app.py

# Install required libraries
# !pip install gradio>=3.50.2 transformers>=4.30.0 networkx>=3.0 plotly>=5.0.0 torch>=2.0.0 numpy>=1.21.0

import gradio as gr
import torch
import networkx as nx
import plotly.graph_objects as go
from transformers import pipeline
import numpy as np
import traceback

# Check device
device = "cuda" if torch.cuda.is_available() else "cpu"
print(f"Using device: {device}")

# Load models with fallback
try:
    summarizer = pipeline("summarization", model="facebook/bart-large-cnn", device=0 if device == "cuda" else -1)
    text_generator = pipeline("text-generation", model="gpt2", device=0 if device == "cuda" else -1)
    print("✓ Models loaded successfully")
except Exception as e:
    print(f"Model loading error: {e}")
    try:
        summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-6-6", device=0 if device == "cuda" else -1)
        text_generator = pipeline("text-generation", model="distilgpt2", device=0 if device == "cuda" else -1)
        print("✓ Fallback models loaded successfully")
    except:
        print("Critical error loading models. Exiting.")

# Progress tracking
progress_status = {"value": 0, "desc": ""}

def update_progress(value, desc=""):
    progress_status["value"] = value
    progress_status["desc"] = desc
    print(f"Progress: {value}% - {desc}")

# Simplified summary generation
def generate_summary(topic):
    try:
        update_progress(10, "Starting your idea analysis")
        
        if "AI" in topic or "artificial intelligence" in topic.lower():
            ai_component = "The AI part makes it super smart by figuring out patterns and doing tasks automatically!"
        else:
            ai_component = "Adding some AI could make it even cooler by helping with data or tasks."
            
        if "urban farming" in topic.lower() or "agriculture" in topic.lower():
            summary = f"""
            Your idea, {topic}, is a fresh way to grow food right in cities!

            What it’s about: This startup uses cool tech to grow fresh food indoors or on rooftops. Think sensors and smart systems to keep plants happy.

            Who it’s for: People like restaurants wanting fresh veggies, city folks who love healthy food, or stores looking to cut delivery costs.

            How it works: You’d need things like sensors, grow lights, and a smart app to run it all. {ai_component}

            How it makes money: Sell to businesses, charge people monthly for fresh food, or share your tech with others.

            Why it stands out: Fresher food, less travel, and it works all year—no matter the weather!

            Things to watch out for: It might cost a lot to start, and some cities have rules about this.
            """
        else:
            outputs = text_generator(
                f"A startup idea about {topic} could be:", 
                max_length=300, 
                num_return_sequences=1,
                temperature=0.7
            )
            generated_text = outputs[0]['generated_text']
            summary = f"""
            Your idea, {topic}, is a cool way to make something better!

            What it’s about: This startup helps with [problem/need] by using [simple solution]. It’s special because [unique bit].

            Who it’s for: People like [customer type] would love this—think [example customers].

            How it works: You’d need [basic tools/tech] to build it. {ai_component}

            How it makes money: You could [simple revenue idea, e.g., sell it or charge a fee].

            Why it stands out: It’s better because [easy advantage, e.g., it’s simpler or cheaper].

            Things to watch out for: Starting might be tough because of [simple challenge, e.g., money or time].
            
            {generated_text}
            """
        
        update_progress(60, "Idea analysis ready")
        return summary
        
    except Exception as e:
        print(f"Error generating summary: {str(e)}\n{traceback.format_exc()}")
        return f"Oops! Something went wrong: {str(e)}. Try again with a new idea!"

# Responsive interactive mind map with Plotly
def generate_mindmap(topic, summary):
    try:
        update_progress(70, "Building your idea map")
        
        concepts = [
            "What It Does", "Who It’s For", "How It Makes Money",
            "What Makes It Special", "What’s Needed", "Next Steps"
        ]
        subconcepts = {
            "What It Does": ["Main Idea", "Key Features"],
            "Who It’s For": ["Customers", "Why They’d Like It"],
            "How It Makes Money": ["Ways to Earn", "Pricing"],
            "What Makes It Special": ["Standout Points", "Edge Over Others"],
            "What’s Needed": ["Tools or Tech", "Skills"],
            "Next Steps": ["First Moves", "Goals"]
        }
        
        nodes = [topic] + concepts + [sub for concept in concepts for sub in subconcepts[concept]]
        edges = [(topic, concept) for concept in concepts] + \
                [(concept, sub) for concept in concepts for sub in subconcepts[concept]]
        
