# Fable Distiller (`gray0/fable-distiller`) Actor Bundle the Claude Fable 5 system prompt and apply it to any LLM model via your own API key. - **URL**: https://apify.com/gray0/fable-distiller.md - **Developed by:** [Safwan Kazi](https://apify.com/gray0) (community) - **Categories:** Agents, AI - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Fable Distiller - Apify Actor Bundle the **Claude Fable 5** system prompt (3,825 lines) and apply it to any LLM model via your own API key. ### How It Works 1. Select your **provider** (OpenAI, Anthropic, OpenRouter, or a custom OpenAI-compatible endpoint) 2. Enter your **API key** and choose a **model** 3. Provide your **messages** as a JSON array 4. The Actor prepends the entire Fable 5 system prompt and sends the request 5. The response is returned with token usage and metadata ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `provider` | select | Yes | `openai`, `anthropic`, `openrouter`, or `custom` | | `model` | string | Yes | Model name/ID (e.g., `gpt-4o`, `claude-sonnet-4-20250514`) | | `apiKey` | secret string | Yes | Your API key for the chosen provider | | `messages` | JSON array | Yes | `[{"role": "user", "content": "..."}]` | | `apiBaseUrl` | string | No | Custom base URL (required for `custom` provider) | | `maxTokens` | integer | No (default: 4096) | Max response tokens | | `temperature` | number | No (default: 1.0) | Response temperature (0.0–2.0) | ### Output **Success:** ```json { "success": true, "provider": "openai", "model": "gpt-4o", "content": "...", "usage": { "inputTokens": 1000, "outputTokens": 500, "totalTokens": 1500 }, "finishReason": "stop", "id": "chatcmpl-xxx" } ```` **Error:** ```json { "success": false, "provider": "openai", "model": "gpt-4o", "error": { "type": "auth_error", "message": "Invalid API key", "statusCode": 401 } } ``` ### Development ```bash ## Copy the Fable 5 prompt into this directory cp ../../claude-fable-5.md ./claude-fable-5.md ## Install dependencies npm install ## Type-check npm run typecheck ## Run tests npm test ## Build npm run build ## Run locally (requires a sample INPUT.json in the actor directory) npx apify run ``` ### Deployment ```bash npx apify login npx apify push ``` # Actor input Schema ## `provider` (type: `string`): Select your LLM provider. ## `model` (type: `string`): Model name/ID (e.g., gpt-4o, claude-sonnet-4-20250514). ## `apiKey` (type: `string`): Your API key for the chosen provider. ## `apiBaseUrl` (type: `string`): Custom base URL (required for "custom" provider, e.g., https://my-endpoint.example.com/v1). ## `messages` (type: `array`): Array of message objects with "role" and "content" fields (e.g., \[{"role": "user", "content": "Hello"}]). ## `maxTokens` (type: `integer`): Maximum number of tokens in the response. ## `temperature` (type: `number`): Temperature for response generation (0.0–2.0). ## Actor input object example ```json { "messages": [ { "role": "user", "content": "Hello, how are you?" } ], "maxTokens": 4096, "temperature": 1 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "apiKey": "", "apiBaseUrl": "", "messages": [ { "role": "user", "content": "Hello, how are you?" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("gray0/fable-distiller").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "apiKey": "", "apiBaseUrl": "", "messages": [{ "role": "user", "content": "Hello, how are you?", }], } # Run the Actor and wait for it to finish run = client.actor("gray0/fable-distiller").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "apiKey": "", "apiBaseUrl": "", "messages": [ { "role": "user", "content": "Hello, how are you?" } ] }' | apify call gray0/fable-distiller --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=gray0/fable-distiller", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Fable Distiller", "description": "Bundle the Claude Fable 5 system prompt and apply it to any LLM model via your own API key.", "version": "0.1", "x-build-id": "gCucRLNURkopLnCsW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/gray0~fable-distiller/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-gray0-fable-distiller", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/gray0~fable-distiller/runs": { "post": { "operationId": "runs-sync-gray0-fable-distiller", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/gray0~fable-distiller/run-sync": { "post": { "operationId": "run-sync-gray0-fable-distiller", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "provider", "model", "apiKey", "messages" ], "properties": { "provider": { "title": "LLM Provider", "enum": [ "openai", "anthropic", "openrouter", "custom" ], "type": "string", "description": "Select your LLM provider." }, "model": { "title": "Model Name", "type": "string", "description": "Model name/ID (e.g., gpt-4o, claude-sonnet-4-20250514)." }, "apiKey": { "title": "API Key", "type": "string", "description": "Your API key for the chosen provider." }, "apiBaseUrl": { "title": "Custom API Base URL", "type": "string", "description": "Custom base URL (required for \"custom\" provider, e.g., https://my-endpoint.example.com/v1)." }, "messages": { "title": "Messages", "type": "array", "description": "Array of message objects with \"role\" and \"content\" fields (e.g., [{\"role\": \"user\", \"content\": \"Hello\"}])." }, "maxTokens": { "title": "Max Tokens", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Maximum number of tokens in the response.", "default": 4096 }, "temperature": { "title": "Temperature", "minimum": 0, "maximum": 2, "type": "number", "description": "Temperature for response generation (0.0–2.0).", "default": 1 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```