Endpoints

Base URL: https://sn1.api.macrocosmos.ai

We provide two primary API endpoints:

• POST /v1/chat/completions

• POST /web_retrieval

Chat completions endpoint

post

Main endpoint that handles both regular, multi step reasoning, test time inference, and mixture of miners chat completion.

Header parameters

api-keyany ofOptional

stringOptional

or

nullOptional

authorizationany ofOptional

stringOptional

or

nullOptional

Body

application/json

Request model for the /v1/chat/completions endpoint.

uidsany ofOptional

List of specific miner UIDs to query. If not provided, miners will be selected automatically.

Example: [1,2,3]

integer[]Optional

or

nullOptional

seedany ofOptional

Random seed for reproducible results. If not provided, a random seed will be generated.

Example: 42

integerOptional

or

nullOptional

taskany ofOptional

Task identifier to choose the inference type.

Default: InferenceTaskExample: InferenceTask

stringOptional

or

nullOptional

modelany ofOptional

Model identifier to filter available miners.

Example: hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4

stringOptional

or

nullOptional

test_time_inferencebooleanOptional

Enable step-by-step reasoning mode that shows the model's thinking process.

Default: false

mixturebooleanOptional

Enable mixture of miners mode that combines responses from multiple miners.

Default: false

sampling_parametersany ofOptional

Parameters to control text generation, such as temperature, top_p, etc.

Default: {"temperature":0.7,"top_p":0.95,"top_k":50,"max_new_tokens":1024,"do_sample":true}Example: {"do_sample":true,"max_new_tokens":512,"temperature":0.7,"top_k":50,"top_p":0.95}

objectOptional

or

nullOptional

inference_modeany ofOptional

Inference mode to use for the task.

Example: Reasoning-Fast

stringOptional

or

nullOptional

json_formatbooleanOptional

Enable JSON format for the response.

Default: falseExample: true

streambooleanOptional

Enable streaming for the response.

Default: falseExample: true

Responses

200

Successful response with streaming text

application/jsontext/event-stream

anyOptional

422

Validation Error

application/json

500

Internal server error or no available miners

post

/v1/chat/completions

HTTPcURLJavaScriptPython

POST /v1/chat/completions HTTP/1.1
Host: sn1.api.macrocosmos.ai
Content-Type: application/json
Accept: */*
Content-Length: 397

{
  "uids": [
    1,
    2,
    3
  ],
  "messages": [
    {
      "content": "Tell me about neural networks",
      "role": "user"
    }
  ],
  "seed": 42,
  "task": "InferenceTask",
  "model": "hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4",
  "test_time_inference": false,
  "mixture": false,
  "sampling_parameters": {
    "do_sample": true,
    "max_new_tokens": 512,
    "temperature": 0.7,
    "top_k": 50,
    "top_p": 0.95
  },
  "inference_mode": "Reasoning-Fast",
  "json_format": true,
  "stream": true
}

{
  "id": "ca0b8681-7b78-4234-8868-71ad1ebfa9ed",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "logprobs": null,
      "message": {
        "content": "Neural networks are a type of machine learning model inspired by the human brain's structure. They consist of interconnected nodes arranged in layers, including input, hidden, and output layers. These networks learn by adjusting weights during training using optimization algorithms. Neural networks find applications in image recognition, speech processing, and many other domains requiring pattern recognition and prediction capabilities.",
        "refusal": null,
        "role": "assistant",
        "audio": null,
        "function_call": null,
        "tool_calls": null
      }
    }
  ],
  "created": 1743016348,
  "model": "hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4",
  "object": "chat.completion",
  "service_tier": null,
  "system_fingerprint": null,
  "usage": null
}

/v1/chat/completions supports various inference strategies, which can be configured via the request parameters.

Supported inference modes:

• Standard Chat Completion

• Multistep Reasoning

• Test-Time Inference

• Mixture of Miners

It selects appropriate miners based on either explicitly provided UIDs or by applying internal filtering logic that matches miners to the task and model requirements.

Web retrieval endpoint

post

Retrieves information from the web based on a search query using multiple miners.

Header parameters

api-keyany ofOptional

stringOptional

or

nullOptional

authorizationany ofOptional

stringOptional

or

nullOptional

Body

application/json

Request model for the /web_retrieval endpoint.

uidsany ofOptional

List of specific miner UIDs to query. If not provided, miners will be selected automatically.

Example: [1,2,3]

integer[]Optional

or

nullOptional

search_querystringRequired

The query to search for on the web.

Example: latest advancements in quantum computing

n_minersinteger · min: 1Optional

Number of miners to query for results.

Default: 3Example: 15

n_resultsinteger · min: 1Optional

Maximum number of results to return in the response.

Default: 1Example: 5

max_response_timeinteger · min: 1Optional

Maximum time to wait for responses in seconds.

Default: 10Example: 15

Responses

200

Successful response with web search results

application/json

Response model for the /web_retrieval endpoint.

422

Validation Error

application/json

500

Internal server error, no available miners, or no successful miner responses

post

/web_retrieval

HTTPcURLJavaScriptPython

POST /web_retrieval HTTP/1.1
Host: sn1.api.macrocosmos.ai
Content-Type: application/json
Accept: */*
Content-Length: 125

{
  "uids": [
    1,
    2,
    3
  ],
  "search_query": "latest advancements in quantum computing",
  "n_miners": 15,
  "n_results": 5,
  "max_response_time": 15
}

{
  "results": [
    {
      "url": "https://example.com/article",
      "content": "Quantum computing has seen significant advancements in the past year...",
      "relevant": "This article discusses the latest breakthroughs in quantum computing research."
    }
  ]
}

/web_retrievalenables distributed web search via a network of miners. A search query is dispatched to multiple miners, each of which performs an independent web retrieval process. The aggregated results are deduplicated based on URLs before being returned to the client.