app.py

import gradio as gr
import pandas as pd
import json
import random
import requests
import os
from datetime import datetime
from tinytroupe.simulation_manager import SimulationManager, SimulationConfig
from tinytroupe.agent.social_types import Content
from tinytroupe.agent.tiny_person import TinyPerson
import tinytroupe.openai_utils as openai_utils

# Initialize Simulation Manager
simulation_manager = SimulationManager()
REMOTE_BACKEND = "https://auxteam-tiny-factory.hf.space"

def generate_personas(business_description, customer_profile, num_personas, api_key=None):
    if api_key: os.environ["BLABLADOR_API_KEY"] = api_key
    use_remote = random.random() < 0.5
    if use_remote:
        try:
            response = requests.post(f"{REMOTE_BACKEND}/api/generate_personas", json={"data": [business_description, customer_profile, num_personas, ""]}, timeout=120)
            if response.status_code == 200: return response.json()["data"][0]
        except: pass
    from tinytroupe.factory.tiny_person_factory import TinyPersonFactory
    factory = TinyPersonFactory(context=f"{business_description} {customer_profile}", total_population_size=int(num_personas))
    personas = factory.generate_people(number_of_people=int(num_personas))
    return [p._persona for p in personas]

def start_simulation(name, content_text, format_type, persona_count, network_type):
    config = SimulationConfig(name=name, persona_count=int(persona_count), network_type=network_type)
    sim = simulation_manager.create_simulation(config)
    content = Content(text=content_text, format=format_type)
    simulation_manager.run_simulation(sim.id, content)
    
    nodes = [{"id": p.name, "label": p.name, "title": f"<b>{p.name}</b><br>{p.minibio()}", "full_bio": json.dumps(p._persona, indent=2)} for p in sim.personas]
    edges = [{"from": e.connection_id.split('_')[0], "to": e.connection_id.split('_')[1]} for e in sim.network.edges]
    analysis_df = pd.DataFrame(sim.analysis_results)
    if analysis_df.empty: analysis_df = pd.DataFrame(columns=["persona_name", "opinion", "analysis", "implications"])
    
    return analysis_df, nodes, edges, sim.id

def get_persona_details(sim_id, persona_name):
    persona = simulation_manager.get_persona(sim_id, persona_name)
    return json.dumps(persona, indent=2) if persona else "Not found"

# API functions for backward compatibility
def generate_social_network_api(name, persona_count, network_type, focus_group_name=None):
    config = SimulationConfig(name=name, persona_count=int(persona_count), network_type=network_type)
    sim = simulation_manager.create_simulation(config, focus_group_name)
    return {"simulation_id": sim.id, "persona_count": len(sim.personas)}

def predict_engagement_api(simulation_id, content_text, format_type):
    sim = simulation_manager.get_simulation(simulation_id)
    if not sim: return {"error": "Simulation not found"}
    content = Content(text=content_text, format=format_type)
    results = []
    for p in sim.personas:
        reaction = p.predict_reaction(content)
        results.append({"persona": p.name, "will_engage": reaction.will_engage, "probability": reaction.probability})
    return results

def start_simulation_async_api(simulation_id, content_text, format_type):
    content = Content(text=content_text, format=format_type)
    simulation_manager.run_simulation(simulation_id, content, background=True)
    return {"status": "started", "simulation_id": simulation_id}

def get_simulation_status_api(simulation_id):
    sim = simulation_manager.get_simulation(simulation_id)
    if not sim: return {"error": "Simulation not found"}
    return {"status": sim.status, "progress": sim.progress}

def send_chat_message_api(simulation_id, sender, message):
    return simulation_manager.send_chat_message(simulation_id, sender, message)

def get_chat_history_api(simulation_id):
    return simulation_manager.get_chat_history(simulation_id)

def generate_variants_api(original_content, num_variants):
    variants = simulation_manager.variant_generator.generate_variants(original_content, int(num_variants))
    return [v.text for v in variants]

def list_simulations_api():
    return simulation_manager.list_simulations()

def list_personas_api(simulation_id):
    return simulation_manager.list_personas(simulation_id)

def get_persona_api(simulation_id, persona_name):
    return simulation_manager.get_persona(simulation_id, persona_name)

