app.py

import gradio as gr
from agent import autonomous_agent
from utils import read_memory, append_feedback
from agent_editor import update_agent_code, read_agent_code
import threading, time

current_task = ""
loop_running = False

def run_task(task):
    global current_task
    current_task = task
    result = autonomous_agent(task)
    return result, read_memory()

def update_memory(new_text):
    with open("memory.txt", "w") as f:
        f.write(new_text)
    return "✅ Memory updated."

def view_logs():
    import os, json
    log_entries = []
    if not os.path.exists("logs"):
        return "No logs yet."
    for filename in sorted(os.listdir("logs"))[-5:]:
        with open(f"logs/{filename}", "r") as f:
            data = json.load(f)
            log_entries.append(f"🕒 {data['timestamp']}\n🔧 Task: {data['task']}\n✅ Result: {data['result'][:100]}...\n---")
    return "\n\n".join(log_entries) if log_entries else "No logs found."

def store_feedback(score):
    append_feedback(current_task, "See logs for result", score)
    return "✅ Feedback stored."

def toggle_loop(toggle: bool, interval: int = 30):
    global loop_running
    loop_running = toggle
    if toggle:
        thread = threading.Thread(target=loop_runner, args=(interval,), daemon=True)
        thread.start()
        return "🔁 Loop started."
    else:
        return "⏹️ Loop stopped."

def loop_runner(interval):
    global loop_running
    while loop_running:
        run_task("Autonomous self-improvement")
        time.sleep(interval)

with gr.Blocks() as demo:
    gr.Markdown("# 🤖 Autonomous AI Agent — Enhanced")

    with gr.Tab("💬 Task Runner"):
        chatbot = gr.Textbox(lines=2, label="What should the AI do?")
        submit = gr.Button("Execute")
        output = gr.Textbox(label="Result")
        memory_out = gr.Textbox(label="Memory Snapshot", lines=6)
        submit.click(run_task, inputs=chatbot, outputs=[output, memory_out])

    with gr.Tab("🧠 Memory Editor"):
        mem_editor = gr.Textbox(label="Edit memory.txt", lines=10)
        save_mem = gr.Button("Save Changes")
        result = gr.Textbox(label="Status")
        save_mem.click(update_memory, inputs=mem_editor, outputs=result)
        demo.load(read_memory, inputs=[], outputs=mem_editor)

    with gr.Tab("📁 Recent Logs"):
        log_output = gr.Textbox(label="Last 5 Logs", lines=20)
        refresh_logs = gr.Button("Refresh")
        refresh_logs.click(view_logs, outputs=log_output)
        demo.load(view_logs, outputs=log_output)

    with gr.Tab("⭐ Feedback"):
        gr.Markdown("Rate the last task:")
        feedback_slider = gr.Slider(0, 10, step=0.5, label="Rating")
        submit_fb = gr.Button("Submit Feedback")
        fb_result = gr.Textbox(label="Status")
        submit_fb.click(store_feedback, inputs=feedback_slider, outputs=fb_result)

    with gr.Tab("🔁 Loop Mode"):
        interval = gr.Slider(10, 300, step=10, label="Loop interval (seconds)", value=60)
        toggle = gr.Checkbox(label="Enable Autonomous Loop")
        loop_status = gr.Textbox(label="Loop Status")
        toggle.change(fn=toggle_loop, inputs=[toggle, interval], outputs=loop_status)

    with gr.Tab("🧬 Agent Code Editor"):
        code_box = gr.Code(label="Edit agent.py")
        code_status = gr.Textbox(label="Update Result")
        code_save = gr.Button("Save agent.py")
        demo.load(read_agent_code, outputs=code_box)
        code_save.click(update_agent_code, inputs=code_box, outputs=code_status)

demo.launch()

import gradio as gr
from goal_manager import save_goal, list_goals
from multi_agent import multi_agent_brain

with demo:
    with gr.Tab("🎯 Goal Manager"):
        goal_input = gr.Textbox(label="Set a New Goal")
        goal_status = gr.Textbox(label="Save Result")
        show_goals = gr.Textbox(label="Latest Goals", lines=8)
        save_button = gr.Button("Save Goal")
        refresh_goals = gr.Button("Show Recent Goals")

        save_button.click(fn=save_goal, inputs=goal_input, outputs=goal_status)
        refresh_goals.click(fn=list_goals, outputs=show_goals)
        demo.load(fn=list_goals, outputs=show_goals)

    with gr.Tab("🤖 Multi-Agent Collaboration"):
        group_task = gr.Textbox(label="Shared Task")
        run_group = gr.Button("Collaborate")
        group_output = gr.Textbox(label="Agent Responses", lines=6)
        run_group.click(fn=multi_agent_brain, inputs=group_task, outputs=group_output)