From badc66992f04154a0ad2a6cc2137f3b39ede38ca Mon Sep 17 00:00:00 2001 From: Templight41 Date: Wed, 17 Dec 2025 10:56:29 +0530 Subject: [PATCH 1/5] feature addition complete --- src/google/adk/cli/adk_web_server.py | 34 ++ .../adk/cli/browser/token-usage-display.js | 464 ++++++++++++++++++ .../adk/flows/llm_flows/base_llm_flow.py | 51 +- src/google/adk/models/llm_response.py | 7 + src/google/adk/utils/gemini_pricing.py | 266 ++++++++++ tests/unittests/utils/test_gemini_pricing.py | 168 +++++++ 6 files changed, 985 insertions(+), 5 deletions(-) create mode 100644 src/google/adk/cli/browser/token-usage-display.js create mode 100644 src/google/adk/utils/gemini_pricing.py create mode 100644 tests/unittests/utils/test_gemini_pricing.py diff --git a/src/google/adk/cli/adk_web_server.py b/src/google/adk/cli/adk_web_server.py index 78fe426628..5582c2682f 100644 --- a/src/google/adk/cli/adk_web_server.py +++ b/src/google/adk/cli/adk_web_server.py @@ -1664,6 +1664,40 @@ async def redirect_root_to_dev_ui(): async def redirect_dev_ui_add_slash(): return RedirectResponse(redirect_dev_ui_url) + @app.get("/dev-ui/index.html") + @app.get("/dev-ui/") + async def serve_index_with_token_display(): + """Serve index.html with token usage display script injected.""" + from pathlib import Path + + from fastapi.responses import HTMLResponse + + index_path = Path(web_assets_dir) / "index.html" + script_path = Path(web_assets_dir) / "token-usage-display.js" + + if not index_path.exists(): + return HTMLResponse("Index not found", status_code=404) + + # Read the index.html content + with open(index_path, "r", encoding="utf-8") as f: + html_content = f.read() + + # Read the token usage script + script_content = "" + if script_path.exists(): + with open(script_path, "r", encoding="utf-8") as f: + script_content = f.read() + + # Inject the token usage display script inline before + script_tag = f"" + if "" in html_content: + html_content = html_content.replace("", f"{script_tag}") + else: + # Fallback: append at the end + html_content += script_tag + + return HTMLResponse(content=html_content) + app.mount( "/dev-ui/", StaticFiles(directory=web_assets_dir, html=True, follow_symlink=True), diff --git a/src/google/adk/cli/browser/token-usage-display.js b/src/google/adk/cli/browser/token-usage-display.js new file mode 100644 index 0000000000..23393cd481 --- /dev/null +++ b/src/google/adk/cli/browser/token-usage-display.js @@ -0,0 +1,464 @@ +/** + * Token Usage and Cost Display + * + * This script monitors SSE events for token usage metadata and displays + * the accumulated token counts and estimated costs in USD. + * UI is integrated into the chat input area, matching the website's theme. + */ + +(function() { + 'use strict'; + + // State management + let sessionTokenUsage = { + totalPromptTokens: 0, + totalOutputTokens: 0, + totalCachedTokens: 0, + totalCost: 0, + totalTokens: 0, + eventCount: 0 + }; + + let isPopoverOpen = false; + let buttonElement = null; + let popoverElement = null; + + // Find the message input textarea + function findMessageInput() { + const selectors = [ + 'textarea[placeholder*="message" i]', + 'textarea[placeholder*="Message" i]', + 'textarea[aria-label*="message" i]', + 'textarea', + 'input[type="text"]', + ]; + + for (const selector of selectors) { + const el = document.querySelector(selector); + if (el) { + console.log('[Token Usage] Found input:', selector); + return el; + } + } + return null; + } + + // Create button container next to input + function createButtonContainer() { + const input = findMessageInput(); + if (!input) { + console.warn('[Token Usage] Could not find message input'); + return null; + } + + // Find the parent container that holds the input and buttons + let container = input.parentElement; + + // Look for a container that has multiple children (input + buttons) + while (container && container.children.length < 2 && container !== document.body) { + container = container.parentElement; + } + + if (!container || container === document.body) { + console.warn('[Token Usage] Could not find suitable container'); + return null; + } + + console.log('[Token Usage] Found container:', container); + + // Create a wrapper div for our button + const buttonWrapper = document.createElement('div'); + buttonWrapper.id = 'token-usage-wrapper'; + buttonWrapper.style.cssText = ` + display: inline-flex; + align-items: center; + margin: 0 8px; + `; + + // Try to append to container + container.appendChild(buttonWrapper); + + return buttonWrapper; + } + + // Create the main button that shows cost and token count + function createUsageButton() { + const button = document.createElement('button'); + button.id = 'token-usage-button'; + button.type = 'button'; + button.setAttribute('aria-label', 'Token usage and cost'); + + // Match the website's button styling + button.style.cssText = ` + background: transparent; + border: 1px solid rgba(128, 128, 128, 0.3); + border-radius: 20px; + padding: 6px 12px; + font-family: inherit; + font-size: 13px; + font-weight: 500; + cursor: pointer; + color: inherit; + display: inline-flex; + align-items: center; + gap: 6px; + transition: all 0.2s; + white-space: nowrap; + `; + + button.innerHTML = ` + $0.00 + | + 0 tokens + `; + + button.addEventListener('mouseenter', () => { + button.style.backgroundColor = 'rgba(128, 128, 128, 0.1)'; + button.style.borderColor = 'rgba(128, 128, 128, 0.5)'; + }); + + button.addEventListener('mouseleave', () => { + button.style.backgroundColor = 'transparent'; + button.style.borderColor = 'rgba(128, 128, 128, 0.3)'; + }); + + button.addEventListener('click', (e) => { + e.preventDefault(); + e.stopPropagation(); + togglePopover(button); + }); + + buttonElement = button; + return button; + } + + // Create the popover that shows detailed breakdown + function createPopover() { + const popover = document.createElement('div'); + popover.id = 'token-usage-popover'; + popover.style.cssText = ` + position: fixed; + background: var(--surface-container, #2d2d2d); + border: 1px solid rgba(255, 255, 255, 0.12); + border-radius: 12px; + padding: 16px; + font-family: inherit; + font-size: 13px; + box-shadow: 0 4px 16px rgba(0, 0, 0, 0.3); + z-index: 10001; + min-width: 200px; + display: none; + color: inherit; + `; + + popover.innerHTML = ` +
+
+ Token Usage + +
+
+ +
+
+ Input + – +
+ +
+ Output + – +
+ +
+ Cost + – +
+
+ +
+
+ Total events + 0 +
+
