app.py

import gradio as gr
from genesis.pipeline import research_once
from genesis.visualization import generate_pathway_graph, generate_funding_network

# Preloaded killer demo queries
DEMO_QUERIES = [
    "CRISPR living therapeutics in clinical trials since 2020",
    "AI-designed enzymes for plastic degradation — literature + pathways",
    "Synthetic biology startups in oncology — funding map",
    "Metabolic pathway for artemisinin biosynthesis in yeast",
    "Oncolytic virus engineering — biosecurity risk analysis"
]

def run_literature_review(query):
    report = research_once(query)
    return (
        report["summary"],
        report["citations"],
        report["structures"],
        report["visual_image_url"],
        report["audio_url"]
    )

def run_pathway_graph():
    entities = ["CRISPR", "Cas9", "DNA Repair", "Therapeutic Delivery"]
    relationships = [
        {"source": "CRISPR", "target": "Cas9", "type": "guides"},
        {"source": "Cas9", "target": "DNA Repair", "type": "triggers"},
        {"source": "DNA Repair", "target": "Therapeutic Delivery", "type": "enables"}
    ]
    return generate_pathway_graph(entities, relationships)

def run_funding_network():
    companies = [
        {"name": "SynBioCorp", "investors": "Sequoia Capital, Andreessen Horowitz"},
        {"name": "BioTheraX", "investors": "SoftBank, ARCH Venture Partners"}
    ]
    return generate_funding_network(companies)

with gr.Blocks(theme=gr.themes.Soft(primary_hue="emerald", secondary_hue="lime")) as app:
    gr.Markdown("# 🧬 GENESIS-AI — Synthetic Biology Command Center")
    gr.Markdown("A next-generation **lab instrument** for literature review, pathway mapping, funding analysis, and biosecurity insights.")

    with gr.Row():
        query_input = gr.Textbox(label="Enter your research query", placeholder="e.g., CRISPR living therapeutics in clinical trials since 2020", lines=2)
        run_button = gr.Button("🚀 Run Literature Review", variant="primary")

    gr.Markdown("### 🔹 Or click a demo query:")
    with gr.Row():
        demo_btns = []
        for dq in DEMO_QUERIES:
            btn = gr.Button(dq)
            btn.click(fn=lambda q=dq: run_literature_review(q),
                      inputs=[],
                      outputs=["summary_box", "citations_box", "structures_box", "image_out", "audio_out"])
            demo_btns.append(btn)

    with gr.Tab("📄 Summary"):
        summary_box = gr.Textbox(label="AI-Generated Summary", lines=15, interactive=False)

    with gr.Tab("📚 Citations"):
        citations_box = gr.JSON(label="Citations")

    with gr.Tab("🧪 Structures"):
        structures_box = gr.JSON(label="3D Molecular Structures")

    with gr.Tab("🖼 Diagram"):
        image_out = gr.Image(label="Generated Diagram")

    with gr.Tab("🔊 Narration"):
        audio_out = gr.Audio(label="Narrated Summary", type="filepath")

    gr.Markdown("## 🧭 Additional Tools")

    with gr.Row():
        pathway_btn = gr.Button("🧬 Generate Pathway Graph")
        pathway_img = gr.Image(label="Pathway Graph")
        pathway_btn.click(fn=run_pathway_graph, inputs=[], outputs=pathway_img)

        funding_btn = gr.Button("💰 Generate Funding Network")
        funding_img = gr.Image(label="Funding Network")
        funding_btn.click(fn=run_funding_network, inputs=[], outputs=funding_img)

    # Link main run button
    run_button.click(
        fn=run_literature_review,
        inputs=query_input,
        outputs=[summary_box, citations_box, structures_box, image_out, audio_out]
    )

app.launch()