Update app.py

app.py

@@ -1,6 +1,7 @@
 import gradio as gr
 from azure.search.documents import SearchClient
 from azure.search.documents.models import QueryType
+from azure.core.credentials import AzureKeyCredential
 import requests
 
 # Azure Configuration
@@ -12,7 +13,7 @@ OPENAI_KEY = "B1XyCaz87o456EVD949oODcGC8KTAEQsNLI7Yq5cnYKk41SMY9PtJQQJ99AKACHYHv
 DEPLOYMENT_ID = "gpt-4"
 
 # Azure Cognitive Search Client
-search_client = SearchClient(endpoint=SEARCH_ENDPOINT, index_name=INDEX_NAME, credential=SEARCH_KEY)
+search_client = SearchClient(endpoint=SEARCH_ENDPOINT, index_name=INDEX_NAME, credential=AzureKeyCredential(SEARCH_KEY))
 
 # Function to call Azure OpenAI API
 def call_openai_api(prompt):
@@ -29,25 +30,27 @@ def call_openai_api(prompt):
     response = requests.post(url, headers=headers, json=data)
     if response.status_code == 200:
         return response.json()["choices"][0]["text"].strip()
-    return "Failed to generate a response."
+    return f"Error: {response.status_code} - {response.text}"
 
 # Function to process user queries
 def process_query(question):
-    # Search in Azure Cognitive Search
-    search_results = search_client.search(
-        search_text=question,
-        query_type=QueryType.SIMPLE,
-        top=3
-    )
-    
-    # Extract search results content
-    content = "\n".join([result['content'] for result in search_results])
-    if not content:
-        return "No relevant information found in the indexed documents."
-    
-    # Use OpenAI to generate an enhanced response
-    prompt = f"Use the following content to answer the question:\n{content}\nQuestion: {question}"
-    return call_openai_api(prompt)
+    try:
+        # Search in Azure Cognitive Search
+        search_results = search_client.search(
+            search_text=question,
+            query_type=QueryType.SIMPLE,
+            top=3
+        )
+        # Extract search results content
+        content = "\n".join([result['content'] for result in search_results])
+        if not content:
+            return "No relevant information found in the indexed documents."
+        
+        # Use OpenAI to generate an enhanced response
+        prompt = f"Use the following content to answer the question:\n{content}\nQuestion: {question}"
+        return call_openai_api(prompt)
+    except Exception as e:
+        return f"Error during query processing: {e}"
 
 # Predefined questions
 predefined_questions = [
@@ -60,7 +63,7 @@ predefined_questions = [
 
 # Gradio UI
 def chatbot_ui(question):
-    if question in predefined_questions:
+    if question:
         response = process_query(question)
         return response
     return "Please select a predefined question or enter a valid query."