config.example.yaml

# add this modeline for validation in vscode
# yaml-language-server: $schema=https://raw.githubusercontent.com/mostlygeek/llama-swap/refs/heads/main/config-schema.json
#
# llama-swap YAML configuration example
# -------------------------------------
#
# 💡 Tip - Use an LLM with this file!
# ====================================
#  This example configuration is written to be LLM friendly. Try
#  copying this file into an LLM and asking it to explain or generate
#  sections for you.
# ====================================

# Usage notes:
# - Below are all the available configuration options for llama-swap.
# - Settings noted as "required" must be in your configuration file
# - Settings noted as "optional" can be omitted

# healthCheckTimeout: number of seconds to wait for a model to be ready to serve requests
# - optional, default: 120
# - minimum value is 15 seconds, anything less will be set to this value
healthCheckTimeout: 500

# logLevel: sets the logging value
# - optional, default: info
# - Valid log levels: debug, info, warn, error
logLevel: info

# logTimeFormat: enables and sets the logging timestamp format
# - optional, default (disabled): ""
# - Valid values: "", "ansic", "unixdate", "rubydate", "rfc822", "rfc822z",
#   "rfc850", "rfc1123", "rfc1123z", "rfc3339", "rfc3339nano", "kitchen",
#   "stamp", "stampmilli", "stampmicro", and "stampnano".
# - For more info, read: https://pkg.go.dev/time#pkg-constants
logTimeFormat: ""

# logToStdout: controls what is logged to stdout
# - optional, default: "proxy"
# - valid values:
#   - "proxy": logs generated by llama-swap when swapping models,
#      handling requests, etc.
#   - "upstream": a copy of an upstream processes stdout logs
#   - "both": both the proxy and upstream logs interleaved together
#   - "none": no logs are ever written to stdout
logToStdout: "proxy"

# metricsMaxInMemory: maximum number of metrics to keep in memory
# - optional, default: 1000
# - controls how many metrics are stored in memory before older ones are discarded
# - useful for limiting memory usage when processing large volumes of metrics
metricsMaxInMemory: 1000

# captureBuffer: how many MBs to allocate for storing request/response captures
# - optional, default: 10
# - set to 0 to disable
captureBuffer: 15

# startPort: sets the starting port number for the automatic ${PORT} macro.
# - optional, default: 5800
# - the ${PORT} macro can be used in model.cmd and model.proxy settings
# - it is automatically incremented for every model that uses it
startPort: 10001

# sendLoadingState: inject loading status updates into the reasoning (thinking)
# field
# - optional, default: false
# - when true, a stream of loading messages will be sent to the client in the
#   reasoning field so chat UIs can show that loading is in progress.
# - see #366 for more details
sendLoadingState: true

# includeAliasesInList: present aliases within the /v1/models OpenAI API listing
# - optional, default: false
# - when true, model aliases will be output to the API model listing duplicating
#   all fields except for Id so chat UIs can use the alias equivalent to the original.
includeAliasesInList: false

# globalTTL: the default TTL in seconds before unloading a model
# - optional, default: 0 (never automatically unload)
# - must be >= 0
globalTTL: 0

# macros: a dictionary of string substitutions
# - optional, default: empty dictionary
# - macros are reusable snippets
# - used in a model's cmd, cmdStop, proxy, checkEndpoint, filters.stripParams
# - useful for reducing common configuration settings
# - macro names are strings and must be less than 64 characters
# - macro names must match the regex ^[a-zA-Z0-9_-]+$
# - macro names must not be a reserved name: PORT or MODEL_ID
# - macro values can be numbers, bools, or strings
# - macros can contain other macros, but they must be defined before they are used
# - environment variables can be referenced with ${env.VAR_NAME} syntax
#   - env macros are substituted first, before regular macros
#   - if the env var is not set, config loading will fail with an error
macros:
  # Example of a multi-line macro
  "latest-llama": >
    /path/to/llama-server/llama-server-ec9e0301
    --port ${PORT}

  "default_ctx": 4096

  # Example of macro-in-macro usage. macros can contain other macros
  # but they must be previously declared.
  "default_args": "--ctx-size ${default_ctx}"

