Update app.py

app.py

@@ -1801,26 +1801,51 @@ This demo presents a GPT-style Multi-Agent AI Assistant, built with **LangChain,
 Feel free to upload a document and ask related questions, or just type a question directly—no file upload required. *Note: CSV file analysis and auto visualisation is coming soon.*
 """
 demo_description6 = """
-This demo showcases a **LangGraph-powered multi-agent pipeline** designed for GPT-like smart document Q&A.
+**Context**:
+This is a **smart multi-document reasoning assistant**, powered by **LangGraph**, **CrewAI**, and **AutoGen**.
+Upload zero to multiple files and ask anything — the system will uses **embedding-based intent detection** to decide whether to summarise, extract, compare, or analyse relationships.
+
+For complex multi-file tasks, it triggers a **collaborative AutoGen team** to deeply reason across documents and generate contextual, evidence-based answers.
 
-🧠 Workflow:
-- Start with a **Document QA Agent**
-- If summarisation is needed → route to **Summariser Agent**
-- If not found in doc → fallback to **General Agent**
-- If still no answer → use **Search Agent**
+**Supported Features**:
+- 📄 Multi-document support (PDF, DOCX, TXT)
+- 🔍 Embedding-based intent detection and semantic routing
+- 🤖 Agents: Summariser, QA Agent, General Agent, Search Agent
+- 🔀 Orchestrated by LangGraph + AutoGen (fallbacks + task handoff)
+- 🧠 AutoGen multi-agent collaboration for cross-file reasoning
+- 🌐 Online search fallback if all the other agent can't handle tasks
 
-Agents are defined via CrewAI, but orchestrated using LangGraph for fine-grained control and agent collaboration.
+**Sample Questions**:
+1. Who are you? | What is GPT4? *(→ General Chat Agent)*
+2. Summarise the document/file/your_doc_name. *(→ Summarisation Agent)*
+3. What is LangChain used for? | What are the latest trends in AI startups in 2025? | Tell me the most recent breakthrough in quantum computing. *(→ Online Rag Agent)*
+4. What's the title in the document? | What are the key ideas mentioned in this file? *(→ RAG QA Agent)*
+5. Compare the proposals in DocA and DocB. | Summarise all files. | Is DocA one of the project in the DocB or DocC. | Which argument is stronger across these files? | Do these documents mention similar policies? | What's the difference between the files? *(→ AutoGen)*
+6. What is LangChain used for? | What are the latest trends in AI startups in 2025? | Tell me the most recent breakthrough in quantum computing. *(→ Online Rag Agent)*
+
+> Built for users who need clear, explainable, and context-aware answers — whether you’re working on documents in law, finance, research, or tech.
 """
 
 
 
 demo = gr.TabbedInterface(
     interface_list=[
+        gr.Interface(
+            fn=langgraph_tab6_main,
+            inputs=[
+                gr.Textbox(label="Ask anything"),
+                gr.File(label="Upload one or more files", file_types=[".pdf", ".txt", ".docx"], file_count="multiple")
+            ],
+            outputs="text",
+            title="Smart Multi-Doc QA (LangGraph + AutoGen)",
+            allow_flagging="never",
+            description=demo_description6
+        ),
         gr.Interface(
             fn=multi_agent_chat_advanced,
             inputs=[
                 gr.Textbox(label="Enter your query"),
-                gr.File(label="Upload file (CSV, PDF, TXT, DOCX)", file_count="single")
+                gr.File(label="Upload file (CSV, PDF, TXT, DOCX)", file_types=[".pdf", ".txt", ".docx"], file_count="single")
             ],
             outputs="text",
             title="Multi-Agent AI Assistant",
@@ -1829,7 +1854,7 @@ demo = gr.TabbedInterface(
         ),
         gr.Interface(
             fn=document_summarize,
-            inputs=[gr.File(label="Upload PDF, TXT, or DOCX")],
+            inputs=[gr.File(label="Upload PDF, TXT, or DOCX",file_types=[".pdf", ".txt", ".docx"])],
             outputs="text",
             title="Document Summarisation",
             allow_flagging="never",
@@ -1837,7 +1862,7 @@ demo = gr.TabbedInterface(
         ),
         gr.Interface(
             fn=upload_and_chat,
-            inputs=[gr.File(label="Upload PDF, TXT, or DOCX"), gr.Textbox(label="Ask a question")],
+            inputs=[gr.File(label="Upload PDF, TXT, or DOCX"), file_types=[".pdf", ".txt", ".docx"], gr.Textbox(label="Ask a question")],
             outputs="text",
             title="Your Docs Q&A (Upload + GPT-4 RAG)",
             allow_flagging="never",
@@ -1859,25 +1884,16 @@ demo = gr.TabbedInterface(
             allow_flagging="never",
             description=demo_description
         ),
-        gr.Interface(
-            fn=langgraph_tab6_main,
-            inputs=[
-                gr.Textbox(label="Ask anything"),
-                gr.File(label="Upload one or more files", file_types=[".pdf", ".txt", ".docx"], file_count="multiple")
-            ],
-            outputs="text",
-            title="LangGraph GPT-like QA (Tab6)",
-            allow_flagging="never",
-            description=demo_description6
-        ),
+        
     ],
     tab_names=[
+        "Smart Multi-Doc QA (LangGraph + AutoGen)",
         "Multi-Agent AI Assistant",
         "Document Summarisation",
         "Your Docs Q&A (Upload + GPT-4 RAG)",
         "Biden Q&A (GPT-4 RAG)",
         "Biden Q&A (LLaMA RAG)",
-        "LangGraph Doc QA (Tab6)"
+        
     ],
     title="Smart RAG + Multi-Agent Assistant (with Web + Document AI)"
 )