Try explainor-v5 with web_server and script file approach

Write gradio script to file and run as subprocess to
avoid ASGI/SSE streaming issues with Modal proxy.

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

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

modal_app.py

@@ -7,7 +7,7 @@ Run locally: modal serve modal_app.py
 import modal
 
 # Define the Modal app
-app = modal.App("explainor-v4")
+app = modal.App("explainor-v5")
 
 # Create image with dependencies
 image = (
@@ -18,6 +18,7 @@ image = (
         "httpx>=0.25.0",
         "python-dotenv>=1.0.0",
         "fastapi",
+        "uvicorn",
     )
     .add_local_dir("src", remote_path="/app/src", copy=True)
 )
@@ -32,127 +33,139 @@ image = (
     timeout=600,
     scaledown_window=300,
 )
-@modal.asgi_app()
+@modal.web_server(port=7860, startup_timeout=120)
 def serve():
-    """Serve the Gradio app."""
+    """Serve the Gradio app via web_server."""
+    import subprocess
     import sys
+    import os
+
+    os.chdir("/app")
     sys.path.insert(0, "/app")
 
-    import os
-    import tempfile
-    import gradio as gr
-    from fastapi import FastAPI
-    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],
-        )
-
-    # Create FastAPI app and mount Gradio
-    fastapi_app = FastAPI()
-
-    # Mount Gradio app
-    fastapi_app = gr.mount_gradio_app(fastapi_app, demo, path="/")
-
-    return fastapi_app
+    # Write a standalone gradio script
+    script = '''
+import sys
+sys.path.insert(0, "/app")
+
+import os
+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=""):
+    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"
+    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],
+    )
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860, share=False)
+'''
+
+    # Write to file and run
+    with open("/app/run_gradio.py", "w") as f:
+        f.write(script)
+
+    # Run the script with environment variables
+    env = os.environ.copy()
+    subprocess.Popen([sys.executable, "/app/run_gradio.py"], env=env)