Update app.py

app.py

@@ -18,13 +18,13 @@ def get_text_from_url(url):
     visible_texts = filter(tag_visible, texts)
     return "\n".join(t.strip() for t in visible_texts)
 
-# Pre-fetch and truncate homepage text to reduce prompt length
+# Pre-fetch and truncate homepage text to keep the prompt concise
 text_list = []
 homepage_url = "https://sites.google.com/view/abhilashnandy/home/"
 extensions = ["", "pmrf-profile-page"]
 for ext in extensions:
     full_text = get_text_from_url(homepage_url + ext)
-    truncated_text = full_text[:1000]  # using first 1000 characters to keep prompt short
+    truncated_text = full_text[:1000]  # use only the first 1000 characters per page
     text_list.append(truncated_text)
 
 SYSTEM_MESSAGE = (
@@ -32,9 +32,8 @@ SYSTEM_MESSAGE = (
     "Context: " + " ".join(text_list)
 )
 
-# Switch to a model optimized for low-latency CPU inference.
-# Here we use a GPT4All model (assuming one is available via the Inference API).
-client = InferenceClient("nomic-ai/gpt4all-lora")
+# Switch to a model that is known to have a valid config and is optimized for CPU inference.
+client = InferenceClient("nomic-ai/gpt4all-j")
 
 def respond(message, history: list[tuple[str, str]], system_message=SYSTEM_MESSAGE,
             max_tokens=100, temperature=0.7, top_p=0.95):
@@ -44,7 +43,7 @@ def respond(message, history: list[tuple[str, str]], system_message=SYSTEM_MESSA
         messages.append({"role": "assistant", "content": "Answer: " + a})
     messages.append({"role": "user", "content": message})
     try:
-        # Use streaming mode to return tokens as they are generated
+        # Use streaming mode to start receiving output as it is generated.
         response_stream = client.chat_completion(
             messages,
             max_tokens=max_tokens,
@@ -70,7 +69,7 @@ with demo:
     gr.Markdown(markdown_note)
     gr.ChatInterface(
         fn=respond,
-        # examples=["Yo who dis Abhilash?", "What is Abhilash's most recent publication?"],
+        examples=["Yo who dis Abhilash?", "What is Abhilash's most recent publication?"],
         additional_inputs=[],
     )