AI Proxy Multi | APISIX & API7 API Gateway Docs

Parameters

See plugin common configurations for configuration options available to all plugins.

fallback_strategy
string or array
vaild vaule:
string: instance_health_and_rate_limiting, http_429, or http_5xx
array: Any combination of rate_limiting, http_429, and http_5xx
Fallback strategy. The option instance_health_and_rate_limiting is kept for backward compatibility and is functionally the same as rate_limiting.
With rate_limiting or instance_health_and_rate_limiting, when the current instance's quota is exhausted, the request is forwarded to the next instance regardless of priority. With http_429, if an instance returns status code 429, the request is retried with other instances. With http_5xx, if an instance returns a 5xx status code, the request is retried with other instances. If all instances fail, the plugin returns the last error response code.
When not set, the plugin will not forward the request to low priority instances when tokens of the high priority instance are exhausted.
max_retries
integer
vaild vaule:
greater than or equal to 0
Maximum number of fallback retries after the initial request fails. This bounds how many additional instances a single request tries, so it does not exhaust every configured instance. Only takes effect together with fallback_strategy. When not set, there is no explicit cap and the plugin retries until an instance succeeds or all instances have been tried. Available in API7 Enterprise from version 3.9.14 and APISIX from version 3.17.0.
retry_on_failure_within_ms
integer
vaild vaule:
greater than or equal to 1
Only fall back to another instance when the upstream fails within this many milliseconds. Fast failures (such as connection errors and quick 429 or 5xx responses) are retried, while a slow failure that takes longer than this is returned to the client directly to avoid doubling the total wait time. Only takes effect together with fallback_strategy. When not set, the plugin retries regardless of how long the failed attempt took. Available in API7 Enterprise from version 3.9.14 and APISIX from version 3.17.0.
balancer
object
Load balancing configurations.
- algorithm
  string
  default: roundrobin
  vaild vaule:
  roundrobin, chash, or semantic
  Load balancing algorithm. When set to roundrobin, weighted round robin algorithm is used. When set to chash, consistent hashing algorithm is used. When set to semantic, the instance whose examples are semantically closest to the prompt is used, configured under semantic_opts.
  The semantic algorithm does not participate in health checks, fallback_strategy, or max_retries. An upstream failure on the selected instance is returned to the client; the algorithm falls back only when no instance clears its threshold or the embedding request fails.
  The semantic algorithm is available in API7 Enterprise from version 3.9.18 on the 3.9 line and from version 3.10.5 on the 3.10 line.
- hash_on
  string
  default: vars
  vaild vaule:
  vars, header, cookie, consumer, or vars_combinations
  Used when type is chash. Support hashing on built-in variables, header, cookie, consumer, or a combination of built-in variables.
- key
  string
  Used when type is chash. When hash_on is set to header or cookie, key is required. When hash_on is set to consumer, key is not required as the consumer name will be used as the key automatically.
semantic_opts
object
Configurations for the semantic balancer algorithm. Required when balancer.algorithm is semantic, and ignored otherwise.
Available in API7 Enterprise from version 3.9.18 on the 3.9 line and from version 3.10.5 on the 3.10 line.
- embeddings
  object
  required
  Embedding service used to turn the prompt and each instance's examples into vectors. The prompt is embedded on every request, so this service is on the request path.
  provider
  string
  required
  vaild vaule:
  openai or azure-openai
  Embedding service provider.
  model
  string
  required
  Name of the embedding model, such as text-embedding-3-small.
  endpoint
  string
  Embedding API endpoint. Optional for openai, which defaults to the public API. Required for azure-openai, where it has to be the full URL, such as https://{resource}.openai.azure.com/openai/deployments/{deployment}/embeddings?api-version={version}.
  auth
  object
  required
  Authentication for the embedding service, carried either as headers or as query parameters.
  header
  object
  Key-value pairs sent as request headers to the embedding service.
  query
  object
  Key-value pairs sent as query parameters to the embedding service.
  timeout
  integer
  default: 3000
  vaild vaule:
  greater than or equal to 1
  Timeout in milliseconds for an embedding request. Because the prompt is embedded synchronously, this bounds the latency added to each request when the embedding service is slow. On a timeout the request is routed to the fallback instance rather than failed.
  ssl_verify
  boolean
  default: true
  If true, verify the embedding service's TLS certificate.
