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kling_master_text

Convert text prompts into dynamic videos with fluid motion using FAL AI models. Specify duration, aspect ratio, and generate high-quality videos directly to your local machine.

Instructions

Kling 2.1 Master - Premium text-to-video with motion fluidity

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aspect_ratioNo16:9
durationNo
promptYesText prompt for video generation

Implementation Reference

  • Core handler function for executing the kling_master_text text-to-video tool. Configures FAL client, calls fal.subscribe on the specific endpoint, processes the video output with downloads and data URLs, and returns formatted JSON response.
    private async handleTextToVideo(args: any, model: any) { const { prompt, duration = 5, aspect_ratio = '16:9' } = args; try { // Configure FAL client lazily with query config override configureFalClient(this.currentQueryConfig); const inputParams: any = { prompt }; if (duration) inputParams.duration = duration; if (aspect_ratio) inputParams.aspect_ratio = aspect_ratio; const result = await fal.subscribe(model.endpoint, { input: inputParams }); const videoData = result.data as FalVideoResult; const videoProcessed = await downloadAndProcessVideo(videoData.video.url, model.id); return { content: [ { type: 'text', text: JSON.stringify({ model: model.name, id: model.id, endpoint: model.endpoint, prompt, video: { url: videoData.video.url, localPath: videoProcessed.localPath, ...(videoProcessed.dataUrl && { dataUrl: videoProcessed.dataUrl }), width: videoData.video.width, height: videoData.video.height, }, metadata: inputParams, download_path: DOWNLOAD_PATH, data_url_settings: { enabled: ENABLE_DATA_URLS, max_size_mb: Math.round(MAX_DATA_URL_SIZE / 1024 / 1024), }, autoopen_settings: { enabled: AUTOOPEN, note: AUTOOPEN ? "Files automatically opened with default application" : "Auto-open disabled" }, }, null, 2), }, ], }; } catch (error) { throw new Error(`${model.name} generation failed: ${error}`); } }
  • Dynamically generates the input schema for the kling_master_text tool (and all text-to-video tools) defining prompt, duration, and aspect_ratio parameters.
    } else if (category === 'textToVideo') { baseSchema.inputSchema.properties = { prompt: { type: 'string', description: 'Text prompt for video generation' }, duration: { type: 'number', default: 5, minimum: 1, maximum: 30 }, aspect_ratio: { type: 'string', enum: ['16:9', '9:16', '1:1', '4:3', '3:4'], default: '16:9' }, }; baseSchema.inputSchema.required = ['prompt']; } else if (category === 'imageToVideo') {
  • src/index.ts:110-118 (registration)
    Model registry defining the kling_master_text tool's id, endpoint, name, and description. Used by list_tools to register the tool and by call_tool to dispatch to handler.
    textToVideo: [ { id: 'veo3', endpoint: 'fal-ai/veo3', name: 'Veo 3', description: 'Google DeepMind\'s latest with speech and audio' }, { id: 'kling_master_text', endpoint: 'fal-ai/kling-video/v2.1/master/text-to-video', name: 'Kling 2.1 Master', description: 'Premium text-to-video with motion fluidity' }, { id: 'pixverse_text', endpoint: 'fal-ai/pixverse/v4.5/text-to-video', name: 'Pixverse V4.5', description: 'Advanced text-to-video generation' }, { id: 'magi', endpoint: 'fal-ai/magi', name: 'Magi', description: 'Creative video generation' }, { id: 'luma_ray2', endpoint: 'fal-ai/luma-dream-machine/ray-2', name: 'Luma Ray 2', description: 'Latest Luma Dream Machine' }, { id: 'wan_pro_text', endpoint: 'fal-ai/wan-pro/text-to-video', name: 'Wan Pro', description: 'Professional video effects' }, { id: 'vidu_text', endpoint: 'fal-ai/vidu/q1/text-to-video', name: 'Vidu Q1', description: 'High-quality text-to-video' } ],
  • src/index.ts:403-404 (registration)
    Dynamically registers kling_master_text (and other text-to-video tools) in the tools/list response by generating schemas from the model registry.
    for (const model of MODEL_REGISTRY.textToVideo) { tools.push(this.generateToolSchema(model, 'textToVideo'));
  • Helper function used by the handler to download video files, generate data URLs, auto-open files, and prepare the output object with localPath and dataUrl.
    async function downloadAndProcessVideo(videoUrl: string, modelName: string): Promise<any> { const filename = generateFilename('video', modelName); const localPath = await downloadFile(videoUrl, filename); const dataUrl = await urlToDataUrl(videoUrl); // Auto-open the downloaded video if available if (localPath) { await autoOpenFile(localPath); } const result: any = {}; // Only include localPath if download was successful if (localPath) { result.localPath = localPath; } // Only include dataUrl if it was successfully generated if (dataUrl) { result.dataUrl = dataUrl; } return result; }

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