chore: import upstream snapshot with attribution

apps/sim/tools/llm/chat.ts

@@ -0,0 +1,178 @@
+import { createLogger } from '@sim/logger'
+import { getProviderFromModel } from '@/providers/utils'
+import type { ToolConfig, ToolResponse } from '@/tools/types'
+
+const logger = createLogger('LLMChatTool')
+
+interface LLMChatParams {
+  model: string
+  systemPrompt?: string
+  context: string
+  apiKey?: string
+  temperature?: number
+  maxTokens?: number
+  azureEndpoint?: string
+  azureApiVersion?: string
+  vertexProject?: string
+  vertexLocation?: string
+  vertexCredential?: string
+  bedrockAccessKeyId?: string
+  bedrockSecretKey?: string
+  bedrockRegion?: string
+}
+
+interface LLMChatResponse extends ToolResponse {
+  output: {
+    content: string
+    model: string
+    tokens?: {
+      prompt?: number
+      completion?: number
+      total?: number
+    }
+  }
+}
+
+export const llmChatTool: ToolConfig<LLMChatParams, LLMChatResponse> = {
+  id: 'llm_chat',
+  name: 'LLM Chat',
+  description: 'Send a chat completion request to any supported LLM provider',
+  version: '1.0.0',
+
+  params: {
+    model: {
+      type: 'string',
+      required: true,
+      description: 'The model to use (e.g., gpt-4o, claude-sonnet-4-5, gemini-2.0-flash)',
+    },
+    systemPrompt: {
+      type: 'string',
+      required: false,
+      description: 'System prompt to set the behavior of the assistant',
+    },
+    context: {
+      type: 'string',
+      required: true,
+      description: 'The user message or context to send to the model',
+    },
+    apiKey: {
+      type: 'string',
+      required: false,
+      visibility: 'hidden',
+      description: 'API key for the provider (uses platform key if not provided for hosted models)',
+    },
+    temperature: {
+      type: 'number',
+      required: false,
+      description: 'Temperature for response generation (0-2)',
+    },
+    maxTokens: {
+      type: 'number',
+      required: false,
+      description: 'Maximum tokens in the response',
+    },
+    azureEndpoint: {
+      type: 'string',
+      required: false,
+      visibility: 'hidden',
+      description: 'Azure OpenAI endpoint URL',
+    },
+    azureApiVersion: {
+      type: 'string',
+      required: false,
+      visibility: 'hidden',
+      description: 'Azure OpenAI API version',
+    },
+    vertexProject: {
+      type: 'string',
+      required: false,
+      visibility: 'hidden',
+      description: 'Google Cloud project ID for Vertex AI',
+    },
+    vertexLocation: {
+      type: 'string',
+      required: false,
+      visibility: 'hidden',
+      description: 'Google Cloud location for Vertex AI (defaults to us-central1)',
+    },
+    vertexCredential: {
+      type: 'string',
+      required: false,
+      visibility: 'hidden',
+      description: 'Google Cloud OAuth credential ID for Vertex AI',
+    },
+    bedrockAccessKeyId: {
+      type: 'string',
+      required: false,
+      visibility: 'hidden',
+      description: 'AWS Access Key ID for Bedrock',
+    },
+    bedrockSecretKey: {
+      type: 'string',
+      required: false,
+      visibility: 'hidden',
+      description: 'AWS Secret Access Key for Bedrock',
+    },
+    bedrockRegion: {
+      type: 'string',
+      required: false,
+      visibility: 'hidden',
+      description: 'AWS region for Bedrock (defaults to us-east-1)',
+    },
+  },
+
+  request: {
+    url: () => '/api/providers',
+    method: 'POST',
+    headers: () => ({
+      'Content-Type': 'application/json',
+    }),
+    body: (params) => {
+      const provider = getProviderFromModel(params.model)
+
+      return {
+        provider,
+        model: params.model,
+        systemPrompt: params.systemPrompt,
+        context: JSON.stringify([{ role: 'user', content: params.context }]),
+        apiKey: params.apiKey,
+        temperature: params.temperature,
+        maxTokens: params.maxTokens,
+        azureEndpoint: params.azureEndpoint,
+        azureApiVersion: params.azureApiVersion,
+        vertexProject: params.vertexProject,
+        vertexLocation: params.vertexLocation,
+        vertexCredential: params.vertexCredential,
+        bedrockAccessKeyId: params.bedrockAccessKeyId,
+        bedrockSecretKey: params.bedrockSecretKey,
+        bedrockRegion: params.bedrockRegion,
+      }
+    },
+  },
+
+  transformResponse: async (response: Response) => {
+    if (!response.ok) {
+      const errorData = await response.json().catch(() => ({}))
+      const errorMessage = errorData.error || `LLM API error: ${response.status}`
+      logger.error('LLM chat request failed', { error: errorMessage })
+      throw new Error(errorMessage)
+    }
+
+    const data = await response.json()
+
+    return {
+      success: true,
+      output: {
+        content: data.content,
+        model: data.model,
+        tokens: data.tokens,
+      },
+    }
+  },
+
+  outputs: {
+    content: { type: 'string', description: 'The generated response content' },
+    model: { type: 'string', description: 'The model used for generation' },
+    tokens: { type: 'object', description: 'Token usage information' },
+  },
+}