Update app.py

app.py

@@ -1,163 +1,149 @@
-import os
-from dotenv import find_dotenv, load_dotenv
+import numpy as np
 import streamlit as st
-from typing import Generator
-from groq import Groq
-
-_ = load_dotenv(find_dotenv())
-st.set_page_config(page_icon="📃", layout="wide", page_title="Groq & LLaMA3 Chat Bot...")
-
-def icon(emoji: str):
-    """Shows an emoji as a Notion-style page icon."""
-    st.write(
-        f'<span style="font-size: 78px; line-height: 1">{emoji}</span>',
-        unsafe_allow_html=True,
-    )
-
-# icon("⚡️")
-
-st.subheader("Groq Chat with LLaMA3 App", divider="rainbow", anchor=False)
-
-# 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
-        )
-        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}",
+from openai import OpenAI
+import os
+import json
+from dotenv import load_dotenv
+
+load_dotenv()
+
+# Initialize the client
+client = OpenAI(
+    base_url=os.environ.get('BASE_URL'),  # Fetch base_url from environment variables
+    api_key=os.environ.get('API_KEY')      # Fetch API key from environment variables
+)
+
+# Create supported models
+model_links = {
+    "Mixtral-8x7B-Instruct-v0.1": "mistralai/Mixtral-8x7B-Instruct-v0.1",
+}
+
+# Random dog images for error message
+random_dog = [
+    "0f476473-2d8b-415e-b944-483768418a95.jpg",
+    "1bd75c81-f1d7-4e55-9310-a27595fa8762.jpg",
+    "526590d2-8817-4ff0-8c62-fdcba5306d02.jpg",
+    "1326984c-39b0-492c-a773-f120d747a7e2.jpg",
+    "42a98d03-5ed7-4b3b-af89-7c4876cb14c3.jpg",
+    "8b3317ed-2083-42ac-a575-7ae45f9fdc0d.jpg",
+    "ee17f54a-83ac-44a3-8a35-e89ff7153fb4.jpg",
+    "027eef85-ccc1-4a66-8967-5d74f34c8bb4.jpg",
+    "08f5398d-7f89-47da-a5cd-1ed74967dc1f.jpg",
+    "0fd781ff-ec46-4bdc-a4e8-24f18bf07def.jpg",
+    "0fb4aeee-f949-4c7b-a6d8-05bf0736bdd1.jpg",
+    "6edac66e-c0de-4e69-a9d6-b2e6f6f9001b.jpg",
+    "bfb9e165-c643-4993-9b3a-7e73571672a6.jpg"
+]
+
+history_file = 'chat_histories.json'
+
+def load_history():
+    if os.path.exists(history_file):
+        with open(history_file, 'r') as f:
+            return json.load(f)
+    return {}
+
+def save_history(histories):
+    with open(history_file, 'w') as f:
+        json.dump(histories, f)
+
+def reset_conversation():
+    '''
+    Resets Conversation
+    '''
+    st.session_state.messages = []
+    st.session_state.current_chat_name = None
+    return None
+
+# Set up the Streamlit page configuration
+st.set_page_config(page_icon="📃", layout="wide", page_title="GPT-CHATBOT.ru")
+
+# Display the header
+st.title("GPT-CHATBOT.ru")
+
+# Initialize session state attributes
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+if "chat_histories" not in st.session_state:
+    st.session_state.chat_histories = load_history()
+
+if "current_chat_name" not in st.session_state:
+    st.session_state.current_chat_name = None
+
+# Define the available models
+models = [key for key in model_links.keys()]
+
+# Create the sidebar with the dropdown for model selection
+selected_model = st.sidebar.selectbox("Select Model", models)
+
+# Create a temperature slider
+temp_values = st.sidebar.slider('Select a temperature value', 0.0, 1.0, 0.5)
+
+# Add reset button to clear conversation
+st.sidebar.button('Reset Chat', on_click=reset_conversation)
+
+# Create a chat history dropdown
+chat_history = st.sidebar.selectbox("Select Chat History", ["Current Chat"] + list(st.session_state.chat_histories.keys()))
+
+if chat_history != "Current Chat":
+    st.session_state.messages = st.session_state.chat_histories[chat_history]
+else:
+    if selected_model not in st.session_state:
+        st.session_state[selected_model] = model_links[selected_model]
+
+# Create a system prompt input
+system_prompt = st.sidebar.text_input("System Prompt", value="", help="Optional system prompt for the chat model.")
+
+# 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"])
+
+# Accept user input
+if prompt := st.chat_input(f"Hi I'm {selected_model}, ask me a question"):
+    with st.chat_message("user", avatar="🧑‍💻"):
+        st.markdown(prompt)
+    st.session_state.messages.append({"role": "user", "content": prompt})
+
+    try:
+        # Construct the list of messages with an optional system prompt
+        messages = [{"role": m["role"], "content": m["content"]} for m in st.session_state.messages]
+        if system_prompt:
+            messages.insert(0, {"role": "system", "content": system_prompt})
+        
+        # Make the API request
+        stream = client.chat.completions.create(
+            model=model_links[selected_model],
+            messages=messages,
+            temperature=temp_values,
+            stream=True,
+            max_tokens=3000,
         )
-        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:
-        main_page()
-
-# If the user is not in the settings page, show the main page
-if not st.sidebar.button("Settings"):
-    main_page()
+        response = st.write_stream(stream)
+
+    except Exception as e:
+        response = "😵‍💫 Looks like someone unplugged something!\
+                \n Either the model space is being updated or something is down.\
+                \n\
+                \n Try again later. \
+                \n\
+                \n Here's a random pic of a 🐶:"
+        st.write(response)
+        random_dog_pick = 'https://random.dog/' + random_dog[np.random.randint(len(random_dog))]
+        st.image(random_dog_pick)
+        st.write("This was the error message:")
+        st.write(e)
+
+    st.session_state.messages.append({"role": "assistant", "content": response})
+
+    # Automatically name and save chat history
+    if not st.session_state.current_chat_name:
+        st.session_state.current_chat_name = f"Chat_{len(st.session_state.chat_histories) + 1}"
+        st.session_state.chat_histories[st.session_state.current_chat_name] = st.session_state.messages
+        save_history(st.session_state.chat_histories)
+
+st.sidebar.write(f"You're now chatting with **{selected_model}**")
+st.sidebar.markdown("*Generated content may be inaccurate or false.*")
+st.sidebar.markdown("\n[TypeGPT](https://typegpt.net).")