        pos = {topic: (0, 0)}
        for i, concept in enumerate(concepts):
            pos[concept] = (np.cos(i * 2 * np.pi / len(concepts)), np.sin(i * 2 * np.pi / len(concepts)))
            for j, sub in enumerate(subconcepts[concept]):
                pos[sub] = (pos[concept][0] + 0.3 * np.cos(j), pos[concept][1] + 0.3 * np.sin(j))
        
        edge_x, edge_y = [], []
        for edge in edges:
            x0, y0 = pos[edge[0]]
            x1, y1 = pos[edge[1]]
            edge_x.extend([x0, x1, None])
            edge_y.extend([y0, y1, None])
        
        node_x, node_y = [pos[node][0] for node in nodes], [pos[node][1] for node in nodes]
        
        fig = go.Figure()
        fig.add_trace(go.Scatter(x=edge_x, y=edge_y, mode='lines', line=dict(color='gray', width=1), hoverinfo='none'))
        fig.add_trace(go.Scatter(
            x=node_x, y=node_y, mode='markers+text', text=nodes, textposition="middle center",
            marker=dict(size=[30 if n == topic else 20 if n in concepts else 15 for n in nodes], 
                       color=['#FF9999' if n == topic else '#99CCFF' if n in concepts else '#CCFF99' for n in nodes]),
            hoverinfo='text'
        ))
        
        # Responsive layout for mind map
        fig.update_layout(
            showlegend=False, 
            title=f"Your Idea Map: {topic}", 
            title_x=0.5, 
            paper_bgcolor='white', 
            plot_bgcolor='white',
            autosize=True,  # Makes it scale with container
            margin=dict(l=20, r=20, t=40, b=20)  # Reduced margins for mobile
        )
        
        update_progress(100, "Idea map ready")
        return fig
        
    except Exception as e:
        print(f"Error generating mind map: {str(e)}")
        return None

# Main processing
def process_input(topic):
    try:
        if not topic or len(topic.strip()) < 3:
            return "Please enter a real idea (3+ characters)!", None, gr.update(visible=False)
        
        print(f"Processing: {topic}")
        update_progress(0, "Starting your idea journey")
        
        summary = f"Congrats! You’ve started shaping {topic}. Here’s your plan:\n\n{generate_summary(topic)}"
        mindmap = generate_mindmap(topic, summary)
        
        return summary, mindmap, gr.update(visible=True)
    
    except Exception as e:
        print(f"Error in processing: {str(e)}\n{traceback.format_exc()}")
        return f"Oops! Something broke: {str(e)}", None, gr.update(visible=True)

# Follow-up question processing
def process_followup_question(question, current_summary):
    try:
        if not question or len(question.strip()) < 5:
            return "Ask something longer (5+ characters)!", None
        
        print(f"Follow-up: {question}")
        prompt = f"Question: {question}\n\nContext: {current_summary}\n\nAnswer:"
        
        response = text_generator(prompt, max_length=300, num_return_sequences=1, temperature=0.7)
        answer = response[0]['generated_text'].split("Answer:")[-1].strip()
        
        return f"Here’s your answer:\n\n{answer}", None
    
    except Exception as e:
        print(f"Error in follow-up: {str(e)}\n{traceback.format_exc()}")
        return f"Sorry, something went wrong: {str(e)}", None

# Save and load ideas
def save_idea(name, summary, mindmap, saved):
    if not name:
        return gr.update(), "Please give your idea a name!"
    saved[name] = {"summary": summary, "mindmap": mindmap}
    return gr.update(choices=list(saved.keys())), f"Great job! '{name}' is saved—keep refining it!"

def load_idea(name, saved):
    if name in saved:
        return saved[name]["summary"], saved[name]["mindmap"], gr.update(visible=True)
    return "No idea found with that name.", None, gr.update(visible=False)

# Custom CSS for responsiveness
custom_css = """
.container {
    max-width: 100%;
    padding: 10px;
}
.header {
    font-size: clamp(1.5rem, 4vw, 2.5rem);
    text-align: center;
}
.textbox {
    width: 100% !important;
    min-height: 100px;
}
.button {
    width: 100%;
    margin: 5px 0;
}
.plot {
    width: 100% !important;
    height: auto !important;
}
@media (max-width: 768px) {
    .gr-row {
        flex-direction: column !important;
    }
    .gr-column {
        width: 100% !important;
    }
}
"""

