Releases & Roadmap¶

stdapi.ai is under active development with regular feature releases.

Version Index¶

Latest: v1.19.1 — released 2026-09-29.

Every release, newest first. Each entry in the Release History below opens with a five-bullet summary.

Roadmap (Tracked on GitHub)¶

Pending features and current deployment state are tracked on the GitHub Project.

Release History¶

v1.19.0 – 2026-09-23 – Long Conversations, Reasoning Control & Medical Transcription (with v1.19.1 maintenance update, 2026-09-29)¶

This release is about what happens when a conversation gets long. An agent session eventually outgrows its model's context window, and the gateway had one answer for that: a refusal, often in the backend's words rather than the API's. The Responses API now trims or compacts a conversation when asked, Claude clears stale tool results through Anthropic's context editing, an overflow that still happens is refused exactly as the vendor refuses it, and a client can count tokens on every text model to see it coming. Around that: reasoning controls that now reach the model families that were dropping them, GPT-6 web search and code interpreter with no configuration, Moonshot Kimi K3, medical transcription, and a pass over reported costs that corrects several prices, one of them reported up to 50% above what AWS bills.

New API Features¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	truncation: "auto" on Responses – an input over the context window has its oldest turns dropped, then the latest turn's longest text cut at its end, until it fits. System and developer messages are always kept, usage reports the input that was kept, and input_tokens counts what a response would keep	Amazon Bedrock - Converse API, Bedrock Mantle
OpenAI	context_management compaction on Responses – once the input crosses compact_threshold, everything but the latest step is summarized into a compaction item that leads output and stands for the whole history when sent back; streamed at index 0 before the answer. A trailing compaction_trigger item compacts on demand, where it was silently dropped. Both calls are billed, and usage adds them up	Amazon Bedrock - Converse API, Bedrock Mantle
OpenAI & Anthropic	The output is capped when only it overflows – an input the window holds alone but not beside max_output_tokens or max_tokens is answered with a shorter output on Responses and Anthropic Messages, as both vendors answer it. Chat Completions keeps refusing it, as OpenAI does	Amazon Bedrock
OpenAI & Anthropic	Token counting on every text model – /v1/responses/input_tokens and /v1/messages/count_tokens count an input past the context window, always above the window so a client learns the conversation no longer fits, plus server tools with their replayed calls, results and citations, inline images, and documents and remote files at an allowance	Amazon Bedrock
Anthropic	Context editing – clear_tool_uses_20250919 and clear_thinking_20251015 with every documented option. Claude applies the edits and reports them in applied_edits, on the final message_delta when streaming, and count_tokens counts the edited prompt beside original_input_tokens. The beta flag is added for you, so the header is optional	Amazon Bedrock - Converse API, Bedrock Mantle
Anthropic	thinking.display – summarized or omitted reaches Claude as sent, so Opus 4.7 and later, Sonnet 5, Fable and Mythos, which omit their thinking text by default, return a summary when asked. The thinking tokens bill the same either way. On Responses, reasoning.summary asks for the same summary	Amazon Bedrock - Converse API
OpenAI	Medical transcription – amazon.transcribe-medical on /v1/audio/transcriptions, for a physician's dictation or a patient–clinician conversation (Type), with Specialty and medical custom vocabularies. json, text, verbose_json and diarized_json are served, and stream=true streams phrase by phrase. A client that can only send a model name reaches a fixed variant through a model alias	Amazon Transcribe Medical

Models & Reasoning¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	GPT-6 web search and code interpreter – served with no header and no configuration wherever a configured Mantle region lists the model, and Chat Completions reaches GPT-6 natively there rather than converted	Amazon Bedrock Mantle
OpenAI	Reasoning effort on GPT-5.x, GPT-6 and gpt-oss – from every dialect: reasoning_effort, reasoning.effort, output_config.effort or thinking. none turns reasoning off where the model can; GPT-6 Astra, and gpt-oss outside Bedrock Mantle, cannot, and are served at their default level with a warning in the request log. gpt-oss gets its own low / medium / high scale	Amazon Bedrock
Moonshot	Kimi K3 – reasoning effort from every dialect, with none answering without reasoning, and automatic prompt caching: a repeated prefix is reported as cached tokens on Chat Completions, Responses and Messages and costed at the cache rates. Cache breakpoints are accepted and ignored, since the model rejects them. A turn replaying the model's own reasoning is served	Amazon Bedrock
Anthropic	Claude Opus 5.5 – a request disabling reasoning on Opus 5.5, which always reasons, is served at its adaptive default with a warning in the request log, as on Fable and Mythos, rather than refused. On Bedrock Mantle, xhigh and max reach Claude 4.7 and later unchanged instead of being capped to high	Amazon Bedrock

Cost Reporting¶

• Daybreak Blue (GPT-5.6 Sol) was reported above what AWS bills: $5.50 / $33.00 per million input / output tokens against AWS's $4.40 / $22.00, and $11.00 / $49.50 against $8.80 / $33.00 past 272K, with the cache rates 25% high as well. It is now costed at GPT-5.6 Sol's rates.
• GPT-5.4 and GPT-5.5 are costed at their long-context rates past 272K input tokens, the boundary AWS publishes for them, where every call was costed at the short rate. See Long-Context Pricing.
• GPT-6 Astra is priced: In-Region $11.00 / $55.00 and Global $10.00 / $50.00 per million input / output tokens, with cache and long-context rates. It had no price at all.
• Kimi K3 calls are priced, where every call reported no cost. A Global call is costed at its Global rate ($3.00 / $15.00) rather than the US one ($3.30 / $16.50), and cache reads and writes are priced. A Grok 4.6 Global call now reaches its Global rate ($2.00 / $6.00) the same way.

Platform Features¶

• Transcription moves on from a region that does not offer the operation. Medical transcription and live streaming run in fewer regions than standard transcription; a region lacking one now hands the request to the next configured region instead of failing it, and when none offers it the answer is a 503. See Resilience.
• The Models page lists Claude Opus 5.5, GPT-6 Sol and GPT-6 Luna (the last two without a price, as AWS publishes none yet), GPT-6 Astra with its prices, the GPT-5.4 and GPT-5.5 long-context tier, and the Global rates of Kimi K3 and Grok 4.6.

Fixes¶

• Claude Code's interleaved thinking reaches Claude. The allowlist carried the interleaved-thinking flag capitalised, which no client sends, so thinking between tool calls silently stayed off. Separately, a request carrying the memory tool or a computer-use tool lost every flag of its anthropic-beta header, the 1M context window's included, when the gateway added the one that tool needs; the two lists are now joined, and count_tokens merges and filters the flags the same way.
• Reasoning effort on Claude 3.7 to 4.5 served by Bedrock Mantle no longer fails: it was sent as an effort level these models refuse, so every such request answered 400. It now becomes the thinking budget they take, scaled on the output limit; an output limit of 1,024 tokens or less leaves no room for one, and the request is served without reasoning and a logged warning.
• A context-window overflow no longer leaks the backend's error text, which on some models named an internal service and a request identifier, and a streamed one is no longer reported as a retryable server_error.
• A failed Responses request on a Bedrock Mantle model converted to that API is refused, where it was answered as an empty success.

Fixes & Maintenance (v1.19.1)¶

• Claude Sonnet 5.5 is served without errors. Turning reasoning off or forcing a tool surfaced a raw 400 from Amazon Bedrock. Thinking turned off on any route (reasoning_effort: "none", enable_thinking: false, reasoning.effort: "none", thinking: {"type": "disabled"}, think: false) now reaches it as between_tools, its lowest setting, and a forced tool choice is refused with a message naming auto, as on Opus 5.5. See Turning Thinking Off on Claude Sonnet 5.5.
• Anthropic Messages accepts thinking: {"type": "between_tools"}, as Anthropic does, on message creation and token counting.
• thinking: {"type": "disabled"} beside an output_config.effort turns thinking off and keeps the effort, as upstream does. Claude reasoned at that effort instead, and was billed for it.
• Grok 4.7 calls are priced, at Global $2.00 / $6.00 per million input / output tokens. Every call was reported as free.
• GPT-6 Astra short prompts are costed at the short-context rate. The Price List rows AWS now publishes for it were read as one tier, so a short prompt could be costed at the long-context rate, up to twice as high.
• GPT-6 Luna, GPT-6 Sol and GLM 4.6 are priced, at the rates on their AWS model cards (GPT-6) and on Z.ai's pricing page (GLM 4.6). Every call was reported as free.
• The Terraform module grants the server the KMS permission its DynamoDB table needs. Since module 1.17.0, a deployment where the module created the table refused every table read and write, so tenant API keys, per-tenant rate limits and the shared model cache were unavailable. Update the module to apply it.
• A conversation replaying a turn that ended after reasoning is answered, where automatic prompt caching made Amazon Bedrock refuse it with a 400; Codex on Nova 2 Lite could not recover from a cut-short answer.
• The Models page lists Claude Sonnet 5.5 and Grok 4.7, names each model once where it is served by two AWS services, quotes the nearest region's rate where the selected region has none, lists Amazon Transcribe in every region that offers it, shows closed models' licence as proprietary, and takes each model's APIs and prompt caching from its AWS model card.

v1.18.0 – 2026-09-19 – Vendor Parity, Tenant Key Rotation & Rate Limits¶

This release is about being the API it claims to mirror. The bulk of it is a compatibility sweep run against the vendors' own endpoints and official clients, not just against the gateway: every divergence it found is either fixed here or documented as a limitation. Alongside it, three things an operator asked for — tenant keys that rotate without anyone moving a secret by hand, per-tenant request and token limits that hold across instances, and a guardrail cost lever that scopes evaluation to the turns you name. Two capabilities round it out: tools on the Realtime API, which is what a voice agent needs to do anything beyond talking, and web search on Chat Completions, the dialect most clients actually speak.

