Switch to explainor-v3 with direct ASGI app return

Try simpler ASGI approach returning demo.app directly
with queue enabled for concurrency handling.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

modal_app.py

@@ -4,23 +4,21 @@ Deploy with: modal deploy modal_app.py
 Run locally: modal serve modal_app.py
 """
 
-import os
 import modal
 
 # Define the Modal app
-app = modal.App("explainor-v2")
+app = modal.App("explainor-v3")
 
 # Create image with dependencies
 image = (
     modal.Image.debian_slim(python_version="3.11")
     .pip_install(
-        "gradio[mcp]>=5.0.0",
+        "gradio>=5.0.0",
         "elevenlabs>=1.0.0",
         "httpx>=0.25.0",
         "python-dotenv>=1.0.0",
     )
     .add_local_dir("src", remote_path="/app/src", copy=True)
-    .add_local_file("app.py", remote_path="/app/app.py", copy=True)
 )
 
 
@@ -32,128 +30,125 @@ image = (
     ],
     timeout=600,
     scaledown_window=300,
-    min_containers=1,  # Keep one container warm to avoid cold starts
 )
-@modal.web_server(port=7860, startup_timeout=60)
+@modal.asgi_app()
 def serve():
-    """Serve the Gradio app via web_server."""
-    import subprocess
-    import os
+    """Serve the Gradio app."""
+    import sys
+    sys.path.insert(0, "/app")
 
