Update app.py

Added IBM endpoints

app.py

@@ -1,77 +1,147 @@
-# Import necessary libraries
-
-import streamlit as st
-import os
-from openai import OpenAI
-import json
-
-def clear_chat():
-    st.session_state.messages = []
-
-st.title("Intel® AI for Enterprise Inference")
-st.header("LLM chatbot")
-
-with st.sidebar:
-    api_key = st.session_state.api_key = st.secrets["openai_apikey"]  #Enter openai_api key under "Secrets " in HF settings
-    base_url = st.session_state.base_url = os.environ.get("base_url") #Enter base_url under "Variables" in HF settings
-    client = OpenAI(api_key=api_key, base_url=base_url)
-    models = client.models.list()
-    model_names = sorted([model.id for model in models])  # Extract 'id' from each model object
-    default_model_name = "meta-llama/Llama-3.3-70B-Instruct"  # Replace with your desired default model name
-    
-    # Use st.session_state to persist the selected model
-    if "selected_model" not in st.session_state:
-        st.session_state.selected_model = default_model_name if default_model_name in model_names else model_names[0]
-
-    # Create the selectbox without the `index` parameter
-    modelname = st.selectbox(
-        "Select an LLM model (running on Intel® Gaudi®). Hosted on Denvr Dataworks.",
-        model_names,
-        key="selected_model",  # This ties the widget to st.session_state["selected_model"]
-    )
-    st.write(f"You selected: {modelname}")
-    st.button("Start New Chat", on_click=clear_chat)
-    
-    st.markdown("---")  # Add a horizontal line for separation
-    st.markdown(
-        """
-        Check the latest models hosted on [Denvr Dataworks](https://www.denvrdata.com/intel), and get your own OpenAI-compatible API key.
-
-        Come and chat with other AI developers on [Intel’s DevHub Discord server](https://discord.gg/kfJ3NKEw5t).
-        """
-    )
-    
-try:
-    if "messages" not in st.session_state:
-        st.session_state.messages = []
-
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.markdown(message["content"])
-
-    if prompt := st.chat_input("What is up?"):
-        st.session_state.messages.append({"role": "user", "content": prompt})
-        with st.chat_message("user"):
-            st.markdown(prompt)
-
-        with st.chat_message("assistant"):
-            try:
-                stream = client.chat.completions.create(
-                    model=modelname,
-                    messages=[
-                        {"role": m["role"], "content": m["content"]}
-                        for m in st.session_state.messages
-                    ],
-                    max_tokens=4096,
-                    stream=True,
-                )
-                response = st.write_stream(stream)
-            except Exception as e:
-                st.error(f"An error occurred while generating the response: {e}")
-                response = "An error occurred while generating the response."
-
-        st.session_state.messages.append({"role": "assistant", "content": response})
-except KeyError as e:
-    st.error(f"Key error: {e}")
-except Exception as e:
-    st.error(f"An unexpected error occurred: {e}")
+import streamlit as st
+import os
+from openai import OpenAI
+import json
+
+def clear_chat():
+    st.session_state.messages = []
+
+def initialize_provider_settings(provider_choice):
+    """Configure API settings based on provider selection"""
+    provider_configs = {
+        "Denvr Dataworks": {
+            "api_key_source": st.secrets.get("openai_apikey", ""),
+            "base_url_source": os.environ.get("base_url", ""),
+            "fallback_model": "meta-llama/Llama-3.3-70B-Instruct"
+        },
+        "IBM": {
+            "api_key_source": os.environ.get("ibm_openai_apikey", ""),
+            "base_url_source": os.environ.get("ibm_base_url", ""),
+            "fallback_model": None
+        }
+    }
+    
+    return provider_configs.get(provider_choice, {})
+
+st.title("Intel® AI for Enterprise Inference")
+st.header("LLM chatbot")
+
+with st.sidebar:
+    # Provider selection dropdown
+    available_providers = ["Denvr Dataworks", "IBM"]
+    
+    if "current_provider_choice" not in st.session_state:
+        st.session_state.current_provider_choice = available_providers[0]
+    
+    provider_selection = st.selectbox(
+        "Choose AI Provider:",
+        available_providers,
+        key="current_provider_choice"
+    )
+    
+    # Get provider-specific settings
+    provider_settings = initialize_provider_settings(provider_selection)
+    
+    # Validate required credentials
+    if not provider_settings.get("api_key_source") or not provider_settings.get("base_url_source"):
+        st.error(f"Configuration missing for {provider_selection}. Check environment variables.")
+        st.stop()
+    
+    # Setup OpenAI client
+    try:
+        api_client = OpenAI(
+            api_key=provider_settings["api_key_source"], 
+            base_url=provider_settings["base_url_source"]
+        )
+        available_models = api_client.models.list()
+        model_list = sorted([m.id for m in available_models])
+        
+        # Handle model selection with provider switching
+        session_key = f"model_for_{provider_selection}"
+        if session_key not in st.session_state or st.session_state.get("last_provider") != provider_selection:
+            preferred_model = provider_settings.get("fallback_model")
+            if preferred_model and preferred_model in model_list:
+                st.session_state[session_key] = preferred_model
+            elif model_list:
+                st.session_state[session_key] = model_list[0]
+            st.session_state.last_provider = provider_selection
+        
+        if not model_list:
+            st.error(f"No models found for {provider_selection}")
+            st.stop()
+        
+        # Model selection interface
+        chosen_model = st.selectbox(
+            f"Available models from {provider_selection}:",
+            model_list,
+            key=session_key,
+        )
+        st.info(f"Active model: {chosen_model}")
+        
+    except Exception as connection_error:
+        st.error(f"Connection failed for {provider_selection}: {connection_error}")
+        st.stop()
+    
+    st.button("Reset Conversation", on_click=clear_chat)
+    
+    st.markdown("---")
+    
+    # Display provider-specific information
+    if provider_selection == "Denvr Dataworks":
+        st.markdown(
+            """
+            **Denvr Dataworks Integration**
+            
+            Visit [Denvr Dataworks](https://www.denvrdata.com/intel) for model information and API access.
+            
+            Join the community: [Intel's DevHub Discord](https://discord.gg/kfJ3NKEw5t)
+            """
+        )
+    elif provider_selection == "IBM":
+        st.markdown(
+            """
+            **IBM AI Services**
+            
+            Connected to IBM's AI infrastructure. Ensure your credentials are properly configured.
+            """
+        )
+
+# Main chat interface
+try:
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+
+    # Display conversation history
+    for msg in st.session_state.messages:
+        with st.chat_message(msg["role"]):
+            st.markdown(msg["content"])
+
+    # Handle new user input
+    if user_input := st.chat_input("Enter your message..."):
+        st.session_state.messages.append({"role": "user", "content": user_input})
+        with st.chat_message("user"):
+            st.markdown(user_input)
+
+        # Generate AI response
+        with st.chat_message("assistant"):
+            try:
+                response_stream = api_client.chat.completions.create(
+                    model=chosen_model,
+                    messages=[
+                        {"role": msg["role"], "content": msg["content"]}
+                        for msg in st.session_state.messages
+                    ],
+                    max_tokens=4096,
+                    stream=True,
+                )
+                ai_response = st.write_stream(response_stream)
+            except Exception as generation_error:
+                st.error(f"Response generation failed: {generation_error}")
+                ai_response = "Unable to generate response due to an error."
+
+        st.session_state.messages.append({"role": "assistant", "content": ai_response})
+
+except KeyError as key_err:
+    st.error(f"Configuration key error: {key_err}")
+except Exception as general_err:
+    st.error(f"Unexpected error occurred: {general_err}")