New API Features¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	Realtime function calling – a session declares tools and answers the calls the model makes, so a voice agent can do more than talk	Amazon Bedrock - Amazon Nova Sonic
OpenAI	web_search_options on Chat Completions – OpenAI's only spelling for server-side web search on the dialect most clients speak, resolved through the same declaration the Responses and Messages dialects already use. A model that runs no web search refuses rather than answering from its own knowledge, which nothing in the response would distinguish	Amazon Bedrock - Nova Grounding, Anthropic web search
OpenAI	Prompt-attack and personal-data moderation – jailbreak and prompt-injection detection, and personal data detection, on /v1/moderations and the moderation parameter of the chat routes, with no guardrail resource to configure	Amazon Bedrock Guardrails
OpenAI	echo on /v1/completions – the prompt is echoed back ahead of the completion, which the gateway can do locally and was silently dropping	Amazon Bedrock - Converse API
Anthropic	Opaque page tokens on GET /v1/files – next_page is served and page accepted, the way the SDK now pages. The token is opaque and refused when it is not one this API issued; the ID cursors stay	Amazon S3
Anthropic	expires_in_seconds on a file upload – the full upstream range (1 hour to 90 days) is honoured and expires_at reported on all three routes. Expiry is enforced on every read, so a TTL longer than the storage sweep still expires at the instant promised	Amazon S3
Ollama	prompt_eval_cached_count, and the base URL's connection test – the cached-prompt count Bedrock already reports is passed through, and the base URL answers Ollama is running rather than a 404. /api/blobs/{digest} joins the store verbs this deployment refuses	Amazon Bedrock - Converse API

Multi-Tenancy¶

Provider	Endpoint/Feature	AWS Backend
stdapi.ai	Tenant key rotation – with TENANT_KEY_SECRETSMANAGER_PREFIX each key is stored as a Secrets Manager secret the tenant reads for itself, so TENANT_KEY_ROTATION_DAYS rotates it with nobody in the loop. The superseded key keeps working for TENANT_KEY_ROTATION_OVERLAP_SECONDS — seven days by default, 0 for a hard cutover — and only the immediately previous key survives	AWS Secrets Manager
stdapi.ai	Per-tenant rate limits – requests_per_minute and tokens_per_minute, per key or as a deployment default, counted in the shared table so a limit holds across every instance. Tokens are admitted on an estimate and reconciled from the billed usage, which is what keeps a Realtime or MCP session from billing to a window that has ended. A counter that cannot be written fails closed with a 503, never a 429 the client did not earn	Amazon DynamoDB

Cost Control¶

Provider	Endpoint/Feature	AWS Backend
stdapi.ai	AWS_BEDROCK_GUARDRAIL_SCOPE_TURNS – a guarded conversation is charged for everything the client replays, because Converse evaluates the whole history on every turn. This scopes input evaluation to the trailing user turns you name: a 6,401-character history bills 7 text units per policy and adds 409 ms, against 1 unit and 194 ms for the last turn alone. Off by default and left off unless you decide otherwise — scoping genuinely lowers detection, not just the bill: a prompt attack split across two turns is blocked today and is not blocked once only the last turn is tagged. Model output is always evaluated in full	Amazon Bedrock Guardrails

Platform Features¶

• Uploads stream to S3. A binary part is handed from the request straight to S3 and re-read in 8 MiB chunks for the session digest, so memory is one chunk whatever the part size. The digest keeps every guarantee it had: the fold still runs under the session lock inside a shield, and the signature is still written in the same critical section as the bytes, so a digest that does not answer for exactly the parts its signature names still cannot reach a completion.
• A batch input file is streamed end to end, rather than being materialised several times over — decoded lines, parsed bodies and a joined upload blob could each hold up to 200 MiB of one request.
• The documentation pages ship a current Swagger UI and ReDoc — swagger-ui-dist 5.33.0, which lays out only the part of a large specification that is on screen, and redoc 2.5.4, which carries accessibility fixes and patched bundled dependencies. /redoc no longer loads anything from cdn.redoc.ly, which the documentation had always promised it did not.

Fixes¶

• A tiny multipart field name can no longer exhaust the gateway: a bracketed index in a form field name drove an unbounded allocation, so a field a few bytes long could OOM-kill the instance. The index and the nesting depth are now bounded, above what every official client actually sends.
• An application-inference-profile ARN no longer hijacks a model's routing: resolving a model from an ARN copied the catalogue entry shallowly and then wrote through the copy, so one caller's ARN changed where every later caller in that region was routed. The lookup now copies what it mutates.
• A realtime session opened with an ephemeral client secret is guarded: the deployment's guardrail was configured on every other entry point and skipped on that one, so the untrusted-browser credential the guardrail exists for was the one case it did not cover.
• Batch creation no longer blocks every other caller, and a queued vector-store indexing job no longer strands a file or orphans its vectors when the job is interrupted or the lookup fails.
• The tenant key reconciliation loop survives an unexpected error: one failure ended it silently, and with it every later mint and rotation, until the instance was restarted.
• Audio and media stop answering with the wrong thing: a truncated encode was served as a complete 200 when its input failed mid-stream, a bad upload to a live transcription never got its 400, and text with an & or a < produced a Bedrock InvalidSsmlException whenever speed was not 1.0. A transcription job that is already gone is now accepted as deleted rather than re-raising.
• A file URL that is fetchable is now usable: URL ingestion follows redirects and falls back to a ranged read, where before a redirect or a server refusing a HEAD probe failed the request outright.
• A stored conversation stays readable: an additional_tools or compaction_trigger item made every later read of that conversation a 500, permanently.
• Requests the vendors accept are accepted: temperature above 1, service_tier aliases including "fast", max_tokens: 0 (the documented cache pre-warm), the 2026 browser and computer toolsets, the container object form, the custom-voice object, a tool_result block with no content, speed up to 4.0 on the Polly engines that honour it, an explicit JSON null on ten nullable image fields, output_compression: 0, an empty Ollama format (which broke langchain-ollama on every call), and the Ollama option sentinels seed: -1 and top_k: 0 that answered 500.
• Responses the vendors send are sent: event: names on streamed image frames, the citations a streamed document answer carries, background and safety_identifier on the Converse path, the code_interpreter_call item the model actually ran instead of an erased one, an item reference answered with the item it names in an envelope the official SDK can parse, and the filenames the vendor keeps rather than sanitising.
• A realtime turn the server detects is now committed like a turn the caller ends: on server_vad, the API's default turn mode, the gateway sent neither input_audio_buffer.committed nor the conversation item the turn became, so a client waiting for either against a detected turn waited for ever.
• The Anthropic file listing honours ids=, where it previously ignored it and returned the wrong set of files.
• Ollama chat keeps what the caller sent: images on a tool, assistant or system message were silently dropped, and two endpoints answered an accidental 404.
• The Models page states what the source measured: two benchmark scores were published against the wrong model — GLM 4.7 carried GLM 4.7 Flash's GPQA Diamond result, and DeepSeek V3.2 carried the previous generation's.
• Four cells in the features comparison table had drifted from what the compared products now do.
• Four silent limitations are now written down: a Chat Completions message name is accepted and ignored, the verbose_json transcription decoder fields are placeholders rather than measurements, a bad batch input file is reported per line rather than refusing the batch, and the moderations input cap is the gateway's own rather than a vendor rule the docs implied it was.

v1.17.0 – 2026-09-08 – Your Own Models, Your Own Tenants, Your Own Spend¶

This release widens what a deployment can serve, who it can serve it to, and what it can tell you about the bill. Models you host yourself: Amazon SageMaker AI endpoints and Amazon Bedrock Marketplace model endpoints you have already deployed join the model list and answer on the same routes as everything else — a fine-tuned model, a model no serverless catalogue carries, or one you scale to zero between requests, reached with the same client code. A new dialect: clients written for the Ollama API, and the many tools that speak only that, now reach Amazon Bedrock unchanged. Per-tenant API keys: one deployment serves several tenants, each scoped to the models and endpoints it may use, revocable on its own, and free to bring its own AWS account. Usage and spend, from the API: the OpenAI Administration API reports what was used and what it cost — per model, per endpoint and, where a deployment identifies callers, per user — read from the metrics the gateway itself writes rather than estimated. Speaking to it, live: the Realtime API gained the WebRTC transport, so a browser negotiates its own media session and the audio path terminates in the gateway, with no WebSocket relay in between.

