Update app.py

app.py

@@ -16,6 +16,7 @@ client = OpenAI(
 model_links ={
     "Meta-Llama-3.1-8B": "meta-llama/Meta-Llama-3.1-8B-Instruct",
     "Mistral-7B-Instruct-v0.3": "mistralai/Mistral-7B-Instruct-v0.3",
+    "Gemma-7b": "google/gemma-7b",
 }
 
 #Pull info about the model to display
@@ -28,24 +29,15 @@ model_info ={
         {'description':"""The Mistral-7B-Instruct-v0.3 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-7B-v0.3.\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':"""Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models.\n \
+    \nThey are text-to-text, decoder-only large language models, available in English, with open weights, pre-trained variants, and instruction-tuned variants. \n"""},
 }
 
 
 #Random dog images for error message
 random_dog = ["BlueLogoBox.jpg"]
 
-
-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()]
 
@@ -55,10 +47,6 @@ 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) #Reset button
-
 # Create model description
 st.sidebar.write(f"You're now chatting with **{selected_model}**")
 st.sidebar.markdown(model_info[selected_model]['description'])
@@ -117,7 +105,7 @@ if prompt := st.chat_input(f"Type message here..."):
                 ],
                 temperature=temp_values,#0.5,
                 stream=True,
-                max_tokens=3000,
+                max_tokens=4000,
             )
     
             response = st.write_stream(stream)