Update app.py

app.py

@@ -1,39 +1,47 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-# --- Configuration ---
-MODEL_QWEN = "Qwen/Qwen2.5-Coder-32B-Instruct"
-MODEL_GLM = "THUDM/codegeex4-all-9b"
+# --- Configuration: Model List ---
+# We use a Dictionary to map "Friendly Names" to "Model IDs"
+MODELS = {
+    "Qwen 2.5 Coder 32B (Recommended)": "Qwen/Qwen2.5-Coder-32B-Instruct",
+    "Llama 3.1 8B (Best Logic)": "meta-llama/Meta-Llama-3.1-8B-Instruct",
+    "DeepSeek Coder V2 Lite (Expert)": "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct",
+    "Mistral Nemo 12B (Strong)": "mistralai/Mistral-Nemo-Instruct-2407",
+    "GLM-4 / CodeGeeX4 9B": "THUDM/codegeex4-all-9b"
+}
+
+# Configuration for Memory
+MAX_HISTORY = 5 
 
 def generate_abap(message, history, model_choice):
-    # Select the model based on user dropdown
-    if model_choice == "GLM-4 (CodeGeeX4)":
-        model_id = MODEL_GLM
-    else:
-        model_id = MODEL_QWEN
-        
+    # 1. Get the Hugging Face Model ID from the dropdown selection
+    model_id = MODELS.get(model_choice, "Qwen/Qwen2.5-Coder-7B-Instruct")
+    
     client = InferenceClient()
     
-    # System Prompt specialized for ABAP
     system_prompt = "You are an expert SAP ABAP Developer. Write modern, efficient ABAP 7.4+ code. Always use inline declarations."
-    
-    # --- FIX: Build structured messages for Chat API ---
     messages = [{"role": "system", "content": system_prompt}]
     
-    # Add history
-    for user_msg, bot_msg in history:
-        messages.append({"role": "user", "content": user_msg})
-        messages.append({"role": "assistant", "content": bot_msg})
+    # 2. Add History (Sliding Window)
+    recent_history = history[-MAX_HISTORY:] 
+    
+    for turn in recent_history:
+        # Extract User and Bot messages safely
+        user_msg = turn[0]
+        bot_msg = turn[1]
+        messages.append({"role": "user", "content": str(user_msg)})
+        messages.append({"role": "assistant", "content": str(bot_msg)})
     
-    # Add current message
-    messages.append({"role": "user", "content": message})
+    # 3. Add Current Message
+    messages.append({"role": "user", "content": str(message)})
 
     try:
-        # --- FIX: Use chat_completion (Conversational API) ---
+        # 4. Stream Response
         stream = client.chat_completion(
             model=model_id,
             messages=messages,
-            max_tokens=1024,
+            max_tokens=2048, # Increased token limit for longer code
             temperature=0.1,
             top_p=0.9,
             stream=True
@@ -41,23 +49,22 @@ def generate_abap(message, history, model_choice):
 
         partial_message = ""
         for chunk in stream:
-            # Extract content from the stream delta
             if chunk.choices and chunk.choices[0].delta.content:
-                content = chunk.choices[0].delta.content
-                partial_message += content
+                partial_message += chunk.choices[0].delta.content
                 yield partial_message
                 
     except Exception as e:
-        yield f"Error: The Free API provider rejected the request. \n\nDetails: {str(e)}"
+        yield f"Error: The Free API is overloaded for {model_choice}. Try switching to Qwen or Llama. \n\nDetails: {str(e)}"
 
 # --- The UI ---
 with gr.Blocks( ) as demo:
-    gr.Markdown("# 🚀 ABAP Coder (Serverless GPU)")
-    gr.Markdown("Generate ABAP code using top open-source models running on Hugging Face's Free API.")
+    gr.Markdown("# 🚀 ABAP Coder Multi-Model")
+    gr.Markdown("Select a model below. If one gives an error, try another!")
     
+    # Dropdown with all our new models
     model_selector = gr.Dropdown(
-        choices=["Qwen 2.5 Coder (Recommended)", "GLM-4 (CodeGeeX4)"],
-        value="Qwen 2.5 Coder (Recommended)",
+        choices=list(MODELS.keys()),
+        value="Qwen 2.5 Coder 7B (Recommended)",
         label="Select AI Model"
     )
     
@@ -65,9 +72,9 @@ with gr.Blocks( ) as demo:
         fn=generate_abap,
         additional_inputs=[model_selector],
         examples=[
-            ["Write a report to select data from MARA using inline declarations.", "Qwen 2.5 Coder (Recommended)"],
-            ["Create a CDS View for Sales Orders (VBAK/VBAP).", "Qwen 2.5 Coder (Recommended)"],
-            ["Explain how to use READ TABLE with ASSIGNING FIELD-SYMBOL.", "Qwen 2.5 Coder (Recommended)"]
+            ["Write a report to select data from MARA using inline declarations.", "Qwen 2.5 Coder 7B (Recommended)"],
+            ["Create a CDS View for Sales Orders (VBAK/VBAP).", "Llama 3.1 8B (Best Logic)"],
+            ["Explain how to use READ TABLE with ASSIGNING FIELD-SYMBOL.", "DeepSeek Coder V2 Lite (Expert)"]
         ]
     )