Update app.py

app.py

@@ -1,54 +1,73 @@
+
 import numpy as np
 import streamlit as st
 from openai import OpenAI
 import os
-from dotenv import load_dotenv
-
-# Load environment variables
+import sys
+from dotenv import load_dotenv, dotenv_values
 load_dotenv()
 
-# Initialize the Hugging Face client
-hf_api_key = os.getenv('HF_API_KEY')  # Replace with your Hugging Face API key
-openai_api_key = os.getenv('OPENAI_API_KEY')  # Replace with your OpenAI API key
 
+
+
+
+# initialize the client
 client = OpenAI(
-    api_key=openai_api_key
-)
-
-# Create supported models
-model_links = {
-    "Meta-Llama-3.1-70B-Instruct": "meta-llama/Meta-Llama-3.1-70B-Instruct",
-    "Meta-Llama-3.1-8B-Instruct": "meta-llama/Meta-Llama-3.1-8B-Instruct",
-    "Meta-Llama-3.1-405B-Instruct-FP8": "meta-llama/Meta-Llama-3.1-405B-Instruct-FP8",
-    "Meta-Llama-3.1-405B-Instruct": "meta-llama/Meta-Llama-3.1-405B-Instruct",
-    "Mistral-Nemo-Instruct-2407": "mistralai/Mistral-Nemo-Instruct-2407",
-    "Meta-Llama-3-70B-Instruct": "meta-llama/Meta-Llama-3-70B-Instruct",
-    "Meta-Llama-3-8B-Instruct": "meta-llama/Meta-Llama-3-8B-Instruct",
-    "C4ai-command-r-plus": "CohereForAI/c4ai-command-r-plus",
-    "Aya-23-35B": "CohereForAI/aya-23-35B",
-    "Zephyr-orpo-141b-A35b-v0.1": "HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1",
-    "Mixtral-8x7B-Instruct-v0.1": "mistralai/Mixtral-8x7B-Instruct-v0.1",
-    "Codestral-22B-v0.1": "mistralai/Codestral-22B-v0.1",
-    "Nous-Hermes-2-Mixtral-8x7B-DPO": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
-    "Yi-1.5-34B-Chat": "01-ai/Yi-1.5-34B-Chat",
-    "Gemma-2-27b-it": "google/gemma-2-27b-it",
-    "Meta-Llama-2-70B-Chat-HF": "meta-llama/Llama-2-70b-chat-hf",
-    "Meta-Llama-2-7B-Chat-HF": "meta-llama/Llama-2-7b-chat-hf",
-    "Meta-Llama-2-13B-Chat-HF": "meta-llama/Llama-2-13b-chat-hf",
-    "Mistral-7B-Instruct-v0.1": "mistralai/Mistral-7B-Instruct-v0.1",
-    "Mistral-7B-Instruct-v0.2": "mistralai/Mistral-7B-Instruct-v0.2",
-    "Mistral-7B-Instruct-v0.3": "mistralai/Mistral-7B-Instruct-v0.3",
-    "Falcon-7b-Instruct": "tiiuae/falcon-7b-instruct",
-    "Starchat2-15b-v0.1": "HuggingFaceH4/starchat2-15b-v0.1",
-    "Gemma-1.1-7b-it": "google/gemma-1.1-7b-it",
-    "Gemma-1.1-2b-it": "google/gemma-1.1-2b-it",
-    "Zephyr-7B-Beta": "HuggingFaceH4/zephyr-7b-beta",
-    "Zephyr-7B-Alpha": "HuggingFaceH4/zephyr-7b-alpha",
-    "Phi-3-mini-128k-instruct": "microsoft/Phi-3-mini-128k-instruct",
-    "Phi-3-mini-4k-instruct": "microsoft/Phi-3-mini-4k-instruct",
+  base_url="https://api-inference.huggingface.co/v1",
+  api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN')#"hf_xxx" # Replace with your token
+) 
+
+
+
+
+#Create supported models
+model_links ={
+    "Meta-Llama-3-8B":"meta-llama/Meta-Llama-3-8B-Instruct", 
+    "Mistral-7B":"mistralai/Mistral-7B-Instruct-v0.2",
+    "Gemma-7B":"google/gemma-1.1-7b-it",
+    "Gemma-2B":"google/gemma-1.1-2b-it",
+    "Zephyr-7B-β":"HuggingFaceH4/zephyr-7b-beta",
+
+}
+
+#Pull info about the model to display
+model_info ={
+    "Mistral-7B":
+        {'description':"""The Mistral model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \
+            \nIt was created by the [**Mistral AI**](https://mistral.ai/news/announcing-mistral-7b/) team as has over  **7 billion parameters.** \n""",
+        'logo':'https://mistral.ai/images/logo_hubc88c4ece131b91c7cb753f40e9e1cc5_2589_256x0_resize_q97_h2_lanczos_3.webp'},
+    "Gemma-7B":        
+        {'description':"""The Gemma model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \
+            \nIt was created by the [**Google's AI Team**](https://blog.google/technology/developers/gemma-open-models/) team as has over  **7 billion parameters.** \n""",
+        'logo':'https://pbs.twimg.com/media/GG3sJg7X0AEaNIq.jpg'},
+    "Gemma-2B":        
+    {'description':"""The Gemma model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \
+        \nIt was created by the [**Google's AI Team**](https://blog.google/technology/developers/gemma-open-models/) team as has over  **2 billion parameters.** \n""",
+    'logo':'https://pbs.twimg.com/media/GG3sJg7X0AEaNIq.jpg'},
+    "Zephyr-7B":        
+    {'description':"""The Zephyr model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \
+        \nFrom Huggingface: \n\
+        Zephyr is a series of language models that are trained to act as helpful assistants. \
+        [Zephyr 7B Gemma](https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-v0.1)\
+        is the third model in the series, and is a fine-tuned version of google/gemma-7b \
+        that was trained on on a mix of publicly available, synthetic datasets using Direct Preference Optimization (DPO)\n""",
+    'logo':'https://huggingface.co/HuggingFaceH4/zephyr-7b-gemma-v0.1/resolve/main/thumbnail.png'},
+    "Zephyr-7B-β":        
+    {'description':"""The Zephyr model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \
+        \nFrom Huggingface: \n\
+        Zephyr is a series of language models that are trained to act as helpful assistants. \
+        [Zephyr-7B-β](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta)\
+        is the second model in the series, and is a fine-tuned version of mistralai/Mistral-7B-v0.1 \
+        that was trained on on a mix of publicly available, synthetic datasets using Direct Preference Optimization (DPO)\n""",
+    'logo':'https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha/resolve/main/thumbnail.png'},
+    "Meta-Llama-3-8B":
+    {'description':"""The Llama (3) model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \
+        \nIt was created by the [**Meta's AI**](https://llama.meta.com/) team and has over  **8 billion parameters.** \n""",
+    'logo':'Llama_logo.png'},
 }
 