Your Own Model Endpoints¶

Provider	Endpoint/Feature	AWS Backend
stdapi.ai	Amazon SageMaker AI endpoints – the endpoints you already run join the model list under the names you pick and answer on the same routes as every other model, streaming included: a fine-tuned model, or one no serverless catalogue carries, reached with unchanged client code	Amazon SageMaker AI
stdapi.ai	Endpoints scaled to zero – an endpoint with no running capacity is woken and waited for rather than refused; one with no capacity to wake answers 503 (retry later), not 400	Amazon SageMaker AI
stdapi.ai	Amazon Bedrock Marketplace model endpoints – the endpoints you have deployed are discovered and served like any other model, invoked through Amazon Bedrock on the server's behalf, and one being updated stays served	Amazon Bedrock - Marketplace model endpoints

New APIs¶

Provider	Endpoint/Feature	AWS Backend
Ollama	POST /ollama/api/chat – conversational responses with tools, images and thinking, streamed as the newline-delimited JSON Ollama clients expect, carrying the timings they read	Amazon Bedrock - Converse API
Ollama	POST /ollama/api/generate – a response for a single prompt, streamed or whole; an empty prompt, here or on /api/chat, is the load/unload no-op Ollama defines rather than a 400	Amazon Bedrock - Converse API
Ollama	POST /ollama/api/embed and POST /ollama/api/embeddings – vector embeddings for one or several inputs, including the legacy single-prompt route older clients still call	Amazon Bedrock - embedding models
Ollama	/ollama/api/tags, /ollama/api/show, /ollama/api/ps, /ollama/api/version and /ollama/api/pull – the discovery verbs an Ollama tool calls before anything else. The verbs that write to a local model store — create, copy, push, delete — are refused, since this deployment stores no models of its own. The /api/blobs/{digest} upload joined that refused set in v1.18.0, which also answers Ollama is running on the base URL for a client's connection test	Amazon Bedrock
OpenAI	GET /v1/organization/usage/* – tokens, images, characters and seconds per bucket, per model, per endpoint and — where a deployment identifies callers — per user, read from the metrics the gateway itself writes. An endpoint that measures nothing answers empty buckets rather than a 404. Off by default: it needs USAGE_API and CLOUDWATCH_METRICS, and grouping by user needs CLOUDWATCH_METRICS_USER_DIMENSION as well	Amazon CloudWatch
OpenAI	GET /v1/organization/costs – what AWS bills this deployment for serving those requests, over the same buckets and the same filters. Needs COST_TRACKING on top of the two settings above	Amazon CloudWatch
OpenAI	POST /v1/realtime/calls – the WebRTC transport: a browser posts its own SDP offer, negotiates a media session directly with the gateway and the audio path terminates there, with no WebSocket relay in between. An offer whose ICE candidates are all private, link-local or mDNS names is refused with invalid_offer; a deployment on a private network sets REALTIME_WEBRTC_ALLOW_PRIVATE_CANDIDATES. Off by default: it needs REALTIME_WEBRTC_ENABLED, and the task must be directly reachable over UDP — behind an HTTP-only load balancer the SDP exchange succeeds but the call carries no audio	Amazon Bedrock - Amazon Nova Sonic

Multi-Tenancy¶

Provider	Endpoint/Feature	AWS Backend
stdapi.ai	Per-tenant API keys – issue a key per tenant, scope it to the models and endpoints that tenant may use, and revoke it without touching anyone else. Files, vector stores, batches, conversations and stored responses stay deployment-wide with no tenant ownership — a documented limitation of this release	Amazon DynamoDB
stdapi.ai	Key delivery that skips Terraform state – the server mints each tenant's secret and delivers it once through a parameter, encrypted with the key named by TENANT_KEY_SSM_KMS_KEY_ID — the deployment's own KMS key when the Terraform module provisions it — so reading it takes a grant on that key and not merely permission on the parameter path	AWS Systems Manager Parameter Store, AWS KMS
stdapi.ai	Tenant AWS credentials – a tenant may bring its own AWS account: its requests then run under its own role, its own Amazon Bedrock quota and its own bill	Amazon Bedrock, AWS STS

Model Discovery¶

Provider	Endpoint/Feature	AWS Backend
stdapi.ai	Wildcard model names – any request that names a model may name a pattern instead — claude-sonnet-*, say — and the most recently released match serves it; an ambiguous tie is refused rather than guessed	Amazon Bedrock
stdapi.ai	GET /search_models – a model= filter lists everything a pattern matches, newest first, so a pattern can be checked before anything relies on it	Amazon Bedrock
stdapi.ai	Shared model list – a fleet discovers models once and shares the result, instead of once per task, and the refresh stays off the request path	Amazon DynamoDB

API Improvements¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	Diarized transcripts streamed – a diarized transcription is returned as speaker-labelled segments as they are recognized, instead of being refused	Amazon Transcribe
Cohere	Fused multimodal embeddings – text and an image embedded together into one vector, on both embed routes	Amazon Bedrock - embedding models
stdapi.ai	Cohere Embed v3 listed as image-capable – Bedrock publishes cohere.embed-english-v3 and cohere.embed-multilingual-v3 as text-only although both embed an image and are billed for it; the catalogue now declares the modalities the listing omits, so /v1/models, /search_models and the Models page agree with what is served	Amazon Bedrock - embedding models

Platform Features¶

Fixes¶

• Images reach the models that read them: the Qwen vision-language line was published by the open-weight family, which advertises text only, so an attached image was refused by models that in fact read it. The line now declares image input and is excluded from the open-weight matcher, so iteration order can no longer decide what a model is published as.
• The Anthropic MCP connector no longer blocks a request: an mcp_servers request was rejected outright and the mcp_tool_use and mcp_tool_result blocks it produces had no accepted shape, so a client using the connector could not call the API at all. The field and the blocks are accepted, and the request is served without the connector rather than refused — it names an extra tool source, it is not the request itself.
• An embedded image is billed for what AWS charges: Cohere Embed v3 meters an image as its own billed unit and reports no token count for it, so image embeddings were attributed at zero cost while AWS billed for them. The images the response reports are now recorded against the model's image rate; later Embed versions bill images inside the tokens and are unaffected.
• A model both catalogues name stays reachable through bedrock-runtime: naming a dual-homed model in AWS_BEDROCK_MANTLE_PREFERRED_MODELS published the preferred entry under that identifier and dropped the other, so the model was reported impossible to batch — batch inference runs on bedrock-runtime alone. The displaced bedrock-runtime entry is kept off-catalogue and read by everything that must reach that endpoint, while the published catalogue keeps naming the preferred entry. It now matters to every deployment, that setting having gained a default.
• Listings report the time they are ordered by: batch and completion listings paged in identifier order while reporting a creation time recorded from another clock, so the sequence a client saw did not match the timestamps it was given and a page boundary could revisit or skip an entry. The reported time is now read from the identifier itself, and a batch listing finds the newest batches whatever the bucket holds, including after a dense burst.
• A one-token answer is served rather than refused: the Anthropic Messages API and Chat Completions both accept a budget of a single token — a client probing a model sends exactly that — while the Responses transport a Bedrock Mantle model is served over refuses anything under 16, so such a request came back as a 400 naming max_output_tokens, a field the caller never sent. The budget is now raised to what the transport accepts.
• An unknown model is a 404 when counting input tokens: POST /v1/responses/input_tokens answered 400 for a model that does not exist, where the official API answers 404 model_not_found — a client branching on the status read a malformed request instead of a missing model. The image routes keep their 400, which is what upstream answers there. Token counting remains unavailable for models served by Bedrock Mantle or a model endpoint, which is a different 400.
• A deployment on your own IPv4-only subnets stops being told it is dual-stack: the VPC module read "has IPv6" from a subnet attribute AWS reports as an empty string rather than as absent, so every subnet_ids deployment looked dual-stack whatever its subnets carried. The load balancer was then asked for dualstack, an AAAA record was published for an address nothing answered on, and the server was told to bind ::. The module now reads the subnet's actual IPv6 block.
• A model's release date is when it launched, not when your region got it: a region that opens a model months after launch reports that rollout as the model's own start-of-life, and whichever region happened to be listed first decided the published date — Claude Haiku 4.5 reads as 2026-01-06 in the seven regions it expanded into and 2025-10-15 in the twenty-four that had it at launch. The earliest date any region publishes is now the one reported, by created in the OpenAI model list, by the Anthropic and Ollama model routes, and on the Models page.
• The Models page states only what a live source backs: a benchmark row is matched to the model release it was measured on, a source that publishes no row now fails the build instead of leaving stale figures in place, facts no longer leak between variants of a family, and a lifecycle date follows one stated rule — the Bedrock API is the reference, and a model card fills a date only where the API states none.
• A deployment on your own subnets can be planned again: the VPC module this one builds on fed a set to a function that takes only lists, so every plan that creates a VPC failed outright — including for a deployment that had changed nothing, since the constraint resolves to the newest release. Fixed in JGoutin/terraform-aws-vpc v1.6.1.
• A deployment on your own subnets can be planned again, twice over: the module's IPv6 out-of-band egress rule read whether the subnets carry IPv6 before checking that the WebRTC media path was even on. On subnet_ids that answer comes from the subnets themselves and is unknown while planning, so the plan failed outright — with the rule set empty and WebRTC off, which is every such deployment.
• A module that names your own VPC no longer deadlocks the plan: the length limit name_prefix carries when a load balancer is enabled was asserted on the variable, which tied it to alb_enabled and through that to subnet_ids. Passing the module's name_prefix output to a VPC and that VPC's subnets back — what the output exists for — closed a dependency cycle. The limit is now checked on the load balancer itself and still refuses too long a prefix while planning.
• The documentation pages load a current Swagger UI: swagger-ui-dist 5.32.15, which scopes its HTML sanitiser to itself instead of mutating the page's global one. Both pins moved on in v1.18.0, to swagger-ui-dist 5.33.0, which lays out only the part of a large specification that is on screen, and redoc 2.5.4, which carries accessibility fixes and patched bundled dependencies.

v1.16.0 – 2026-08-21 – Conversations, Batches, Vector Stores, Realtime Speech & Per-User Identity (with v1.16.1 maintenance update, 2026-08-25)¶

This release adds four API surfaces and finishes the speech story. New APIs: Conversations keep a thread server-side, so a client continues it by id instead of resending the history; the OpenAI Batch API and Anthropic Message Batches API run large request sets asynchronously at the discounted batch price; Vector Stores index and search files by meaning — or address a knowledge base you already run — with a model reaching either kind for itself through file_search; and the Realtime API holds a spoken conversation over one WebSocket. Speech: 100,000-character synthesis spoken as it is produced, live transcription needing no bucket, and Amazon Nova Sonic as the lowest-cost speech-to-text backend here. Identity per caller: Amazon Cognito tokens alongside or instead of the API key, published discovery so an agent authenticates itself, and per-user cost attribution reporting each end user's spend from the AWS invoice rather than an estimate.

