Chat completion

Given a list of messages comprising a conversation, the model will return a response.

Create chat completion

Creates a model response for the given chat conversation

POST https://api.eternalai.org/v1/chat/completions

We strive to keep EternalAI Chat Completion API as similar to OpenAI's as possible, making it easy for developers who have built apps using OpenAI APIs to switch seamlessly.

The only differences are the inclusion of chain_id in the request body and onchain_data in the response body, as EternalAI APIs are empowered by a decentralized AI infrastructure.

Request body

messages array Required

A list of messages comprising the conversation so far.

model string Required

ID of the model to use.
For additional details, refer to the Onchain Models.

chain_id string Optional Defaults to 45762 (Symbiosis' chain id)

ID of blockchain hosting the model to use.
For additional details, refer to the Onchain Models.

store boolean or null Optional Defaults to false

Whether or not to store the output of this chat completion request for use in our model distillation or evals products.

metadata object or null Optional

Developer-defined tags and values used for filtering completions in the dashboard.

frequency_penalty number or null Optional Defaults to 0

Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.

logit_bias map Optional Defaults to null

Modify the likelihood of specified tokens appearing in the completion.
Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.

logprobs boolean or null Optional Defaults to false

Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message.

top_logprobs integer or null Optional

An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to true if this parameter is used.

max_tokens (Deprecated) integer or null Optional

The maximum number of tokens that can be generated in the chat completion. This value can be used to control costs for text generated via API.
This value is now deprecated in favor of max_completion_tokens, and is not compatible with o1 series models.

max_completion_tokens integer or null Optional

An upper bound for the number of tokens that can be generated for a completion, including visible output tokens and reasoning tokens.

n integer or null Optional Defaults to 1

How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.

modalities array or null Optional

Output types that you would like the model to generate for this request. Most models are capable of generating text, which is the default: ["text"]

prediction object Optional

Configuration for a Predicted Output, which can greatly improve response times when large parts of the model response are known ahead of time. This is most common when you are regenerating a file with only minor changes to most of the content.

audio object or null Optional [TODO]

Parameters for audio output. Required when audio output is requested with modalities: ["audio"].

presence_penalty number or null Optional Defaults to 0

Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.

response_format object Optional

An object specifying the format that the model must output.
Setting to { "type": "json_schema", "json_schema": {...} } enables Structured Outputs which ensures the model will match your supplied JSON schema. Learn more in the Structured Outputs guide.
Setting to { "type": "json_object" } enables JSON mode, which ensures the message the model generates is valid JSON.
Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if finish_reason="length", which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.

seed integer or null Optional

This feature is in Beta. If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.

service_tier string or null Optional Defaults to auto

Specifies the latency tier to use for processing the request. This parameter is relevant for customers subscribed to the scale tier service:
- If set to 'auto', and the Project is Scale tier enabled, the system will utilize scale tier credits until they are exhausted.
- If set to 'auto', and the Project is not Scale tier enabled, the request will be processed using the default service tier with a lower uptime SLA and no latency guarentee.
- If set to 'default', the request will be processed using the default service tier with a lower uptime SLA and no latency guarentee.
- When not set, the default behavior is 'auto'.
When this parameter is set, the response body will include the service_tier utilized.

stop string / array / null Optional Defaults to null

Up to 4 sequences where the API will stop generating further tokens.

stream boolean or null Optional Defaults to false

If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message.

stream_options object or null Optional Defaults to null

Options for streaming response. Only set this when you set stream: true.

temperature number or null Optional Defaults to 1

What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
We generally recommend altering this or top_p but not both.

top_p number or null Optional Defaults to 1

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or temperature but not both.

tools array Optional

A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.

tool_choice string or object Optional

Controls which (if any) tool is called by the model. none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools. Specifying a particular tool via {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.
none is the default when no tools are present. auto is the default if tools are present.

parallel_tool_calls boolean Optional Defaults to true

Whether to enable parallel function calling during tool use.

user string Optional

A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.

function_call (Deprecated) string or object Optional

Deprecated in favor of tool_choice.
Controls which (if any) function is called by the model. none means the model will not call a function and instead generates a message. auto means the model can pick between generating a message or calling a function. Specifying a particular function via {"name": "my_function"} forces the model to call that function.
none is the default when no functions are present. auto is the default if functions are present.

functions (Deprecated) array Optional

Deprecated in favor of tools.
A list of functions the model may generate JSON inputs for.

Response body

Represents a chat completion response returned by model, based on the provided input.

id string

A unique identifier for the chat completion.

choices array

A list of chat completion choices. Can be more than one if n is greater than 1.

created integer

The Unix timestamp (in seconds) of when the chat completion was created.

model string

The model used for the chat completion.

service_tier string or null

The service tier used for processing the request. This field is only included if the service_tier parameter is specified in the request.

system_fingerprint string

This fingerprint represents the backend configuration that the model runs with.
Can be used in conjunction with the seed request parameter to understand when backend changes have been made that might impact determinism.

object string

The object type, which is always chat.completion.

usage object

Usage statistics for the completion request.

onchain_data object

assignment_addresses array
- addresses of model miners assigned to serve the inference
infer_tx string
- tx hash of inference request tx
submit_tx string
- tx hash of inference response tx submitted by a miner
input_cid string
- content of inference prompt
output_cid string
- content of inference response

Example request & response

The ETERNALAI_API_KEY can be obtained by following the guide

Request

 
curl --location 'https://api.eternalai.org/v1/chat/completions' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer $ETERNALAI_API_KEY' \
--data '{
    "chain_id": "8453",
    "model": "DeepSeek-R1-Distill-Llama-70B",
    "messages": [
        {
            "role": "system",
            "content": "You are a helpful assistant."
        },
        {
            "role": "user",
            "content": "Hello!"
        }
    ]
}'

Response

{
  "id": "chatcmpl-p5n76HCHiWOYFMYj4S4LNRv9g0Pz91z3",
  "object": "chat.completion",
  "created": 1737471058,
  "model": "DeepSeek-R1-Distill-Llama-70B",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "<think>\nOkay, the user greeted me with \"Hello!\" and I responded warmly. Now, they're asking me to act as a helpful assistant. I should keep the conversation going by inviting them to ask questions or share what they need help with. I'll make sure to sound friendly and approachable.\n</think>\n\nHello! How can I assist you today? If you have any questions or need help with something, feel free to ask!"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 11,
    "completion_tokens": 89,
    "total_tokens": 100
  },
  "system_fingerprint": "b4519-80d0d6b4",
  "message": "",
  "type": "",
  "param": null,
  "code": 0,
  "onchain_data": {
    "infer_id": "13209",
    "pbft_committee": [
      "0xc557e228d2443b437e5297a8266b0f3257b2109a",
      "0xb9deb8db9724e2cb551164cdab0dd03a484cb9da",
      "0xfe5598e12532c8fe8fa586f8f6d2e12e82bb2825"
    ],
    "proposer": "0xfe5598e12532c8fe8fa586f8f6d2e12e82bb2825",
    "infer_tx": "0xd3b7adde419d44083e5d66489191053e15b250aea5dc168b8f6f4e18c90b2ff2",
    "propose_tx": "0x57d40d2720b512fbb64541e70611d044c8703c6fc05b7122a561f95645bc0f62"
  }
}

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