+ `; + + document.body.appendChild(popover); + + // Add reset button handler + const resetBtn = document.getElementById('reset-usage-btn'); + if (resetBtn) { + resetBtn.addEventListener('mouseenter', () => { + resetBtn.style.backgroundColor = 'rgba(255, 255, 255, 0.08)'; + }); + resetBtn.addEventListener('mouseleave', () => { + resetBtn.style.backgroundColor = 'transparent'; + }); + resetBtn.addEventListener('click', (e) => { + e.stopPropagation(); + resetUsage(); + }); + } + + // Close popover when clicking outside + document.addEventListener('click', (e) => { + const popoverEl = document.getElementById('token-usage-popover'); + const buttonEl = document.getElementById('token-usage-button'); + if (isPopoverOpen && + popoverEl && + !popoverEl.contains(e.target) && + buttonEl && + !buttonEl.contains(e.target)) { + closePopover(); + } + }); + + popoverElement = popover; + return popover; + } + + // Position popover relative to button + function positionPopover(button) { + const popover = document.getElementById('token-usage-popover'); + if (!popover || !button) return; + + const buttonRect = button.getBoundingClientRect(); + + // Position above the button + popover.style.bottom = `${window.innerHeight - buttonRect.top + 8}px`; + popover.style.right = `${window.innerWidth - buttonRect.right}px`; + popover.style.left = 'auto'; + popover.style.top = 'auto'; + } + + // Toggle popover visibility + function togglePopover(button) { + const popover = document.getElementById('token-usage-popover'); + if (!popover) return; + + isPopoverOpen = !isPopoverOpen; + + if (isPopoverOpen) { + positionPopover(button); + popover.style.display = 'block'; + } else { + popover.style.display = 'none'; + } + } + + // Close popover + function closePopover() { + const popover = document.getElementById('token-usage-popover'); + if (popover) { + popover.style.display = 'none'; + isPopoverOpen = false; + } + } + + // Update the button display + function updateButton() { + const costDisplay = document.getElementById('cost-display'); + const tokenCountDisplay = document.getElementById('token-count-display'); + + if (costDisplay) { + const costFormatted = sessionTokenUsage.totalCost >= 0.01 + ? `$${sessionTokenUsage.totalCost.toFixed(2)}` + : `$${sessionTokenUsage.totalCost.toFixed(4)}`; + costDisplay.textContent = costFormatted; + } + + if (tokenCountDisplay) { + const totalTokens = sessionTokenUsage.totalPromptTokens + sessionTokenUsage.totalOutputTokens; + tokenCountDisplay.textContent = `${totalTokens.toLocaleString()} token${totalTokens !== 1 ? 's' : ''}`; + } + } + + // Update the popover display + function updatePopover() { + const inputTokensEl = document.getElementById('popover-input-tokens'); + const outputTokensEl = document.getElementById('popover-output-tokens'); + const costEl = document.getElementById('popover-cost'); + const eventCountEl = document.getElementById('popover-event-count'); + + if (inputTokensEl) { + inputTokensEl.textContent = sessionTokenUsage.totalPromptTokens > 0 + ? sessionTokenUsage.totalPromptTokens.toLocaleString() + : '–'; + } + + if (outputTokensEl) { + outputTokensEl.textContent = sessionTokenUsage.totalOutputTokens > 0 + ? sessionTokenUsage.totalOutputTokens.toLocaleString() + : '–'; + } + + if (costEl) { + const costFormatted = sessionTokenUsage.totalCost >= 0.01 + ? `$${sessionTokenUsage.totalCost.toFixed(2)}` + : sessionTokenUsage.totalCost > 0 + ? `$${sessionTokenUsage.totalCost.toFixed(4)}` + : '–'; + costEl.textContent = costFormatted; + } + + if (eventCountEl) { + eventCountEl.textContent = sessionTokenUsage.eventCount.toString(); + } + } + + // Update all displays + function updateDisplay() { + updateButton(); + updatePopover(); + } + + // Reset usage statistics + function resetUsage() { + sessionTokenUsage = { + totalPromptTokens: 0, + totalOutputTokens: 0, + totalCachedTokens: 0, + totalCost: 0, + totalTokens: 0, + eventCount: 0 + }; + updateDisplay(); + } + + // Process an event from the SSE stream + function processEvent(eventData) { + try { + const event = JSON.parse(eventData); + + // Check if the event has usage metadata + if (event.usageMetadata) { + const metadata = event.usageMetadata; + + // Update token counts + if (metadata.promptTokenCount) { + sessionTokenUsage.totalPromptTokens += metadata.promptTokenCount; + } + if (metadata.candidatesTokenCount) { + sessionTokenUsage.totalOutputTokens += metadata.candidatesTokenCount; + } + if (metadata.cachedContentTokenCount) { + sessionTokenUsage.totalCachedTokens += metadata.cachedContentTokenCount; + } + + // Update cost if available + if (event.costUsd !== undefined && event.costUsd !== null) { + sessionTokenUsage.totalCost += event.costUsd; + sessionTokenUsage.eventCount++; + } + + // Update the display + updateDisplay(); + } + } catch (e) { + console.error('Error processing event for token usage:', e); + } + } + + // Intercept fetch requests to monitor SSE events + const originalFetch = window.fetch; + window.fetch = function(...args) { + const request = args[0]; + + // Check if this is a run_sse request + if (typeof request === 'string' && request.includes('/run_sse')) { + return originalFetch.apply(this, args).then(response => { + // Clone the response so we can read it + const clonedResponse = response.clone(); + + // Process the SSE stream + const reader = clonedResponse.body.getReader(); + const decoder = new TextDecoder(); + + function readStream() { + reader.read().then(({ done, value }) => { + if (done) return; + + const chunk = decoder.decode(value, { stream: true }); + const lines = chunk.split('\n'); + + for (const line of lines) { + if (line.startsWith('data: ')) { + const data = line.substring(6); + if (data && data !== '[DONE]') { + processEvent(data); + } + } + } + + readStream(); + }); + } + + readStream(); + + return response; + }); + } + + return originalFetch.apply(this, args); + }; + + // Try to inject the button + function tryInject(retries = 15) { + console.log(`[Token Usage] Injection attempt ${16 - retries}/15`); + + const wrapper = createButtonContainer(); + + if (wrapper) { + const button = createUsageButton(); + wrapper.appendChild(button); + createPopover(); + console.log('[Token Usage] ✓ Button injected successfully'); + return true; + } else if (retries > 0) { + setTimeout(() => tryInject(retries - 1), 1000); + return false; + } else { + console.warn('[Token Usage] ✗ Could not find suitable location after 15 attempts'); + + // Fallback: Create floating button + console.log('[Token Usage] Creating fallback floating button'); + const button = createUsageButton(); + button.style.position = 'fixed'; + button.style.bottom = '20px'; + button.style.right = '20px'; + button.style.zIndex = '10000'; + document.body.appendChild(button); + createPopover(); + console.log('[Token Usage] ✓ Fallback button created'); + return true; + } + } + + // Initialize when the DOM is ready + function initialize() { + console.log('[Token Usage] Initializing...'); + + if (document.readyState === 'loading') { + document.addEventListener('DOMContentLoaded', () => { + console.log('[Token Usage] DOM loaded, starting injection'); + tryInject(); + }); + } else { + console.log('[Token Usage] DOM already loaded, starting injection'); + tryInject(); + } + } + + initialize(); +})(); diff --git a/src/google/adk/flows/llm_flows/base_llm_flow.py b/src/google/adk/flows/llm_flows/base_llm_flow.py index 824cd26be1..174c6a761a 100644 --- a/src/google/adk/flows/llm_flows/base_llm_flow.py +++ b/src/google/adk/flows/llm_flows/base_llm_flow.py @@ -544,8 +544,8 @@ async def _postprocess_async( return # Builds the event. - model_response_event = self._finalize_model_response_event( - llm_request, llm_response, model_response_event + model_response_event = await self._finalize_model_response_event( + invocation_context, llm_request, llm_response, model_response_event ) yield model_response_event @@ -637,8 +637,8 @@ async def _postprocess_live( return # Builds the event. - model_response_event = self._finalize_model_response_event( - llm_request, llm_response, model_response_event + model_response_event = await self._finalize_model_response_event( + invocation_context, llm_request, llm_response, model_response_event ) yield model_response_event @@ -914,8 +914,9 @@ async def _maybe_add_grounding_metadata( return await _maybe_add_grounding_metadata(callback_response) return await _maybe_add_grounding_metadata() - def _finalize_model_response_event( + async def _finalize_model_response_event( self, + invocation_context: InvocationContext, llm_request: LlmRequest, llm_response: LlmResponse, model_response_event: Event, @@ -925,6 +926,46 @@ def _finalize_model_response_event( **llm_response.model_dump(exclude_none=True), }) + # Calculate cost if usage metadata is available + if model_response_event.usage_metadata: + from ...utils.gemini_pricing import calculate_token_cost + + try: + llm = self.__get_llm(invocation_context) + model_name = llm.model + + prompt_tokens = ( + model_response_event.usage_metadata.prompt_token_count or 0 + ) + output_tokens = ( + model_response_event.usage_metadata.candidates_token_count or 0 + ) + cached_tokens = ( + model_response_event.usage_metadata.cached_content_token_count or 0 + ) + + # Subtract cached tokens from prompt tokens to avoid double counting + prompt_tokens = max(0, prompt_tokens - cached_tokens) + + logger.debug( + 'Calculating token cost: model=%s, prompt=%d, output=%d, cached=%d', + model_name, + prompt_tokens, + output_tokens, + cached_tokens, + ) + + cost = await calculate_token_cost( + model_name, prompt_tokens, output_tokens, cached_tokens + ) + if cost is not None: + model_response_event.cost_usd = cost + logger.debug('Token cost calculated: $%.6f', cost) + else: + logger.warning('Token cost is None for model: %s', model_name) + except Exception as e: + logger.warning('Failed to calculate token cost: %s', e) + if model_response_event.content: function_calls = model_response_event.get_function_calls() if function_calls: diff --git a/src/google/adk/models/llm_response.py b/src/google/adk/models/llm_response.py index 0e42c02d09..3f144a6ccd 100644 --- a/src/google/adk/models/llm_response.py +++ b/src/google/adk/models/llm_response.py @@ -135,6 +135,13 @@ class LlmResponse(BaseModel): This field is automatically populated when citation is enabled. """ + cost_usd: Optional[float] = None + """The estimated cost in USD for this LLM response. + + This field is calculated based on the usage_metadata and the model's pricing. + Only populated when pricing information is available. + """ + @staticmethod def create( generate_content_response: types.GenerateContentResponse, diff --git a/src/google/adk/utils/gemini_pricing.py b/src/google/adk/utils/gemini_pricing.py new file mode 100644 index 0000000000..caa1c7b893 --- /dev/null +++ b/src/google/adk/utils/gemini_pricing.py @@ -0,0 +1,266 @@ +# Copyright 2025 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +import asyncio +from dataclasses import dataclass +from datetime import datetime +from datetime import timedelta +import logging +from typing import Optional + +import aiohttp + +_logger = logging.getLogger(__name__) + + +@dataclass +class ModelPricing: + """Pricing information for a specific Gemini model. + + All prices are in USD per 1 million tokens. + """ + + input_price_low: float + input_price_high: float + output_price_low: float + output_price_high: float + cached_input_price_low: float + cached_input_price_high: float + threshold_tokens: int = 200_000 + + def calculate_cost( + self, + prompt_tokens: int, + output_tokens: int, + cached_tokens: int = 0, + ) -> float: + """Calculate the total cost for a request. + + Args: + prompt_tokens: Number of prompt tokens (excluding cached tokens). + output_tokens: Number of output tokens generated. + cached_tokens: Number of cached prompt tokens. + + Returns: + Total cost in USD. + """ + total_input_tokens = prompt_tokens + cached_tokens + + # Determine if we're in the high-tier pricing + use_high_tier = total_input_tokens > self.threshold_tokens + + # Calculate input cost (non-cached) + input_price = ( + self.input_price_high if use_high_tier else self.input_price_low + ) + input_cost = (prompt_tokens / 1_000_000) * input_price + + # Calculate cached input cost + cached_price = ( + self.cached_input_price_high + if use_high_tier + else self.cached_input_price_low + ) + cached_cost = (cached_tokens / 1_000_000) * cached_price + + # Calculate output cost + output_price = ( + self.output_price_high if use_high_tier else self.output_price_low + ) + output_cost = (output_tokens / 1_000_000) * output_price + + return input_cost + cached_cost + output_cost + + +# Default pricing for common Gemini models (fallback if fetching fails) +# Prices are per 1 million tokens in USD +_DEFAULT_MODEL_PRICING = { + 'gemini-2.5-pro': ModelPricing( + input_price_low=1.25, + input_price_high=2.50, + output_price_low=10.00, + output_price_high=15.00, + cached_input_price_low=0.125, + cached_input_price_high=0.250, + ), + 'gemini-2.5-flash': ModelPricing( + input_price_low=0.30, + input_price_high=0.30, + output_price_low=2.50, + output_price_high=2.50, + cached_input_price_low=0.030, + cached_input_price_high=0.030, + ), + 'gemini-2.5-flash-lite': ModelPricing( + input_price_low=0.10, + input_price_high=0.10, + output_price_low=0.40, + output_price_high=0.40, + cached_input_price_low=0.010, + cached_input_price_high=0.010, + ), + 'gemini-2.0-flash': ModelPricing( + input_price_low=0.15, + input_price_high=0.15, + output_price_low=0.60, + output_price_high=0.60, + cached_input_price_low=0.015, + cached_input_price_high=0.015, + ), + 'gemini-2.0-flash-lite': ModelPricing( + input_price_low=0.075, + input_price_high=0.075, + output_price_low=0.30, + output_price_high=0.30, + cached_input_price_low=0.0075, + cached_input_price_high=0.0075, + ), + 'gemini-1.5-pro': ModelPricing( + input_price_low=1.25, + input_price_high=2.50, + output_price_low=5.00, + output_price_high=10.00, + cached_input_price_low=0.3125, + cached_input_price_high=0.625, + threshold_tokens=128_000, + ), + 'gemini-1.5-flash': ModelPricing( + input_price_low=0.075, + input_price_high=0.15, + output_price_low=0.30, + output_price_high=0.60, + cached_input_price_low=0.01875, + cached_input_price_high=0.0375, + threshold_tokens=128_000, + ), +} + + +class GeminiPricingService: + """Service for fetching and caching Gemini API pricing information.""" + + def __init__( + self, + pricing_url: str = ( + 'https://cloud.google.com/vertex-ai/generative-ai/pricing' + ), + cache_duration: timedelta = timedelta(hours=24), + ): + """Initialize the pricing service. + + Args: + pricing_url: URL to fetch pricing information from. + cache_duration: How long to cache pricing data before refreshing. + """ + self._pricing_url = pricing_url + self._cache_duration = cache_duration + self._cached_pricing: dict[str, ModelPricing] = _DEFAULT_MODEL_PRICING + self._last_updated: Optional[datetime] = None + self._fetch_lock = asyncio.Lock() + + async def get_pricing(self, model_name: str) -> Optional[ModelPricing]: + """Get pricing for a specific model. + + Args: + model_name: Name of the Gemini model (e.g., "gemini-2.5-flash"). + + Returns: + ModelPricing object if found, None otherwise. + """ + # Normalize model name (remove prefixes like "models/") + normalized_name = model_name.split('/')[-1] + + # Check if we need to refresh the cache + if self._should_refresh_cache(): + await self._refresh_pricing() + + # Try to find exact match + if normalized_name in self._cached_pricing: + return self._cached_pricing[normalized_name] + + # Try to find fuzzy match (e.g., "gemini-2.5-flash-001" -> "gemini-2.5-flash") + for key in self._cached_pricing: + if normalized_name.startswith(key): + return self._cached_pricing[key] + + _logger.warning( + 'Pricing not found for model: %s, using default', model_name + ) + return None + + def _should_refresh_cache(self) -> bool: + """Check if the pricing cache should be refreshed.""" + if self._last_updated is None: + return False # Use defaults on first run + return datetime.now() - self._last_updated > self._cache_duration + + async def _refresh_pricing(self) -> None: + """Refresh pricing data from the Vertex AI pricing page. + + Note: This is a placeholder implementation. In production, you would + either parse the pricing page HTML or use an official API if available. + For now, we use the hardcoded defaults. + """ + async with self._fetch_lock: + # Double-check to avoid race conditions + if not self._should_refresh_cache(): + return + + try: + # TODO: Implement actual pricing page parsing or API call + # For now, we just use the hardcoded defaults + _logger.info('Using default Gemini pricing (no dynamic fetch yet)') + self._last_updated = datetime.now() + except Exception as e: + _logger.error('Failed to refresh Gemini pricing: %s', e) + + +# Global pricing service instance +_pricing_service: Optional[GeminiPricingService] = None + + +def get_pricing_service() -> GeminiPricingService: + """Get the global pricing service instance.""" + global _pricing_service + if _pricing_service is None: + _pricing_service = GeminiPricingService() + return _pricing_service + + +async def calculate_token_cost( + model_name: str, + prompt_tokens: int, + output_tokens: int, + cached_tokens: int = 0, +) -> Optional[float]: + """Calculate the cost of a model invocation. + + Args: + model_name: Name of the Gemini model. + prompt_tokens: Number of prompt tokens. + output_tokens: Number of output tokens. + cached_tokens: Number of cached tokens. + + Returns: + Total cost in USD, or None if pricing not available. + """ + service = get_pricing_service() + pricing = await service.get_pricing(model_name) + + if pricing is None: + return None + + return pricing.calculate_cost(prompt_tokens, output_tokens, cached_tokens) diff --git a/tests/unittests/utils/test_gemini_pricing.py b/tests/unittests/utils/test_gemini_pricing.py new file mode 100644 index 0000000000..85512a3c90 --- /dev/null +++ b/tests/unittests/utils/test_gemini_pricing.py @@ -0,0 +1,168 @@ +# Copyright 2025 Google LLC +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from __future__ import annotations + +from google.adk.utils.gemini_pricing import calculate_token_cost +from google.adk.utils.gemini_pricing import GeminiPricingService +from google.adk.utils.gemini_pricing import ModelPricing +import pytest + + +class TestModelPricing: + """Test the ModelPricing class.""" + + def test_calculate_cost_low_tier(self): + """Test cost calculation for low-tier usage.""" + pricing = ModelPricing( + input_price_low=1.25, + input_price_high=2.50, + output_price_low=10.00, + output_price_high=15.00, + cached_input_price_low=0.125, + cached_input_price_high=0.250, + threshold_tokens=200_000, + ) + + # Test with 1000 prompt tokens, 500 output tokens, no cache + cost = pricing.calculate_cost(1000, 500, 0) + expected = (1000 / 1_000_000) * 1.25 + (500 / 1_000_000) * 10.00 + assert abs(cost - expected) < 0.000001 + + def test_calculate_cost_high_tier(self): + """Test cost calculation for high-tier usage (>200K tokens).""" + pricing = ModelPricing( + input_price_low=1.25, + input_price_high=2.50, + output_price_low=10.00, + output_price_high=15.00, + cached_input_price_low=0.125, + cached_input_price_high=0.250, + threshold_tokens=200_000, + ) + + # Test with 250K prompt tokens, 50K output tokens + cost = pricing.calculate_cost(250_000, 50_000, 0) + expected = (250_000 / 1_000_000) * 2.50 + (50_000 / 1_000_000) * 15.00 + assert abs(cost - expected) < 0.000001 + + def test_calculate_cost_with_cache(self): + """Test cost calculation with cached tokens.""" + pricing = ModelPricing( + input_price_low=1.25, + input_price_high=2.50, + output_price_low=10.00, + output_price_high=15.00, + cached_input_price_low=0.125, + cached_input_price_high=0.250, + threshold_tokens=200_000, + ) + + # Test with 1000 prompt tokens, 500 output tokens, 5000 cached tokens + cost = pricing.calculate_cost(1000, 500, 5000) + expected = ( + (1000 / 1_000_000) * 1.25 + + (5000 / 1_000_000) * 0.125 + + (500 / 1_000_000) * 10.00 + ) + assert abs(cost - expected) < 0.000001 + + def test_calculate_cost_flash_model(self): + """Test cost calculation for Flash model.""" + pricing = ModelPricing( + input_price_low=0.30, + input_price_high=0.30, + output_price_low=2.50, + output_price_high=2.50, + cached_input_price_low=0.030, + cached_input_price_high=0.030, + ) + + # Test with 10000 prompt tokens, 5000 output tokens + cost = pricing.calculate_cost(10_000, 5_000, 0) + expected = (10_000 / 1_000_000) * 0.30 + (5_000 / 1_000_000) * 2.50 + assert abs(cost - expected) < 0.000001 + + +class TestGeminiPricingService: + """Test the GeminiPricingService class.""" + + @pytest.mark.asyncio + async def test_get_pricing_exact_match(self): + """Test getting pricing for an exact model name match.""" + service = GeminiPricingService() + pricing = await service.get_pricing("gemini-2.5-pro") + assert pricing is not None + assert pricing.input_price_low == 1.25 + + @pytest.mark.asyncio + async def test_get_pricing_fuzzy_match(self): + """Test getting pricing for a model with version suffix.""" + service = GeminiPricingService() + pricing = await service.get_pricing("gemini-2.5-flash-001") + assert pricing is not None + assert pricing.input_price_low == 0.30 + + @pytest.mark.asyncio + async def test_get_pricing_with_prefix(self): + """Test getting pricing for a model with 'models/' prefix.""" + service = GeminiPricingService() + pricing = await service.get_pricing("models/gemini-2.0-flash") + assert pricing is not None + assert pricing.input_price_low == 0.15 + + @pytest.mark.asyncio + async def test_get_pricing_unknown_model(self): + """Test getting pricing for an unknown model.""" + service = GeminiPricingService() + pricing = await service.get_pricing("unknown-model-xyz") + assert pricing is None + + +class TestCalculateTokenCost: + """Test the calculate_token_cost helper function.""" + + @pytest.mark.asyncio + async def test_calculate_token_cost_gemini_25_pro(self): + """Test