Upgraded gradio interface

app.py

@@ -224,11 +224,11 @@ def upload_file_handler(files):
         return files
     return []
 
-async def generate_plan(history, file_cache, progress=gr.Progress()):
+async def generate_plan(history, file_cache):
     """Generate a plan using the planning prompt and Gemini API"""
     
     # Build conversation history
-    progress(0, desc="Starting")
+    yield "**⏳ Generating plan...** (Starting)"
 
     conversation_history = ""
     if history:
@@ -236,7 +236,7 @@ async def generate_plan(history, file_cache, progress=gr.Progress()):
             conversation_history += f"User: {user_msg}\n"
             if ai_msg:
                 conversation_history += f"Assistant: {ai_msg}\n"
-    progress(0.05, desc="Getting HF MCP tools")
+    yield "**⏳ Generating plan...** (Getting HF MCP tools)"
     try:
         mcp_tool_func = modal.Function.from_name("HuggingFace-MCP","connect_and_get_tools")
         hf_query_gen_tool_details = mcp_tool_func.remote()
@@ -249,14 +249,14 @@ async def generate_plan(history, file_cache, progress=gr.Progress()):
         Tool_Details=hf_query_gen_tool_details
     ) + "\n\n" + conversation_history
     # Get plan from Gemini
-    progress(0.15, desc="Strategizing which tools to call")
+    yield "**⏳ Generating plan...** (Strategizing which tools to call)"
 
     plan = generate_with_gemini(formatted_prompt, "Planning with gemini")
     # Parse the plan
     parsed_plan = parse_json_codefences(plan)
     print(parsed_plan)
     # Call tool to get tool calls
-    progress(0.50, desc="calling HF platform tools and getting data")
+    yield "**⏳ Generating plan...** (calling HF platform tools and getting data)"
 
     try:
         mcp_call_tool_func = modal.Function.from_name(app_name="HuggingFace-MCP",name="call_tool")
@@ -267,7 +267,7 @@ async def generate_plan(history, file_cache, progress=gr.Progress()):
         print(str(e))
         tool_calls = []
     print(tool_calls)
-    progress(0.75, desc="Generating Plan context from tool call info")
+    yield "**⏳ Generating plan...** (Generating Plan context from tool call info)"
 
     if tool_calls!=[]:
         formatted_context_prompt = hf_context_gen_prompt.format(
@@ -284,19 +284,19 @@ async def generate_plan(history, file_cache, progress=gr.Progress()):
             Results="Couldn't generate the tool calls results but use your knowledge about huggingface platform(models, datasets, spaces, training libraries, transfomers library etc.) as backup to generate the plan"
         )
         context = generate_with_gemini(formatted_context_prompt, "Generating context for plan")
-    progress(1, desc="Complete Plan generated")
+    yield context
 
-    return context
-
-def generate_code_with_devstral(plan_text, history, file_cache, progress=gr.Progress()):
+def generate_code_with_devstral(plan_text, history, file_cache):
     """Generate code using the deployed Devstral model via Modal"""
-    progress(0, desc="Starting Codegen")
+    yield "**⏳ Generating code...** (Starting Codegen)"
 
     if not MODAL_AVAILABLE:
-        return "❌ Modal not available. Please install Modal to use code generation."
+        yield "❌ Modal not available. Please install Modal to use code generation."
+        return
     
-    if not plan_text or not plan_text.strip():
-        return "❌ Please generate a plan first before generating code."
+    if not plan_text or not plan_text.strip() or "**Plan will be generated here...**" in plan_text:
+        yield "❌ Please generate a plan first before generating code."
+        return
     