-    # Disable MCP server on Modal
-    os.environ["ENABLE_MCP_SERVER"] = "false"
-    os.chdir("/app")
-
-    # Debug: Print available env vars (without values)
-    print("Available env vars:", [k for k in os.environ.keys() if 'KEY' in k or 'API' in k or 'NEBIUS' in k or 'ELEVEN' in k])
-
-    # Pass environment variables to subprocess
-    env = os.environ.copy()
-
-    # Start Gradio app as subprocess with inherited env
-    subprocess.Popen(["python", "-c", """
-import sys
-sys.path.insert(0, '/app')
-
-import gradio as gr
-from src.personas import get_persona_names, get_persona
-from src.agent import run_agent
-from src.tts import generate_speech
-import tempfile
-
-def format_sources(sources):
-    if not sources:
-        return "*No external sources used*"
-    md = ""
-    for i, src in enumerate(sources, 1):
-        if src.get("url"):
-            md += f"{i}. [{src['title']}]({src['url']})\\n"
-        else:
-            md += f"{i}. {src['title']} ({src.get('source', 'General')})\\n"
-    return md
-
-def format_mcp_tools(tools):
-    if not tools:
-        return "*No tools used*"
-    md = "**Agent Tool Calls:**\\n\\n"
-    for tool in tools:
-        md += f"| {tool['icon']} | `{tool['name']}` | {tool['desc']} |\\n"
-    return md
-
-def explain_topic(topic, persona_name, audience=""):
     import os
-    import traceback
-    if not topic.strip():
-        return "Please enter a topic!", "", "", ""
-    if not persona_name:
-        persona_name = "5-Year-Old"
-
-    # Check API key
-    nebius_key = os.getenv("NEBIUS_API_KEY")
-    if not nebius_key:
-        available_keys = [k for k in os.environ.keys() if 'KEY' in k or 'API' in k or 'NEBIUS' in k]
-        return f"Error: NEBIUS_API_KEY not found. Available: {available_keys}", "", "", ""
-
-    steps_log = []
-    explanation = ""
-    sources = []
-    mcp_tools = []
-    try:
-        for update in run_agent(topic, persona_name, audience):
-            if update["type"] == "step":
-                steps_log.append(f"**{update['title']}**\\n{update['content']}")
-                if update["step"] == "research_done" and "sources" in update:
-                    sources = update["sources"]
-            elif update["type"] == "result":
-                explanation = update["explanation"]
-                sources = update.get("sources", sources)
-                mcp_tools = update.get("mcp_tools", [])
-    except Exception as e:
-        return f"Error: {str(e)}\\n\\n{traceback.format_exc()}", "", "\\n\\n---\\n\\n".join(steps_log), ""
-    return explanation, format_sources(sources), "\\n\\n---\\n\\n".join(steps_log), format_mcp_tools(mcp_tools)
-
-def generate_audio(explanation, persona_name):
-    if not explanation or not explanation.strip():
-        return None
-    if not persona_name:
-        persona_name = "5-Year-Old"
-    persona = get_persona(persona_name)
-    audio_bytes = generate_speech(explanation, persona["voice_id"], persona.get("voice_settings"))
-    with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as f:
-        f.write(audio_bytes)
-        return f.name
-
-with gr.Blocks(title="Explainor") as demo:
-    gr.Markdown("# Explainor\\n### Learn anything through the voice of your favorite characters!")
-    with gr.Row():
-        topic_input = gr.Textbox(label="Topic", placeholder="e.g., Quantum Computing")
-        persona_dropdown = gr.Dropdown(choices=list(get_persona_names()), value="5-Year-Old", label="Persona")
-    audience_dropdown = gr.Dropdown(choices=["Just me", "Confused grandmother", "Skeptical robot", "Alien"], value="Just me", label="Audience")
-    explain_btn = gr.Button("Explain!", variant="primary")
-    explanation_output = gr.Textbox(label="Explanation", lines=6)
-    read_aloud_btn = gr.Button("Read Aloud")
-    audio_output = gr.Audio(label="Listen", type="filepath", autoplay=True)
-    with gr.Accordion("Tools", open=False):
-        mcp_output = gr.Markdown("")
-    with gr.Accordion("Sources", open=False):
-        sources_output = gr.Markdown("")
-    with gr.Accordion("Trace", open=False):
-        steps_output = gr.Markdown("")
-
-    def do_explain(topic, persona, audience):
-        aud = "" if "Just me" in audience else audience
-        return explain_topic(topic, persona, aud)
-
-    explain_btn.click(fn=do_explain, inputs=[topic_input, persona_dropdown, audience_dropdown],
-                      outputs=[explanation_output, sources_output, steps_output, mcp_output])
-    read_aloud_btn.click(fn=generate_audio, inputs=[explanation_output, persona_dropdown], outputs=[audio_output])
-
-demo.launch(server_name="0.0.0.0", server_port=7860)
-"""], env=env)
-
-
-# For local testing
-if __name__ == "__main__":
-    # Run with: python modal_app.py
-    print("Run with: modal serve modal_app.py")
-    print("Or deploy: modal deploy modal_app.py")
+    import tempfile
+    import gradio as gr
+    from src.personas import get_persona_names, get_persona
+    from src.agent import run_agent
+    from src.tts import generate_speech
+
+    def format_sources(sources):
+        if not sources:
+            return "*No external sources used*"
+        md = ""
+        for i, src in enumerate(sources, 1):
+            if src.get("url"):
+                md += f"{i}. [{src['title']}]({src['url']})\n"
+            else:
+                md += f"{i}. {src['title']} ({src.get('source', 'General')})\n"
+        return md
+
+    def format_mcp_tools(tools):
+        if not tools:
+            return "*No tools used*"
+        md = "**Agent Tool Calls:**\n\n"
+        for tool in tools:
+            md += f"| {tool['icon']} | `{tool['name']}` | {tool['desc']} |\n"
+        return md
+
+    def explain_topic(topic, persona_name, audience=""):
+        if not topic.strip():
+            return "Please enter a topic!", "", "", ""
+        if not persona_name:
+            persona_name = "5-Year-Old"
+
+        # Check API key
+        nebius_key = os.getenv("NEBIUS_API_KEY")
+        if not nebius_key:
+            available_keys = [k for k in os.environ.keys() if 'KEY' in k or 'API' in k or 'NEBIUS' in k]
+            return f"Error: NEBIUS_API_KEY not found. Available: {available_keys}", "", "", ""
+
+        steps_log = []
+        explanation = ""
+        sources = []
+        mcp_tools = []
+        try:
+            for update in run_agent(topic, persona_name, audience):
+                if update["type"] == "step":
+                    steps_log.append(f"**{update['title']}**\n{update['content']}")
+                    if update["step"] == "research_done" and "sources" in update:
+                        sources = update["sources"]
+                elif update["type"] == "result":
+                    explanation = update["explanation"]
+                    sources = update.get("sources", sources)
+                    mcp_tools = update.get("mcp_tools", [])
+        except Exception as e:
+            import traceback
+            return f"Error: {str(e)}\n\n{traceback.format_exc()}", "", "\n\n---\n\n".join(steps_log), ""
+        return explanation, format_sources(sources), "\n\n---\n\n".join(steps_log), format_mcp_tools(mcp_tools)
+
+    def generate_audio(explanation, persona_name):
+        if not explanation or not explanation.strip():
+            return None
+        if not persona_name:
+            persona_name = "5-Year-Old"
+        try:
+            persona = get_persona(persona_name)
+            audio_bytes = generate_speech(explanation, persona["voice_id"], persona.get("voice_settings"))
+            with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as f:
+                f.write(audio_bytes)
+                return f.name
+        except Exception as e:
+            raise gr.Error(f"Audio generation failed: {str(e)}")
+
+    # Get persona names as a static list
+    persona_names = list(get_persona_names())
+
+    with gr.Blocks(title="Explainor") as demo:
+        gr.Markdown("# Explainor\n### Learn anything through the voice of your favorite characters!")
+        with gr.Row():
+            topic_input = gr.Textbox(label="Topic", placeholder="e.g., Quantum Computing")
+            persona_dropdown = gr.Dropdown(choices=persona_names, value="5-Year-Old", label="Persona")
+        audience_dropdown = gr.Dropdown(
+            choices=["Just me", "Confused grandmother", "Skeptical robot", "Alien"],
+            value="Just me",
+            label="Audience"
+        )
+        explain_btn = gr.Button("Explain!", variant="primary")
+        explanation_output = gr.Textbox(label="Explanation", lines=6)
+        read_aloud_btn = gr.Button("Read Aloud")
+        audio_output = gr.Audio(label="Listen", type="filepath", autoplay=True)
+        with gr.Accordion("Tools", open=False):
+            mcp_output = gr.Markdown("")
+        with gr.Accordion("Sources", open=False):
+            sources_output = gr.Markdown("")
+        with gr.Accordion("Trace", open=False):
+            steps_output = gr.Markdown("")
+
+        def do_explain(topic, persona, audience):
+            aud = "" if "Just me" in audience else audience
+            return explain_topic(topic, persona, aud)
+
+        explain_btn.click(
+            fn=do_explain,
+            inputs=[topic_input, persona_dropdown, audience_dropdown],
+            outputs=[explanation_output, sources_output, steps_output, mcp_output],
+        )
+        read_aloud_btn.click(
+            fn=generate_audio,
+            inputs=[explanation_output, persona_dropdown],
+            outputs=[audio_output],
+        )
+
+    # Use Gradio's queue with specific settings for Modal
+    demo.queue(default_concurrency_limit=5)
+
+    # Return the ASGI app
+    return demo.app