Trying to get token count right

gemini/gemini.py

@@ -324,7 +324,7 @@ def main():
 
             config = types.GenerateContentConfig(**config_kwargs)
 
-            print("Generating response (this may take a moment for large outputs)...\n")
+            print("Generating response (this may take a moment for large outputs)...")
             
             full_response_text = ""
             usage_metadata = None
@@ -348,8 +348,9 @@ def main():
                                 usage_metadata = chunk.usage_metadata
                             if chunk.candidates and chunk.candidates[0].finish_reason:
                                 finish_reason_str = chunk.candidates[0].finish_reason.name
-                    print(f"Done! Raw output saved directly to {args.output}", file=sys.stderr)
+                    print(f"Done! Raw output saved directly to {args.output}")
                 else:
+                    print()
                     for chunk in response_stream:
                         if chunk.text:
                             print(chunk.text, end="", flush=True)
@@ -358,10 +359,10 @@ def main():
                             usage_metadata = chunk.usage_metadata
                         if chunk.candidates and chunk.candidates[0].finish_reason:
                             finish_reason_str = chunk.candidates[0].finish_reason.name
-                    print() 
-
+                    print("\n") 
+                    
             except Exception as e:
-                # Catch the 404 Model Not Found error (or other API failures) gracefully
+                # Catch 404 Model Not Found or other critical generation errors gracefully
                 if "404" in str(e) and "NOT_FOUND" in str(e):
                     print(f"\n[Error] The model '{args.model}' does not exist or is not available.", file=sys.stderr)
                 else:
@@ -378,16 +379,23 @@ def main():
                 output_tokens = usage_metadata.candidates_token_count or 0
                 cached_tokens = getattr(usage_metadata, 'cached_content_token_count', 0) or 0
                 
-                uncached_tokens = max(0, prompt_tokens - cached_tokens)
-                rates = pricing_data.get(args.model, {})
+                # Handle API variations where prompt_token_count might strictly be the uncached tokens
+                if prompt_tokens >= cached_tokens:
+                    uncached_tokens = prompt_tokens - cached_tokens
+                else:
+                    uncached_tokens = prompt_tokens
+                    
+                total_input_tokens = uncached_tokens + cached_tokens
+                
+                rates = pricing_data.get(args.model, {"input": 0.0, "cached": 0.0, "output": 0.0})
                 
                 input_rate = rates.get("input", 0.0)
                 cached_rate = rates.get("cached", 0.0)
                 output_rate = rates.get("output", 0.0)
                 tier_label = "Base Tier"
                 
-                # Check if prompt exceeded 200k tokens to apply tier pricing
-                if prompt_tokens > 200_000 and "input_over_200k" in rates:
+                # Apply 200k+ tier pricing if total prompt size exceeds 200k
+                if total_input_tokens > 200_000 and "input_over_200k" in rates:
                     if rates.get("input_over_200k", 0.0) > 0:
                         input_rate = rates["input_over_200k"]
                         tier_label = ">200k Tier"