     # try:
         # Extract user query from conversation history
@@ -341,7 +341,7 @@ def generate_code_with_devstral(plan_text, history, file_cache, progress=gr.Prog
     api_key = os.getenv("DEVSTRAL_API_KEY")
     print(f"🚀 Generating code using Devstral...")
     print(f"📡 Connecting to: {base_url}")
-    progress(0.1, desc="Calling Devstral VLLM API server deployed on Modal")
+    yield "**⏳ Generating code...** (Calling Devstral VLLM API server deployed on Modal)"
 
     try:
         devstral_inference_func = modal.Function.from_name("devstral-inference-client", "run_devstral_inference")
@@ -353,28 +353,30 @@ def generate_code_with_devstral(plan_text, history, file_cache, progress=gr.Prog
             mode="single"
         )
         if result and "response" in result:
-            progress(1, desc="Code has been generated")
-
             code_output = result["response"]
-            return f"🚀 **Generated Code:**\n\n{code_output}"
+            yield f"🚀 **Generated Code:**\n\n{code_output}"
         else:
-            progress(1, desc="Error")
-
-            return "❌ **Error:** No response received from Devstral model."
+            yield "❌ **Error:** No response received from Devstral model."
     except Exception as e:
-        progress(1, desc="Error")
-
-        return f"❌ **Error:** {str(e)}"
-def execute_code(code_output, progress=gr.Progress()):
-    progress(0, desc="Starting Code Execution")
+        yield f"❌ **Error:** {str(e)}"
+def execute_code(code_output):
+    """Executes Python code from a string and returns the output."""
+    yield "**⏳ Executing code...** (Starting)"
 
     try:
-        progress(0.05, desc="Parsing Python codefence")
+        if "**Code will be generated here...**" in code_output or "Generated Code" not in code_output:
+            yield "❌ Please generate code first before executing."
+            return
 
+        yield "**⏳ Executing code...** (Parsing code)"
         code = parse_python_codefences(code_output)
         print(code)
-        progress(0.1, desc="Running code in sandbox")
-
+        
+        if not code or not code.strip():
+            yield "❌ No Python code found to execute."
+            return
+        
+        yield "**⏳ Executing code...** (Running in sandbox)"
         result = code_eval(code)
         if isinstance(result, dict):
             result_str = json.dumps(result, indent=4)
@@ -383,13 +385,9 @@ def execute_code(code_output, progress=gr.Progress()):
         else:
             result_str = str(result)
 
-        progress(1, desc="Code Execution Complete")
-
-        return result_str
+        yield f"**✅ Execution Complete:**\n\n```\n{result_str}\n```"
     except Exception as e:
-        progress(1, desc="Error")
-
-        return f"❌ **Error:** {str(e)}"
+        yield f"❌ **Error executing code:** {str(e)}"
         
 # Custom CSS for a sleek design
 custom_css = """
@@ -465,6 +463,14 @@ custom_css = """
     font-size: 1.2em !important;
     margin-bottom: 30px !important;
 }
+
+.output-markdown {
+    height: 250px;
+    overflow-y: auto !important;
+    border: 1px solid #e0e0e0;
+    padding: 10px;
+    border-radius: 5px;
+}
 """
 
 # Create the Gradio interface
@@ -490,18 +496,20 @@ with gr.Blocks(css=custom_css, title="Data Science Requirements Gathering Agent"
             )
 
             plan_output = gr.Markdown(
+                            "**Plan will be generated here...**",
                             label="Generated Plan",
-                            visible=True,
-                            max_height=150,
+                            elem_classes=["output-markdown"],
                         )
 
             code_output = gr.Markdown(
+                            "**Code will be generated here...**",
                             label="Generated Code",
-                            visible=True,max_height=150,
+                            elem_classes=["output-markdown"],
                         )
             execution_output = gr.Markdown(
+                            "**Execution output will be shown here...**",
                             label="Execution Output",
-                            visible=True,max_height=150,
+                            elem_classes=["output-markdown"],
                         )
             with gr.Row():
                 with gr.Column(scale=4):

prompts/devstral_coding_prompt.py

@@ -14,4 +14,6 @@ devstral_code_gen_user_prompt ="""
 {context}
 
 Just return the full execution code block in a python codefence as shown below without any explanation or suffix or prefix text.
+
+Ensure that the code is EXECUTABLE and does not contain any errors.
 """