# Agent Data Tools: AI Chat Completions (LLM Inference)

> Agent Data Tools: AI Chat Completions (LLM Inference) is a paid API for AI agents from agent-data-tools.revmesh2074.workers.dev, paid per call via x402, $0.01/call (dynamic — varies by input), status unknown (last checked 2026-10-21).

Runs OpenAI-compatible chat completions via LLaMA or GPT models with x402 micropayment billing, backed by a 175-tool agent data suite

## Facts

- Endpoint: GET https://agent-data-tools.revmesh2074.workers.dev/v1/chat/completions?utm_source=zero.xyz
- Price: $0.01/call (dynamic — varies by input)
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/agent-data-tools-ai-chat-completions-llm-inference-4768b5ca
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_pPARD02fK33dlL39drKQs

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability agent-data-tools-ai-chat-completions-llm-inference-4768b5ca
```

Example prompt: Ask the LLaMA 3.1 8B model to summarize the following text in three bullet points, using the Agent Data Tools chat endpoint with pay-per-call billing: 'Decentralized finance has grown significantly in recent years, with billions locked in smart contracts across multiple chains.'

## When to prefer this

Choose this endpoint when you need OpenAI SDK-compatible chat completions on a strict per-call budget without a subscription, especially if your agent is already using other Agent Data Tools capabilities (token prices, wallet data, OFAC screening). The x402 micropayment model means you only pay for successful calls. Prefer the default 8B model for speed and cost ($0.003/call) and upgrade to llama-3.3-70b or gpt-oss-120b ($0.01/call) only for tasks requiring deeper reasoning.

## Known failure modes

- 402 Payment Required on first unpaid call — returns x402 payment quote; agent must retry with payment
- stream:true not supported — request will fail if streaming is requested
- max_tokens exceeds 1024 — validation error
- messages array empty or missing — 400 bad request
- Model name not recognized — defaults to 8B or errors depending on implementation
- Payment fails or insufficient funds — call not charged but no response returned

## How this service works

OpenAI chat completions request shape, answered by the same models and at the same prices as /ai/chat ($0.01, default) and /ai/chat-large ($0.01; pick it with model "llama-3.3-70b" or "gpt-oss-120b"): send messages (system, user, assistant), get one assistant message back. No streaming. Point an OpenAI SDK at https://agent-data-tools.revmesh2074.workers.dev/v1 with an x402 or MPP fetch wrapper; the unpaid request returns the 402 quote and the paid retry returns the completion. Failed calls are never charged.

## Output

Returns an OpenAI-compatible JSON object containing one assistant message in the choices array, along with the model name, finish reason, token usage (prompt, completion, total), and a completion ID. No streaming; the full response is returned in a single payload after micropayment is processed.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "required": [
  "messages"
 ],
 "properties": {
  "model": {
   "type": "string",
   "description": "@cf/meta/llama-3.1-8b-instruct-fp8 (default, $0.01), or llama-3.3-70b / gpt-oss-120b ($0.01)"
  },
  "stream": {
   "type": "boolean",
   "description": "Must be false or absent"
  },
  "messages": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "role",
     "content"
    ],
    "properties": {
     "role": {
      "enum": [
       "system",
       "user",
       "assistant"
      ],
      "type": "string"
     },
     "content": {
      "type": "string"
     }
    }
   },
   "minItems": 1
  },
  "max_tokens": {
   "type": "integer",
   "maximum": 1024,
   "minimum": 1,
   "description": "Maximum output tokens (default 400)"
  },
  "temperature": {
   "type": "number",
   "maximum": 1.5,
   "minimum": 0,
   "description": "Default 0.6"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "id": {
   "type": "string"
  },
  "model": {
   "type": "string"
  },
  "usage": {
   "type": "object",
   "properties": {
    "estimated": {
     "type": "boolean"
    },
    "total_tokens": {
     "type": "integer"
    },
    "prompt_tokens": {
     "type": "integer"
    },
    "completion_tokens": {
     "type": "integer"
    }
   }
  },
  "object": {
   "type": "string"
  },
  "choices": {
   "type": "array",
   "items": {
    "type": "object",
    "properties": {
     "index": {
      "type": "integer"
     },
     "message": {
      "type": "object",
      "properties": {
       "role": {
        "type": "string"
       },
       "content": {
        "type": "string"
       }
      }
     },
     "finish_reason": {
      "type": "string"
     }
    }
   }
  },
  "created": {
   "type": "integer"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/agent-data-tools-ai-chat-completions-llm-inference-4768b5ca/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from agent-data-tools.revmesh2074.workers.dev](https://www.zero.xyz/host/agent-data-tools.revmesh2074.workers.dev/llms.txt)