- threshold
  number
  default: 0
  vaild vaule:
  between -1 and 1 inclusive
  Global minimum cosine similarity an instance has to reach to be selected. An instance's own threshold overrides this value. The default of 0 admits almost any prompt, so the fallback instance is only ever reached once a threshold above 0 is set.
- fallback
  string
  Name of the instance to route to when no instance clears its threshold or the embedding request fails. It is otherwise a normally ranked instance and needs its own examples. Defaults to the first instance when unset.
- debugging
  boolean
  default: false
  If true, return the per-instance similarity scores and the routing decision in the X-AI-Semantic-Scores and X-AI-Semantic-Picked-Instance response headers. Intended for tuning examples and thresholds, not for production traffic.
instances
array[object]
required
LLM instance configurations.
- name
  string
  required
  Name of the LLM service instance.
- examples
  array[string]
  vaild vaule:
  between 1 and 64 items
  Example utterances representing what this instance handles. Each one is embedded into its own reference vector, and the semantic balancer routes a request to the instance whose closest example is most similar to the prompt.
  Required for every instance when balancer.algorithm is semantic, including the instance named by semantic_opts.fallback. Ignored by the other algorithms.
  Available in API7 Enterprise from version 3.9.18 on the 3.9 line and from version 3.10.5 on the 3.10 line.
- threshold
  number
  vaild vaule:
  between -1 and 1 inclusive
  Minimum cosine similarity a prompt has to reach for this instance to be selected by the semantic balancer. Overrides semantic_opts.threshold for this instance.
  Available in API7 Enterprise from version 3.9.18 on the 3.9 line and from version 3.10.5 on the 3.10 line.
- provider
  string
  required
  vaild vaule:
  openai, deepseek, azure-openai, aimlapi, gemini, vertex-ai, anthropic, openrouter, bedrock, openai-compatible
  LLM service provider.
  When set to openai, the plugin sends detected Chat Completions, Responses API, and Embeddings requests to their corresponding OpenAI endpoints.
  When set to deepseek, the plugin will proxy requests to https://api.deepseek.com/chat/completions.
  When set to gemini (available from APISIX 3.15.0 and Enterprise 3.9.2), the plugin will proxy requests to https://generativelanguage.googleapis.com/v1beta/openai/chat/completions. If you are proxying requests to an embedding model, you should configure the embedding model endpoint in the override.
  When set to vertex-ai (available from APISIX 3.15.0 and Enterprise 3.9.2), the plugin proxies requests to Google Cloud Vertex AI. For chat completions, the plugin will proxy requests to https://{region}-aiplatform.googleapis.com/v1beta1/projects/{project_id}/locations/{region}/endpoints/openapi/chat/completions. For embeddings, the plugin will proxy requests to https://{region}-aiplatform.googleapis.com/v1/projects/{project_id}/locations/{region}/publishers/google/models/{model}:predict. These require configuring provider_conf with project_id and region. Alternatively, you can configure override for a custom endpoint.
  When set to anthropic (available from APISIX 3.15.0 and Enterprise 3.9.2), the plugin sends detected Chat Completions requests to https://api.anthropic.com/v1/chat/completions and native Anthropic Messages requests to https://api.anthropic.com/v1/messages.
  When set to openrouter (available from APISIX 3.15.0 and Enterprise 3.9.2), the plugin will proxy requests to https://openrouter.ai/api/v1/chat/completions.
  When set to bedrock (available from API7 Enterprise 3.9.12 and APISIX 3.17.0), the plugin proxies requests to AWS Bedrock using the Converse API.
  When set to aimlapi (available from APISIX 3.14.0 and Enterprise 3.8.17), the plugin uses the OpenAI-compatible driver and proxies the request to https://api.aimlapi.com/v1/chat/completions.
  When set to openai-compatible, the plugin proxies requests to the custom endpoint configured in override.
  When set to azure-openai, the plugin also proxies requests to the custom endpoint configured in override and additionally removes the model parameter from user requests.
- priority
  integer
  default: 0
  Priority of the LLM instance in load balancing. priority takes precedence over weight.
