Update app.py

app.py

@@ -1,110 +1,180 @@
+# app.py
 import os
 import gradio as gr
-from genesis.pipeline import research_once
-from genesis.visualization import generate_pathway_graph, generate_funding_network
-
-# Environment variables
-OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
-ELEVEN_LABS_API_KEY = os.getenv("ELEVEN_LABS_API_KEY")
-
-# Preloaded 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"
-]
-
-# Custom LCARS biotech theme
-CUSTOM_CSS = """
-body {background-color: #001f1f; color: #ccffcc;}
-.gradio-container {font-family: 'Orbitron', sans-serif;}
-button {background-color: #ff6600 !important; color: white !important;}
-textarea, input {background-color: #003333; color: #ccffcc;}
-.tab-nav {background-color: #004d4d !important;}
-"""
+from genesis.pipeline import (
+    run_literature_mode,
+    run_molecule_mode,
+    run_pathway_mode,
+    run_funding_mode,
+    run_image_mode
+)
+from genesis.utils.pdf_export import export_pdf_report
+
+# Load CSS
+with open(os.path.join("genesis", "static", "style.css"), "r") as f:
+    custom_css = f.read()
+
+HF_SPACE = os.environ.get("HF_SPACE", "false").lower() == "true"
+
+# ---------------------------------------------------------
+# Wrappers to ensure click-to-run functionality
+# ---------------------------------------------------------
+
+def literature_tab(query, narration, export_pdf):
+    result = run_literature_mode(query, narration=narration)
+    pdf_path = None
+    if export_pdf:
+        pdf_path = export_pdf_report(result)
+    return (
+        result.get("summary", ""),
+        result.get("citations", []),
+        result.get("visuals", None),
+        result.get("audio_url", None),
+        pdf_path
+    )
 
-# -------------------- UI Functions -------------------- #
-def run_text_query(query, narration):
-    result = research_once(query, narration=narration)
+def molecule_tab(identifier, narration, export_pdf):
+    result = run_molecule_mode(identifier, narration=narration)
+    pdf_path = None
+    if export_pdf:
+        pdf_path = export_pdf_report(result)
     return (
-        result["summary"],
-        format_citations(result["citations"]),
-        result["visual_image_url"],
-        result["structures"],
-        result["audio_url"] if narration else None
+        result.get("summary", ""),
+        result.get("structure_3d", None),
+        result.get("properties", ""),
+        result.get("audio_url", None),
+        pdf_path
     )
 
-def run_pathway_query(pathway_name):
-    return generate_pathway_graph(pathway_name)
+def pathway_tab(pathway_name, narration, export_pdf):
+    result = run_pathway_mode(pathway_name, narration=narration)
+    pdf_path = None
+    if export_pdf:
+        pdf_path = export_pdf_report(result)
+    return (
+        result.get("summary", ""),
+        result.get("graph_svg", None),
+        result.get("analysis", ""),
+        result.get("audio_url", None),
+        pdf_path
+    )
 
-def run_funding_query(topic):
-    return generate_funding_network(topic)
+def funding_tab(query, narration, export_pdf):
+    result = run_funding_mode(query, narration=narration)
+    pdf_path = None
+    if export_pdf:
+        pdf_path = export_pdf_report(result)
+    return (
+        result.get("summary", ""),
+        result.get("funding_graph", None),
+        result.get("top_investors", ""),
+        result.get("audio_url", None),
+        pdf_path
+    )
 
-def format_citations(citations):
-    if not citations:
-        return "No citations found."
-    md = ""
-    for cite in citations:
-        md += f"- [{cite['type']}]({cite['url']})\n"
-    return md
+def image_tab(image, narration, export_pdf):
+    result = run_image_mode(image, narration=narration)
+    pdf_path = None
+    if export_pdf:
+        pdf_path = export_pdf_report(result)
+    return (
+        result.get("summary", ""),
+        result.get("annotations", None),
+        result.get("enhanced_image", None),
+        result.get("audio_url", None),
+        pdf_path
+    )
 
