Update app.py

app.py

@@ -18,44 +18,48 @@ def validate_metadata(metadata):
         return "No metadata provided.", "", ""
     return "Field", "Unused field detected", "Remove it to improve performance"
 
-# Fixed Natural Language Processor
+# Ask AI (Natural Language)
 def process_nlp_query(query):
     if not query.strip():
         return "No query provided."
 
-    # Well-structured prompt to guide the model
-    prompt = f"""You are a helpful software assistant. Answer the following technical question clearly and concisely:\n\n{query}\n\nAnswer:"""
+    # Enhanced prompt
+    prompt = f"""
+    You are a Salesforce and Apex expert. Provide a clear and technically accurate answer to the following question:
+
+    {query}
+
+    Answer:
+    """
 
-    # Generate response with good sampling and repetition control
     result = nlp_model(
         prompt,
-        max_length=200,
+        max_length=256,
         temperature=0.7,
-        top_k=50,
-        repetition_penalty=1.2,
-        do_sample=True,
-        num_return_sequences=1
+        top_k=40,
+        top_p=0.9,
+        repetition_penalty=1.3,
+        do_sample=True
     )
 
-    response = result[0]["generated_text"]
+    output = result[0]["generated_text"]
 
-    # Remove echoed prompt or repetition
-    if "Answer:" in response:
-        response = response.split("Answer:")[-1].strip()
+    # Extract answer after "Answer:"
+    if "Answer:" in output:
+        output = output.split("Answer:")[-1]
 
     # Remove duplicate lines
-    lines = response.splitlines()
-    seen = set()
+    lines = output.strip().splitlines()
     unique_lines = []
+    seen = set()
     for line in lines:
         if line.strip() not in seen:
             seen.add(line.strip())
-            unique_lines.append(line)
-    cleaned_response = "\n".join(unique_lines)
+            unique_lines.append(line.strip())
 
-    return cleaned_response.strip()
+    return "\n".join(unique_lines).strip()
 
-# Gradio Interface
+# Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("# 🤖 AI Code Review & Metadata Validator")
 
@@ -76,8 +80,8 @@ with gr.Blocks() as demo:
         metadata_button.click(validate_metadata, inputs=metadata_input, outputs=[mtype, issue, recommendation])
 
     with gr.Tab("Ask AI (Natural Language)"):
-        query_input = gr.Textbox(label="Your question", lines=2, placeholder="e.g. How to optimize SOQL?")
-        response_output = gr.Textbox(label="AI Response", lines=6)
+        query_input = gr.Textbox(label="Your question", lines=2, placeholder="e.g. What is a governor limit in Apex?")
+        response_output = gr.Textbox(label="AI Response", lines=8)
         nlp_button = gr.Button("Ask")
         nlp_button.click(process_nlp_query, inputs=query_input, outputs=response_output)