Reverted to initial CODE

app.py

@@ -1,10 +1,9 @@
 import os
 import gc
+import psutil
 import gradio as gr
 import keras_nlp
 from huggingface_hub import login
-import markdown
-from bs4 import BeautifulSoup
 
 # Get the API key from environment variable
 api_key = os.getenv("HUGGINGFACE_API_KEY")
@@ -18,11 +17,6 @@ login(api_key)
 model_path = "MNLobago/EcoWise_model"
 gemma_lm = keras_nlp.models.GemmaCausalLM.from_preset(f"hf://{model_path}")
 
-# Function to convert Markdown to HTML (preserving the formatting)
-def markdown_to_html(markdown_text):
-    html = markdown.markdown(markdown_text)  # Convert Markdown to HTML
-    return html  # Return the HTML with formatting preserved
-
 class GemmaChat:
     def __init__(self, model, max_length=150, system=""):
         self.model = model
@@ -42,10 +36,7 @@ class GemmaChat:
         response = self.model.generate(prompt, max_length=self.max_length)
         model_response = response.replace(prompt, "").strip()
         
-        # Convert the Markdown response to HTML
-        model_response = markdown_to_html(model_response)
-        
-        # Sanitize the response if necessary (optional)
+        # Sanitize the response
         model_response = model_response.rstrip('?')
 
         # Ensure the response ends with a period if it doesn't end with a punctuation mark
@@ -70,7 +61,7 @@ def chat_with_model(input_text):
 demo = gr.Interface(
     fn=chat_with_model,
     inputs="text",
-    outputs="html",  # Output as HTML to render the formatted response
+    outputs="chatbot",
     description="🌍 Welcome to EcoWise, your go-to climate-savvy chatbot! I'm here to help you."
 )