sasas

app.py

@@ -741,4 +741,114 @@ def parse_analysis_sections(analysis_text):
         elif line.startswith("# Perspectives"):
             current_section = "Perspectives"
             continue
-        elif line.startswith
+        elif line.startswith("# Implications"):
+            current_section = "Implications"
+            continue
+        elif line.startswith("# Controversies"):
+            current_section = "Controversies"
+            continue
+        
+        if current_section:
+            sections[current_section] += line + "\n"
+    
+    return sections
+
+def research_assistant(query, file, use_ddg, progress=gr.Progress()):
+    """Main entry point for the research assistant with streaming"""
+    logging.info(f"Research assistant called with query: {query}")
+    for step in orchestrator.run(query, file, use_ddg, progress):
+        yield step
+
+# Create Gradio interface
+with gr.Blocks(
+    css=custom_css, 
+    title="Research Assistant",
+    head="""
+        <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/styles/github-dark.min.css">
+        <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/highlight.min.js"></script>
+        <script>hljs.highlightAll();</script>
+    """
+) as demo:
+    gr.Markdown(f"""
+    <div class="header">
+        <h1 class="title">🧠 AI Research Assistant</h1>
+        <p class="subtitle">Your intelligent research companion</p>
+        <div class="version-info">🧬 Version: {VERSION['version']}</div>
+    </div>
+    """)
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            with gr.Group(elem_classes=["card", "input-section"]):
+                gr.Markdown("### 🔍 Research Input")
+                query_input = gr.Textbox(
+                    label="Research Query",
+                    placeholder="Enter your research question...",
+                    lines=3
+                )
+                file_upload = gr.File(
+                    label="📄 Upload Files (PDF, Images)",
+                    file_types=[".pdf", ".png", ".jpg", ".jpeg"]
+                )
+                ddg_checkbox = gr.Checkbox(
+                    label="Use DuckDuckGo Search (Alternative)",
+                    value=False
+                )
+                submit_btn = gr.Button("Research", elem_classes=["btn-primary"])
+        
+        with gr.Column(scale=2):
+            with gr.Group(elem_classes=["card", "output-section"]):
+                gr.Markdown("### 📊 Analysis Results")
+                
+                # Progress bar
+                progress_container = gr.HTML("""
+                    <div class="progress-container">
+                        <div class="progress-bar" id="progress-bar"></div>
+                    </div>
+                """)
+                
+                # Collapsible sections
+                with gr.Accordion("🔍 Overview", open=True):
+                    overview = gr.Markdown()
+                
+                with gr.Accordion("📊 Key Findings", open=False):
+                    findings = gr.Markdown()
+                
+                with gr.Accordion("🧭 Perspectives", open=False):
+                    perspectives = gr.Markdown()
+                
+                with gr.Accordion("🔮 Implications", open=False):
+                    implications = gr.Markdown()
+                
+                with gr.Accordion("⚠️ Controversies", open=False):
+                    controversies = gr.Markdown()
+                
+                status_indicator = gr.HTML("""
+                <div class="status-indicator">
+                    <div class="spinner"></div>
+                    <span class="progress-text">Ready for your research query</span>
+                </div>
+                """)
+    
+    submit_btn.click(
+        fn=research_assistant,
+        inputs=[query_input, file_upload, ddg_checkbox],
+        outputs=[overview, findings, perspectives, implications, controversies]
+    )
+    
+    query_input.submit(
+        fn=research_assistant,
+        inputs=[query_input, file_upload, ddg_checkbox],
+        outputs=[overview, findings, perspectives, implications, controversies]
+    )
+    
+    gr.Markdown("""
+    <div class="footer">
+        <p>Built with ❤️ for researchers worldwide</p>
+        <p><span class="highlight">Features:</span> File upload • Web search • Real-time analysis</p>
+        <p><strong>Note:</strong> The AI model server may take up to 4-5 minutes to start initially.</p>
+    </div>
+    """)
+
+if __name__ == "__main__":
+    demo.launch(share=True)