ea4all-gradio-agents-mcp-hackathon-ui-retrofit

ea4all/ea4all_mcp.py

@@ -369,6 +369,10 @@ with gr.Blocks(title="Your ArchitectGPT",fill_height=True, fill_width=True) as e
         Streamline the architecture operating model, taking the best of agentic workflows and architects working together.
     """
     
+    #Wrapper for functions not to be exposed by the MCP Server
+    wrapper = gr.Button(visible=False) #wrapper.click(UIUtils.ea4all_about, show_api=False,)
+    wrapper1 = gr.Button(visible=False) #wrapper1.click(init_dbr, show_api=False,)
+
     #EA4ALL-Agentic system menu
     with gr.Tabs(selected="how_to") as tabs:
         with gr.Tab(label="Architect Demand Management"):
@@ -403,7 +407,7 @@ with gr.Blocks(title="Your ArchitectGPT",fill_height=True, fill_width=True) as e
             with gr.Tabs(selected="id_dbr") as tabs_reference_architecture:
                 with gr.Tab(label='Business Requirement', id="id_dbr"):
                     gr.Markdown(value=agentic_togaf_desc)
-                    dbr_text=gr.TextArea(value=init_dbr, lines=14, interactive=True)
+                    dbr_text=gr.TextArea(value=wrapper1.click(init_dbr,show_api=False), lines=14, interactive=True)
                     with gr.Row():
                         dbr_file=gr.File(
                             value=e4u._join_paths(BaseConfiguration.ea4all_store, gra.dbr_mock),
@@ -462,10 +466,10 @@ with gr.Blocks(title="Your ArchitectGPT",fill_height=True, fill_width=True) as e
                 container=True,
                 interactive=False,
             )
-            gr.Markdown(UIUtils.ea4all_about)
+            gr.Markdown(value=wrapper.click(UIUtils.ea4all_about, show_api=False))
 
     #Podcast upload progress
-    podcast.change(show_progress='full', show_api=False,)
+    podcast.change(show_progress='full', show_api=False)
    
     #Togaf upload file
     #dbr_file.clear(unload_dbr,outputs=dbr_text)
@@ -474,22 +478,22 @@ with gr.Blocks(title="Your ArchitectGPT",fill_height=True, fill_width=True) as e
     #dbr_cls.click(off_dbrtext,outputs=[dbr_text, tabs_togaf, tab_diagram])
 
     #Refactored ea4all_chatbot / vqa_chatbot (ChatInterface -> Chatbot)
-    qna_prompt.submit(run_qna_agentic_system,[qna_prompt,ea4all_chatbot],ea4all_chatbot)
+    qna_prompt.submit(run_qna_agentic_system,[qna_prompt,ea4all_chatbot],ea4all_chatbot, api_name="landscape_answering_agent")
     #qna_prompt.submit(lambda: "", None, [qna_prompt])
     #ea4all_chatbot.like(fn=get_user_feedback)
     #qna_examples.input(lambda value: value, qna_examples, qna_prompt)
 
     #Execute Reference Architecture
-    dbr_run.click(run_reference_architecture_agentic_system,show_progress='full',inputs=[dbr_text],outputs=[togaf_vision,tabs_togaf,tabs_reference_architecture, architecture_runway, diagram_header, tab_diagram])
+    dbr_run.click(run_reference_architecture_agentic_system,show_progress='full',inputs=[dbr_text],outputs=[togaf_vision,tabs_togaf,tabs_reference_architecture, architecture_runway, diagram_header, tab_diagram], api_name="togaf_blueprint_generation")
 
     chat_msg = vqa_prompt.submit(UIUtils.add_message, [vqa_prompt, ea4all_vqa], [vqa_prompt, ea4all_vqa], show_api=False)
-    bot_msg = chat_msg.then(run_vqa_agentic_system, [vqa_prompt, ea4all_vqa], ea4all_vqa, api_name="bot_response")
+    bot_msg = chat_msg.then(run_vqa_agentic_system, [vqa_prompt, ea4all_vqa], ea4all_vqa, api_name="diagram_answering_agent")
     
     #ea4all_vqa.like(fn=get_user_feedback)
     #vqa_examples.input(lambda value: value, vqa_examples, vqa_prompt)
 
     #Invoke CrewAI PMO Agentic System
-    pmo_prompt.submit(run_pmo_agentic_system,[pmo_prompt,pmo_chatbot],pmo_chatbot)
+    pmo_prompt.submit(run_pmo_agentic_system,[pmo_prompt,pmo_chatbot],pmo_chatbot, api_name="architect_demand_agent")
     pmo_prompt.submit(lambda: "", None, [pmo_prompt], show_api=False)
     #pmo_examples.input(lambda value: value, pmo_examples, pmo_prompt)