New APIs¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/conversations – create, retrieve, update and delete a conversation, list and manage its items, and continue it from the Responses API with the conversation parameter	Amazon Bedrock - session management
OpenAI	/v1/vector_stores – attach files, follow the indexing as it progresses, then search by meaning with attribute filters and per-passage scores	Amazon S3 Vectors, Amazon Bedrock - embedding models
OpenAI	/v1/vector_stores – address an Amazon Bedrock knowledge base you already run as a vector store, Bedrock managed or customer-managed: search it, attach, list, read and delete documents. Allowlisted per knowledge base, never created or deleted here	Amazon Bedrock - Knowledge Bases
OpenAI	file_search on /v1/responses – a chat model answers from the stores you name, reporting the searches it ran and citing a file_citation per file it drew on	Amazon S3 Vectors, Amazon Bedrock - Knowledge Bases
OpenAI	/v1/batches – run a JSONL file of chat completion or embedding requests asynchronously at the batch price: submit, poll, cancel, read the result files	Amazon Bedrock - batch inference
Anthropic	/anthropic/v1/messages/batches – the same asynchronous, batch-priced run for the Messages API, results streamed back as JSONL; each request may name its own model, up to eight per batch	Amazon Bedrock - batch inference
OpenAI	WS /v1/realtime – a live speech-to-speech session over one WebSocket, with a transcript of both sides, server-side turn detection or manual turns, barge-in, and G.711 for telephony	Amazon Bedrock - Amazon Nova Sonic
OpenAI	POST /v1/realtime/client_secrets – mint a short-lived, browser-safe credential carrying a session configuration; signed and stateless, so any instance verifies one minted by any other	Amazon Bedrock - Amazon Nova Sonic

Speech & Audio¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/audio/speech – up to 100,000 billed characters per request, 24× the upstream 4,096, with no API change and no new request field	Amazon Polly
OpenAI	/v1/audio/speech – long input is spoken as it is synthesized instead of after a whole job finishes; generative voices reach 20,000 characters with no bucket at all, and each request takes whichever path can serve it, so long input is no longer tied to one voice	Amazon Polly
OpenAI	/v1/audio/transcriptions – naming Amazon Nova Sonic transcribes at the lowest cost available here, streamed as it is recognized; json and text only, up to 10 minutes, no timestamps. No existing request is re-routed	Amazon Bedrock - Amazon Nova Sonic
OpenAI	/v1/audio/translations – Amazon Nova Sonic translates speech to English itself, in one request	Amazon Bedrock - Amazon Nova Sonic
OpenAI	/v1/audio/transcriptions – stream=true returns each phrase as it is recognized, whenever the request names the language to expect; needs no bucket. gpt-live-transcribe is now an alias, and requests naming no language are unchanged unless AWS_TRANSCRIBE_STREAM_LANGUAGES says which to expect	Amazon Transcribe
OpenAI	/v1/audio/transcriptions – per-language custom vocabularies and language models, so a request identifying between several languages can apply the right resources to each one instead of being refused. Accepted only where the backend would use them: alongside a single fixed language, where they would apply to nothing, they are still refused	Amazon Transcribe
stdapi.ai	AWS_TRANSCRIBE_OUTPUT_ENCRYPTION_KEY_ARN – encrypt a transcription's output with a key you name rather than the bucket's own. The job's request identifiers travel as the encryption context, so a key policy can be scoped to this workload instead of to the whole bucket	Amazon Transcribe, AWS KMS
OpenAI	/v1/audio/translations – the supported language pairs are read once at startup and checked before the call, so a pair that cannot be served is named as the request problem it is instead of surfacing as a failure after the audio was transcribed. The permission that reads them is optional: without it the check stays off and everything else works	AWS Translate

Identity & Cost Attribution¶

Provider	Endpoint/Feature	AWS Backend
stdapi.ai	Amazon Cognito user pool tokens – accept access tokens instead of, or alongside, the API key, so each caller reaches the API with their own credential; validated in-process against the pool's published keys, with no AWS call on the request path	Amazon Cognito
stdapi.ai	AUTHENTICATION_MODE – assert the posture rather than infer it: the server refuses to start when the selected method is not configured, or when a configured method would be silently ignored	Amazon Cognito
stdapi.ai	Authentication discovery for agents – an OAuth 2.0 protected resource metadata document, pointed at by every unauthorized response, so an MCP client finds the authorization server and the scope it needs without being configured for this deployment; published only once an authorization server is declared	Amazon Cognito, or any OAuth 2.0 authorization server
stdapi.ai	Per-user cost attribution – model calls issued under a short-lived role session tagged with the caller, so AWS reports each end user's spend in Cost Explorer and the Cost and Usage Report, from the invoice rather than an estimate. Off by default; a deployment can also require every call to name its end user rather than bill it to the deployment	Amazon Bedrock, AWS STS
stdapi.ai	Vector store cost reporting – a search against a Bedrock-managed knowledge base is recorded and priced like every other billed unit; what cannot be accounted for is stated rather than approximated	Amazon Bedrock - Knowledge Bases

Platform Features¶

Fixes¶

• Vector store durability: an attached file whose indexing was interrupted is now reported failed with a last_error instead of sitting in_progress for ever; a detached file leaves every listing and search immediately and is gone only once its passages are, so a server replaced mid-delete no longer leaves a deleted document answering searches; indexing is bounded for the whole server rather than per request, so memory and embedding quota no longer scale with the number of callers; and deployments that would rather the work finished than reported can hand indexing to a queue
• Work a request left running is finished before the server stops: a deployment, scale-in or Spot interruption used to drop temporary file cleanups, vector store indexing and live audio session releases with nothing in the logs. Shutdown now waits under SHUTDOWN_DRAIN_TIMEOUT (10 seconds by default), settles whatever the deadline leaves, and counts it in the stop event. Raise it together with your container runtime's kill delay, never one alone
• Streamed responses run the work they scheduled: the drain was attached before the body produced a byte, so three leaks followed — a vector store searched only through streamed answers could expire mid-query, an expired store left a paid index behind, and a streamed transcription falling back to a job left its audio, transcript and job record behind on every request
• Realtime speaks the released vocabulary, not the beta one: item events were unparsable, the caller's transcript event was dropped for a missing field, and the item lifecycle clients wait on was never emitted. Barge-in did not work at all — the session refused truncation precisely while an answer was playing, the only moment it is ever sent. Truncate, retrieve and delete now work against the tracked conversation, a written turn is answered instead of timing out, and every answer reports the six response fields upstream always sends
• Batch API: listing a batch neither settled nor published it, so a client that only ever listed never had its usage recorded; every validation failure at submission was reported as an unsupported model, quota and role failures included; and the batch record was written only after the jobs started, leaving billable work running with nothing on disk to stop it
• Knowledge-base stores answer in this API's own words: attaching to a managed knowledge base always failed, listing its files always failed, deleted documents never left a listing, and internal bookkeeping reached the caller as attributes. A file refused because the corpus is maintained elsewhere is now told so in the store's terms, and a refused file is explained by the store that refused it rather than by one fixed sentence describing limits the caller never met
• Cost reporting matches what AWS charges: GPT-5.6 Luna was reported at five times its real cost and Terra a quarter over, since AWS repriced them on the model's own page rather than in the live price catalogue; a Global cross-Region call — the only way Luna, Sol and Terra are ever served — was costed at the In-Region rate, about 10% over; and moderation usage naming an alias matched no price at all. Every source page is now re-checked weekly
• Reasoning and web search reach the models that serve them: Amazon Nova 2 and DeepSeek V3 refused the token budget the Anthropic dialect requires, leaving extended thinking unreachable on that route while the identical ask worked elsewhere; and a web_search sent to a GPT-5.6 model resolved to its non-Mantle twin travelled as an ordinary function tool, so no search ran and nothing said so — now a 400 naming both ways to route the model to the endpoint that serves it
• The Messages surface reports what an answer cost and why it stopped: refusals carry the policy category, the reasoning-token breakdown is reported, and service tier and per-TTL cache-creation counts are populated — most visibly on a batch, which claimed no tier while being billed as one
• Audio, embeddings and attachments are bounded correctly: inline audio was measured against raw bytes where the backend enforces the encoded length, so files between ~18.75 MB and 25 MB passed and were refused downstream; long text-to-speech now answers with the length a bucket-less deployment can honour; and models that embed one input per call no longer open a connection per chunk
• The interactive documentation pages render with no outbound access: /docs and /redoc pulled the icon, Swagger UI, ReDoc and a web font from three third parties — blank pages in an air-gapped VPC, and elsewhere a report to those hosts of who was reading this API and when, running whatever a floating major version tag resolved to that day. Both are now served whole from the image, pinned to exact releases verified by SHA-256 at build time, with upstream licences beside them
• MCP tools return what they produce: every route answering with bytes was published as a tool an agent could call and then could not use. An image now arrives as an image and audio as audio, anything the protocol cannot carry arrives as a reference rather than failing, and the 4 MiB body cap that blocked image edits now follows MAX_INPUT_FILE_SIZE
• Addresses and listings are the ones this deployment serves: a custom route prefix still quoted default paths to search_models and to video job polling, neither recoverable client-side; and a file's created_at and its place in a listing came from two different clocks, so a multipart upload sat among older files reporting a later time. The Anthropic listing also answered oldest first, hiding every recent file, and now runs newest first as upstream does
• Diagnostics name their cause: an unreachable Region rendered six different conditions as one identical sentence, and the slow startup beside it was the container metadata lookup retrying, unreported; a request abandoned mid-flight left its OpenTelemetry trace current, so later work was recorded under a closed request's trace id; and behind a proxy, client_ip recorded the load balancer whatever PROXY_TRUSTED_HOSTS allowed
• The API describes itself, not the service behind it: a synthesis limit credited to the service enforcing it, prices credited to their catalogue and a moderation route naming the engine underneath all shipped in the OpenAPI document and in the tool descriptions agents read before calling

