
* Initial implementation * Fix handling of return_step_logits in return * Fixed OpenAI parameter expectations and logprob structure and datatypes * pre-commit black formatting * Remove unused parameter * fix log probs * fix colorize * nits in server * nits in server * Fix top_logprobs structure (a dict) and include tokens in logprobs response * nits * fix types --------- Co-authored-by: Awni Hannun <awni@apple.com>
2.5 KiB
HTTP Model Server
You use mlx-lm
to make an HTTP API for generating text with any supported
model. The HTTP API is intended to be similar to the OpenAI chat
API.
Note
The MLX LM server is not recommended for production as it only implements basic security checks.
Start the server with:
mlx_lm.server --model <path_to_model_or_hf_repo>
For example:
mlx_lm.server --model mlx-community/Mistral-7B-Instruct-v0.3-4bit
This will start a text generation server on port 8080
of the localhost
using Mistral 7B instruct. The model will be downloaded from the provided
Hugging Face repo if it is not already in the local cache.
To see a full list of options run:
mlx_lm.server --help
You can make a request to the model by running:
curl localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"messages": [{"role": "user", "content": "Say this is a test!"}],
"temperature": 0.7
}'
Request Fields
-
messages
: An array of message objects representing the conversation history. Each message object should have a role (e.g. user, assistant) and content (the message text). -
role_mapping
: (Optional) A dictionary to customize the role prefixes in the generated prompt. If not provided, the default mappings are used. -
stop
: (Optional) An array of strings or a single string. Thesse are sequences of tokens on which the generation should stop. -
max_tokens
: (Optional) An integer specifying the maximum number of tokens to generate. Defaults to100
. -
stream
: (Optional) A boolean indicating if the response should be streamed. If true, responses are sent as they are generated. Defaults to false. -
temperature
: (Optional) A float specifying the sampling temperature. Defaults to1.0
. -
top_p
: (Optional) A float specifying the nucleus sampling parameter. Defaults to1.0
. -
repetition_penalty
: (Optional) Applies a penalty to repeated tokens. Defaults to1.0
. -
repetition_context_size
: (Optional) The size of the context window for applying repetition penalty. Defaults to20
. -
logit_bias
: (Optional) A dictionary mapping token IDs to their bias values. Defaults toNone
. -
logprobs
: (Optional) An integer specifying the number of top tokens and corresponding log probabilities to return for each output in the generated sequence. If set, this can be any value between 1 and 10, inclusive.