cost calculation for Gemini 2.5 Pro.""" + cost = await calculate_token_cost("gemini-2.5-pro", 1000, 500, 0) + assert cost is not None + expected = (1000 / 1_000_000) * 1.25 + (500 / 1_000_000) * 10.00 + assert abs(cost - expected) < 0.000001 + + @pytest.mark.asyncio + async def test_calculate_token_cost_gemini_25_flash(self): + """Test cost calculation for Gemini 2.5 Flash.""" + cost = await calculate_token_cost("gemini-2.5-flash", 10_000, 5_000, 0) + assert cost is not None + expected = (10_000 / 1_000_000) * 0.30 + (5_000 / 1_000_000) * 2.50 + assert abs(cost - expected) < 0.000001 + + @pytest.mark.asyncio + async def test_calculate_token_cost_with_cache(self): + """Test cost calculation with cached tokens.""" + cost = await calculate_token_cost("gemini-2.5-pro", 1000, 500, 5000) + assert cost is not None + expected = ( + (1000 / 1_000_000) * 1.25 + + (5000 / 1_000_000) * 0.125 + + (500 / 1_000_000) * 10.00 + ) + assert abs(cost - expected) < 0.000001 + + @pytest.mark.asyncio + async def test_calculate_token_cost_unknown_model(self): + """Test cost calculation for unknown model.""" + cost = await calculate_token_cost("unknown-model", 1000, 500, 0) + assert cost is None From eefda164980f7b5a0f4b6966eabec3bf4f63146b Mon Sep 17 00:00:00 2001 From: Templight41 Date: Wed, 17 Dec 2025 11:24:56 +0530 Subject: [PATCH 2/5] live api pricing update --- src/google/adk/utils/gemini_pricing.py | 207 ++++++++++++++++--- tests/unittests/utils/test_gemini_pricing.py | 19 +- 2 files changed, 194 insertions(+), 32 deletions(-) diff --git a/src/google/adk/utils/gemini_pricing.py b/src/google/adk/utils/gemini_pricing.py index caa1c7b893..5771605a30 100644 --- a/src/google/adk/utils/gemini_pricing.py +++ b/src/google/adk/utils/gemini_pricing.py @@ -12,6 +12,21 @@ # See the License for the specific language governing permissions and # limitations under the License. +"""Gemini API pricing calculator with live pricing fetching. + +This module provides utilities to calculate token costs for Gemini models. +On first use, it attempts to fetch the latest pricing from Google Cloud's +pricing page and caches it permanently for the session. If fetching fails, +it falls back to hardcoded defaults (accurate as of December 2025). + +Features: + - Automatic pricing fetch from cloud.google.com/vertex-ai/generative-ai/pricing + - One-time fetch on first request, then cached permanently + - Fallback to hardcoded defaults only if fetching fails + - Support for tiered pricing (low/high token thresholds) + - Cached token pricing calculation +""" + from __future__ import annotations import asyncio @@ -19,6 +34,7 @@ from datetime import datetime from datetime import timedelta import logging +import re from typing import Optional import aiohttp @@ -87,6 +103,7 @@ def calculate_cost( # Default pricing for common Gemini models (fallback if fetching fails) # Prices are per 1 million tokens in USD +# Last updated: December 2025 from https://cloud.google.com/vertex-ai/generative-ai/pricing _DEFAULT_MODEL_PRICING = { 'gemini-2.5-pro': ModelPricing( input_price_low=1.25, @@ -157,75 +174,209 @@ def __init__( pricing_url: str = ( 'https://cloud.google.com/vertex-ai/generative-ai/pricing' ), - cache_duration: timedelta = timedelta(hours=24), + enable_fetch: bool = True, ): """Initialize the pricing service. Args: pricing_url: URL to fetch pricing information from. - cache_duration: How long to cache pricing data before refreshing. + enable_fetch: If False, skip fetching and use hardcoded defaults only. + Useful for testing. """ self._pricing_url = pricing_url - self._cache_duration = cache_duration - self._cached_pricing: dict[str, ModelPricing] = _DEFAULT_MODEL_PRICING - self._last_updated: Optional[datetime] = None + self._enable_fetch = enable_fetch + self._cached_pricing: Optional[dict[str, ModelPricing]] = None + self._fetch_attempted: bool = False self._fetch_lock = asyncio.Lock() async def get_pricing(self, model_name: str) -> Optional[ModelPricing]: """Get pricing for a specific model. + Fetches pricing from Google Cloud on first call, then caches permanently. + Falls back to hardcoded defaults only if fetching fails or is disabled. + Args: model_name: Name of the Gemini model (e.g., "gemini-2.5-flash"). Returns: ModelPricing object if found, None otherwise. """ + # Fetch pricing on first call (if enabled) + if self._enable_fetch and not self._fetch_attempted: + await self._refresh_pricing() + # Normalize model name (remove prefixes like "models/") normalized_name = model_name.split('/')[-1] - # Check if we need to refresh the cache - if self._should_refresh_cache(): - await self._refresh_pricing() + # Use cached pricing (either fetched or fallback) + pricing_data = self._cached_pricing or _DEFAULT_MODEL_PRICING # Try to find exact match - if normalized_name in self._cached_pricing: - return self._cached_pricing[normalized_name] + if normalized_name in pricing_data: + return pricing_data[normalized_name] # Try to find fuzzy match (e.g., "gemini-2.5-flash-001" -> "gemini-2.5-flash") - for key in self._cached_pricing: + for key in pricing_data: if normalized_name.startswith(key): - return self._cached_pricing[key] + return pricing_data[key] _logger.warning( 'Pricing not found for model: %s, using default', model_name ) return None - def _should_refresh_cache(self) -> bool: - """Check if the pricing cache should be refreshed.""" - if self._last_updated is None: - return False # Use defaults on first run - return datetime.now() - self._last_updated > self._cache_duration - async def _refresh_pricing(self) -> None: - """Refresh pricing data from the Vertex AI pricing page. + """Fetch pricing data from the Vertex AI pricing page on first call. - Note: This is a placeholder implementation. In production, you would - either parse the pricing page HTML or use an official API if available. - For now, we use the hardcoded defaults. + Attempts to fetch and parse the latest pricing from Google Cloud's + pricing page. Falls back to hardcoded defaults only if fetching fails. + This is called only once - on the first pricing request. """ async with self._fetch_lock: # Double-check to avoid race conditions - if not self._should_refresh_cache(): + if self._fetch_attempted: return + self._fetch_attempted = True + try: - # TODO: Implement actual pricing page parsing or API call - # For now, we just use the hardcoded defaults - _logger.info('Using default Gemini pricing (no dynamic fetch yet)') - self._last_updated = datetime.now() + _logger.info( + 'Fetching latest Gemini pricing from %s', self._pricing_url + ) + + async with aiohttp.ClientSession() as session: + async with session.get( + self._pricing_url, timeout=aiohttp.ClientTimeout(total=10) + ) as response: + if response.status != 200: + _logger.warning( + 'Failed to fetch pricing page (status %d), using hardcoded' + ' defaults', + response.status, + ) + self._cached_pricing = _DEFAULT_MODEL_PRICING + return + + html_content = await response.text() + parsed_pricing = self._parse_pricing_page(html_content) + + if parsed_pricing: + # Merge parsed pricing with defaults (in case some models