import gradio as gr
from chains.coordinator_chain import coordinator_chain
from chains.frontend_chain import frontend_chain
from chains.backend_chain import backend_chain
from chains.review_chain import review_chain


def ai_pipeline(brief):
    if not brief.strip():
        return "Please enter a valid project brief.", "", "", "", ""

    # Step 1 — Coordinator Agent
    tasks_json = coordinator_chain.run(brief)

    # Step 2 — Frontend Agent
    frontend_code = frontend_chain.run(tasks_json)

    # Step 3 — Backend Agent
    backend_code = backend_chain.run(tasks_json)

    # Step 4 — Review Agent
    review_notes = review_chain.run({
        "tasks": tasks_json,
        "frontend": frontend_code,
        "backend": backend_code
    })

    return tasks_json, frontend_code, backend_code, review_notes


with gr.Blocks(title="AI Project Decomposer") as demo:
    gr.Markdown("# 🤖 AI Project Decomposer (LangChain x HuggingFace)")
    gr.Markdown("Enter a project brief — the AI will split it into frontend/backend tasks and generate code!")

    brief = gr.Textbox(
        lines=6,
        label="Project Brief",
        placeholder="Example: Build a task management app with authentication and task sharing."
    )

    generate_btn = gr.Button("🚀 Generate Technical Plan")

    coordinator_out = gr.Code(label="🧠 Coordinator (Task Breakdown)", language="json")
    frontend_out = gr.Code(label="🎨 Frontend Agent (React Code)", language="javascript")
    backend_out = gr.Code(label="⚙️ Backend Agent (API + Schema)", language="python")
    review_out = gr.Textbox(label="🔍 Review Agent Feedback", lines=6)

    generate_btn.click(
        ai_pipeline,
        inputs=brief,
        outputs=[coordinator_out, frontend_out, backend_out, review_out]
    )

demo.launch()