Update app.py

app.py

@@ -1,57 +1,58 @@
 import yaml
+import re
 from smolagents import CodeAgent, HfApiModel
 from tools.final_answer import FinalAnswerTool
 from Gradio_UI import GradioUI
 
-# Simplified system prompt without any code-related instructions
+# 🚀 Updated system prompt: No code recognition or extraction allowed.
 system_prompt = (
     "You are a health and lifestyle advisor specializing in the early detection and prevention of hypertension. "
-    "Provide direct and concise lifestyle advice based on the user's details. "
-    "Output a clear answer as plain text with no extra commentary."
+    "Provide only the final, direct, and concise lifestyle advice based solely on the user's details. "
+    "Do NOT recognize, extract, or output any code snippets, programming-related information, or technical explanations. "
+    "Only output the final advice as plain text. "
+    "For example, if the user mentions alcohol consumption, simply say: 'Reduce alcohol intake, as it can raise blood pressure.'"
 )
 
-def clean_response(text):
-    """
-    Simple cleanup function that removes extra whitespace and ensures proper formatting.
-    """
-    # Remove extra whitespace
-    text = ' '.join(text.split())
-    # Split into paragraphs for readability
-    paragraphs = text.split('\n\n')
-    cleaned_paragraphs = [p.strip() for p in paragraphs if p.strip()]
-    return '\n\n'.join(cleaned_paragraphs)
-
-# Load prompt templates from YAML
-with open("prompts.yaml", 'r') as stream:
-    prompt_templates = yaml.safe_load(stream)
+# 🛑 Function to remove any detected code snippets.
+def remove_code_snippets(text):
+    """Removes potential code snippets from the output."""
+    pattern = r"```.*?```|`[^`]+`"  # Matches both block and inline code
+    return re.sub(pattern, "", text, flags=re.DOTALL).strip()
 
-# Initialize the model with simplified settings
+# ✅ Use only the final_answer tool.
+final_answer = FinalAnswerTool()
+
+# 🎯 Model setup
 model = HfApiModel(
-    max_tokens=1024,
+    max_tokens=2096,
     temperature=0.5,
-    model_id='Qwen/Qwen2.5-Coder-32B-Instruct'
+    model_id='deepseek-ai/DeepSeek-R1-Distill-Qwen-32B',
+    custom_role_conversions=None,
 )
 
-# Initialize CodeAgent with minimal configuration
+# 📖 Load prompt templates from YAML file.
+with open("prompts.yaml", 'r') as stream:
+    prompt_templates = yaml.safe_load(stream)
+
+# 🔄 Initialize CodeAgent (but block code extraction)
 agent = CodeAgent(
     model=model,
-    tools=[FinalAnswerTool()],
-    max_steps=1,
-    verbosity_level=0,
-    name="Health Advisor",
+    tools=[final_answer],  # Restricted to final advice only.
+    max_steps=6,
+    verbosity_level=1,
+    grammar=None,
+    planning_interval=None,
+    name="Hypertension Prevention Advisor",
     description=system_prompt,
     prompt_templates=prompt_templates
 )
 
+# 🛑 Run agent with filtering.
 def run_agent(user_input):
-    """
-    Runs the agent and returns a clean, formatted response.
-    """
-    try:
-        response = agent.run(user_input)
-        return clean_response(response)
-    except Exception as e:
-        return f"I apologize, but I couldn't process your request. Please try again."
-
-# Launch the Gradio UI
+    """Runs the agent and ensures no code snippets are in the output."""
+    raw_response = agent.run(user_input)
+    clean_response = remove_code_snippets(raw_response)  # Filter out code snippets
+    return clean_response
+
+# 🚀 Launch the Gradio UI.
 GradioUI(agent).launch()