Fixes & Maintenance (v1.16.1)¶

• Update cryptography to 50.0.1, rebuilt against OpenSSL 4.0.2

v1.15.0 – 2026-08-03 – Reliability, Performance & Feature Completeness¶

This release focuses on making the whole gateway better rather than just bigger. Reliability and quality: the largest correctness pass to date — three successive deep audits plus an independent full-branch review closed hundreds of fidelity gaps across all three API dialects, every fix pinned by tests and the whole surface validated by real, unmodified client applications. Performance: hot paths now run in compiled native code and independent work in parallel, measurably cutting the gateway's processing overhead. Feature completeness: existing capabilities are rounded out end to end — explicit prompt caching, operator reasoning controls, the Responses API prompt parameter from Amazon Bedrock Prompt Management, native mid-conversation system messages on Claude 4.8+, richer speech and transcription (Polly speech marks, Transcribe/Translate extras, generic Converse speech-to-text), Cohere embedding_types and Rerank v1 structured documents, guardrail enforcement on every route, and an inline guardrail-checks moderation backend.

Explicit Prompt Caching¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	Explicit cache breakpoints on chat completions and responses, mapped to Bedrock cachePoint blocks with the per-request block budget enforced	Amazon Bedrock - Converse API
OpenAI	prompt_cache_options – cache TTL control on chat completions and responses, honoured on models that support it	Amazon Bedrock - Converse API

Prompt caching itself is not new — this release adds explicit placement and lifetime control on the OpenAI dialect, and fixes the caching plumbing that already existed (see Fixes).

Reasoning Controls¶

Provider	Endpoint/Feature	AWS Backend
stdapi.ai	CHAT_COMPLETIONS_REASONING_FIELD – return thinking text under reasoning_content, reasoning, or suppress it with none; applied identically to streamed deltas and final messages	Amazon Bedrock - Converse API & Mantle
OpenAI	OpenRouter-style reasoning request object accepted on chat completions (effort, max_tokens, enabled, exclude)	Amazon Bedrock - Converse API & Mantle

New API Features¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	Responses API prompt parameter – serve prompts stored in Bedrock Prompt Management, with versions and variables (opt-in, AWS_BEDROCK_ALLOW_PROMPT_ARN)	Amazon Bedrock - Prompt Management
Anthropic / OpenAI	Mid-conversation system messages forwarded natively on Claude 4.8+ and Claude 5 family models instead of being folded into the system prompt	Amazon Bedrock - Converse API & Mantle
stdapi.ai	Guardrail asynchronous stream processing via the X-Amzn-Bedrock-GuardrailStreamProcessingMode request header	Amazon Bedrock - Guardrails
stdapi.ai	Configured guardrails enforced on every route: embeddings, rerank, images, videos, and audio now apply them via the ApplyGuardrail API (route coverage)	Amazon Bedrock - Guardrails
OpenAI	Moderations amazon.bedrock-runtime-guardrail-checks model – inline guardrail content filter checks with no guardrail resource required, the new default fallback for omni-moderation-* in supported regions	Amazon Bedrock - Guardrails

Speech & Audio¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/audio/speech – Polly SpeechMarkTypes for word/sentence/viseme/SSML timing marks	Amazon Polly
OpenAI	/v1/audio/transcriptions – Amazon Transcribe extra parameters: multi-language identification, custom vocabularies, PII redaction, and more	Amazon Transcribe
OpenAI	/v1/audio/transcriptions – gpt-transcribe context inputs: keywords and multi-language languages, with detected languages reported in the response	Amazon Transcribe
OpenAI	/v1/audio/transcriptions & translations – any Converse-capable speech-input Bedrock model transcribes through a generic default (Voxtral rebuilt on the Converse API); uploads outside the accepted formats are transcoded automatically	Amazon Bedrock - Converse API
OpenAI	/v1/audio/translations – AWS Translate Formality, Profanity, Brevity, and custom terminologies	AWS Translate

Cohere Embed & Rerank¶

Provider	Endpoint/Feature	AWS Backend
Cohere	embedding_types – quantized (int8/uint8/binary/ubinary) and base64 embeddings on both embed routes; image embedding metadata reported	Amazon Bedrock - embedding models
Cohere	Rerank v1 – structured JSON documents with rank_fields selection	Amazon Bedrock - Rerank API

Platform Features¶

Verified with Real Clients¶

Compatibility claims in this release are backed by a new test tier that runs complete, unmodified third-party client software against a live gateway — not just HTTP assertions. Coding agents (Claude Code, Codex, pi, Qwen Code), the n8n workflow platform, Open WebUI, Home Assistant's voice bridge, a Haystack RAG pipeline, and the LangChain and pydantic-ai libraries drive real multi-turn tool-calling, retrieval, and speech sessions across dozens of models and all three API dialects, in isolated sandboxes. Alongside them, every served model is empirically probed for the parameters it genuinely honours, with the results recorded and pinned by tests. See Quality Assurance for the full methodology.

Fixes¶

Three audit passes and an independent full-branch review closed over a hundred fidelity gaps. The user-visible highlights:

• MCP tool calls match their schemas: union-typed parameters no longer advertise a contradictory single type (which made valid string arguments randomly fail schema validation), and the JSON image edit/variation bodies accept the plain string references the tool schemas advertise
• Clean errors on log-exempt paths: a 404 or 405 on paths kept out of request logs (e.g. /favicon.ico, auto-requested by every browser visiting /) returned a 500 with a traceback instead of the JSON error envelope
• Prompt caching plumbing: Anthropic cache_control breakpoints land on their marked block; cache reads and writes are counted, priced, and reported consistently in responses, request logs, and count_tokens
• Reasoning: reasoning_effort="max" accepted end to end; thinking text returned by Bedrock Mantle models is surfaced on every API instead of dropped; unsigned reasoning is no longer replayed to models that would reject it
• Streaming parity: streamed and non-streamed results are now identical (tool-call indices, same-role message merging, text concatenation); mid-stream errors emit proper error events on every API instead of ending streams silently; redacted thinking and web-search results round-trip exactly as native Anthropic emits them; failed generations return 502 instead of an empty 200
• Routing & billing: a read timeout on an already-sent request is no longer re-invoked in another region (no double billing), on Converse and Mantle alike; region failover now tries each candidate region at most once per request instead of looping back over regions it just marked as throttled, so a single request can no longer escalate a region's quota backoff toward the one-hour ceiling; Bedrock prompt-router usage is billed against the actually-invoked model; the price card reprices a standard-tier row served as a tier fallback at the rate that tier actually bills; store=true degrades gracefully with a logged warning in regions without the session API
• Responses API parity: the type surface is synchronized with the current OpenAI SDK (tool fields, error codes, tool-call caller provenance); Anthropic count_tokens counts exactly what generation sends, and error bodies carry the request_id
• Audio & images: the transcoding pipeline is fully bounded — a stalled or failed encode returns a clean error instead of holding the connection open; multipart forms bind every list field the OpenAI SDK sends; size="auto" works on generation, edits, and variations; zh-TW/pt-PT stay distinct in translation; PII-redacted transcripts are read from the key Amazon Transcribe actually writes; Polly voice auto-selection is deterministic; batch-purpose files apply the documented 30-day default expiry, and an expired file now disappears from file listings instead of being listed with an entry that 404s on retrieve

v1.14.0 – 2026-07-12 – Bedrock Mantle, Video Generation, Cohere APIs, Moderation & Stored Conversations¶

