🚧 WIP: Merge Dev Build (#4611)

* refactor: Agent CodeFiles, abortUpload WIP

* feat: code environment file upload

* refactor: useLazyEffect

* refactor:
- Add `watch` from `useFormContext` to check if code execution is enabled
- Disable file upload button if `agent_id` is not selected or code execution is disabled

* WIP: primeCodeFiles; refactor: rename sessionId to session_id for uniformity

* Refactor: Rename session_id to sessionId for uniformity in AuthService.js

* chore: bump @librechat/agents to version 1.7.1

* WIP: prime code files

* refactor: Update code env file upload method to use read stream

* feat: reupload code env file if no longer active

* refactor: isAssistantTool -> isEntityTool + address type issues

* feat: execute code tool hook

* refactor: Rename isPluginAuthenticated to checkPluginAuth in PluginController.js

* refactor: Update PluginController.js to use AuthType constant for comparison

* feat: verify tool authentication (execute_code)

* feat: enter librechat_code_api_key

* refactor: Remove unused imports in BookmarkForm.tsx

* feat: authenticate code tool

* refactor: Update Action.tsx to conditionally render the key and revoke key buttons

* refactor(Code/Action): prevent uncheck-able 'Run Code' capability when key is revoked

* refactor(Code/Action): Update Action.tsx to conditionally render the key and revoke key buttons

* fix: agent file upload edge cases

* chore: bump @librechat/agents

* fix: custom endpoint providerValue icon

* feat: ollama meta modal token values + context

* feat: ollama agents

* refactor: Update token models for Ollama models

* chore: Comment out CodeForm

* refactor: Update token models for Ollama and Meta models

api/utils/tokens.js

@@ -77,13 +77,27 @@ const anthropicModels = {
 };
 
 const metaModels = {
-  'llama2-13b': 4000,
-  'llama2-70b': 4000,
-  'llama3-8b': 8000,
-  'llama3-70b': 8000,
-  'llama3-1-8b': 127500,
-  'llama3-1-70b': 127500,
+  llama3: 8000,
+  llama2: 4000,
+  'llama3.1': 127500,
+  'llama3-1': 127500,
+  'llama3.1:405b': 127500,
+  'llama3.1:70b': 127500,
+  'llama3.1:8b': 127500,
   'llama3-1-405b': 127500,
+  'llama3-1-70b': 127500,
+  'llama3-1-8b': 127500,
+  'llama3-70b': 8000,
+  'llama3-8b': 8000,
+  'llama2-70b': 4000,
+  'llama2-13b': 4000,
+  'llama3:70b': 8000,
+  'llama3:8b': 8000,
+  'llama2:70b': 4000,
+};
+
+const ollamaModels = {
+  'qwen2.5': 32000,
 };
 
 const ai21Models = {
@@ -102,6 +116,7 @@ const bedrockModels = {
   ...anthropicModels,
   ...mistralModels,
   ...cohereModels,
+  ...ollamaModels,
   ...metaModels,
   ...ai21Models,
   ...amazonModels,

api/utils/tokens.spec.js

@@ -1,5 +1,5 @@
 const { EModelEndpoint } = require('librechat-data-provider');
-const { getModelMaxTokens, matchModelName, maxTokensMap } = require('./tokens');
+const { getModelMaxTokens, processModelData, matchModelName, maxTokensMap } = require('./tokens');
 