-# -------------------- Build UI -------------------- #
-with gr.Blocks(css=CUSTOM_CSS, theme="default") as demo:
-    gr.Markdown("# 🧬 GENESIS-AI — Synthetic Biology Command Center")
-    gr.Markdown("**Multi-modal AI platform linking molecules, pathways, funding, and regulations**")
+# ---------------------------------------------------------
+# Build Gradio Interface
+# ---------------------------------------------------------
+with gr.Blocks(css=custom_css, theme=gr.themes.Monochrome()) as demo:
+    gr.Markdown("# 🧬 GENESIS-AI — The Synthetic Biology OS")
+    gr.Markdown("Multi-modal AI for Literature, Molecules, Pathways, Funding, and Images.")
 
-    with gr.Tabs():
-        # ---------- TEXT QUERY TAB ----------
-        with gr.Tab("📜 Literature & Regulatory Analysis"):
+    with gr.Tab("📚 Literature Review"):
+        with gr.Row():
+            query = gr.Textbox(label="Research Query")
             narration = gr.Checkbox(label="Enable Narration", value=False)
-            text_input = gr.Textbox(label="Enter your query", placeholder="Type your synthetic biology research question...")
-            run_btn = gr.Button("Run Research")
-
-            demo_btns = gr.Row()
-            for q in DEMO_QUERIES:
-                demo_btns.add(gr.Button(q))
-
-            summary_out = gr.Textbox(label="Summary")
-            cites_out = gr.Markdown()
-            img_out = gr.Image(label="Generated Diagram")
-            struct_out = gr.JSON(label="Molecular Structures")
-            audio_out = gr.Audio(label="Narration", type="filepath")
-
-            run_btn.click(
-                fn=run_text_query,
-                inputs=[text_input, narration],
-                outputs=[summary_out, cites_out, img_out, struct_out, audio_out]
-            )
-
-            for q in DEMO_QUERIES:
-                demo_btns.children[DEMO_QUERIES.index(q)].click(
-                    fn=run_text_query,
-                    inputs=[gr.Textbox(value=q, visible=False), narration],
-                    outputs=[summary_out, cites_out, img_out, struct_out, audio_out]
-                )
-
-        # ---------- PATHWAY TAB ----------
-        with gr.Tab("🧪 Metabolic Pathway Mapping"):
-            pathway_input = gr.Textbox(label="Pathway Name", placeholder="e.g., artemisinin biosynthesis")
-            pathway_btn = gr.Button("Generate Pathway Graph")
-            pathway_graph_out = gr.Image(label="Pathway Graph")
-            pathway_btn.click(run_pathway_query, inputs=pathway_input, outputs=pathway_graph_out)
-
-        # ---------- FUNDING TAB ----------
-        with gr.Tab("💰 Funding & Investor Networks"):
-            funding_input = gr.Textbox(label="Topic", placeholder="e.g., synthetic biology oncology startups")
-            funding_btn = gr.Button("Generate Funding Map")
-            funding_graph_out = gr.Image(label="Funding Network")
-            funding_btn.click(run_funding_query, inputs=funding_input, outputs=funding_graph_out)
-
-        # ---------- IMAGE ANALYSIS TAB ----------
-        with gr.Tab("🖼️ Microscopy / Image Analysis"):
-            img_upload = gr.Image(type="filepath", label="Upload Image")
-            img_btn = gr.Button("Analyze Image")
-            img_analysis_out = gr.Textbox(label="Analysis Result")
-            # Hook to your vision model here
-            img_btn.click(lambda img: f"Analysis for {img}", inputs=img_upload, outputs=img_analysis_out)
-
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+            export_pdf = gr.Checkbox(label="Export PDF", value=False)
+        run_btn = gr.Button("Run Literature Review 🚀")
+        summary = gr.Textbox(label="Summary", lines=10)
+        citations = gr.JSON(label="Citations")
