✨ feat: Add token usage indicator to chat input

Add TokenUsageIndicator component with circular progress ring
Create useTokenUsage hook with Jotai atom for state
Add model context window lookups to data-provider
Consolidate token utilities (output limits, TOKEN_DEFAULTS)
Display input/output tokens and percentage of context used

packages/api/src/agents/initialize.ts

@@ -8,6 +8,7 @@ import {
   isAgentsEndpoint,
   replaceSpecialVars,
   providerEndpointMap,
+  TOKEN_DEFAULTS,
 } from 'librechat-data-provider';
 import type {
   AgentToolResources,
@@ -337,7 +338,7 @@ export async function initializeAgent(
       providerEndpointMap[provider as keyof typeof providerEndpointMap],
       options.endpointTokenConfig,
     ),
-    18000,
+    TOKEN_DEFAULTS.AGENT_CONTEXT_FALLBACK,
   );
 
   if (
@@ -394,7 +395,7 @@ export async function initializeAgent(
     agent.additional_instructions = artifactsPromptResult ?? undefined;
   }
 
-  const agentMaxContextNum = Number(agentMaxContextTokens) || 18000;
+  const agentMaxContextNum = Number(agentMaxContextTokens) || TOKEN_DEFAULTS.AGENT_CONTEXT_FALLBACK;
   const maxOutputTokensNum = Number(maxOutputTokens) || 0;
 
   const finalAttachments: IMongoFile[] = (primedAttachments ?? [])
@@ -413,7 +414,9 @@ export async function initializeAgent(
     toolContextMap: toolContextMap ?? {},
     useLegacyContent: !!options.useLegacyContent,
     tools: (tools ?? []) as GenericTool[] & string[],
-    maxContextTokens: Math.round((agentMaxContextNum - maxOutputTokensNum) * 0.9),
+    maxContextTokens: Math.round(
+      (agentMaxContextNum - maxOutputTokensNum) * TOKEN_DEFAULTS.CONTEXT_SAFETY_MARGIN,
+    ),
   };
 
   return initializedAgent;

packages/api/src/utils/tokens.ts

@@ -1,34 +1,16 @@
 import z from 'zod';
-import { EModelEndpoint } from 'librechat-data-provider';
+import {
+  EModelEndpoint,
+  TOKEN_DEFAULTS,
+  findMatchingPattern as findMatchingPatternSimple,
+  getModelMaxTokens as getModelMaxTokensSimple,
+  getModelMaxOutputTokens as getModelMaxOutputTokensSimple,
+  matchModelName as matchModelNameSimple,
+} from 'librechat-data-provider';
 import type { EndpointTokenConfig, TokenConfig } from '~/types';
 
-/**
- * Model Token Configuration Maps
- *
- * IMPORTANT: Key Ordering for Pattern Matching
- * ============================================
- * The `findMatchingPattern` function iterates through object keys in REVERSE order
- * (last-defined keys are checked first) and uses `modelName.includes(key)` for matching.
- *
- * This means:
- * 1. BASE PATTERNS must be defined FIRST (e.g., "kimi", "moonshot")
- * 2. SPECIFIC PATTERNS must be defined AFTER their base patterns (e.g., "kimi-k2", "kimi-k2.5")
- *
- * Example ordering for Kimi models:
- *   kimi: 262144,           // Base pattern - checked last
- *   'kimi-k2': 262144,      // More specific - checked before "kimi"
- *   'kimi-k2.5': 262144,    // Most specific - checked first
- *
- * Why this matters:
- * - Model name "kimi-k2.5" contains both "kimi" and "kimi-k2" as substrings
- * - If "kimi" were checked first, it would incorrectly match "kimi-k2.5"
- * - By defining specific patterns AFTER base patterns, they're checked first in reverse iteration
- *
- * When adding new model families:
- * 1. Define the base/generic pattern first
- * 2. Define increasingly specific patterns after
- * 3. Ensure no pattern is a substring of another that should match differently
- */
+// Re-export from data-provider for backwards compatibility
+export { TOKEN_DEFAULTS };
 
 const openAIModels = {
   'o4-mini': 200000,
@@ -421,6 +403,14 @@ export const maxOutputTokensMap = {
   [EModelEndpoint.custom]: { ...modelMaxOutputs, ...deepseekMaxOutputs },
 };
 
+// Re-export simple versions (for use without EndpointTokenConfig)
+export {
+  findMatchingPatternSimple,
+  getModelMaxTokensSimple,
+  getModelMaxOutputTokensSimple,
+  matchModelNameSimple,
+};
+
 /**
  * Finds the first matching pattern in the tokens map.
  * @param {string} modelName