 describe('getModelMaxTokens', () => {
   test('should return correct tokens for exact match', () => {
@@ -317,3 +317,108 @@ describe('matchModelName', () => {
     expect(matchModelName('chat-', EModelEndpoint.google)).toBe('chat-');
   });
 });
+
+describe('Meta Models Tests', () => {
+  describe('getModelMaxTokens', () => {
+    test('should return correct tokens for LLaMa 2 models', () => {
+      expect(getModelMaxTokens('llama2')).toBe(4000);
+      expect(getModelMaxTokens('llama2.70b')).toBe(4000);
+      expect(getModelMaxTokens('llama2-13b')).toBe(4000);
+      expect(getModelMaxTokens('llama2-70b')).toBe(4000);
+    });
+
+    test('should return correct tokens for LLaMa 3 models', () => {
+      expect(getModelMaxTokens('llama3')).toBe(8000);
+      expect(getModelMaxTokens('llama3.8b')).toBe(8000);
+      expect(getModelMaxTokens('llama3.70b')).toBe(8000);
+      expect(getModelMaxTokens('llama3-8b')).toBe(8000);
+      expect(getModelMaxTokens('llama3-70b')).toBe(8000);
+    });
+
+    test('should return correct tokens for LLaMa 3.1 models', () => {
+      expect(getModelMaxTokens('llama3.1:8b')).toBe(127500);
+      expect(getModelMaxTokens('llama3.1:70b')).toBe(127500);
+      expect(getModelMaxTokens('llama3.1:405b')).toBe(127500);
+      expect(getModelMaxTokens('llama3-1-8b')).toBe(127500);
+      expect(getModelMaxTokens('llama3-1-70b')).toBe(127500);
+      expect(getModelMaxTokens('llama3-1-405b')).toBe(127500);
+    });
+
+    test('should handle partial matches for Meta models', () => {
+      // Test with full model names
+      expect(getModelMaxTokens('meta/llama3.1:405b')).toBe(127500);
+      expect(getModelMaxTokens('meta/llama3.1:70b')).toBe(127500);
+      expect(getModelMaxTokens('meta/llama3.1:8b')).toBe(127500);
+      expect(getModelMaxTokens('meta/llama3-1-8b')).toBe(127500);
+
+      // Test base versions
+      expect(getModelMaxTokens('meta/llama3.1')).toBe(127500);
+      expect(getModelMaxTokens('meta/llama3-1')).toBe(127500);
+      expect(getModelMaxTokens('meta/llama3')).toBe(8000);
+      expect(getModelMaxTokens('meta/llama2')).toBe(4000);
+    });
+  });
+
+  describe('matchModelName', () => {
+    test('should match exact LLaMa model names', () => {
+      expect(matchModelName('llama2')).toBe('llama2');
+      expect(matchModelName('llama3')).toBe('llama3');
+      expect(matchModelName('llama3.1:8b')).toBe('llama3.1:8b');
+    });
+
+    test('should match LLaMa model variations', () => {
+      // Test full model names
+      expect(matchModelName('meta/llama3.1:405b')).toBe('llama3.1:405b');
+      expect(matchModelName('meta/llama3.1:70b')).toBe('llama3.1:70b');
+      expect(matchModelName('meta/llama3.1:8b')).toBe('llama3.1:8b');
+      expect(matchModelName('meta/llama3-1-8b')).toBe('llama3-1-8b');
+
+      // Test base versions
+      expect(matchModelName('meta/llama3.1')).toBe('llama3.1');
+      expect(matchModelName('meta/llama3-1')).toBe('llama3-1');
+    });
+
+    test('should handle custom endpoint for Meta models', () => {
+      expect(matchModelName('llama2', EModelEndpoint.bedrock)).toBe('llama2');
+      expect(matchModelName('llama3', EModelEndpoint.bedrock)).toBe('llama3');
+      expect(matchModelName('llama3.1:8b', EModelEndpoint.bedrock)).toBe('llama3.1:8b');
+    });
+  });
+
+  describe('processModelData with Meta models', () => {
+    test('should process Meta model data correctly', () => {
+      const input = {
+        data: [
+          {
+            id: 'llama2',
+            pricing: {
+              prompt: '0.00001',
+              completion: '0.00003',
+            },
+            context_length: 4000,
+          },
+          {
+            id: 'llama3',
+            pricing: {
+              prompt: '0.00002',
+              completion: '0.00004',
+            },
+            context_length: 8000,
+          },
+        ],
+      };
+
+      const result = processModelData(input);
+      expect(result.llama2).toEqual({
+        prompt: 10,
+        completion: 30,
+        context: 4000,
+      });
+      expect(result.llama3).toEqual({
+        prompt: 20,
+        completion: 40,
+        context: 8000,
+      });
+    });
+  });
+});