- weight
  integer
  required
  vaild vaule:
  greater than or equal to 0
  Weight of the LLM instance in load balancing.
- auth
  object
  required
  Authentication configurations.
  header
  object
  Authentication headers. At least one of the header and query should be configured. You can configure additional custom headers that will be forwarded to the upstream LLM service.
  query
  object
  Authentication query parameters. At least one of the header and query should be configured.
  gcp
  object
  GCP service account authentication for Vertex AI. Available in API7 Enterprise from 3.9.2 and APISIX from version 3.17.0.
  service_account_json
  string
  GCP service account JSON content used for authentication. This can be configured using this parameter or by setting the GCP_SERVICE_ACCOUNT environment variable.
  max_ttl
  integer
  Maximum TTL for GCP access token caching, in seconds.
  expire_early_secs
  integer
  default: 60
  Number of seconds to expire the access token before its actual expiration time. This prevents edge cases where tokens expire during active requests.
  aws
  object
  AWS IAM credentials for SigV4 signing. Required when provider is bedrock (for Bedrock, auth.aws is sufficient and auth.header/auth.query are not required). Available in API7 Enterprise from version 3.9.12 and APISIX from version 3.17.0.
  access_key_id
  string
  required
  AWS IAM access key ID.
  secret_access_key
  string
  required
  AWS IAM secret access key.
  session_token
  string
  AWS session token for temporary credentials (e.g. from STS AssumeRole).
- options
  object
  Model configurations.
  In addition to model, you can configure additional parameters and they will be forwarded to the upstream LLM service in the request body. For instance, if you are working with OpenAI or DeepSeek, you can configure additional parameters such as max_tokens, temperature, top_p, and stream. See your LLM provider's API documentation for more available options.
  model
  string
  Name of the LLM model, such as gpt-4 or gpt-3.5. See your LLM provider's API documentation for more available models.
- provider_conf
  object
  Provider-specific configuration. Required when provider is bedrock. When provider is vertex-ai, configure either provider_conf or override.endpoint.
  Available in API7 Enterprise from 3.9.2 and APISIX from version 3.17.0.
  project_id
  string
  Google Cloud Project ID for Vertex AI.
  region
  string
  required
  Cloud region. For vertex-ai, this is the GCP region. For bedrock, this is the AWS region (e.g. us-east-1).
- override
  object
  Override setting.
  endpoint
  string
  LLM provider endpoint to replace the endpoint selected for the detected request protocol.
  llm_options
  object
  Provider-aware LLM option overrides. Available in API7 Enterprise from version 3.9.10 and APISIX from version 3.17.0.
  max_tokens
  integer
  Maximum number of output tokens. The gateway automatically maps this to the correct field name for the target provider, such as max_completion_tokens for OpenAI Chat or max_output_tokens for OpenAI Responses API, and overwrites the client value.
  request_body
  object
  Per target-protocol request body overrides. Keys are target protocol names, such as openai-chat, openai-responses, openai-embeddings, anthropic-messages, bedrock-converse, and passthrough. Values are partial request bodies that are deep-merged into the outgoing body. Available in API7 Enterprise from version 3.9.10 and APISIX from version 3.17.0.
  request_body_force_override
  boolean
  default: false
  When false (default), client request body fields take priority and request_body override values only fill in missing fields. When true, request_body override values overwrite client fields. Available in API7 Enterprise from version 3.9.10 and APISIX from version 3.17.0.
- checks
  object
  Health check configurations.
  Note that at the moment, OpenAI and DeepSeek do not provide an official health check endpoint. Other LLM services that you can configure under openai-compatible provider may have available health check endpoints.
  active
  object
  required
  Active health check configurations.
  type
  string
  default: http
  vaild vaule:
  http, https, or tcp
  Type of health check connection.
  timeout
  number
  default: 1
  Health check timeout in seconds.
  concurrency
  integer
  default: 10
  Number of upstream nodes to be checked at the same time.
  host
  string
  HTTP host.
  port
  integer
  vaild vaule:
  between 1 and 65535 inclusive
  HTTP port.
  http_path
  string
  default: /
  Path for HTTP probing requests.