  # Example of environment variable macros
  # - ${env.VAR_NAME} pulls the value from the system environment
  # - useful for paths, secrets, or machine-specific configuration
  "models_dir": "${env.HOME}/models"

# apiKeys: require an API key when making requests to inference endpoints
# - optional, default: []
# - when empty (the default) authorization will not be checked as llama-swap is default-allow
# - each key is a non-empty string
apiKeys:
  - "sk-hunter2"
  # tip, one liner: printf "sk-%s\n" "$(head -c 48 /dev/urandom | base64 )"
  - "sk-gyCPiKUcIfPlaM4OSMZekkprgijPx6+OsmQs8Rsg0xZ9qpy6gKWsIKqHOk+cgXVx"

  # use environment variable macros to keep secrets out of the config
  - "${env.API_KEY_1}"
  - "${env.API_KEY_2}"

# models: a dictionary of model configurations
# - required
# - each key is the model's ID, used in API requests
# - model settings have default values that are used if they are not defined here
# - the model's ID is available in the ${MODEL_ID} macro, also available in macros defined above
# - below are examples of the all the settings a model can have
models:
  # keys are the model names used in API requests
  "gpt-oss-120b":
    # macros: a dictionary of string substitutions specific to this model
    # - optional, default: empty dictionary
    # - macros defined here override macros defined in the global macros section
    # - model level macros follow the same rules as global macros
    macros:
      "default_ctx": 16384
      "temp": 0.7

    # cmd: the command to run to start the inference server.
    # - required
    # - it is just a string, similar to what you would run on the CLI
    # - using `|` allows for comments in the command, these will be parsed out
    # - macros can be used within cmd
    cmd: |
      # ${latest-llama} is a macro that is defined above
      ${latest-llama}
      --model path/to/gpt-oss-120B.gguf
      --ctx-size ${default_ctx}
      --temperature ${temp}

    # name: a display name for the model
    # - optional, default: empty string
    # - if set, it will be used in the v1/models API response
    # - if not set, it will be omitted in the JSON model record
    name: "gpt-oss 120B"

    # description: a description for the model
    # - optional, default: empty string
    # - if set, it will be used in the v1/models API response
    # - if not set, it will be omitted in the JSON model record
    description: "A thinking model from OpenAI"

    # env: define an array of environment variables to inject into cmd's environment
    # - optional, default: empty array
    # - each value is a single string
    # - in the format: ENV_NAME=value
    env:
      - "CUDA_VISIBLE_DEVICES=0,1,2"

    # proxy: the URL where llama-swap routes API requests
    # - optional, default: http://localhost:${PORT}
    # - if you used ${PORT} in cmd this can be omitted
    # - if you use a custom port in cmd this *must* be set
    proxy: http://127.0.0.1:8999

    # checkEndpoint: URL path to check if the server is ready
    # - optional, default: /health
    # - endpoint is expected to return an HTTP 200 response
    # - all requests wait until the endpoint is ready or fails
    # - use "none" to skip endpoint health checking
    checkEndpoint: /custom-endpoint

    # ttl: automatically unload the model after ttl seconds
    # - optional, default: -1 (use global default)
    # - ttl values must be a value greater than or equal to 0
    # - a ttl of -1 will use the global TTL value as the default
    # - a ttl of 0 will mean never unload
    # - a value of 0 disables automatic unloading of the model
    ttl: 60

    # useModelName: override the model name that is sent to upstream server
    # - optional, default: ""
    # - useful for when the upstream server expects a specific model name that
    #   is different from the model's ID
    useModelName: "openai/gpt-oss-120B"

    # filters: a dictionary of filter settings
    # - optional, default: empty dictionary
    # - same capabilities as peer filters (stripParams, setParams)
    filters:
      # stripParams: a comma separated list of parameters to remove from the request
      # - optional, default: ""
      # - useful for server side enforcement of sampling parameters
      # - the `model` parameter can never be removed
      # - can be any JSON key in the request body
      # - recommended to stick to sampling parameters
      stripParams: "temperature, top_p, top_k"

