Update app.py

app.py

@@ -18,122 +18,146 @@ def icon(emoji: str):
 
 st.subheader("Groq Chat with LLaMA3 App", divider="rainbow", anchor=False)
 
-# Get the API keys from the environment variable
-api_keys = os.environ['GROQ_API_KEYS'].split(',')
-
-# Initialize the Groq client with the first API key
-client = None
-for api_key in api_keys:
-    try:
-        client = Groq(api_key=api_key)
-        break
-    except Exception as e:
-        st.error(f"Failed to initialize client with API key {api_key}: {e}")
-        continue
-
-if client is None:
-    st.error("Failed to initialize client with any API key")
-    st.stop()
-
-# Initialize chat history and selected model
-if "messages" not in st.session_state:
-    st.session_state.messages = []
-
-if "selected_model" not in st.session_state:
-    st.session_state.selected_model = None
-
-# Define model details
-models = {
-    "llama3-70b-8192": {"name": "LLaMA3-70b", "tokens": 8192, "developer": "Meta"},
-    "llama3-8b-8192": {"name": "LLaMA3-8b", "tokens": 8192, "developer": "Meta"},
-    "llama2-70b-4096": {"name": "LLaMA2-70b-chat", "tokens": 4096, "developer": "Meta"},
-    "gemma-7b-it": {"name": "Gemma-7b-it", "tokens": 8192, "developer": "Google"},
-    "mixtral-8x7b-32768": {
-        "name": "Mixtral-8x7b-Instruct-v0.1",
-        "tokens": 32768,
-        "developer": "Mistral",
-    },
-}
-
-# Layout for model selection and max_tokens slider
-col1, col2 = st.columns([1, 3])  # Adjust the ratio to make the first column smaller
-
-with col1:
-    model_option = st.selectbox(
-        "Choose a model:",
-        options=list(models.keys()),
-        format_func=lambda x: models[x]["name"],
-        index=0,  # Default to the first model in the list
-    )
-    max_tokens_range = models[model_option]["tokens"]
-    max_tokens = st.slider(
-        "Max Tokens:",
-        min_value=512,
-        max_value=max_tokens_range,
-        value=min(32768, max_tokens_range),
-        step=512,
-        help=f"Adjust the maximum number of tokens (words) for the model's response. Max for selected model: {max_tokens_range}",
-    )
-    system_message = {}
-    if system_prompt := st.text_input("System Prompt"):
-        system_message = {"role": "system", "content": system_prompt}
-
-# Detect model change and clear chat history if model has changed
-if st.session_state.selected_model != model_option:
-    st.session_state.messages = []
-    st.session_state.selected_model = model_option
-
-# Add a "Clear Chat" button
-if st.button("Clear Chat"):
-    st.session_state.messages = []
-
-# Display chat messages from history on app rerun
-for message in st.session_state.messages:
-    avatar = "🔋" if message["role"] == "assistant" else "🧑‍💻"
-    with st.chat_message(message["role"], avatar=avatar):
-        st.markdown(message["content"])
-
-def generate_chat_responses(chat_completion) -> Generator[str, None, None]:
-    """Yield chat response content from the Groq API response."""
-    for chunk in chat_completion:
-        if chunk.choices[0].delta.content:
-            yield chunk.choices[0].delta.content
-
-if prompt := st.chat_input("Enter your prompt here..."):
-    st.session_state.messages.append({"role": "user", "content": prompt})
-
-    with st.chat_message("user", avatar="🧑‍💻"):  
-        st.markdown(prompt)
-
-    messages=[
-        {"role": m["role"], "content": m["content"]}
-        for m in st.session_state.messages]
-    if system_message:
-        messages.insert(0,system_message)
-    # Fetch response from Groq API
-    try:
-        chat_completion = client.chat.completions.create(
-            model=model_option,
-            messages=messages,
-            max_tokens=max_tokens,
-            stream=True,
+# Create a settings page
+def settings_page():
+    st.title("Settings")
+    api_keys = st.text_input("Enter your API keys (comma-separated):")
+    if st.button("Save"):
+        os.environ['GROQ_API_KEYS'] = api_keys
+        st.success("API keys saved successfully!")
+
+# Create a main page
+def main_page():
+    # Get the API keys from the environment variable
+    api_keys = os.environ.get('GROQ_API_KEYS')
+    if api_keys is None:
+        st.error("Please set your API keys in the settings page.")
+        return
+
+    # Initialize the Groq client with the first API key
+    client = None
+    for api_key in api_keys.split(','):
+        try:
+            client = Groq(api_key=api_key)
+            break
+        except Exception as e:
+            st.error(f"Failed to initialize client with API key {api_key}: {e}")
+            continue
+
+    if client is None:
+        st.error("Failed to initialize client with any API key")
+        st.stop()
+
+    # Initialize chat history and selected model
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+
+    if "selected_model" not in st.session_state:
+        st.session_state.selected_model = None
+
+    # Define model details
+    models = {
+        "llama3-70b-8192": {"name": "LLaMA3-70b", "tokens": 8192, "developer": "Meta"},
