Hive Compute

Run inference via Hive's OpenAI-compatible router. Submit a prompt or message array to any available model. Billed per input+output token in USDC on Base L2. Hive routes to the cheapest available model meeting your latency and quality spec.

{
  "type": "object",
  "properties": {
    "messages": {
      "type": "array",
      "description": "OpenAI-compatible messages array. Each item must have role (system|user|assistant) and content (string).",
      "items": {
        "type": "object",
        "properties": {
          "role": {
            "type": "string",
            "description": "Message role. One of: system, user, assistant."
          },
          "content": {
            "type": "string",
            "description": "Message content text."
          }
        }
      }
    },
    "model": {
      "type": "string",
      "description": "Specific model to use (e.g. gpt-4o, claude-3-5-sonnet, llama-3-70b). Omit to let Hive auto-route to the cheapest qualifying model."
    },
    "max_tokens": {
      "type": "integer",
      "description": "Maximum tokens to generate in the response. Default 512."
    },
    "temperature": {
      "type": "number",
      "description": "Sampling temperature between 0.0 and 2.0. Default 0.7."
    },
    "max_cost_usdc": {
      "type": "number",
      "description": "Hard cap on USDC spend for this inference call. Request rejected if estimated cost exceeds this. Default 0.05."
    },
    "did": {
      "type": "string",
      "description": "Agent DID (e.g. did:hive:xxxx). USDC billed to this agent's Hive wallet."
    },
    "api_key": {
      "type": "string",
      "description": "Agent API key issued by HiveGate. Required for authenticated inference."
    }
  },
  "required": [
    "messages",
    "did",
    "api_key"
  ]
}

Generate vector embeddings via Hive's embedding router. Billed per 1K input tokens in USDC on Base L2. Returns a float array suitable for semantic search, clustering, or RAG pipelines.

{
  "type": "object",
  "properties": {
    "input": {
      "type": "string",
      "description": "Text to embed. Pass a string for a single embedding or use the batch endpoint for multiple inputs."
    },
    "model": {
      "type": "string",
      "description": "Embedding model to use. Defaults to text-embedding-3-small. Options: text-embedding-3-small, text-embedding-3-large, embed-multilingual-v3."
    },
    "dimensions": {
      "type": "integer",
      "description": "Desired embedding dimensions. Must be supported by the selected model."
    },
    "did": {
      "type": "string",
      "description": "Agent DID. Billing is per 1K tokens."
    },
    "api_key": {
      "type": "string",
      "description": "Agent API key issued by HiveGate."
    }
  },
  "required": [
    "input",
    "did",
    "api_key"
  ]
}

Browse all models available through the Hive inference router — including per-token pricing in USDC, context window size, latency tier, and provider. No authentication required.

{
  "type": "object",
  "properties": {
    "family": {
      "type": "string",
      "description": "Filter by model family. One of: gpt-4, claude-3, llama-3, mistral, gemini, embed."
    },
    "max_price_per_1m": {
      "type": "number",
      "description": "Filter to models priced below this amount per 1M tokens in USDC."
    }
  }
}

Estimate the USDC cost for a prompt before running inference. Returns cost breakdown by input tokens, output tokens, and routing fee. Helps agents budget before committing a payment.

{
  "type": "object",
  "properties": {
    "prompt": {
      "type": "string",
      "description": "The prompt text to estimate cost for. Tokenized to determine input token count."
    },
    "model": {
      "type": "string",
      "description": "Model to estimate cost for. Use compute.list_models to browse available models and their per-token prices."
    },
    "max_output_tokens": {
      "type": "integer",
      "description": "Assumed maximum output tokens for cost estimation. Default 512."
    }
  },
  "required": [
    "prompt",
    "model"
  ]
}

Get an agent's compute usage history — total tokens consumed, total USDC spent, breakdown by model, and inference call log with timestamps.

{
  "type": "object",
  "properties": {
    "did": {
      "type": "string",
      "description": "Agent DID to fetch usage history for."
    },
    "api_key": {
      "type": "string",
      "description": "Agent API key for authentication."
    },
    "limit": {
      "type": "integer",
      "description": "Number of recent inference calls to return. Default 20, max 200."
    },
    "since": {
      "type": "string",
      "description": "ISO 8601 timestamp to filter usage from (e.g. 2025-01-01T00:00:00Z). Optional."
    }
  },
  "required": [
    "did",
    "api_key"
  ]
}