are missing) + self._cached_pricing = { + **_DEFAULT_MODEL_PRICING, + **parsed_pricing, + } + _logger.info( + 'Successfully fetched pricing for %d models from API', + len(parsed_pricing), + ) + else: + _logger.warning( + 'No pricing found in API response, using hardcoded defaults' + ) + self._cached_pricing = _DEFAULT_MODEL_PRICING + except Exception as e: - _logger.error('Failed to refresh Gemini pricing: %s', e) + _logger.warning( + 'Failed to fetch Gemini pricing: %s, using hardcoded defaults', e + ) + self._cached_pricing = _DEFAULT_MODEL_PRICING + + def _parse_pricing_page(self, html_content: str) -> dict[str, ModelPricing]: + """Parse pricing information from the HTML page. + + Args: + html_content: HTML content of the pricing page. + + Returns: + Dictionary mapping model names to ModelPricing objects. + Returns empty dict if parsing fails or produces invalid results. + """ + pricing_data = {} + + try: + # Look for pricing tables in the HTML + # The pricing page typically has tables with model names and prices + # Pattern: Match prices in format like "$0.30" or "$1.25" + price_pattern = r'\$(\d+\.?\d*)' + + # Try to find Gemini model sections and their associated prices + # This is a best-effort parsing and may need updates if the page structure changes + + # Look for common model names in the content + model_patterns = { + 'gemini-2.5-flash': r'Gemini 2\.5 Flash', + 'gemini-2.5-pro': r'Gemini 2\.5 Pro', + 'gemini-2.0-flash': r'Gemini 2\.0 Flash', + 'gemini-1.5-pro': r'Gemini 1\.5 Pro', + 'gemini-1.5-flash': r'Gemini 1\.5 Flash', + } + + for model_key, model_pattern in model_patterns.items(): + match = re.search(model_pattern, html_content, re.IGNORECASE) + if match: + # Find the section containing this model + section_start = match.start() + section_end = min(section_start + 5000, len(html_content)) + section = html_content[section_start:section_end] + + # Extract all prices in this section + prices = re.findall(price_pattern, section) + + if len(prices) >= 4: + # Typically: input_low, input_high, output_low, output_high + # or just: input, output (if no tiering) + try: + input_low = float(prices[0]) + output_low = float(prices[1]) if len(prices) > 1 else input_low + + # Check if there's tiered pricing + input_high = float(prices[2]) if len(prices) > 2 else input_low + output_high = float(prices[3]) if len(prices) > 3 else output_low + + # Validate pricing - sanity check to avoid garbage data + # Gemini prices should be < $100 per 1M tokens + if ( + input_low > 100 + or input_high > 100 + or output_low > 100 + or output_high > 100 + ): + _logger.warning( + 'Parsed pricing for %s looks invalid (>$100/1M tokens),' + ' skipping', + model_key, + ) + continue + + # Cached pricing is typically 10% of regular pricing + cached_low = input_low * 0.1 + cached_high = input_high * 0.1 + + pricing_data[model_key] = ModelPricing( + input_price_low=input_low, + input_price_high=input_high, + output_price_low=output_low, + output_price_high=output_high, + cached_input_price_low=cached_low, + cached_input_price_high=cached_high, + ) + _logger.debug( + 'Parsed pricing for %s: in=$%.2f-$%.2f, out=$%.2f-$%.2f', + model_key, + input_low, + input_high, + output_low, + output_high, + ) + except (ValueError, IndexError) as e: + _logger.debug('Failed to parse prices for %s: %s', model_key, e) + continue + + except Exception as e: + _logger.warning('Error parsing pricing page: %s', e) + + return pricing_data # Global pricing service instance diff --git a/tests/unittests/utils/test_gemini_pricing.py b/tests/unittests/utils/test_gemini_pricing.py index 85512a3c90..1e7101031f 100644 --- a/tests/unittests/utils/test_gemini_pricing.py +++ b/tests/unittests/utils/test_gemini_pricing.py @@ -14,12 +14,23 @@ from __future__ import annotations +from google.adk.utils import gemini_pricing from google.adk.utils.gemini_pricing import calculate_token_cost from google.adk.utils.gemini_pricing import GeminiPricingService from google.adk.utils.gemini_pricing import ModelPricing import pytest +@pytest.fixture(autouse=True) +def disable_pricing_fetch(): + """Disable live pricing fetch for all tests.""" + # Reset the global pricing service before each test + gemini_pricing._pricing_service = GeminiPricingService(enable_fetch=False) + yield + # Clean up after test + gemini_pricing._pricing_service = None + + class TestModelPricing: """Test the ModelPricing class.""" @@ -101,7 +112,7 @@ class TestGeminiPricingService: @pytest.mark.asyncio async def test_get_pricing_exact_match(self): """Test getting pricing for an exact model name match.""" - service = GeminiPricingService() + service = GeminiPricingService(enable_fetch=False) pricing = await service.get_pricing("gemini-2.5-pro") assert pricing is not None assert pricing.input_price_low == 1.25 @@ -109,7 +120,7 @@ async def test_get_pricing_exact_match(self): @pytest.mark.asyncio async def test_get_pricing_fuzzy_match(self): """Test getting pricing for a model with version suffix.""" - service = GeminiPricingService() + service = GeminiPricingService(enable_fetch=False) pricing = await service.get_pricing("gemini-2.5-flash-001") assert pricing is not None assert pricing.input_price_low == 0.30 @@ -117,7 +128,7 @@ async def test_get_pricing_fuzzy_match(self): @pytest.mark.asyncio async def test_get_pricing_with_prefix(self): """Test getting pricing for a model with 'models/' prefix.""" - service = GeminiPricingService() + service = GeminiPricingService(enable_fetch=False) pricing = await service.get_pricing("models/gemini-2.0-flash") assert pricing is not None assert pricing.input_price_low == 0.15 @@ -125,7 +136,7 @@ async def test_get_pricing_with_prefix(self): @pytest.mark.asyncio async def test_get_pricing_unknown_model(self): """Test getting pricing for an unknown model.""" - service = GeminiPricingService() + service = GeminiPricingService(enable_fetch=False) pricing = await service.get_pricing("unknown-model-xyz") assert pricing is None From 1deb9976164e430a3b9f76a642fe09df95446b70 Mon Sep 17 00:00:00 2001 From: Templight41 Date: Wed, 17 Dec 2025 12:18:42 +0530 Subject: [PATCH 3/5] chore: Remove frontend code - to be implemented in adk-web repo Removed frontend-specific code as per maintainer feedback: - Deleted src/google/adk/cli/browser/token-usage-display.js - Removed JavaScript injection endpoint from adk_web_server.py Backend API remains intact: - Token cost calculation in base_llm_flow.py - cost_usd field in LlmResponse model - Gemini pricing service with live API fetching - All unit tests passing (12/12) Frontend implementation will be done in the separate adk-web repository. --- src/google/adk/cli/adk_web_server.py | 34 -- .../adk/cli/browser/token-usage-display.js | 464 ------------------ 2 files changed, 498 deletions(-) delete mode 100644 src/google/adk/cli/browser/token-usage-display.js diff --git a/src/google/adk/cli/adk_web_server.py b/src/google/adk/cli/adk_web_server.py index b11912f7db..5d71591466 100644 --- a/src/google/adk/cli/adk_web_server.py +++ b/src/google/adk/cli/adk_web_server.py @@ -1696,40 +1696,6 @@ async def redirect_root_to_dev_ui(): async