+        visuals = gr.Image(label="Visuals")
+        audio_url = gr.Audio(label="Narration Audio")
+        pdf_out = gr.File(label="Download PDF")
+        run_btn.click(
+            literature_tab,
+            inputs=[query, narration, export_pdf],
+            outputs=[summary, citations, visuals, audio_url, pdf_out]
+        )
+
+    with gr.Tab("🧪 Molecule Explorer"):
+        identifier = gr.Textbox(label="Molecule Name / Gene ID")
+        narration2 = gr.Checkbox(label="Enable Narration", value=False)
+        export_pdf2 = gr.Checkbox(label="Export PDF", value=False)
+        run_btn2 = gr.Button("Run Molecule Analysis 🔍")
+        summary2 = gr.Textbox(label="Summary", lines=10)
+        structure_3d = gr.HTML(label="3D Structure Viewer")
+        properties = gr.Textbox(label="Properties")
+        audio_url2 = gr.Audio(label="Narration Audio")
+        pdf_out2 = gr.File(label="Download PDF")
+        run_btn2.click(
+            molecule_tab,
+            inputs=[identifier, narration2, export_pdf2],
+            outputs=[summary2, structure_3d, properties, audio_url2, pdf_out2]
+        )
+
+    with gr.Tab("🧬 Pathway Mapper"):
+        pathway_name = gr.Textbox(label="Pathway Name")
+        narration3 = gr.Checkbox(label="Enable Narration", value=False)
+        export_pdf3 = gr.Checkbox(label="Export PDF", value=False)
+        run_btn3 = gr.Button("Run Pathway Mapping 🧩")
+        summary3 = gr.Textbox(label="Summary", lines=10)
+        graph_svg = gr.HTML(label="Pathway Graph")
+        analysis = gr.Textbox(label="Analysis")
+        audio_url3 = gr.Audio(label="Narration Audio")
+        pdf_out3 = gr.File(label="Download PDF")
+        run_btn3.click(
+            pathway_tab,
+            inputs=[pathway_name, narration3, export_pdf3],
+            outputs=[summary3, graph_svg, analysis, audio_url3, pdf_out3]
+        )
+
+    with gr.Tab("💰 Funding Network"):
+        funding_query = gr.Textbox(label="Funding Query (global)")
+        narration4 = gr.Checkbox(label="Enable Narration", value=False)
+        export_pdf4 = gr.Checkbox(label="Export PDF", value=False)
+        run_btn4 = gr.Button("Run Funding Analysis 🌍")
+        summary4 = gr.Textbox(label="Summary", lines=10)
+        funding_graph = gr.HTML(label="Funding Network Graph")
+        top_investors = gr.Textbox(label="Top Investors")
+        audio_url4 = gr.Audio(label="Narration Audio")
+        pdf_out4 = gr.File(label="Download PDF")
+        run_btn4.click(
+            funding_tab,
+            inputs=[funding_query, narration4, export_pdf4],
+            outputs=[summary4, funding_graph, top_investors, audio_url4, pdf_out4]
+        )
+
+    with gr.Tab("🖼️ Image Analysis"):
+        img_input = gr.Image(type="filepath", label="Upload Microscopy or Diagram")
+        narration5 = gr.Checkbox(label="Enable Narration", value=False)
+        export_pdf5 = gr.Checkbox(label="Export PDF", value=False)
+        run_btn5 = gr.Button("Run Image Analysis 🖼️")
+        summary5 = gr.Textbox(label="Summary", lines=10)
+        annotations = gr.Image(label="Annotated Image")
+        enhanced_image = gr.Image(label="Enhanced Image")
+        audio_url5 = gr.Audio(label="Narration Audio")
+        pdf_out5 = gr.File(label="Download PDF")
+        run_btn5.click(
+            image_tab,
+            inputs=[img_input, narration5, export_pdf5],
+            outputs=[summary5, annotations, enhanced_image, audio_url5, pdf_out5]
+        )
+
+# ---------------------------------------------------------
+# Launch
+# ---------------------------------------------------------
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860, share=HF_SPACE)