This release adds enabled-by-default Amazon Bedrock Mantle support — models served by the Bedrock Mantle endpoint (OpenAI GPT-5.4/5.5/5.6, xAI Grok 4.3, Google Gemma 4, Qwen3, GLM, DeepSeek, MiniMax, Kimi, Nemotron, and more) become available through all four text APIs, with transparent API conversion, native stored conversations, and independent throughput quotas. It also turns stdapi.ai into a three-dialect gateway with the new Cohere-compatible API (Rerank and Embed), adds the OpenAI-compatible Videos API for asynchronous video generation, content moderation backed by Amazon Bedrock Guardrails or Amazon Comprehend toxicity detection, stored responses and chat completions with store=true, previous_response_id multi-turn continuation, and a full list/retrieve/update/delete lifecycle on Amazon Bedrock session storage, and conversation compaction. The Responses API gains extended reasoning: Bedrock reasoningContent now surfaces as native reasoning output items, both non-streaming and streamed, with signatures and redacted payloads round-tripping through an encrypted_content envelope. A broader compatibility pass brings request/response parity closer to the OpenAI SDK — hosted and agent tool types (web search, computer use, custom tools) are now accepted and ignored instead of rejected, streams correctly terminate with response.incomplete/response.failed, cached tokens are counted in input_tokens, and citation annotations are emitted with their streaming events — validated end-to-end against the OpenAI Codex CLI as an agent client. Operations gain a model pricing API, multi-region failover for every AWS AI service, fault-tolerant startup, real AWS-billed usage and costs in request logs (optionally exported as CloudWatch metrics), and a security hardening pass covering SSRF protection, input validation, and log/error redaction.

Amazon Bedrock Mantle¶

Enabled-by-default support (AWS_BEDROCK_MANTLE_ENABLED) for models served by the Amazon Bedrock Mantle endpoint — OpenAI GPT-5.4/5.5/5.6 (Sol, Terra, Luna), xAI Grok 4.3, Google Gemma 4, Qwen3, GLM 4.x/5, DeepSeek V3.x, MiniMax M2.x, Kimi K2.5, Nemotron, and more — alongside the classic Bedrock Converse catalog:

• All four text APIs (chat completions, responses, messages, legacy completions) are served for every Mantle model — native passthrough where the model supports the API upstream, transparent conversion otherwise
• Models available on both bedrock-runtime and Mantle are served by bedrock-runtime by default; AWS_BEDROCK_MANTLE_PREFERRED_MODELS or the opt-in x-stdapi-service request header (AWS_BEDROCK_MANTLE_SERVICE_HEADER) route them through Mantle instead — e.g. to tap Mantle's independent throughput quotas
• Native Mantle stored conversations on /v1/responses (store, previous_response_id, retrieval and deletion) — 30-day retention, region-local, project-scoped
• Multi-region failover and quota backoff across AWS_BEDROCK_MANTLE_REGIONS, matching classic Bedrock region routing
• Authentication via short-term bearer tokens derived from the server's AWS credential chain — no static secrets
• Usage recorded and priced at bedrock-mantle rates, including cached tokens and service tiers
• Optional Bedrock Project/Workspace attribution for cost tracking via AWS_BEDROCK_MANTLE_PROJECT, with per-request override (AWS_BEDROCK_ALLOW_MANTLE_PROJECT_OVERRIDE) through the OpenAI-Project / anthropic-workspace header

Bedrock Mantle Models

New APIs¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/videos – create, poll, list, download, and delete video generation jobs	Amazon Bedrock - Amazon Nova Reel, Luma Ray 2
OpenAI	/v1/moderations – text and image content classification	Amazon Bedrock - Guardrails, Amazon Comprehend
Cohere	/cohere/v2/rerank – document reranking (Amazon Rerank 1.0, Cohere Rerank 3.5)	Amazon Bedrock - Rerank API
Cohere	/cohere/v2/embed – embeddings over all Bedrock embedding models	Amazon Bedrock - embedding models
stdapi.ai	/model_pricing – exact AWS unit prices per model	AWS Price List API

Extended Reasoning¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/responses – Bedrock reasoningContent returned as reasoning output items	Amazon Bedrock - Converse API
OpenAI	Streaming response.output_item.added / response.reasoning_text.delta / .done events for reasoning content	Amazon Bedrock - Converse API
OpenAI	include=["reasoning.encrypted_content"] – signature/redacted round-trip for multi-turn reasoning continuation	Amazon Bedrock - Converse API

Conversations¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	store=true + GET/DELETE /v1/responses/{id}, input items listing, and previous_response_id continuation	Amazon Bedrock - session management
OpenAI	POST /v1/responses/{id}/cancel – endpoint parity for the cancel lifecycle (always fails for session-stored responses, which never run in background mode; Mantle-stored responses are cancelled upstream)	Amazon Bedrock - session management
OpenAI	store=true + GET/DELETE /v1/chat/completions/{id}, GET /v1/chat/completions listing, POST /v1/chat/completions/{id} metadata updates, and input messages listing	Amazon Bedrock - session management
OpenAI	/v1/responses/compact – stateless conversation compaction	Amazon Bedrock - Converse API
OpenAI	moderation request parameter on chat completions and responses, with results reported in the response	Amazon Bedrock - Guardrails

Platform Features¶

Security Hardening¶

• MCP transports and /search_models now require authentication when an API key is configured — clients that relied on these endpoints being open must now send the API key
• SSRF protection hardened against IP-literal encoding and DNS-rebinding bypasses on URL file inputs
• s3:// file inputs are restricted to the server's allowed buckets, and multipart upload filenames are validated
• Decoded image size is capped against decompression-bomb payloads
• ARNs and AWS account IDs are redacted from client-facing error messages, and presigned URL signatures are stripped from logs and traces
• An empty resolved API key (e.g. a blank secret value) now disables authentication cleanly instead of matching an empty bearer token, and CORS no longer allows credentialed cross-origin requests
• Reduced container attack surface: the images no longer carry the video codec, X11 and font libraries that a distribution ffmpeg package links — x264, x265, AOM, dav1d, SVT-AV1 and SDL2 among them — nor the gRPC stack. None were reachable from the audio transcoding ffmpeg is used for, and they accounted for the bulk of the images' third-party native code. ffmpeg is built from the same version the base distribution ships, with only the audio encoders in use, and enables no GPL-licensed component

Agent SDK Compatibility¶

The Responses API request/response surface was audited and hardened against the OpenAI SDK and real agent clients, end-to-end tested against the OpenAI Codex CLI:

• Hosted and agent tool types (web_search, computer_use, file_search, custom/namespace tools, and other items without a Bedrock equivalent) are now accepted and dropped instead of rejected with 400, preserving compatibility with existing agent tooling
• Streaming responses now correctly terminate with response.incomplete or response.failed (matching upstream behavior) instead of always reporting response.completed
• Mid-stream errors emit the spec-compliant error SSE event
• input_tokens usage now includes cache read/write tokens, matching OpenAI's accounting
• url_citation annotations are emitted alongside their streaming events
• Echoed reasoning items tolerate the field variations produced by different SDKs and agent clients

Fixes¶

• Rerank models are no longer incorrectly advertised on Converse-based chat routes and MCP tools
• Fixed per-request model parameter overrides (default_model_params) occasionally leaking into subsequent requests for the same model
• 5xx provider errors now report server-side error types (server_error/api_error) in OpenAI and Anthropic error envelopes instead of invalid_request_error
• Unknown paths (404) and wrong methods (405) now return the error envelope of the API family they were sent to, instead of the framework's default detail payload
• The Anthropic Messages API now returns 404 instead of 400 for an unknown model, matching the upstream API, and rejects a top_p above 1.0
• Audio transcription returns plain text for response_format=text and now defaults verbose_json to segment timestamps
• Responses API usage reports input_tokens_details.cache_write_tokens, which recent OpenAI SDKs require to parse a response
• Files API listing and cursor pagination order by creation time again: file IDs now use an order-preserving alphabet, where the previous one could sort a newer file first. IDs issued before this release keep working, but sort among themselves as before until they expire
• Newer Anthropic client request fields (free-form JSON Schema keywords in tool input_schema, adaptive thinking display) are accepted instead of rejected in strict validation mode
• Amazon Nova 2 no longer fails on max_tokens combined with high reasoning effort (the cap is dropped with a logged warning)
• Explicit cache points are kept off tool-related content blocks for models without tool caching support
• The Files API unavailable error no longer exposes the S3 bucket configuration detail
• Fixed input files from one request occasionally leaking into later requests served by the same connection, which could fail those requests with internal errors
• Anthropic Messages streams now emit an empty tool-input delta for tool calls without arguments, so SDK stream accumulators no longer fail on argument-less tool calls
• JSON-body image edit and variation requests now accept the model field instead of rejecting the request
• Model listings now report service: "AWS Bedrock Runtime" for classic Bedrock models (previously "Amazon Bedrock"), distinguishing them from "AWS Bedrock Mantle"
• High reasoning effort now maps to the intended thinking-token budget on Anthropic Claude models (the budget factor was previously miscomputed)
• Setting log_level to disabled now suppresses all log output as documented, instead of publishing every event
• Server startup no longer fails when the ECS container metadata endpoint answers slowly, which could prevent small Fargate tasks from starting: the lookup is retried, then falls back to the STS caller identity with a startup warning
• Multipart upload parts are numbered from the parts already stored in S3 instead of a per-instance counter: with several server instances behind a load balancer, two parts of one upload could be given the same number, overwriting each other and failing the upload
• Multi-region failover now covers a region that does not offer the service at all: with no AWS_COMPREHEND_REGION set, a Bedrock region without Amazon Comprehend moves on to the next one as documented, instead of failing language detection and Comprehend moderation

v1.13.0 – 2026-07-03 – Terraform Module Compliance & Security Hardening¶

This release focuses on the stdapi-ai Terraform module and its child modules — VPC, KMS, and ECS Fargate — adding detailed AWS Security Hub control documentation and closing several compliance gaps: default security group lockdown, ALB access logging, EFS POSIX user enforcement with native backups, and optional compliance/GuardDuty/DNS Firewall VPC integrations. All four modules now also accept a tags variable for custom resource tagging.