def redirect_dev_ui_add_slash(): return RedirectResponse(redirect_dev_ui_url) - @app.get("/dev-ui/index.html") - @app.get("/dev-ui/") - async def serve_index_with_token_display(): - """Serve index.html with token usage display script injected.""" - from pathlib import Path - - from fastapi.responses import HTMLResponse - - index_path = Path(web_assets_dir) / "index.html" - script_path = Path(web_assets_dir) / "token-usage-display.js" - - if not index_path.exists(): - return HTMLResponse("Index not found", status_code=404) - - # Read the index.html content - with open(index_path, "r", encoding="utf-8") as f: - html_content = f.read() - - # Read the token usage script - script_content = "" - if script_path.exists(): - with open(script_path, "r", encoding="utf-8") as f: - script_content = f.read() - - # Inject the token usage display script inline before - script_tag = f"" - if "" in html_content: - html_content = html_content.replace("", f"{script_tag}") - else: - # Fallback: append at the end - html_content += script_tag - - return HTMLResponse(content=html_content) - app.mount( "/dev-ui/", StaticFiles(directory=web_assets_dir, html=True, follow_symlink=True), diff --git a/src/google/adk/cli/browser/token-usage-display.js b/src/google/adk/cli/browser/token-usage-display.js deleted file mode 100644 index 23393cd481..0000000000 --- a/src/google/adk/cli/browser/token-usage-display.js +++ /dev/null @@ -1,464 +0,0 @@ -/** - * Token Usage and Cost Display - * - * This script monitors SSE events for token usage metadata and displays - * the accumulated token counts and estimated costs in USD. - * UI is integrated into the chat input area, matching the website's theme. - */ - -(function() { - 'use strict'; - - // State management - let sessionTokenUsage = { - totalPromptTokens: 0, - totalOutputTokens: 0, - totalCachedTokens: 0, - totalCost: 0, - totalTokens: 0, - eventCount: 0 - }; - - let isPopoverOpen = false; - let buttonElement = null; - let popoverElement = null; - - // Find the message input textarea - function findMessageInput() { - const selectors = [ - 'textarea[placeholder*="message" i]', - 'textarea[placeholder*="Message" i]', - 'textarea[aria-label*="message" i]', - 'textarea', - 'input[type="text"]', - ]; - - for (const selector of selectors) { - const el = document.querySelector(selector); - if (el) { - console.log('[Token Usage] Found input:', selector); - return el; - } - } - return null; - } - - // Create button container next to input - function createButtonContainer() { - const input = findMessageInput(); - if (!input) { - console.warn('[Token Usage] Could not find message input'); - return null; - } - - // Find the parent container that holds the input and buttons - let container = input.parentElement; - - // Look for a container that has multiple children (input + buttons) - while (container && container.children.length < 2 && container !== document.body) { - container = container.parentElement; - } - - if (!container || container === document.body) { - console.warn('[Token Usage] Could not find suitable container'); - return null; - } - - console.log('[Token Usage] Found container:', container); - - // Create a wrapper div for our button - const buttonWrapper = document.createElement('div'); - buttonWrapper.id = 'token-usage-wrapper'; - buttonWrapper.style.cssText = ` - display: inline-flex; - align-items: center; - margin: 0 8px; - `; - - // Try to append to container - container.appendChild(buttonWrapper); - - return buttonWrapper; - } - - // Create the main button that shows cost and token count - function createUsageButton() { - const button = document.createElement('button'); - button.id = 'token-usage-button'; - button.type = 'button'; - button.setAttribute('aria-label', 'Token usage and cost'); - - // Match the website's button styling - button.style.cssText = ` - background: transparent; - border: 1px solid rgba(128, 128, 128, 0.3); - border-radius: 20px; - padding: 6px 12px; - font-family: inherit; - font-size: 13px; - font-weight: 500; - cursor: pointer; - color: inherit; - display: inline-flex; - align-items: center; - gap: 6px; - transition: all 0.2s; - white-space: nowrap; - `; - - button.innerHTML = ` - $0.00 - | - 0 tokens - `; - - button.addEventListener('mouseenter', () => { - button.style.backgroundColor = 'rgba(128, 128, 128, 0.1)'; - button.style.borderColor = 'rgba(128, 128, 128, 0.5)'; - }); - - button.addEventListener('mouseleave', () => { - button.style.backgroundColor = 'transparent'; - button.style.borderColor = 'rgba(128, 128, 128, 0.3)'; - }); - - button.addEventListener('click', (e) => { - e.preventDefault(); - e.stopPropagation(); - togglePopover(button); - }); - - buttonElement = button; - return button; - } - - // Create the popover that shows detailed breakdown - function createPopover() { - const popover = document.createElement('div'); - popover.id = 'token-usage-popover'; - popover.style.cssText = ` - position: fixed; - background: var(--surface-container, #2d2d2d); - border: 1px solid rgba(255, 255, 255, 0.12); - border-radius: 12px; - padding: 16px; - font-family: inherit; - font-size: 13px; - box-shadow: 0 4px 16px rgba(0, 0, 0, 0.3); - z-index: 10001; - min-width: 200px; - display: none; - color: inherit; - `; - - popover.innerHTML = ` -
-
- Token Usage - -
-
- -
-
- Input - – -
- -
- Output - – -
- -
- Cost - – -
-
- -
-
- Total events - 0 -
-
- `; - - document.body.appendChild(popover); - - // Add reset button handler - const resetBtn = document.getElementById('reset-usage-btn'); - if (resetBtn) { - resetBtn.addEventListener('mouseenter', () => { - resetBtn.style.backgroundColor = 'rgba(255, 255, 255, 0.08)'; - }); - resetBtn.addEventListener('mouseleave', () => { - resetBtn.style.backgroundColor = 'transparent'; - }); - resetBtn.addEventListener('click', (e) => { - e.stopPropagation(); - resetUsage(); - }); - } - - // Close popover when clicking outside - document.addEventListener('click', (e) => { - const popoverEl = document.getElementById('token-usage-popover'); - const buttonEl = document.getElementById('token-usage-button'); - if (isPopoverOpen && - popoverEl && - !popoverEl.contains(e.target) && - buttonEl && - !buttonEl.contains(e.target)) { - closePopover(); - } - }); - - popoverElement = popover; - return popover; - } - - // Position popover relative to button - function positionPopover(button) { - const popover = document.getElementById('token-usage-popover'); - if (!popover || !button) return; - - const buttonRect = button.getBoundingClientRect(); - - // Position above the button - popover.style.bottom = `${window.innerHeight - buttonRect.top + 8}px`; - popover.style.right = `${window.innerWidth - buttonRect.right}px`; - popover.style.left = 'auto'; - popover.style.top = 'auto'; - } - - // Toggle popover visibility - function togglePopover(button) { - const popover = document.getElementById('token-usage-popover'); - if (!popover) return; - - isPopoverOpen = !isPopoverOpen; - - if (isPopoverOpen) { - positionPopover(button); - popover.style.display = 'block'; - } else { - popover.style.display = 'none'; - } - } - - // Close popover - function closePopover() { - const popover = document.getElementById('token-usage-popover'); - if (popover) { - popover.style.display = 'none'; - isPopoverOpen = false; - } - } - - // Update the button display - function updateButton() { - const costDisplay = document.getElementById('cost-display'); - const tokenCountDisplay = document.getElementById('token-count-display'); - - if (costDisplay) { - const costFormatted = sessionTokenUsage.totalCost >= 0.01 - ? `$${sessionTokenUsage.totalCost.toFixed(2)}` - : `$${sessionTokenUsage.totalCost.toFixed(4)}`; - costDisplay.textContent = costFormatted; - } - - if (tokenCountDisplay) { - const totalTokens = sessionTokenUsage.totalPromptTokens + sessionTokenUsage.totalOutputTokens; - tokenCountDisplay.textContent = `${totalTokens.toLocaleString()} token${totalTokens !