def delete_simulation_api(simulation_id):
    success = simulation_manager.delete_simulation(simulation_id)
    return {"success": success}

def export_simulation_api(simulation_id):
    return simulation_manager.export_simulation(simulation_id)

def get_network_graph_api(simulation_id):
    sim = simulation_manager.get_simulation(simulation_id)
    if not sim: return {"error": "Simulation not found"}
    nodes = [{"id": p.name, "label": p.name, "role": p._persona.get("occupation")} for p in sim.personas]
    edges = [{"source": e.connection_id.split('_')[0], "target": e.connection_id.split('_')[1]} for e in sim.network.edges]
    return {"nodes": nodes, "edges": edges}

def list_focus_groups_api():
    return simulation_manager.list_focus_groups()

def save_focus_group_api(name, simulation_id):
    sim = simulation_manager.get_simulation(simulation_id)
    if not sim: return {"error": "Simulation not found"}
    simulation_manager.save_focus_group(name, sim.personas)
    return {"status": "success", "name": name}

# UI Layout
with gr.Blocks(css=".big-input textarea { height: 300px !important; } #mesh-network-container { height: 600px; background: #101622; border-radius: 12px; }", title="Tiny Factory") as demo:
    gr.HTML('<script src="https://unpkg.com/vis-network/standalone/umd/vis-network.min.js"></script>')
    gr.Markdown("# 🌐 Tiny Factory: Social Simulation Dashboard")
    
    current_sim_id = gr.State()
    
    with gr.Tabs():
        with gr.Tab("Simulation Dashboard"):
            with gr.Row():
                with gr.Column(scale=1):
                    gr.Markdown("### 📝 Content Input")
                    sim_name = gr.Textbox(label="Simulation Name", value="Market Pulse")
                    content_input = gr.Textbox(label="Content (Blog, LinkedIn, etc.)", lines=10, elem_classes="big-input")
                    content_format = gr.Dropdown(choices=["Blog Post", "LinkedIn Update", "Tweet", "Email"], label="Format", value="LinkedIn Update")
                    num_personas_sim = gr.Slider(minimum=5, maximum=50, value=10, step=1, label="Number of Personas")
                    network_type_sim = gr.Dropdown(choices=["scale_free", "small_world"], label="Network Topology", value="scale_free")
                    run_btn = gr.Button("🚀 Run Simulation", variant="primary")
                with gr.Column(scale=2):
                    gr.Markdown("### 🕸️ Persona Mesh Network (Hover for Bio, Click for Details)")
                    gr.HTML('<div id="mesh-network-container"></div>')
                    with gr.Accordion("Detailed Persona Profile", open=False):
                        detail_name = gr.Textbox(label="Name", interactive=False)
                        detail_json = gr.Code(label="Profile JSON", language="json")
            gr.Markdown("### 📊 Simulation Analysis & Implications (Helmholtz alias-huge)")
            analysis_table = gr.Dataframe(headers=["persona_name", "opinion", "analysis", "implications"], label="Analysis Results")

        with gr.Tab("Persona Generator"):
             with gr.Row():
                with gr.Column():
                    biz_desc = gr.Textbox(label="Business Description", lines=5)
                    cust_prof = gr.Textbox(label="Customer Profile", lines=5)
                    gen_count = gr.Number(label="Count", value=5)
                    blablador_key = gr.Textbox(label="API Key (Optional)", type="password")
                    gen_btn = gr.Button("Generate Personas")
                with gr.Column():
                    gen_out = gr.JSON(label="Generated Personas")

    nodes_state = gr.State([])
    edges_state = gr.State([])
    
    # Hidden components for JS interaction
    js_trigger = gr.Textbox(visible=False, elem_id="js_trigger_textbox")
    js_trigger_btn = gr.Button("trigger", visible=False, elem_id="js_trigger_btn")

