImageDraw.Draw(img)
    
    # Head
    draw.ellipse([150, 50, 250, 150], fill='beige', outline='black')
    # Eyes
    draw.ellipse([175, 80, 190, 95], fill='white', outline='black')
    draw.ellipse([210, 80, 225, 95], fill='white', outline='black')
    draw.ellipse([180, 85, 185, 90], fill='black')
    draw.ellipse([215, 85, 220, 90], fill='black')
    # Mouth
    draw.arc([185, 110, 215, 130], start=0, end=180, fill='black')
    
    # Body
    draw.rectangle([175, 150, 225, 400], fill='beige', outline='black')
    
    # Arms
    draw.rectangle([125, 150, 175, 350], fill='beige', outline='black')
    draw.rectangle([225, 150, 275, 350], fill='beige', outline='black')
    
    # Hands
    draw.ellipse([100, 300, 150, 350], fill='beige', outline='black')
    draw.ellipse([250, 300, 300, 350], fill='beige', outline='black')
    
    # Legs
    draw.rectangle([175, 400, 200, 550], fill='beige', outline='black')
    draw.rectangle([200, 400, 225, 550], fill='beige', outline='black')
    
    # Feet
    draw.ellipse([165, 550, 210, 600], fill='beige', outline='black')
    draw.ellipse([190, 550, 235, 600], fill='beige', outline='black')
    
    return img

avatar_image = create_avatar()

# Streamlit app
st.title("Advanced Humanoid Techno-Sensory Simulation")

# Display avatar
st.image(avatar_image, use_column_width=True)

# Touch input
touch_x = st.slider("Touch X coordinate", 0, AVATAR_WIDTH, AVATAR_WIDTH // 2)
touch_y = st.slider("Touch Y coordinate", 0, AVATAR_HEIGHT, AVATAR_HEIGHT // 2)

# Touch duration
touch_duration = st.slider("Touch duration (seconds)", 0.1, 5.0, 1.0, 0.1)

if st.button("Apply Touch"):
    sensation = avatar_sensation_map[touch_y, touch_x]
    pain, pleasure, pressure_sens, temp_sens, texture_sens, em_sens, tickle_sens = sensation

    measured_pressure = Sensors.measure_pressure(pressure_sens, touch_duration)
    measured_temp = Sensors.measure_temperature(37, touch_duration)
    measured_texture = Sensors.measure_texture(touch_x, touch_y)
    measured_em = Sensors.measure_em_field(touch_x, touch_y) * em_sens

    # Calculate overall sensation
    pain_level = pain * measured_pressure
    pleasure_level = pleasure * (measured_temp - 37) / 5
    tickle_level = tickle_sens * (1 - np.exp(-touch_duration / 0.5))

    st.write(f"Touch applied at ({touch_x}, {touch_y}) for {touch_duration:.1f} seconds")
    st.write(f"Pressure: {measured_pressure:.2f}")
    st.write(f"Temperature: {measured_temp:.2f}°C")
    st.write(f"Texture: {measured_texture}")
    st.write(f"Electromagnetic field: {measured_em:.2f}")
    st.write(f"Pain level: {pain_level:.2f}")
    st.write(f"Pleasure level: {pleasure_level:.2f}")
    st.write(f"Tickle level: {tickle_level:.2f}")

    # Generate description
    prompt = f"""Human: Describe the sensation when touched at ({touch_x}, {touch_y}) for {touch_duration:.1f} seconds with these measurements:
    Pressure: {measured_pressure:.2f}
    Temperature: {measured_temp:.2f}°C
    Texture: {measured_texture}
    Electromagnetic field: {measured_em:.2f}
    Resulting in:
    Pain: {pain_level:.2f}, Pleasure: {pleasure_level:.2f}, Tickle: {tickle_level:.2f}
    Avatar:"""
    
    input_ids = tokenizer.encode(prompt, return_tensors="pt")
    output = model.generate(input_ids, max_length=200, num_return_sequences=1, no_repeat_ngram_size=2, top_k=50, top_p=0.95, temperature=0.7)
    
    response = tokenizer.decode(output[0], skip_special_tokens=True).split("Avatar: ")[-1].strip()
    
    st.write("Avatar's response:")
    st.write(response)

# Visualize sensation map
st.subheader("Sensation Map Visualization")
fig, axs = plt.subplots(2, 4, figsize=(20, 10))
titles = ['Pain', 'Pleasure', 'Pressure', 'Temperature', 'Texture', 'EM Field', 'Tickle']

for i, title in enumerate(titles):
    ax = axs[i // 4, i % 4]
    im = ax.imshow(avatar_sensation_map[:, :, i], cmap='viridis')
    ax.set_title(title)
    fig.colorbar(im, ax=ax)

axs[1, 3].axis('off')  # Turn off the last unused subplot
plt.tight_layout()
st.pyplot(fig)

st.write("The sensation map shows the sensitivity of different body parts to various stimuli. Brighter colors indicate higher sensitivity.")

# Add some context about the avatar's sensory capabilities
st.subheader("Avatar Sensory Capabilities")
st.write("""
This advanced humanoid avatar is equipped with cutting-edge sensory technology:

1. Pressure Sensors: Highly sensitive to touch, with increased sensitivity in hands and feet.
2. Temperature Sensors: Can detect slight changes in temperature, simulating human thermal perception.
3. Texture Analysis: Capable of distinguishing between various textures, from smooth to rough.
4. Electromagnetic Field Detection: Mimics the subtle EM sensitivity some humans report.
5. Pain and Pleasure Processing: Simulates the complex interplay of pain and pleasure responses.
6. Tickle Sensation: Replicates the unique tickle response, which can be pleasurable or uncomfortable.

The avatar's responses are generated using an advanced language model, attempting to describe the sensations in human-like terms.
""")

# Footer
st.write("---")
st.write("Advanced Humanoid Techno-Sensory Simulation v1.0")
st.write("Disclaimer: This is a simulation and does not represent actual human sensory experiences.")