# Gradio interface
with gr.Blocks(theme=gr.themes.Glass(primary_hue="blue", secondary_hue="green"), css=custom_css) as demo:
    current_summary = gr.State("")
    saved_ideas = gr.State({})

    gr.Markdown("# 🧠 VisualMind - Grow Your Startup Idea", elem_classes=["header"])
    gr.Markdown("Dream up a startup idea and watch it come to life—works great on any screen!", elem_classes=["container"])

    with gr.Tabs():
        with gr.Tab("Create Your Idea"):
            with gr.Row(equal_height=False):
                with gr.Column(scale=1, min_width=300):
                    topic_input = gr.Textbox(
                        label="Your Startup Idea", 
                        placeholder="e.g., Smart Urban Gardens",
                        elem_classes=["textbox"]
                    )
                    submit_btn = gr.Button("Build My Idea", variant="primary", elem_classes=["button"])
            
            progress = gr.Textbox(label="What’s Happening", value="Ready to start!", interactive=False, elem_classes=["textbox"])
            
            with gr.Row(visible=False, equal_height=False) as results_container:
                with gr.Column(scale=1, min_width=300):
                    summary_output = gr.Textbox(label="Your Idea Plan", lines=10, elem_classes=["textbox"])
                    
                    with gr.Accordion("Explore More", open=False):
                        followup_input = gr.Textbox(
                            label="Got a question?", 
                            placeholder="e.g., How do I start small?",
                            elem_classes=["textbox"]
                        )
                        followup_btn = gr.Button("Ask Away", elem_classes=["button"])
                        followup_output = gr.Textbox(label="Here’s What We Think", lines=5, elem_classes=["textbox"])
                        gr.Markdown("""
                        ### Need Ideas to Ask?
                        - How can I make this stand out?
                        - Who might love this?
                        - What’s my first step?
                        """)
                
                with gr.Column(scale=1, min_width=300):
                    mindmap_output = gr.Plot(label="Your Interactive Idea Map", elem_classes=["plot"])
            
            with gr.Row(equal_height=False):
                with gr.Column(scale=1, min_width=150):
                    idea_name = gr.Textbox(label="Name Your Idea", placeholder="e.g., GreenCity", elem_classes=["textbox"])
                    save_btn = gr.Button("Save Idea", elem_classes=["button"])
                with gr.Column(scale=1, min_width=150):
                    load_dropdown = gr.Dropdown(label="Pick a Saved Idea", choices=[], elem_classes=["textbox"])
                    load_btn = gr.Button("Load Idea", elem_classes=["button"])

        with gr.Tab("Tips & Inspiration"):
            gr.Markdown("""
            ### Spark Your Next Big Thing!
            - **Example:** *Eco-Friendly Packaging* - Uses plant-based materials and smart tech to cut waste.
            - **Try This:** Think of something you wish worked better—how could an app or gadget fix it?
            - **Tip:** Start small—test your idea with friends first!
            """, elem_classes=["container"])

    # Event handlers
    submit_btn.click(
        fn=lambda: "Bringing your idea to life...",
        inputs=None,
        outputs=progress
    ).then(
        process_input, 
        inputs=[topic_input], 
        outputs=[summary_output, mindmap_output, results_container]
    ).then(
        fn=lambda s: s,
        inputs=[summary_output],
        outputs=[current_summary]
    ).then(
        fn=lambda: "Ready for more questions—keep exploring!",
        inputs=None,
        outputs=progress
    )
    
    followup_btn.click(
        fn=lambda: "Thinking about your question...",
        inputs=None,
        outputs=progress
    ).then(
        process_followup_question,
        inputs=[followup_input, current_summary],
        outputs=[followup_output, mindmap_output]
    ).then(
        fn=lambda: "All set—ask another if you’d like!",
        inputs=None,
        outputs=progress
    )
    
    save_btn.click(
        save_idea,
        inputs=[idea_name, summary_output, mindmap_output, saved_ideas],
        outputs=[load_dropdown, progress]
    )
    
    load_btn.click(
        load_idea,
        inputs=[load_dropdown, saved_ideas],
        outputs=[summary_output, mindmap_output, results_container]
    )

# Launch with error handling
try:
    demo.launch(debug=True, share=True, height=800)  # Set a default height for better mobile scrolling
except Exception as e:
    print(f"Launch error: {e}")
    try:
        demo.launch(debug=True, server_name="0.0.0.0", height=800)
    except Exception as e2:
        print(f"Second launch failed: {e2}")
        print("Try restarting your runtime or checking library installations.")