    run_btn.click(
        fn=start_simulation,
        inputs=[sim_name, content_input, content_format, num_personas_sim, network_type_sim],
        outputs=[analysis_table, nodes_state, edges_state, current_sim_id]
    ).then(
        fn=None, inputs=[nodes_state, edges_state], outputs=None,
        js="""(nodes, edges) => {
            const container = document.getElementById('mesh-network-container');
            const data = { nodes: new vis.DataSet(nodes), edges: new vis.DataSet(edges) };
            const options = { 
                nodes: { shape: 'dot', size: 25, font: { color: '#fff', size: 16 }, color: { background: '#135bec', border: '#fff' }, shadow: true }, 
                edges: { color: 'rgba(19,91,236,0.4)', width: 2, smooth: { type: 'continuous' } }, 
                physics: { enabled: true, stabilization: false, barnesHut: { gravitationalConstant: -3000 } } 
            };
            const network = new vis.Network(container, data, options);
            network.on("click", (params) => {
                if(params.nodes.length) {
                    const node = nodes.find(n => n.id === params.nodes[0]);
                    const trigger = document.getElementById('js_trigger_textbox').querySelector('input');
                    trigger.value = node.id;
                    trigger.dispatchEvent(new Event('input'));
                    document.getElementById('js_trigger_btn').click();
                }
            });
            setInterval(() => { network.stopSimulation(); network.startSimulation(); }, 4000);
        }"""
    )

    def on_persona_click(name, sim_id):
        details = simulation_manager.get_persona(sim_id, name)
        return name, json.dumps(details, indent=2)

    js_trigger_btn.click(on_persona_click, inputs=[js_trigger, current_sim_id], outputs=[detail_name, detail_json])

    gen_btn.click(generate_personas, inputs=[biz_desc, cust_prof, gen_count, blablador_key], outputs=gen_out, api_name="generate_personas")

    # API endpoints (backward compatibility)
    with gr.Tab("API", visible=False):
        gr.Button("find_best_persona").click(lambda x: {"message": "Searching: "+x}, inputs=[gr.Textbox()], outputs=gr.JSON(), api_name="find_best_persona")
        gr.Button("generate_social_network").click(generate_social_network_api, inputs=[gr.Textbox(), gr.Number(), gr.Dropdown(choices=["scale_free", "small_world"]), gr.Textbox()], outputs=gr.JSON(), api_name="generate_social_network")
        gr.Button("predict_engagement").click(predict_engagement_api, inputs=[gr.Textbox(), gr.Textbox(), gr.Textbox()], outputs=gr.JSON(), api_name="predict_engagement")
        gr.Button("start_simulation_async").click(start_simulation_async_api, inputs=[gr.Textbox(), gr.Textbox(), gr.Textbox()], outputs=gr.JSON(), api_name="start_simulation_async")
        gr.Button("get_simulation_status").click(get_simulation_status_api, inputs=[gr.Textbox()], outputs=gr.JSON(), api_name="get_simulation_status")
        gr.Button("send_chat_message").click(send_chat_message_api, inputs=[gr.Textbox(), gr.Textbox(), gr.Textbox()], outputs=gr.JSON(), api_name="send_chat_message")
        gr.Button("get_chat_history").click(get_chat_history_api, inputs=[gr.Textbox()], outputs=gr.JSON(), api_name="get_chat_history")
        gr.Button("generate_variants").click(generate_variants_api, inputs=[gr.Textbox(), gr.Number()], outputs=gr.JSON(), api_name="generate_variants")
        gr.Button("list_simulations").click(list_simulations_api, outputs=gr.JSON(), api_name="list_simulations")
        gr.Button("list_personas").click(list_personas_api, inputs=[gr.Textbox()], outputs=gr.JSON(), api_name="list_personas")
        gr.Button("get_persona").click(get_persona_api, inputs=[gr.Textbox(), gr.Textbox()], outputs=gr.JSON(), api_name="get_persona")
        gr.Button("delete_simulation").click(delete_simulation_api, inputs=[gr.Textbox()], outputs=gr.JSON(), api_name="delete_simulation")
        gr.Button("export_simulation").click(export_simulation_api, inputs=[gr.Textbox()], outputs=gr.JSON(), api_name="export_simulation")
        gr.Button("get_network_graph").click(get_network_graph_api, inputs=[gr.Textbox()], outputs=gr.JSON(), api_name="get_network_graph")
        gr.Button("list_focus_groups").click(list_focus_groups_api, outputs=gr.JSON(), api_name="list_focus_groups")
        gr.Button("save_focus_group").click(save_focus_group_api, inputs=[gr.Textbox(), gr.Textbox()], outputs=gr.JSON(), api_name="save_focus_group")

if __name__ == "__main__":
    demo.launch()