Update app.py

app.py

@@ -16,14 +16,12 @@ load_dotenv()
 # initialize the client
 client = OpenAI(
     base_url="https://p7fw46eiw6xfkxvj.us-east-1.aws.endpoints.huggingface.cloud/v1/",
-    # "hf_xxx" # Replace with your token
     api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN')
 )
 
 # Create supported models
 model_links = {
     "HAH v0.1": "drmasad/HAH-2024-v0.11",
-    "Mistral": "mistralai/Mistral-7B-Instruct-v0.2",
 }
 
 # Pull info about the model to display
@@ -32,11 +30,6 @@ model_info = {
         {'description': """HAH 0.1 is a fine tuned model based on Mistral 7b instruct.\n \
             \nIt was created by Dr M. As'ad using 250k dB rows sourced from open source articles on diabetes** \n""",
          'logo': 'https://www.hmgaihub.com/untitled.png'},
-    "Mistral":
-        {'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'},
-
 }
 
 
@@ -119,7 +112,7 @@ if prompt := st.chat_input(f"Hi I'm {selected_model}, ask me a question"):
             ],
             temperature=temp_values,  # 0.5,
             stream=True,
-            max_tokens=3000,
+            max_tokens=1024,
         )
 
         response = st.write_stream(stream)