Update app.py

updated crawler

app.py

@@ -1,32 +1,49 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+from huggingface_hub import InferenceClient, hf_hub_download
+import json
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
+# Initialize the model client
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+def load_website_data():
+    try:
+        # Download the latest crawl data
+        file_path = hf_hub_download(
+            repo_id="SmokeyBandit/SletcherSystems",
+            filename="data/latest_crawl.json",
+            repo_type="dataset"
+        )
+        with open(file_path, 'r') as f:
+            return json.load(f)
+    except Exception as e:
+        print(f"Error loading website data: {e}")
+        return None
+
+WEBSITE_DATA = load_website_data()
 
 def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
+    message, 
+    history: list[tuple[str, str]], 
+    system_message, 
+    max_tokens, 
+    temperature, 
     top_p,
 ):
+    # Augment system message with website data if available
+    if WEBSITE_DATA:
+        system_message = f"{system_message}\n\nWebsite Content:\n{WEBSITE_DATA['content'][:2000]}"
+    
     messages = [{"role": "system", "content": system_message}]
-
+    
     for val in history:
         if val[0]:
             messages.append({"role": "user", "content": val[0]})
         if val[1]:
             messages.append({"role": "assistant", "content": val[1]})
-
+    
     messages.append({"role": "user", "content": message})
-
+    
     response = ""
-
     for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
@@ -35,18 +52,16 @@ def respond(
         top_p=top_p,
     ):
         token = message.choices[0].delta.content
-
         response += token
         yield response
 
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Textbox(
+            value="You are a friendly chatbot assistant for SletcherSystems. Answer questions based on the website content.",
+            label="System message"
+        ),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
         gr.Slider(
@@ -59,6 +74,5 @@ demo = gr.ChatInterface(
     ],
 )
 
-
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()