      # setParams: a dictionary of parameters to set/override in requests
      # - optional, default: empty dictionary
      # - useful for enforcing specific parameter values
      # - protected params like "model" cannot be overridden
      # - values can be strings, numbers, booleans, arrays, or objects
      # - always runs for the model
      setParams:
        # Example: enforce specific sampling parameters
        temperature: 0.7
        top_p: 0.9

      # setParamsByID: a dictionary of parameters to set based the model ID
      # - optional, default: empty dictionary
      # - combine with aliases to create variant behaviour without reloading the model
      # - parameters are set in the request body JSON
      # - run after setParams so it will override any settings
      # - protected params like "model" cannot be overridden
      # - values can be strings, numbers, booleans, arrays, or objects
      # - model aliases will be automatically created for each key
      setParamsByID:
        "${MODEL_ID}":
          chat_template_kwargs:
            reasoning_effort: medium
        "${MODEL_ID}:high":
          chat_template_kwargs:
            reasoning_effort: high
        "${MODEL_ID}:low":
          chat_template_kwargs:
            reasoning_effort: low

    # aliases: alternative model names that this model configuration is used for
    # - optional, default: empty array
    # - aliases must be unique globally
    # - useful for impersonating a specific model
    aliases:
      - "gpt-4o-mini"

    # metadata: a dictionary of arbitrary values that are included in /v1/models
    # - optional, default: empty dictionary
    # - while metadata can contains complex types it is recommended to keep it simple
    # - metadata is only passed through in /v1/models responses
    metadata:
      # port will remain an integer
      port: ${PORT}

      # the ${temp} macro will remain a float
      temperature: ${temp}
      note: "The ${MODEL_ID} is running on port ${PORT} temp=${temp}, context=${default_ctx}"

      a_list:
        - 1
        - 1.23
        - "macros are OK in list and dictionary types: ${MODEL_ID}"

      an_obj:
        a: "1"
        b: 2
        # objects can contain complex types with macro substitution
        # becomes: c: [0.7, false, "model: llama"]
        c: ["${temp}", false, "model: ${MODEL_ID}"]

    # concurrencyLimit: overrides the allowed number of active parallel requests to a model
    # - optional, default: 0
    # - useful for limiting the number of active parallel requests a model can process
    # - must be set per model
    # - any number greater than 0 will override the internal default value of 10
    # - any requests that exceeds the limit will receive an HTTP 429 Too Many Requests response
    # - recommended to be omitted and the default used
    concurrencyLimit: 0

    # sendLoadingState: overrides the global sendLoadingState setting for this model
    # - optional, default: undefined (use global setting)
    sendLoadingState: false

  # Unlisted model example:
  "qwen-unlisted":
    # unlisted: boolean, true or false
    # - optional, default: false
    # - unlisted models do not show up in /v1/models api requests
    # - can be requested as normal through all apis
    unlisted: true
    cmd: llama-server --port ${PORT} -m Llama-3.2-1B-Instruct-Q4_K_M.gguf -ngl 0

  # Docker example:
  # container runtimes like Docker and Podman can be used reliably with
  # a combination of cmd, cmdStop, and ${MODEL_ID}
  "docker-llama":
    proxy: "http://127.0.0.1:${PORT}"
    cmd: |
      docker run --name ${MODEL_ID}
      --init --rm -p ${PORT}:8080 -v /mnt/nvme/models:/models
      ghcr.io/ggml-org/llama.cpp:server
      --model '/models/Qwen2.5-Coder-0.5B-Instruct-Q4_K_M.gguf'

    # cmdStop: command to run to stop the model gracefully
    # - optional, default: ""
    # - useful for stopping commands managed by another system
    # - the upstream's process id is available in the ${PID} macro
    #
    # When empty, llama-swap has this default behaviour:
    # - on POSIX systems: a SIGTERM signal is sent
    # - on Windows, calls taskkill to stop the process
    # - processes have 5 seconds to shutdown until forceful termination is attempted
    cmdStop: docker stop ${MODEL_ID}

