AI Proxy変更履歴

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Changelog

Kong Gateway 3.9.x

• Disabled the HTTP/2 ALPN handshake for connections on routes configured with AI Proxy. #13735
• Fixed an issue where tools (function) calls to Anthropic would return empty results. #13760
• Fixed an issue where tools (function) calls to Bedrock would return empty results. #13760
• Fixed an issue where Bedrock Guardrail config was ignored. #13760
• Fixed an issue where tools (function) calls to Cohere would return empty results. #13760
• Fixed an issue where the Gemini provider would return an error if content safety failed in AI Proxy. #13760
• Fixed an issue where tools (function) calls to Gemini (or via Vertex) would return empty results. #13760
• Fixed an issue where multi-modal requests were blocked on the Azure AI provider. #13702

Kong Gateway 3.8.x

• Added the allow_override option to allow overriding the upstream model auth parameter or header from the caller’s request. #13158
• Replaced the library and use cycle_aware_deep_copy for the request_table object. #13582
• The Mistral provider can now use mistral.ai-managed services by omitting the upstream_url. #13481
• Added the new response header X-Kong-LLM-Model, which displays the name of the language model used in the AI Proxy plugin. #13472
• Latency data is now pushed to logs and metrics. #13428
• Kong AI Gateway now supports all AWS Bedrock Converse API models. #12948
• Kong AI Gateway now supports the Google Gemini chat (generateContent) interface. #12948
• Fixed various issues #13000:
  • Fixed an issue where certain Azure models would return partial tokens/words when in response-streaming mode.
  • Fixed an issue where Cohere and Anthropic providers didn’t read the model parameter properly from the caller’s request body.
  • Fixed an issue where using OpenAI Function inference requests would log a request error, and then hang until timeout.
  • Fixed an issue where AI Proxy would still allow callers to specify their own model, ignoring the plugin-configured model name.
  • Fixed an issue where AI Proxy would not take precedence of the plugin’s configured model tuning options over those in the user’s LLM request.
  • Fixed an issue where setting OpenAI SDK model parameter null caused analytics to not be written to the logging plugin(s).
• Fixed an issue when response was gzipped even if the client didn’t accept the format. #13155
• Fixed an issue where the object constructor would set data on the class instead of the instance. #13028
• Added a configuration validation to prevent log_statistics from being enabled on providers that don’t support statistics. Accordingly, the default of log_statistics has changed from true to false, and a database migration has been added for disabling log_statistics if it has already been enabled upon unsupported providers. #12860
• Fixed an issue where the plugin couldn’t be applied per consumer or per service. #13209

Kong Gateway 3.7.x

• To support the new messages API of Anthropic, the upstream path of the Anthropic for llm/v1/chat route type has changed from /v1/complete to /v1/messages.
• Added support for streaming event-by-event responses back to the client on supported providers. #12792
• AI Proxy now reads most prompt tuning parameters from the client, while the plugin config parameters under model_options are now just defaults. This fixes support for using the respective provider’s native SDK. #12903
• You can now use an existing OpenAI-compatible SDK (for example, Python OpenAI) to call different models, providers, and configurations with Kong AI Gateway. AI Proxy now has a preserve option for route_type, where the requests and responses are passed directly to the upstream LLM. This enables compatibility with any models and SDKs that may be used when calling the AI services. #12903
• Added support for streaming event-by-event responses back to the client on supported providers. #12792
• Enterprise feature: You can now use Azure’s native authentication mechanism to secure your cloud-hosted models.

Kong Gateway 3.6.x

• Introduced the AI Proxy plugin, which can mediate request and response formats, as well as authentication between users. This plugin supports a variety of Large Language Model (LLM) AI services.