Update src/streamlit_app.py

src/streamlit_app.py

@@ -9,10 +9,10 @@ st.markdown("This dashboard helps you budget your API calls to various LLMs base
 
 # Define LLM models and their costs
 llm_data = {
-    "GPT-4o": {"input_cost_per_m": 2.50, "output_cost_per_m": 10.00, "description": "OpenAI's GPT-4o model"},
-    "Claude 3.7 Sonnet": {"input_cost_per_m": 3.00, "output_cost_per_m": 15.00, "description": "Anthropic's Claude 3.7 Sonnet model"},
-    "Gemini Flash 1.5-8b": {"input_cost_per_m": 0.038, "output_cost_per_m": 0.15, "description": "Google's Gemini Flash 1.5-8b model"},
-    "o3-mini": {"input_cost_per_m": 1.10, "output_cost_per_m": 4.40, "description": "Created Jan 31, 2025, 200k context"}
+    "GPT-4o": {"input_cost_per_m": 2.50, "output_cost_per_m": 10.00},
+    "Claude 3.7 Sonnet": {"input_cost_per_m": 3.00, "output_cost_per_m": 15.00},
+    "Gemini Flash 1.5-8b": {"input_cost_per_m": 0.038, "output_cost_per_m": 0.15},
+    "o3-mini": {"input_cost_per_m": 1.10, "output_cost_per_m": 4.40}
 }
 
 # Convert the LLM data to a DataFrame for displaying in a table