Website url

app.py

@@ -1,7 +1,7 @@
 import streamlit as st
 import asyncio
 import tokonomics
-from utils import  create_model_hierarchy
+from utils import create_model_hierarchy
 
 st.set_page_config(page_title="LLM Pricing App", layout="wide")
 
@@ -52,7 +52,8 @@ def estimate_cost(num_alerts, input_size, output_size, model_id):
         return "NA"
     input_tokens = round(input_size * 1.3)
     output_tokens = round(output_size * 1.3)
-    price_day = cost_token.get("input_cost_per_token", 0) * input_tokens + cost_token.get("output_cost_per_token", 0) * output_tokens
+    price_day = cost_token.get("input_cost_per_token", 0) * input_tokens + \
+                cost_token.get("output_cost_per_token", 0) * output_tokens
     price_total = price_day * num_alerts
     return f"""## Estimated Cost:
 
@@ -76,11 +77,15 @@ if "data_loaded" not in st.session_state:
 # Sidebar
 # --------------------------
 with st.sidebar:
-    st.image("https://cdn.prod.website-files.com/630f558f2a15ca1e88a2f774/631f1436ad7a0605fecc5e15_Logo.svg", use_container_width=True)
+    st.image("https://cdn.prod.website-files.com/630f558f2a15ca1e88a2f774/631f1436ad7a0605fecc5e15_Logo.svg",
+             use_container_width=True)
+    st.markdown(
+        """ Visit: [https://www.priam.ai](https://www.priam.ai)
+        """
+    )
     st.divider()
     st.sidebar.title("LLM Pricing Calculator")
 
-
 # --------------------------
 # Main Content Layout (Model Selection Tab)
 # --------------------------
@@ -92,13 +97,25 @@ with tab1:
     # --- Row 1: Provider/Type and Model Selection ---
     col_left, col_right = st.columns(2)
     with col_left:
-        selected_provider = st.selectbox("Select a provider", st.session_state["providers"])
+        selected_provider = st.selectbox(
+            "Select a provider",
+            st.session_state["providers"],
+            index=st.session_state["providers"].index("azure") if "azure" in st.session_state["providers"] else 0
+        )
         selected_type = st.radio("Select type", options=["text", "image"], index=0)
+
     with col_right:
         # Filter models based on the selected provider and type
         filtered_models = provider_change(selected_provider, selected_type)
+        
         if filtered_models:
-            selected_model = st.selectbox("Select a model", options=filtered_models)
+            # Force "gpt-4-turbo" as default if available; otherwise, default to the first model.
+            default_model = "o1" if "o1" in filtered_models else filtered_models[0]
+            selected_model = st.selectbox(
+                "Select a model",
+                options=filtered_models,
+                index=filtered_models.index(default_model)
+            )
         else:
             selected_model = None
             st.write("No models available")