@mastra/core/dist/test-utils/llm-mock.cjs.map

Mastra is the Typescript framework for building AI agents and assistants. It’s used by some of the largest companies in the world to build internal AI automation tooling and customer-facing agents.

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mockText : JSON.stringify(mockText),\n      };\n    },\n    doStream: async props => {\n      if (spyStream) {\n        spyStream(props);\n      }\n\n      const text = typeof mockText === 'string' ? mockText : JSON.stringify(mockText);\n      // Split the mock text into chunks for streaming\n      const chunks = text.split(' ').map(word => ({\n        type: 'text-delta' as const,\n        textDelta: word + ' ',\n      }));\n\n      return {\n        stream: simulateReadableStream({\n          chunks: [\n            ...chunks,\n            {\n              type: 'finish',\n              finishReason: 'stop',\n              logprobs: undefined,\n              usage: { completionTokens: 10, promptTokens: 3 },\n            },\n          ],\n        }),\n        rawCall: { rawPrompt: null, rawSettings: {} },\n      };\n    },\n  });\n\n  return mockModel;\n}\n\nexport class MockProvider extends MastraLLMV1 {\n  constructor({\n    spyGenerate,\n    spyStream,\n    objectGenerationMode,\n    mockText = 'Hello, world!',\n  }: {\n    spyGenerate?: (props: any) => void;\n    spyStream?: (props: any) => void;\n    objectGenerationMode?: 'json';\n    mockText?: string | Record<string, any>;\n  }) {\n    const mockModel = new MockLanguageModelV1({\n      defaultObjectGenerationMode: objectGenerationMode,\n      doGenerate: async props => {\n        if (spyGenerate) {\n          spyGenerate(props);\n        }\n\n        if (objectGenerationMode === 'json') {\n          return {\n            rawCall: { rawPrompt: null, rawSettings: {} },\n            finishReason: 'stop',\n            usage: { promptTokens: 10, completionTokens: 20 },\n            text: JSON.stringify(mockText),\n          };\n        }\n\n        return {\n          rawCall: { rawPrompt: null, rawSettings: {} },\n          finishReason: 'stop',\n          usage: { promptTokens: 10, completionTokens: 20 },\n          text: typeof mockText === 'string' ? mockText : JSON.stringify(mockText),\n        };\n      },\n      doStream: async props => {\n        if (spyStream) {\n          spyStream(props);\n        }\n\n        const text = typeof mockText === 'string' ? mockText : JSON.stringify(mockText);\n        // Split the mock text into chunks for streaming\n        const chunks = text.split(' ').map(word => ({\n          type: 'text-delta' as const,\n          textDelta: word + ' ',\n        }));\n\n        return {\n          stream: simulateReadableStream({\n            chunks: [\n              ...chunks,\n              {\n                type: 'finish',\n                finishReason: 'stop',\n                logprobs: undefined,\n                usage: { completionTokens: 10, promptTokens: 3 },\n              },\n            ],\n          }),\n          rawCall: { rawPrompt: null, rawSettings: {} },\n        };\n      },\n    });\n\n    super({ model: mockModel });\n  }\n\n  // @ts-ignore\n  stream(...args: any): PromiseLike<StreamReturn<any, any, any>> {\n    // @ts-ignore\n    const result = super.stream(...args);\n\n    return {\n      ...result,\n      // @ts-ignore on await read the stream\n      then: (onfulfilled, onrejected) => {\n        // @ts-ignore\n        return result.baseStream.pipeTo(new WritableStream()).then(onfulfilled, onrejected);\n      },\n    };\n  }\n\n  // @ts-ignore\n  __streamObject(...args): PromiseLike<StreamObjectResult<any>> {\n    // @ts-ignore\n    const result = super.__streamObject(...args);\n\n    return {\n      ...result,\n      // @ts-ignore on await read the stream\n      then: (onfulfilled, onrejected) => {\n        // @ts-ignore\n        return result.baseStream.pipeTo(new WritableStream()).then(onfulfilled, onrejected);\n      },\n    };\n  }\n}\n"]}