== 1 ? 's' : ''}`; - } - } - - // Update the popover display - function updatePopover() { - const inputTokensEl = document.getElementById('popover-input-tokens'); - const outputTokensEl = document.getElementById('popover-output-tokens'); - const costEl = document.getElementById('popover-cost'); - const eventCountEl = document.getElementById('popover-event-count'); - - if (inputTokensEl) { - inputTokensEl.textContent = sessionTokenUsage.totalPromptTokens > 0 - ? sessionTokenUsage.totalPromptTokens.toLocaleString() - : '–'; - } - - if (outputTokensEl) { - outputTokensEl.textContent = sessionTokenUsage.totalOutputTokens > 0 - ? sessionTokenUsage.totalOutputTokens.toLocaleString() - : '–'; - } - - if (costEl) { - const costFormatted = sessionTokenUsage.totalCost >= 0.01 - ? `$${sessionTokenUsage.totalCost.toFixed(2)}` - : sessionTokenUsage.totalCost > 0 - ? `$${sessionTokenUsage.totalCost.toFixed(4)}` - : '–'; - costEl.textContent = costFormatted; - } - - if (eventCountEl) { - eventCountEl.textContent = sessionTokenUsage.eventCount.toString(); - } - } - - // Update all displays - function updateDisplay() { - updateButton(); - updatePopover(); - } - - // Reset usage statistics - function resetUsage() { - sessionTokenUsage = { - totalPromptTokens: 0, - totalOutputTokens: 0, - totalCachedTokens: 0, - totalCost: 0, - totalTokens: 0, - eventCount: 0 - }; - updateDisplay(); - } - - // Process an event from the SSE stream - function processEvent(eventData) { - try { - const event = JSON.parse(eventData); - - // Check if the event has usage metadata - if (event.usageMetadata) { - const metadata = event.usageMetadata; - - // Update token counts - if (metadata.promptTokenCount) { - sessionTokenUsage.totalPromptTokens += metadata.promptTokenCount; - } - if (metadata.candidatesTokenCount) { - sessionTokenUsage.totalOutputTokens += metadata.candidatesTokenCount; - } - if (metadata.cachedContentTokenCount) { - sessionTokenUsage.totalCachedTokens += metadata.cachedContentTokenCount; - } - - // Update cost if available - if (event.costUsd !== undefined && event.costUsd !== null) { - sessionTokenUsage.totalCost += event.costUsd; - sessionTokenUsage.eventCount++; - } - - // Update the display - updateDisplay(); - } - } catch (e) { - console.error('Error processing event for token usage:', e); - } - } - - // Intercept fetch requests to monitor SSE events - const originalFetch = window.fetch; - window.fetch = function(...args) { - const request = args[0]; - - // Check if this is a run_sse request - if (typeof request === 'string' && request.includes('/run_sse')) { - return originalFetch.apply(this, args).then(response => { - // Clone the response so we can read it - const clonedResponse = response.clone(); - - // Process the SSE stream - const reader = clonedResponse.body.getReader(); - const decoder = new TextDecoder(); - - function readStream() { - reader.read().then(({ done, value }) => { - if (done) return; - - const chunk = decoder.decode(value, { stream: true }); - const lines = chunk.split('\n'); - - for (const line of lines) { - if (line.startsWith('data: ')) { - const data = line.substring(6); - if (data && data !== '[DONE]') { - processEvent(data); - } - } - } - - readStream(); - }); - } - - readStream(); - - return response; - }); - } - - return originalFetch.apply(this, args); - }; - - // Try to inject the button - function tryInject(retries = 15) { - console.log(`[Token Usage] Injection attempt ${16 - retries}/15`); - - const wrapper = createButtonContainer(); - - if (wrapper) { - const button = createUsageButton(); - wrapper.appendChild(button); - createPopover(); - console.log('[Token Usage] ✓ Button injected successfully'); - return true; - } else if (retries > 0) { - setTimeout(() => tryInject(retries - 1), 1000); - return false; - } else { - console.warn('[Token Usage] ✗ Could not find suitable location after 15 attempts'); - - // Fallback: Create floating button - console.log('[Token Usage] Creating fallback floating button'); - const button = createUsageButton(); - button.style.position = 'fixed'; - button.style.bottom = '20px'; - button.style.right = '20px'; - button.style.zIndex = '10000'; - document.body.appendChild(button); - createPopover(); - console.log('[Token Usage] ✓ Fallback button created'); - return true; - } - } - - // Initialize when the DOM is ready - function initialize() { - console.log('[Token Usage] Initializing...'); - - if (document.readyState === 'loading') { - document.addEventListener('DOMContentLoaded', () => { - console.log('[Token Usage] DOM loaded, starting injection'); - tryInject(); - }); - } else { - console.log('[Token Usage] DOM already loaded, starting injection'); - tryInject(); - } - } - - initialize(); -})(); From 4431fb9015b9d29aeb78705d1de1c7728ec6561a Mon Sep 17 00:00:00 2001 From: Ari <88184960+Templight41@users.noreply.github.com> Date: Wed, 17 Dec 2025 12:28:25 +0530 Subject: [PATCH 4/5] Update src/google/adk/utils/gemini_pricing.py Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> --- src/google/adk/utils/gemini_pricing.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/google/adk/utils/gemini_pricing.py b/src/google/adk/utils/gemini_pricing.py index 5771605a30..ee24e89a3f 100644 --- a/src/google/adk/utils/gemini_pricing.py +++ b/src/google/adk/utils/gemini_pricing.py @@ -323,7 +323,7 @@ def _parse_pricing_page(self, html_content: str) -> dict[str, ModelPricing]: # Extract all prices in this section prices = re.findall(price_pattern, section) - if len(prices) >= 4: + if len(prices) >= 2: # Typically: input_low, input_high, output_low, output_high # or just: input, output (if no tiering) try: From 9e5b272c7666b37d3a10435bd701545f76ff506b Mon Sep 17 00:00:00 2001 From: Templight41 Date: Wed, 17 Dec 2025 12:31:24 +0530 Subject: [PATCH 5/5] remove unused variabled --- src/google/adk/utils/gemini_pricing.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/src/google/adk/utils/gemini_pricing.py b/src/google/adk/utils/gemini_pricing.py index ee24e89a3f..0b08408074 100644 --- a/src/google/adk/utils/gemini_pricing.py +++ b/src/google/adk/utils/gemini_pricing.py @@ -31,8 +31,6 @@ import asyncio from dataclasses import dataclass -from datetime import datetime -from datetime import timedelta import logging import re from typing import Optional