@langchain/core/dist/language_models/profile.d.cts.map

Core LangChain.js abstractions and schemas

{"version":3,"file":"profile.d.cts","names":["ModelProfile"],"sources":["../../src/language_models/profile.d.ts"],"sourcesContent":["/**\n * Represents the capabilities and constraints of a language model.\n *\n * This interface defines the various features and limitations that a model may have,\n * including input/output constraints, multimodal support, and advanced capabilities\n * like tool calling and structured output.\n */\nexport interface ModelProfile {\n    /**\n     * Maximum number of tokens that can be included in the input context window.\n     *\n     * This represents the total token budget for the model's input, including\n     * the prompt, system messages, conversation history, and any other context.\n     *\n     * @example\n     * ```typescript\n     * const profile: ModelProfile = {\n     *   maxInputTokens: 128000 // Model supports up to 128k tokens\n     * };\n     * ```\n     */\n    maxInputTokens?: number;\n    /**\n     * Whether the model supports image inputs.\n     *\n     * When `true`, the model can process images as part of its input, enabling\n     * multimodal interactions where visual content can be analyzed alongside text.\n     *\n     * @see {@link imageUrlInputs} for URL-based image input support\n     */\n    imageInputs?: boolean;\n    /**\n     * Whether the model supports image URL inputs.\n     *\n     * When `true`, the model can accept URLs pointing to images rather than\n     * requiring the image data to be embedded directly in the request. This can\n     * be more efficient for large images or when images are already hosted.\n     *\n     * @see {@link imageInputs} for direct image input support\n     */\n    imageUrlInputs?: boolean;\n    /**\n     * Whether the model supports PDF document inputs.\n     *\n     * When `true`, the model can process PDF files as input, allowing it to\n     * analyze document content, extract information, or answer questions about\n     * PDF documents.\n     */\n    pdfInputs?: boolean;\n    /**\n     * Whether the model supports audio inputs.\n     *\n     * When `true`, the model can process audio data as input, enabling\n     * capabilities like speech recognition, audio analysis, or multimodal\n     * interactions involving sound.\n     */\n    audioInputs?: boolean;\n    /**\n     * Whether the model supports video inputs.\n     *\n     * When `true`, the model can process video data as input, enabling\n     * capabilities like video analysis, scene understanding, or multimodal\n     * interactions involving moving images.\n     */\n    videoInputs?: boolean;\n    /**\n     * Whether the model supports image content in tool messages.\n     *\n     * When `true`, tool responses can include images that the model can process\n     * and reason about. This enables workflows where tools return visual data\n     * that the model needs to interpret.\n     */\n    imageToolMessage?: boolean;\n    /**\n     * Whether the model supports PDF content in tool messages.\n     *\n     * When `true`, tool responses can include PDF documents that the model can\n     * process and reason about. This enables workflows where tools return\n     * document data that the model needs to interpret.\n     */\n    pdfToolMessage?: boolean;\n    /**\n     * Maximum number of tokens the model can generate in its output.\n     *\n     * This represents the upper limit on the length of the model's response.\n     * The actual output may be shorter depending on the completion criteria\n     * (e.g., natural stopping point, stop sequences).\n     *\n     * @example\n     * ```typescript\n     * const profile: ModelProfile = {\n     *   maxOutputTokens: 4096 // Model can generate up to 4k tokens\n     * };\n     * ```\n     */\n    maxOutputTokens?: number;\n    /**\n     * Whether the model supports reasoning or chain-of-thought output.\n     *\n     * When `true`, the model can produce explicit reasoning steps or\n     * chain-of-thought explanations as part of its output. This is useful\n     * for understanding the model's decision-making process and improving\n     * transparency in complex reasoning tasks.\n     */\n    reasoningOutput?: boolean;\n    /**\n     * Whether the model can generate image outputs.\n     *\n     * When `true`, the model can produce images as part of its response,\n     * enabling capabilities like image generation, editing, or visual\n     * content creation.\n     */\n    imageOutputs?: boolean;\n    /**\n     * Whether the model can generate audio outputs.\n     *\n     * When `true`, the model can produce audio data as part of its response,\n     * enabling capabilities like text-to-speech, audio generation, or\n     * sound synthesis.\n     */\n    audioOutputs?: boolean;\n    /**\n     * Whether the model can generate video outputs.\n     *\n     * When `true`, the model can produce video data as part of its response,\n     * enabling capabilities like video generation, editing, or visual\n     * content creation with motion.\n     */\n    videoOutputs?: boolean;\n    /**\n     * Whether the model supports tool calling (function calling).\n     *\n     * When `true`, the model can invoke external tools or functions during\n     * its reasoning process. The model can decide which tools to call,\n     * with what arguments, and can incorporate the tool results into its\n     * final response.\n     *\n     * @see {@link toolChoice} for controlling tool selection behavior\n     * @see {@link https://docs.langchain.com/oss/javascript/langchain/models#tool-calling}\n     */\n    toolCalling?: boolean;\n    /**\n     * Whether the model supports tool choice control.\n     *\n     * When `true`, the caller can specify how the model should select tools,\n     * such as forcing the use of a specific tool, allowing any tool, or\n     * preventing tool use entirely. This provides fine-grained control over\n     * the model's tool-calling behavior.\n     *\n     * @see {@link toolCalling} for basic tool calling support\n     */\n    toolChoice?: boolean;\n    /**\n     * Whether the model supports structured output generation.\n     *\n     * When `true`, the model can generate responses that conform to a\n     * specified schema or structure (e.g., JSON with a particular format).\n     * This is useful for ensuring the model's output can be reliably parsed\n     * and processed programmatically.\n     *\n     * @example\n     * ```typescript\n     * // Model can be instructed to return JSON matching a schema\n     * const profile: ModelProfile = {\n     *   structuredOutput: true\n     * };\n     * ```\n     */\n    structuredOutput?: boolean;\n}\n//# sourceMappingURL=profile.d.ts.map"],"mappings":";;AAOA;;;;;;UAAiBA,YAAAA"}