Fixes¶

• Added the missing 1h and 5m values to PromptCacheRetention for Bedrock-specific prompt cache TTLs in the OpenAI Responses API

Security Hub & Compliance Hardening¶

Other Infrastructure Changes¶

MCP Token Optimization¶

• Significantly reduced the size of MCP tool descriptions across the API, lowering the token cost of every AI agent session connected to this server
• No change in functionality: all parameter constraints and usage guidance remain intact

v1.12.0 – 2026-05-29 – Completions API, Video Understanding & File References¶

This release adds the OpenAI-compatible /v1/completions endpoint for text-first coding agents and legacy completion clients, TwelveLabs Pegasus video understanding for analyzing video/* inputs in chat completions, and an input token counting endpoint for the Responses API. Files uploaded through the Files API can now be referenced anywhere a URL is accepted using the new file-id: URI scheme. The Anthropic Messages API now accepts system-role messages (merged into the system prompt for compatibility), reasoning can be explicitly enabled or disabled, and a new DEFAULT_MODEL_SERVICE_TIERS setting applies per-model service tiers automatically.

Chat Completions¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/completions – text completion endpoint for text-first coding agents	Amazon Bedrock - foundation models
OpenAI	/v1/responses/input_tokens – input token counting	Amazon Bedrock - CountTokens API
Anthropic	/v1/messages – accepts system-role messages (merged into the system prompt)	Amazon Bedrock - Claude models
Twelve Labs	Pegasus video understanding (video/* inputs)	Amazon Bedrock - TwelveLabs Pegasus

Speech & Audio¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/audio/speech – case-insensitive voice names & default model	Amazon Polly

Platform Features¶

v1.11.0 – 2026-05-02 – MCP Server, Agent Discovery & Model Search (with v1.11.1–v1.11.4 maintenance updates, through 2026-05-28)¶

This release introduces a Model Context Protocol (MCP) server, making all stdapi.ai API endpoints directly accessible as MCP tools for AI agents and agentic workflows. A new /search_models endpoint enables precise discovery of models by route, MCP tool, region, streaming support, and legacy status. Agent-friendly discovery metadata is now exposed via RFC 8288 Link headers and an RFC 9727 machine-readable API catalog at /.well-known/api-catalog. Endpoints that previously required binary multipart/form-data uploads now also accept an application/json body for MCP and HTTP client compatibility. The Anthropic Messages API now accepts xhigh as a reasoning_effort value.

MCP Server¶

Model Search¶

Agent Discovery¶

Chat Completions & Messages¶

Provider	Endpoint/Feature	AWS Backend
Anthropic	/v1/messages reasoning_effort=xhigh support	Amazon Bedrock - Claude models

Deprecation Mappings¶

• Added automatic fallback for amazon.nova-reel-v1:0 and anthropic.claude-3-haiku-20240307-v1:0 to their respective replacements

Fixes¶

• Fix reasoning token double-counting in usage calculation in OpenAI Responses API adapter
• Fix missing file_id inputs for image and file processing in OpenAI Responses API adapter
• Remove store parameter from unsupported validations in chat completions to ensure client compatibility

Fixes & Maintenance (v1.11.1–v1.11.4)¶

v1.11.1

• Make max_tokens optional in Anthropic /v1/messages to align with the Anthropic API specification
• Remove unsupported reasoning configuration checks for broader client compatibility
• Rename /v1/responses route tag from "Responses" to "Chat" in OpenAPI documentation for consistency

v1.11.2-v1.11.3

• Add missing MCP dependencies to container image.

v1.11.4

• Upgrade Starlette dependency to fix CVE-2026-48710.

v1.10.0 – 2026-04-17 – OpenAI Responses API¶

This release adds support for the OpenAI /v1/responses endpoint—OpenAI's next-generation API designed for building agents and multi-step AI workflows. Drop-in compatible with the OpenAI SDK, it works with all Amazon Bedrock Converse-compatible models and supports streaming, function tools, built-in tools (web search, code interpreter, image generation), extended reasoning, and structured output.

Responses (OpenAI-Compatible)¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/responses	Amazon Bedrock - foundation models
OpenAI	/v1/responses – web_search / web_search_preview built-in tool	Amazon Nova models
OpenAI	/v1/responses – code_interpreter built-in tool	Amazon Nova models
OpenAI	/v1/responses – image_generation built-in tool	Amazon Bedrock - image models

Fixes¶

• Fix prompt caching error when messages contain tool-related content on models that do not support tool caching
• Make signature field optional in Anthropic message types
• Fix model legacy detection when the end-of-life date falls before the next cache refresh

v1.9.0 – 2026-04-10 – Files API & Images API JSON Body¶

This release introduces a Files API backed by Amazon S3, available through both the OpenAI-compatible and Anthropic-compatible interfaces. Files uploaded via either API share the same S3 storage and can be referenced across both interfaces. Large files can be uploaded incrementally using the OpenAI multipart uploads API. Stored files can be referenced by ID directly in image edit and variation requests (JSON body), as well as in chat completion messages as document or image inputs. The image edits endpoint now also accepts an application/json body as an alternative to multipart form-data, making it easier to chain pipeline steps without re-uploading files.

Files & Storage¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/files – CRUD operations	Amazon S3
OpenAI	/v1/uploads – multipart uploads	Amazon S3
Anthropic	/v1/files – CRUD operations	Amazon S3

Image Generation¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/images/edits – JSON body with images/mask referencing Files API IDs or URLs	Amazon Bedrock - image models
OpenAI	/v1/images/variations – JSON body with image referencing a Files API ID or URL	Amazon Bedrock - image models

Chat Completions & Messages¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	Files API file IDs usable as document/image inputs in chat completions	Amazon Bedrock - foundation models
Anthropic	Files API file IDs usable as document/image inputs in messages	Amazon Bedrock - foundation models

Fixes¶

• Document inputs via S3 URLs are not supported as Bedrock Converse API inputs for some models (e.g., Claude) — now properly detected and handled

v1.8.0 – 2026-04-04 – Broader Model Compatibility & Structured Output¶

This release focuses on improving reliability and compatibility across a wide variety of models. Structured response formats (JSON object and JSON schema) are now supported on OpenAI chat completions, and request metadata can be forwarded to Bedrock. Tool handling has been significantly improved—both for model-specific system tools and for Amazon Nova's grounding tool, including multi-turn support. Region routing is now more robust, correctly enforcing non-global inference profiles for region-restricted models and handling edge cases gracefully.

Chat Completions¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	response_format – JSON object and JSON schema structured output	Amazon Bedrock - foundation models
OpenAI	metadata – request metadata forwarding to Bedrock	Amazon Bedrock - foundation models
Amazon Nova	Nova Code Interpreter global profile support	Amazon Bedrock - Nova models

Messages (Anthropic-Compatible)¶

Provider	Endpoint/Feature	AWS Backend
Amazon Nova	nova_grounding responses mapped to web_search content blocks	Amazon Bedrock - Nova models
Amazon Nova	Multi-turn conversation support with nova_grounding	Amazon Bedrock - Nova models

Platform Features¶

Fixes¶

• Fix systemTool_ prefix handling: removed broken auto-promotion logic; system tools require specific tool output handling not compatible with generic tool forwarding
• AWS_BEDROCK_LEGACY default changed from true to false to prevent access denied errors on legacy models that have not been actively used recently
• Bedrock read timeouts are now handled as standard model errors (503) instead of unhandled exceptions, and are properly retried across regions when multi-region routing is enabled

v1.7.0 – 2026-03-20 – Automatic Region Routing, Deprecated Model Fallback & Resilience Improvements¶

The headline feature of v1.7 is automatic multi-region routing: stdapi.ai now intelligently distributes requests across your configured AWS regions, failing over automatically on quota limits or unavailability—and because each region carries its own independent quota, adding regions directly multiplies your effective tokens-per-minute and daily limits. Alongside this, deprecated model IDs are transparently redirected to their replacements so clients survive AWS model retirements without any code changes. This release also adds S3 URL support for file inputs across all relevant endpoints, a configurable AI response timeout, and memory efficiency improvements.