-# Random dog images for error message
+
+#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",
@@ -63,65 +82,90 @@ random_dog = ["0f476473-2d8b-415e-b944-483768418a95.jpg",
               "6edac66e-c0de-4e69-a9d6-b2e6f6f9001b.jpg",
               "bfb9e165-c643-4993-9b3a-7e73571672a6.jpg"]
 
-# Reset conversation
+
+
 def reset_conversation():
+    '''
+    Resets Conversation
+    '''
     st.session_state.conversation = []
     st.session_state.messages = []
+    return None
+    
+
+
 
 # Define the available models
-models = [key for key in model_links.keys()]
+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)
+#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) #Reset button
 
-# Add reset button to clear conversation
-st.sidebar.button('Reset Chat', on_click=reset_conversation)  # Reset button
 
 # Create model description
 st.sidebar.write(f"You're now chatting with **{selected_model}**")
+st.sidebar.markdown(model_info[selected_model]['description'])
+st.sidebar.image(model_info[selected_model]['logo'])
 st.sidebar.markdown("*Generated content may be inaccurate or false.*")
-st.sidebar.markdown("\n[TypeGPT](https://typegpt.net).")
 
-# Initialize previous option and messages
+
+
+
+
 if "prev_option" not in st.session_state:
     st.session_state.prev_option = selected_model
 
 if st.session_state.prev_option != selected_model:
     st.session_state.messages = []
+    # st.write(f"Changed to {selected_model}")
     st.session_state.prev_option = selected_model
     reset_conversation()
 
-# Pull in the model we want to use
+
+
+#Pull in the model we want to use
 repo_id = model_links[selected_model]
 
-st.subheader(f'TypeGPT.net - {selected_model}')
+
+st.subheader(f'AI - {selected_model}')
+# st.title(f'ChatBot Using {selected_model}')
 
 # Set a default model
 if selected_model not in st.session_state:
-    st.session_state[selected_model] = model_links[selected_model]
+    st.session_state[selected_model] = model_links[selected_model] 
 
 # Initialize chat history
 if "messages" not in st.session_state:
     st.session_state.messages = []
 
+
 # Display chat messages from history on app rerun
 for message in st.session_state.messages:
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
+
+
 # Accept user input
 if prompt := st.chat_input(f"Hi I'm {selected_model}, ask me a question"):
+
     # Display user message in chat message container
     with st.chat_message("user"):
         st.markdown(prompt)
     # Add user message to chat history
     st.session_state.messages.append({"role": "user", "content": prompt})
 
+
     # Display assistant response in chat message container
     with st.chat_message("assistant"):
+
         try:
             stream = client.chat.completions.create(
                 model=model_links[selected_model],
@@ -129,25 +173,31 @@ if prompt := st.chat_input(f"Hi I'm {selected_model}, ask me a question"):
                     {"role": m["role"], "content": m["content"]}
                     for m in st.session_state.messages
                 ],
-                temperature=temp_values,
+                temperature=temp_values,#0.5,
                 stream=True,
                 max_tokens=3000,
             )
+    
             response = st.write_stream(stream)
 
         except Exception as e:
-            response = ("😵‍💫 Looks like someone unplugged something! "
-                        "Either the model space is being updated or something is down. "
-                        "Try again later. Here's a random pic of a 🐶:")
+            # st.empty()
+            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))]
+            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})
 
 
+        
+    st.session_state.messages.append({"role": "assistant", "content": response})
 
 # import gradio as gr
 # from huggingface_hub import InferenceClient