+        "llama3-8b-8192": {"name": "LLaMA3-8b", "tokens": 8192, "developer": "Meta"},
+        "llama2-70b-4096": {"name": "LLaMA2-70b-chat", "tokens": 4096, "developer": "Meta"},
+        "gemma-7b-it": {"name": "Gemma-7b-it", "tokens": 8192, "developer": "Google"},
+        "mixtral-8x7b-32768": {
+            "name": "Mixtral-8x7b-Instruct-v0.1",
+            "tokens": 32768,
+            "developer": "Mistral",
+        },
+    }
+
+    # Layout for model selection and max_tokens slider
+    col1, col2 = st.columns([1, 3])  # Adjust the ratio to make the first column smaller
+
+    with col1:
+        model_option = st.selectbox(
+            "Choose a model:",
+            options=list(models.keys()),
+            format_func=lambda x: models[x]["name"],
+            index=0,  # Default to the first model in the list
         )
-
-        # Use the generator function with st.write_stream
-        with st.chat_message("assistant", avatar="🔋"):
-            chat_responses_generator = generate_chat_responses(chat_completion)
-            full_response = st.write_stream(chat_responses_generator)
-    except Exception as e:
-        st.error(e, icon="❌")
-
-    # Append the full response to session_state.messages
-    if isinstance(full_response, str):
-        st.session_state.messages.append(
-            {"role": "assistant", "content": full_response}
+        max_tokens_range = models[model_option]["tokens"]
+        max_tokens = st.slider(
+            "Max Tokens:",
+            min_value=512,
+            max_value=max_tokens_range,
+            value=min(32768, max_tokens_range),
+            step=512,
+            help=f"Adjust the maximum number of tokens (words) for the model's response. Max for selected model: {max_tokens_range}",
         )
+        system_message = {}
+        if system_prompt := st.text_input("System Prompt"):
+            system_message = {"role": "system", "content": system_prompt}
+
+    # Detect model change and clear chat history if model has changed
+    if st.session_state.selected_model != model_option:
+        st.session_state.messages = []
+        st.session_state.selected_model = model_option
+
+    # Add a "Clear Chat" button
+    if st.button("Clear Chat"):
+        st.session_state.messages = []
+
+    # Display chat messages from history on app rerun
+    for message in st.session_state.messages:
+        avatar = "🔋" if message["role"] == "assistant" else "🧑‍💻"
+        with st.chat_message(message["role"], avatar=avatar):
+            st.markdown(message["content"])
+
+    def generate_chat_responses(chat_completion) -> Generator[str, None, None]:
+        """Yield chat response content from the Groq API response."""
+        for chunk in chat_completion:
+            if chunk.choices[0].delta.content:
+                yield chunk.choices[0].delta.content
+
+    if prompt := st.chat_input("Enter your prompt here..."):
+        st.session_state.messages.append({"role": "user", "content": prompt})
+
+        with st.chat_message("user", avatar="🧑‍💻"):  
+            st.markdown(prompt)
+
+        messages=[
+            {"role": m["role"], "content": m["content"]}
+            for m in st.session_state.messages]
+        if system_message:
+            messages.insert(0,system_message)
+        # Fetch response from Groq API
+        try:
+            chat_completion = client.chat.completions.create(
+                model=model_option,
+                messages=messages,
+                max_tokens=max_tokens,
+                stream=True,
+            )
+
+            # Use the generator function with st.write_stream
+            with st.chat_message("assistant", avatar="🔋"):
+                chat_responses_generator = generate_chat_responses(chat_completion)
+                full_response = st.write_stream(chat_responses_generator)
+        except Exception as e:
+            st.error(e, icon="❌")
+
+        # Append the full response to session_state.messages
+        if isinstance(full_response, str):
+            st.session_state.messages.append(
+                {"role": "assistant", "content": full_response}
+            )
+        else:
+            # Handle the case where full_response is not a string
+            combined_response = "\n".join(str(item) for item in full_response)
+            st.session_state.messages.append(
+                {"role": "assistant", "content": combined_response}
+            )
+
+# Create a sidebar with a settings button
+with st.sidebar:
+    if st.button("Settings"):
+        settings_page()
     else:
-        # Handle the case where full_response is not a string
-        combined_response = "\n".join(str(item) for item in full_response)
-        st.session_state.messages.append(
-            {"role": "assistant", "content": combined_response}
-        )
+        main_page()
+
+# If the user is not in the settings page, show the main page
+if not st.sidebar.button("Settings"):
+    main_page()