  http_method
  string
  default: GET
  vaild vaule:
  CONNECT, DELETE, GET, HEAD, OPTIONS, PATCH, POST, PURGE, PUT, or TRACE
  HTTP method for active health check probing requests. Available in API7 Enterprise and not available in APISIX yet.
  http_req_body
  string
  Request body to send in active health check probing requests. This is useful when http_method is set to POST. Defaults to empty string. Available in API7 Enterprise and not available in APISIX yet.
  https_verify_certificate
  boolean
  default: true
  If true, verify the node's TLS certificate.
  healthy
  object
  Healthy check configurations.
  interval
  integer
  default: 1
  Time interval of checking healthy nodes, in seconds.
  http_statuses
  array[integer]
  default: [200,302]
  vaild vaule:
  status code between 200 and 599 inclusive
  An array of HTTP status codes that defines a healthy node.
  successes
  integer
  default: 2
  vaild vaule:
  between 1 and 254 inclusive
  Number of successful probes to define a healthy node.
  req_headers
  array[string]
  List of additional HTTP headers to send in health check probing requests, in "Header: Value" format.
  unhealthy
  object
  Unhealthy check configurations.
  interval
  integer
  default: 1
  Time interval of checking unhealthy nodes, in seconds.
  http_statuses
  array[integer]
  default: [429,404,500,501,502,503,504,505]
  vaild vaule:
  status code between 200 and 599 inclusive
  An array of HTTP status codes that defines an unhealthy node.
  http_failures
  integer
  default: 5
  vaild vaule:
  between 1 and 254 inclusive
  Number of HTTP failures to define an unhealthy node.
  tcp_failures
  integer
  default: 2
  vaild vaule:
  between 1 and 254 inclusive
  Number of TCP failures to define an unhealthy node.
  timeouts
  integer
  default: 3
  vaild vaule:
  between 1 and 254 inclusive
  Number of probe timeouts to define an unhealthy node.
logging
object
Logging configurations. These configurations apply to access logs and logs sent to logging plugins, and do not affect the error log.
- summaries
  boolean
  default: false
  If true, log request LLM model, duration, request and response tokens.
- payloads
  boolean
  default: false
  If true, log request and response payload.
timeout
integer
default: 30000
vaild vaule:
between 1 and 600000 inclusive
Request timeout in milliseconds when requesting the LLM service.
max_req_body_size
integer
default: 67108864
vaild vaule:
greater than or equal to 1
Maximum request body size in bytes that the plugin reads into memory. Larger requests are rejected with HTTP 413. This prevents unbounded memory buffering of large request bodies. The default is 67108864 bytes (64 MB). Available in API7 Enterprise from version 3.9.14 and APISIX from version 3.17.0.
max_stream_duration_ms
integer
vaild vaule:
greater than or equal to 1
Maximum wall-clock duration, in milliseconds, for a streaming AI response. If the upstream keeps sending data past this deadline, the gateway closes the connection. When the limit is reached mid-stream, the downstream stream is truncated without a protocol-specific terminator such as [DONE], message_stop, or response.completed. Available in API7 Enterprise from version 3.9.10 and APISIX from version 3.17.0.
max_response_bytes
integer
vaild vaule:
greater than or equal to 1
Maximum total bytes read from the upstream for a single AI response, including streaming and non-streaming responses. If the response exceeds this value, the gateway closes the connection. Available in API7 Enterprise from version 3.9.10 and APISIX from version 3.17.0.
streaming_flush_interval_ms
integer
default: 10
vaild vaule:
greater than or equal to 0
Background flush interval in milliseconds for streaming responses. A positive value periodically flushes buffered output to bound client latency when the upstream sends tokens in bursts. Set to 0 to flush each chunk synchronously. Available in API7 Enterprise from version 3.9.13 and APISIX from version 3.17.0.
keepalive
boolean
default: true
If true, keep the connection alive when requesting the LLM service.
keepalive_timeout
integer
default: 60000
vaild vaule:
greater than or equal to 1000
Keepalive timeout in milliseconds when requesting the LLM service.
keepalive_pool
integer
default: 30
vaild vaule:
greater than or equal to 1
Keepalive pool size for when connecting with the LLM service.
ssl_verify
boolean
default: true
If true, verify the LLM service's certificate.

Parameters​

Parameters