Fix factor thousand

app.py

@@ -71,15 +71,15 @@ def update_model_list(function_calling, litellm_provider, max_price, supports_vi
     list_models = filtered_models['model'].tolist()
     return gr.Dropdown(choices=list_models, value=list_models[0] if list_models else "No model found for this combination!")
 
-def compute_all(input_type, prompt_text, completion_text, prompt_tokens, completion_tokens, models):
+def compute_all(input_type, prompt_text, completion_text, base_prompt_tokens, base_completion_tokens, models):
     results = []
     for model in models:
         if input_type == "Text Input":
             prompt_tokens = count_string_tokens(prompt_text, model)
             completion_tokens = count_string_tokens(completion_text, model)
         else:  # Token Count Input
-            prompt_tokens = int(prompt_tokens * 1000)
-            completion_tokens = int(completion_tokens * 1000)
+            prompt_tokens = int(base_prompt_tokens)
+            completion_tokens = int(base_completion_tokens)
 
         model_data = TOKEN_COSTS[TOKEN_COSTS['model'] == model].iloc[0]
         prompt_cost, completion_cost = calculate_total_cost(prompt_tokens, completion_tokens, model)
@@ -177,8 +177,8 @@ with gr.Blocks(css="""
                 completion_text = gr.Textbox(label="Completion", value="Certainly: Why did the neural network go to therapy? It had too many deep issues!", lines=3)
             
             with gr.Group(visible=False) as token_input_group:
-                prompt_tokens_input = gr.Number(label="Prompt Tokens (thousands)", value=1.5)
-                completion_tokens_input = gr.Number(label="Completion Tokens (thousands)", value=2)
+                prompt_tokens_input = gr.Number(label="Prompt Tokens", value=1500)
+                completion_tokens_input = gr.Number(label="Completion Tokens", value=2000)
 
         with gr.Column():
             gr.Markdown("## Model choice:")
@@ -187,7 +187,7 @@ with gr.Blocks(css="""
                     function_calling = gr.Checkbox(label="Supports Tool Calling", value=False)
                     supports_vision = gr.Checkbox(label="Supports Vision", value=False)
                 with gr.Column():
-                    supports_max_input_tokens = gr.Slider(label="Min Supported Input Length (thousands)", minimum=2, maximum=256, step=2, value=2)
+                    supports_max_input_tokens = gr.Slider(label="Min Supported Input Length (thousands tokens)", minimum=2, maximum=256, step=2, value=2)
                     max_price = gr.Slider(label="Max Price per Input Token", minimum=0, maximum=0.001, step=0.00001, value=0.001, visible=False, interactive=False)
                 litellm_provider = gr.Dropdown(label="Inference Provider", choices=["Any"] + TOKEN_COSTS['litellm_provider'].unique().tolist(), value="Any")