Platform Features¶

Fixes¶

• Fix SSE stream error handling in monitoring to handle specific API and AWS client errors gracefully
• Fix audio MIME type detection failure when libmagic's in-memory buffer path silently returns application/octet-stream; fall back to file-based detection to ensure correct format is sent to Bedrock

v1.6.0 – 2026-02-27 – Anthropic API Compatibility & Advanced Claude Capabilities¶

Introduces a full Anthropic-compatible API layer, enabling direct use of the Anthropic SDK and Claude-native tools with Amazon Bedrock. Adds Claude server tools support via OpenAI chat completions, token count estimation, automatic Anthropic beta flag filtering, and configurable route prefixes.

Chat Completions¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/chat/completions Claude server tools (bash, str_replace_based_edit_tool, computer, memory)	Claude models on Amazon Bedrock

Messages (Anthropic-Compatible)¶

Provider	Endpoint/Feature	AWS Backend
Anthropic	/v1/messages – Full Anthropic Messages API	Amazon Bedrock - Converse API
Anthropic	/v1/messages/count_tokens – Token counting	Amazon Bedrock - CountTokens API
Claude	Claude server tools (bash, text editor, computer, memory)	Amazon Bedrock - Claude models
Amazon Nova	Web search tool (web_search → nova_grounding)	Amazon Bedrock - Nova models

Model Discovery (Anthropic-Compatible)¶

Provider	Endpoint/Feature	AWS Backend
Anthropic	/v1/models – List models (Anthropic format)	Amazon Bedrock - model catalog
Anthropic	/v1/models/{model_id} – Get model details	Amazon Bedrock - model catalog

Platform Features¶

v1.5.0 – 2026-02-15 – Advanced Reasoning & Model Compatibility (with v1.5.1–v1.5.2 maintenance updates, through 2026-02-18)¶

Introduces advanced reasoning capabilities with Amazon Nova 2 and Anthropic Claude 4.6+ adaptive reasoning, enhanced system prompt handling for broader model compatibility.

Chat Completions¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	System prompt handling for unsupported models	Amazon Bedrock - foundation models
Amazon Nova	Nova 2 chat model reasoning implementation	Amazon Bedrock - foundation models
Claude	Claude 4.6+ adaptive reasoning configuration	Amazon Bedrock - Claude models

Fixes & Maintenance (v1.5.1–v1.5.2)¶

v1.5.2

• Add "/" route to avoid 404 errors on root endpoint
• Fix empty system content block handling (improves Amazon Bedrock Converse API compatibility)

v1.5.1

• Fix Amazon Nova Canvas image editing to fall back to TEXT_IMAGE task type when no mask is provided

v1.4.0 – 2026-02-11 – Audio Enhancements & Model Compatibility¶

Expands audio capabilities with Mistral Voxtral support, speaker diarization, audio formats for chat completions, and introduces prompt caching TTL and model aliasing for better OpenAI compatibility.

Chat Completions¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/chat/completions audio format support	Amazon Bedrock - foundation models
OpenAI	/v1/chat/completions extended Bedrock finish reasons mapping	Amazon Bedrock
OpenAI	Prompt caching TTL support	Amazon Bedrock - prompt caching

Speech & Audio¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/audio/transcriptions diarized_json format	Amazon Transcribe
Mistral	Voxtral audio model	Amazon Bedrock - foundation models

Platform Features¶

Fixes¶

• Fix chat completion file input handling and refactor base64 decoding and MIME handling for file processing.
• Re-raise startup exceptions and disable botocore logging to improve error visibility

v1.3.0 – 2026-01-11 – Image Editing & Variation Support (with v1.3.1–v1.3.5 maintenance updates, through 2026-02-02)¶

Adds support for OpenAI's image editing and variation endpoints, enabling image manipulation capabilities backed by Amazon Bedrock. Includes maintenance updates for content block handling, tool call validation, streaming fixes, and TTS optimization.

Image Generation¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/images/edits	Amazon Bedrock - image models
OpenAI	/v1/images/variations	Amazon Bedrock - image models

Speech & Audio (v1.3.2)¶

Fixes & Maintenance (v1.3.1–v1.3.5)¶

v1.3.5

• Refactor content block handling to skip empty entries in assistant responses

v1.3.4

• Handle invalid tool call arguments with robust JSON content validation
• Add deprecation mapping for amazon.titan-image-generator-v2:0 → amazon.nova-canvas-v1:0

v1.3.3

• Remove premature stop condition for contentBlockStop in streaming chat completions

v1.3.2

• Support image[] array-style notation for OpenAI image edits
• Handle empty audio segments in transcription duration calculation

v1.3.1

• Improve JSON parsing for tool arguments and results
• Correct example → examples in OpenAPI model path parameter

v1.2.0 – 2025-12-18 – Service Tiers, System Tools & Performance Enhancements¶

Introduces service tiers and latency headers for all Bedrock routes, Bedrock-specific system tools (Nova grounding), GPT5.2 API compatibility, configurable guardrail overrides, and Python 3.14 optimization.

Chat Completions¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/chat/completions service_tier parameter	Amazon Bedrock - service tiers
OpenAI	/v1/chat/completions Bedrock-specific system tools (Nova grounding)	Amazon Bedrock - system tools
OpenAI	/v1/chat/completions GPT5.2 API update (reasoning_effort=xhigh)

Content Safety & Moderation¶

Feature	AWS Backend
Configuration flag for guardrail override allow	Amazon Bedrock Guardrails

Platform Features¶

Feature	AWS Backend / Description
Service tiers and latency headers (all Bedrock routes)	Amazon Bedrock - service tiers
Python 3.14 support	Upgraded to Python 3.14 with performance optimization
Dependency update	Direct aiobotocore usage (replaced aioboto3)

Fixes¶

• Fix warnings for duplicated FastAPI routes (/docs and /openapi.json).

v1.1.0 – 2025-11-27 – Embeddings Enhancement, Prompt Caching & Advanced Routing¶

Expands multimodal embedding capabilities, adds prompt caching support, and introduces advanced routing with application inference profiles and prompt routers.

Chat Completions¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	Prompt caching /v1/chat/completions prompt_cache_key	Amazon Bedrock - prompt caching
OpenAI	/v1/chat/completions GPT5.1 API update (reasoning_effort=none)

Embeddings¶

Provider	Endpoint/Feature	AWS Backend
	Intelligent S3 multimodal upload	Amazon S3
	Intelligent Sync/async Bedrock invocation	Amazon Bedrock
Amazon Nova	Multimodal embeddings models
Twelve Labs	Marengo V3 models

Advanced Routing¶

Feature	AWS Backend
Application inference profiles	Amazon Bedrock - application inference profiles
Prompt routers	Amazon Bedrock - prompt routers
Server-side ARN mapping	Amazon Bedrock
Client-side ARN passing (optional)	Amazon Bedrock

Fixes¶

• /v1/chat/completions: Fix default value passed to the converse API for tools without parameters.
• stdapi-ai Terraform module: Fix error if alarms_enabled = true but sns_topic_arn undefined.

v1.0.0 – 2025-11-10 – Foundation Release¶

The initial release establishes core OpenAI API compatibility with Amazon Bedrock backing.

Chat Completions¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/chat/completions	Amazon Bedrock - foundation models
	All models supporting Converse/ConverseStream APIs	Amazon Bedrock - Converse API
DeepSeek	/v1/chat/completions reasoning_content	Amazon Bedrock - foundation models
Qwen	enable_thinking + thinking_budget parameter	Amazon Bedrock - foundation models
Qwen	top_k parameter	Amazon Bedrock - foundation models

Embeddings¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/embeddings	Amazon Bedrock - embedding models
Cohere	Embed V3 & V4 models
Twelve Labs	Marengo V2 models
Amazon Titan	Embed V1 & V2 models

Speech & Audio¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/audio/speech	Amazon Polly + Amazon Comprehend
OpenAI	/v1/audio/transcriptions	Amazon Transcribe
OpenAI	/v1/audio/translations	Amazon Transcribe + Amazon Translate

Image Generation¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/images/generations	Amazon Bedrock - image models
Amazon Nova	Canvas V1 models
Amazon Titan	Image Generator V1 & V2 models
Stability AI	Image Core, Ultra and SD3.5 Large models

Model Discovery¶

Provider	Endpoint/Feature	AWS Backend
OpenAI	/v1/models	Amazon Bedrock - model catalog

Platform Features¶

Feature	AWS Backend
Bedrock Features
Content filtering and safety	Amazon Bedrock Guardrails
Cross-region inference	Amazon Bedrock - global/regional
Application inference profiles	Amazon Bedrock - inference profiles
Model parameters (temperature, top_p, etc.)	Amazon Bedrock - native parameters
Multi-region failover	Amazon Bedrock - multi-region
Bedrock guardrails	Amazon Bedrock Guardrails
AWS Services
File storage	Amazon S3 - presigned URLs, Transfer Acceleration
Authentication
Static token authentication	AWS SSM Parameter Store / Secrets Manager
Development mode (no auth)
Observability
Distributed tracing	AWS X-Ray + OpenTelemetry
Structured logging	Amazon CloudWatch (When running on ECS/EKS)
Health check endpoint
HTTP/Security
CORS support
Trusted host validation
Proxy headers (X-Forwarded-*)
GZip compression
📚 Documentation
Interactive API docs & OpenAPI schema
🔌 Compatibility
Provider-specific parameters