Update chat model initialization in main.py to use "qwen-qwq-32b" and add a new ping function in ping.gs for testing the chatbot API response.

main.py

@@ -31,7 +31,7 @@ if not os.environ.get("GROQ_API_KEY"):
 # print(f"GROQ_API_KEY: {os.getenv('GROQ_API_KEY')}")
 # print(f"HUGGING_FACE_API_KEY: {os.getenv('HUGGING_FACE_API_KEY')}")
 
-llm = init_chat_model("deepseek-r1-distill-llama-70b", model_provider="groq", api_key=os.environ["GROQ_API_KEY"])
+llm = init_chat_model("qwen-qwq-32b", model_provider="groq", api_key=os.environ["GROQ_API_KEY"])
 '''
 embeddings = HuggingFaceInferenceAPIEmbeddings(
     api_key = os.getenv('HUGGING_FACE_API_KEY'),

ping.gs

@@ -0,0 +1,40 @@
+function pingChatbot() {
+  // Your FastAPI endpoint URL
+  var url = "https://amanm10000-mlsc-coherence-25-faq-chatbot-api.hf.space/chat";
+  
+  // Create query parameters
+  var params = {
+    "question": "Who are the sponsors baby?"
+  };
+  
+  // Build URL with query parameters
+  var queryString = Object.keys(params)
+    .map(key => key + '=' + encodeURIComponent(params[key]))
+    .join('&');
+  var fullUrl = url + '?' + queryString;
+  
+  // Request options
+  var options = {
+    "method": "get",
+    "muteHttpExceptions": true
+  };
+  
+  try {
+    // Make the request
+    var response = UrlFetchApp.fetch(fullUrl, options);
+    
+    // Get response code and content
+    var responseCode = response.getResponseCode();
+    var responseText = response.getContentText();
+    
+    // Log the response
+    Logger.log("Response Code: " + responseCode);
+    Logger.log("Response: " + responseText);
+    
+    return responseText;
+    
+  } catch (error) {
+    Logger.log("Error: " + error.toString());
+    return "Error: " + error.toString();
+  }
+}