Create minimal Gradio interface to test basic functionality: Remove all complex components and use only basic elements

app.py

@@ -1,118 +1,32 @@
 import os
 from dotenv import load_dotenv
-import asyncio
 import gradio as gr
 
-from orchestrator.research_orchestrator import ResearchOrchestrator
-from save_to_pdf import save_draft_to_pdf
-
-
 # Load .env (for OPENAI_API_KEY)
 load_dotenv()
 
-
-def _safe_filename(name: str) -> str:
-    import re
-    s = (name or "").strip().replace("\n", " ")
-    s = re.sub(r'[\\/:*?"<>|]', '', s)
-    return s[:100] or "research_paper"
-
-
-async def run_workflow(topic: str):
-    if not topic.strip():
-        return "Please enter a topic.", "", "", ""
-
-    try:
-        orchestrator = ResearchOrchestrator()
-        result = await orchestrator.run(topic)
-
-        # Interrupted for outline review
-        if result.get("status") == "interrupted":
-            current_state = result.get("current_state", {})
-            outline = current_state.get("outline", "")
-            return "Outline generated. Review below.", outline, "", ""
-
-        # Completed directly (edge case)
-        if result.get("status") == "completed":
-            data = result.get("result", {})
-            draft = data.get("draft") or ""
-            pdf_path = f"data/{_safe_filename(data.get('refined_topic', topic))}.pdf"
-            os.makedirs("data", exist_ok=True)
-            try:
-                save_draft_to_pdf(data.get('refined_topic', topic), draft, data.get("bibliography", ""), pdf_path)
-            except Exception:
-                pdf_path = ""
-            return "Workflow completed.", draft, pdf_path, ""
-
-        # Error
-        return f"Error: {result.get('error', 'unknown')}", "", "", ""
-
-    except Exception as e:
-        return f"Error: {str(e)}", "", "", ""
-
-
-async def resume_workflow(decision: str, feedback: str):
-    try:
-        # For now, return a simple message
-        if decision == "approve":
-            return "Outline approved. Generating draft...", "Draft will be generated here.", "", "Draft Preview"
-        elif decision == "revise":
-            return f"Revision requested: {feedback}", "Revised outline will appear here.", "", "Outline Preview"
-        else:
-            return "Workflow rejected.", "", "", "Output Preview"
-    except Exception as e:
-        return f"Error: {str(e)}", "", "", ""
-
-
-# Create a simple interface
-with gr.Blocks(title="Research Draft Generator") as demo:
-    gr.Markdown("# Research Draft Generator")
-    gr.Markdown("Enter a topic to generate a research paper outline and draft.")
-    
-    with gr.Row():
+def simple_interface():
+    """Create the most basic possible Gradio interface"""
+    with gr.Blocks(title="Research Draft Generator") as demo:
+        gr.Markdown("# Research Draft Generator")
+        gr.Markdown("Enter a topic to generate a research paper outline and draft.")
+        
         topic = gr.Textbox(label="Topic", placeholder="e.g., Federated learning for healthcare")
         start_btn = gr.Button("Generate Outline", variant="primary")
-    
-    info = gr.Textbox(label="Status", interactive=False)
-    
-    with gr.Row():
-        with gr.Column():
-            gr.Markdown("### Outline")
-            outline_display = gr.Textbox(label="Generated Outline", lines=10, interactive=False)
         
-        with gr.Column():
-            gr.Markdown("### Draft")
-            draft_display = gr.Textbox(label="Generated Draft", lines=10, interactive=False)
-    
-    with gr.Row():
-        feedback = gr.Textbox(label="Revision feedback", placeholder="What should be improved?")
-        approve = gr.Button("Approve", variant="primary")
-        revise = gr.Button("Request Revision")
-        reject = gr.Button("Reject", variant="secondary")
-    
-    pdf_output = gr.File(label="PDF Output")
-    
-    # Wire actions
-    start_btn.click(
-        run_workflow, 
-        inputs=[topic], 
-        outputs=[info, outline_display, draft_display, pdf_output]
-    )
-    
-    approve.click(
-        lambda: resume_workflow("approve", ""), 
-        outputs=[info, outline_display, draft_display, pdf_output]
-    )
-    
-    revise.click(
-        lambda: resume_workflow("revise", feedback.value), 
-        outputs=[info, outline_display, draft_display, pdf_output]
-    )
+        output = gr.Textbox(label="Output", lines=10, interactive=False)
+        
+        def process_topic(topic_text):
+            if not topic_text.strip():
+                return "Please enter a topic."
+            return f"Processing topic: {topic_text}\n\nThis is a placeholder response. The full functionality will be implemented once the interface is working."
+        
+        start_btn.click(process_topic, inputs=[topic], outputs=[output])
     
-    reject.click(
-        lambda: resume_workflow("reject", ""), 
-        outputs=[info, outline_display, draft_display, pdf_output]
-    )
+    return demo
+
+# Create and launch the interface
+demo = simple_interface()
 
 # Launch the app for Hugging Face Spaces
 port = int(os.getenv("PORT", 7860))

requirements.txt

@@ -1,25 +1,10 @@
 gradio==4.43.0
-transformers
-torch
-numpy
-pandas
-scikit-learn
-matplotlib
-seaborn
-plotly
-streamlit
-langchain
-openai
-langchain-community
-langchain-openai
-anthropic
-tiktoken
-python-dotenv
-requests
-beautifulsoup4
-markdown
-fastapi
-uvicorn
-pydantic>=2
-langgraph>=0.2.30
-reportlab
+langgraph>=0.2.0
+langchain>=0.2.0
+langchain-community>=0.2.0
+langchain-openai>=0.2.0
+langchain-core>=0.2.0
+openai>=1.0.0
+python-dotenv>=1.0.0
+reportlab>=4.0.0
+pydantic>=2