# OpenClaw — 9-LLM Consensus Engine (`yanmiayn/openclaw-consensus`) Actor Consensus answers from 9 AI models. Eliminates hallucinations. - **URL**: https://apify.com/yanmiayn/openclaw-consensus.md - **Developed by:** [yanmiayn](https://apify.com/yanmiayn) (community) - **Categories:** AI, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## OpenClaw — 9-LLM Consensus Engine Get consensus answers from **9 AI models simultaneously**. Instead of trusting one model's answer, OpenClaw asks multiple models and synthesizes where they agree. ### What It Does 1. Takes your prompt 2. Sends it to 9 AI models (GPT-4o, Claude, Gemini, DeepSeek, Mistral, and more) 3. Synthesizes a **consensus answer** with a **confidence score** 4. Returns individual model responses + final agreement ### Why 9-Model Consensus? Single models hallucinate. When 9 different models trained on different data all agree, the answer is far more reliable. Confidence score tells you how much they agreed. - Confidence > 0.8: High agreement — very reliable - Confidence 0.6-0.8: Moderate agreement — generally trustworthy - Confidence < 0.6: Low agreement — treat with caution ### Pricing **$0.10 per consensus call** (pay-per-use via Apify) No monthly fee. Only pay when you use it. ### Input ```json { "prompt": "What is the most reliable way to handle database transactions in Python?", "providers": ["openai", "anthropic", "google"], "minConsensus": 0.6 } ```` | Field | Type | Required | Description | |-------|------|----------|-------------| | `prompt` | string | Yes | Your question or task | | `providers` | array | No | Which AI providers to use. Default: all available | | `minConsensus` | number | No | Min confidence threshold (0-1). Default: 0.6 | ### Output ```json { "prompt": "...", "consensus_answer": "Use SQLAlchemy with explicit transaction management...", "confidence": 0.87, "providers_used": ["openai", "anthropic", "google", "deepseek"], "provider_count": 4, "timestamp": "2026-04-29T12:00:00Z" } ``` ### Deployment Instructions ```bash ## 1. Install Apify CLI npm install -g apify-cli ## 2. Login apify login ## 3. Navigate to actor directory cd apify_openclaw_actor ## 4. Set your OpenClaw API key as actor secret apify secrets:add OPENCLAW_API_KEY your-rapidapi-key ## 5. Test locally apify run --input '{"prompt": "Best Python web framework 2026?"}' ## 6. Deploy to Apify platform apify push ## 7. Enable pay-per-event billing in Apify Console: ## Go to your Actor > Monetization > Enable "Pay per event" ## Set event name: "consensus_call" ## Set price: $0.10 per event ``` ### Get Your OpenClaw API Key 1. Go to [RapidAPI Hub](https://rapidapi.com/hub) 2. Search for "OpenClaw" 3. Subscribe to a plan (BASIC/PRO/ULTRA) 4. Copy your RapidAPI key 5. Set as `OPENCLAW_API_KEY` environment variable ### Use Cases - **Code review**: Get consensus on best practices - **Research synthesis**: Ask complex questions, get reliable answers - **Content verification**: Cross-check facts across models - **Decision support**: Get multi-model perspective on technical decisions *** Made by [yanmiayn](https://yanmiayn.com) · Powered by [OpenClaw](https://rapidapi.com/hub) ## Actor input object example ```json {} ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("yanmiayn/openclaw-consensus").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = {} # Run the Actor and wait for it to finish run = client.actor("yanmiayn/openclaw-consensus").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 '{}' | apify call yanmiayn/openclaw-consensus --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=yanmiayn/openclaw-consensus", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "OpenClaw — 9-LLM Consensus Engine", "description": "Consensus answers from 9 AI models. Eliminates hallucinations.", "version": "0.1", "x-build-id": "BVgkpAKvxBe9ehJ0X" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/yanmiayn~openclaw-consensus/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-yanmiayn-openclaw-consensus", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/yanmiayn~openclaw-consensus/runs": { "post": { "operationId": "runs-sync-yanmiayn-openclaw-consensus", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/yanmiayn~openclaw-consensus/run-sync": { "post": { "operationId": "run-sync-yanmiayn-openclaw-consensus", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": {} }, "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 } } } } } } } } } } ```