# groups: a dictionary of group settings
# - optional, default: empty dictionary
# - provides advanced controls over model swapping behaviour
# - using groups some models can be kept loaded indefinitely, while others are swapped out
# - model IDs must be defined in the Models section
# - a model can only be a member of one group
# - group behaviour is controlled via the `swap`, `exclusive` and `persistent` fields
# - see issue #109 for details
#
# NOTE: the example below uses model names that are not defined above for demonstration purposes
groups:
  # group1 works the same as the default behaviour of llama-swap where only one model is allowed
  # to run a time across the whole llama-swap instance
  "group1":
    # swap: controls the model swapping behaviour in within the group
    # - optional, default: true
    # - true : only one model is allowed to run at a time
    # - false: all models can run together, no swapping
    swap: true

    # exclusive: controls how the group affects other groups
    # - optional, default: true
    # - true: causes all other groups to unload when this group runs a model
    # - false: does not affect other groups
    exclusive: true

    # members references the models defined above
    # required
    members:
      - "llama"
      - "qwen-unlisted"

  # Example:
  # - in group2 all models can run at the same time
  # - when a different group is loaded it causes all running models in this group to unload
  "group2":
    swap: false

    # exclusive: false does not unload other groups when a model in group2 is requested
    # - the models in group2 will be loaded but will not unload any other groups
    exclusive: false
    members:
      - "docker-llama"
      - "modelA"
      - "modelB"

  # Example:
  # - a persistent group, prevents other groups from unloading it
  "forever":
    # persistent: prevents over groups from unloading the models in this group
    # - optional, default: false
    # - does not affect individual model behaviour
    persistent: true

    # set swap/exclusive to false to prevent swapping inside the group
    # and the unloading of other groups
    swap: false
    exclusive: false
    members:
      - "forever-modelA"
      - "forever-modelB"
      - "forever-modelc"

# hooks: a dictionary of event triggers and actions
# - optional, default: empty dictionary
# - the only supported hook is on_startup
hooks:
  # on_startup: a dictionary of actions to perform on startup
  # - optional, default: empty dictionary
  # - the only supported action is preload
  on_startup:
    # preload: a list of model ids to load on startup
    # - optional, default: empty list
    # - model names must match keys in the models sections
    # - when preloading multiple models at once, define a group
    #   otherwise models will be loaded and swapped out
    preload:
      - "llama"

# peers: a dictionary of remote peers and models they provide
# - optional, default empty dictionary
# - peers can be another llama-swap
# - peers can be any server that provides the /v1/ generative api endpoints supported by llama-swap
peers:
  # keys is the peer'd ID
  llama-swap-peer:
    # proxy: a valid base URL to proxy requests to
    # - required
    # - requested path to llama-swap will be appended to the end of the proxy value
    proxy: http://192.168.1.23
    # models: a list of models served by the peer
    # - required
    models:
      - model_a
      - model_b
      - embeddings/model_c
  openrouter:
    proxy: https://openrouter.ai/api
    # apiKey: a string key to be injected into the request
    # - optional, default: ""
    # - if blank, no key will be added to the request
    # - key will be injected into headers: Authorization: Bearer <key> and x-api-key: <key>
    # - can be a string or a macro
    apiKey: ${env.OPENROUTER_API_KEY}
    models:
      - meta-llama/llama-3.1-8b-instruct
      - qwen/qwen3-235b-a22b-2507
      - deepseek/deepseek-v3.2
      - z-ai/glm-4.7
      - moonshotai/kimi-k2-0905
      - minimax/minimax-m2.1
    # filters: a dictionary of filter settings for peer requests
    # - optional, default: empty dictionary
    # - same capabilities as model filters (stripParams, setParams)
    filters:
      # stripParams: a comma separated list of parameters to remove from the request
      # - optional, default: ""
      # - useful for removing parameters that the peer doesn't support
      # - the `model` parameter can never be removed
      stripParams: "temperature, top_p"

      # setParams: a dictionary of parameters to set/override in requests to this peer
      # - optional, default: empty dictionary
      # - useful for injecting provider-specific settings like data retention policies
      # - protected params like "model" cannot be overridden
      # - values can be strings, numbers, booleans, arrays, or objects
      setParams:
        # Example: enforce zero-data-retention for OpenRouter
        provider:
          data_collection: "deny"
          zdr: true