Update app.py

app.py

@@ -1,74 +1,78 @@
+import os
+import time
 import requests
 import gradio as gr
 
-# Azure OpenAI Service configuration
-OPENAI_ENDPOINT = "https://rag-openai-service-ak.openai.azure.com/openai/deployments/gpt-4-rag-ak/completions?api-version=2023-05-15"
+# Azure OpenAI Configuration
 OPENAI_KEY = "B1XyCaz87o456EVD949oODcGC8KTAEQsNLI7Yq5cnYKk41SMY9PtJQQJ99AKACHYHv6XJ3w3AAABACOGAaCZ"
+OPENAI_ENDPOINT = "https://rag-openai-service-ak.openai.azure.com/openai/deployments/gpt-4-rag-ak/completions?api-version=2023-05-15"
 
-# Azure Cognitive Search configuration
-SEARCH_ENDPOINT = "https://rag-search-service-ak.search.windows.net"
-SEARCH_KEY = "Kq2Ww1XBwGCvV4JXTMvWT6qo1O9HprGo74elTSNYHiAzSeDETx4y"
-SEARCH_INDEX = "rag-index-ak"
-
+# Retry mechanism for handling rate limits
 def query_openai(prompt):
     headers = {
         "Content-Type": "application/json",
-        "api-key": OPENAI_KEY
+        "Authorization": f"Bearer {OPENAI_KEY}"
     }
     payload = {
         "prompt": prompt,
-        "max_tokens": 500,
-        "temperature": 0.7,
-        "stop": "\n"
-    }
-    response = requests.post(OPENAI_ENDPOINT, headers=headers, json=payload)
-    response.raise_for_status()
-    return response.json()["choices"][0]["text"]
-
-def query_search_service(query):
-    url = f"{SEARCH_ENDPOINT}/indexes/{SEARCH_INDEX}/docs/search?api-version=2021-04-30-Preview"
-    headers = {
-        "Content-Type": "application/json",
-        "api-key": SEARCH_KEY
-    }
-    payload = {
-        "search": query,
-        "top": 3
+        "max_tokens": 100,
+        "temperature": 0.7
     }
-    response = requests.post(url, headers=headers, json=payload)
-    response.raise_for_status()
-    results = response.json()
-    return "\n".join([doc["content"] for doc in results["value"]])
+    retry_count = 0
+    max_retries = 5
+    while retry_count < max_retries:
+        response = requests.post(OPENAI_ENDPOINT, headers=headers, json=payload)
+        if response.status_code == 429:
+            retry_count += 1
+            print(f"Rate limit hit. Retrying in {2 ** retry_count} seconds...")
+            time.sleep(2 ** retry_count)
+        else:
+            response.raise_for_status()
+            return response.json()
+    raise Exception("Exceeded maximum retries due to rate limits.")
 
+# Process user queries
 def process_query(question):
-    # Search the documents
-    search_results = query_search_service(question)
-
-    # Combine the search results with the user's question
-    full_prompt = f"Answer the question based on the following context:\n{search_results}\n\nQuestion: {question}\nAnswer:"
-
-    # Query the OpenAI model
-    return query_openai(full_prompt)
+    full_prompt = f"Answer the following question based on the documents: {question}"
+    try:
+        response = query_openai(full_prompt)
+        return response.get("choices", [{}])[0].get("text", "No response available.")
+    except Exception as e:
+        return f"Error: {str(e)}"
 
+# Gradio UI
 def chatbot_ui(predefined_question, custom_question):
-    question = predefined_question if custom_question.strip() == "" else custom_question
+    question = predefined_question if predefined_question else custom_question
+    if not question:
+        return "Please provide a question to proceed."
     return process_query(question)
 
-# Gradio UI setup
+# Predefined questions
+predefined_questions = [
+    "What are the career opportunities in AI?",
+    "What is the CPT start date?",
+    "Explain the MEng Handbook policies."
+]
+
+# Gradio Interface
 with gr.Blocks() as demo:
     gr.Markdown("# Azure-Powered RAG Chatbot")
-
     with gr.Row():
         predefined_question = gr.Dropdown(
-            ["What are the career opportunities in AI?", "What is the CPT start date?"],
-            label="Select a predefined question"
+            choices=predefined_questions,
+            label="Select a predefined question",
+            interactive=True
         )
-        custom_question = gr.Textbox(label="Or type your own question")
-
-    submit_button = gr.Button("Submit")
-
-    chatbot_response = gr.Textbox(label="Chatbot Response")
+        custom_question = gr.Textbox(
+            label="Or type your own question",
+            placeholder="Type your custom question here...",
+        )
+    submit_btn = gr.Button("Submit")
+    chatbot_response = gr.Textbox(
+        label="Chatbot Response",
+        interactive=False
+    )
 
-    submit_button.click(chatbot_ui, inputs=[predefined_question, custom_question], outputs=[chatbot_response])
+    submit_btn.click(chatbot_ui, inputs=[predefined_question, custom_question], outputs=chatbot_response)
 
-demo.launch()
+demo.launch()