OpenAI

OpenAI API conversion guide - what to know when using OpenAI through Bifrost

Overview

OpenAI is the baseline schema for Bifrost. When using OpenAI directly, parameters are passed through with minimal conversion - mostly validation and filtering of OpenAI-specific features.

Supported Operations

Operation	Non-Streaming	Streaming	Endpoint
Chat Completions	✅	✅	/v1/chat/completions
Responses API	✅	✅	/v1/responses
Responses Lifecycle	✅	-	/v1/responses/{response_id}
Text Completions	✅	✅	/v1/completions
Embeddings	✅	-	/v1/embeddings
Speech (TTS)	✅	✅	/v1/audio/speech
Transcriptions (STT)	✅	✅	/v1/audio/transcriptions
Image Generation	✅	✅	/v1/images/generations
Image Edit	✅	✅	/v1/images/edits
Image Variation	✅	-	/v1/images/variations
Files	✅	-	/v1/files
Batch	✅	-	/v1/batches
Video Generation	✅	-	/v1/videos
Context Compaction	✅	-	/v1/responses/compact
List Models	✅	-	/v1/models

Setup & Configuration

Configure OpenAI as a provider.

Web UI

1. Navigate to Models > Model Providers. Look for OpenAI under Configured Providers. If it is missing, click on Add New Provider and select OpenAI.
2. Click Add Key or edit an existing key.
3. Set a name for your key.
4. Paste your API key directly or use an environment variable (for example, env.OPENAI_API_KEY).
5. Set Allowed Models to All Models (default) or the specific model allowlist you want this key to serve.
6. Save the provider configuration.

config.json

{
  "providers": {
    "openai": {
      "keys": [
        {
          "name": "openai-key-1",
          "value": "env.OPENAI_API_KEY",
          "models": [
            "*"
          ],
          "weight": 1.0
        }
      ],
      "openai_config": {
        "disable_store": false
      }
    }
  }
}

API

Refer to the API documentation for Provider Keys Management.

Go SDK

case schemas.OpenAI:
    return []schemas.Key{{
        Name:   "openai-key-1",
        Value:  *schemas.NewSecretVar("env.OPENAI_API_KEY"),
        Models: []string{"*"},
        Weight: 1.0,
    }}, nil

Optional provider settings include network_config for timeouts, retries, proxy/TLS settings, and openai_config.disable_store to force store=false on outgoing OpenAI requests.

---

1. Chat Completions

Request Parameters

Parameter	Type	Required	Notes
model	string	✅	Model identifier
messages	array	✅	ChatMessage array with roles (docs)
temperature	float	❌	Sampling temperature (0-2)
top_p	float	❌	Nucleus sampling parameter
stop	string/array	❌	Stop sequences
max_completion_tokens	int	❌	Min 16, max output tokens
frequency_penalty	float	❌	Frequency penalty (-2 to 2)
presence_penalty	float	❌	Presence penalty (-2 to 2)
logit_bias	object	❌	Token logit adjustments
logprobs	bool	❌	Include log probabilities
top_logprobs	int	❌	Number of log probabilities per token
seed	int	❌	Reproducibility seed
response_format	object	❌	Output format (docs)
tools	array	❌	Tool objects (docs)
tool_choice	string/object	❌	"auto", "none", "required", or specific tool
parallel_tool_calls	bool	❌	Allow multiple simultaneous tool calls
stream_options	object	❌	Streaming options (docs)
reasoning	object	❌	Reasoning parameters (Bifrost docs, OpenAI docs)
user	string	❌	Truncated to 64 chars
metadata	object	❌	Custom metadata
store	bool	❌	Filtered for non-OpenAI routing
service_tier	string	❌	Filtered for non-OpenAI routing
prompt_cache_key	string	❌	Filtered for non-OpenAI routing
prediction	object	❌	Predicted output for acceleration
audio	object	❌	Audio output config
modalities	array	❌	Response modalities (text, audio)

---

• Reasoning: OpenAI supports reasoning.effort (minimal, low, medium, high) and reasoning.max_tokens - both passed through directly. When routing to other providers, "minimal" effort is converted to "low" for compatibility. See Bifrost reasoning docs.
• Messages: All message roles are supported: system, user, assistant, tool, developer (treated as system). Content types: text, images via URL (image_url), audio input (input_audio). Tool messages include a tool_call_id.
• Tools: Standard OpenAI tool format with strict mode support. Tool choice: "auto", "none", "required", or specific tool by name.
• Responses: Passed through in standard OpenAI format. Finish reasons: stop, length, tool_calls, content_filter. Usage includes token counts and optionally cached/reasoning token details.
• Streaming: Server-Sent Events format with delta.content, delta.tool_calls, finish_reason, and usage (final chunk only, automatically included by Bifrost). stream_options: { include_usage: true } is set by default for all streaming calls.
• Cache Control: cache_control fields are stripped from messages, their content blocks, and tools before sending.
• Token Enforcement: max_completion_tokens is enforced to have a minimum of 16. Values below 16 are automatically set to 16.
• Special handling: user field is truncated to 64 characters; prompt_cache_key, store, service_tier are filtered when routing to non-OpenAI providers

---

2. Responses API

The Responses API is OpenAI’s structured output API.

Request Parameters

Parameter	Type	Required	Notes
model	string	✅	Model identifier
input	string/array	✅	Text or ContentBlock array (docs)
max_output_tokens	int	✅	Maximum output length
background	bool	❌	Run request in background mode
conversation	string	❌	Conversation ID for continuing a conversation
include	array	❌	Array of fields to include in response (e.g., "web_search_call.action.sources")
instructions	string	❌	System instructions
max_tool_calls	int	❌	Maximum number of tool calls
metadata	object	❌	Custom metadata
parallel_tool_calls	bool	❌	Allow multiple simultaneous tool calls
previous_response_id	string	❌	ID of previous response to continue from
prompt_cache_key	string	❌	Prompt caching key
reasoning	object	❌	ResponsesParametersReasoning configuration (Bifrost docs)
safety_identifier	string	❌	Safety identifier for content filtering
service_tier	string	❌	Service tier for the request
stream_options	object	❌	ResponsesStreamOptions configuration
store	bool	❌	Store the response for later retrieval
temperature	float	❌	Sampling temperature
text	object	❌	ResponsesTextConfig for output formatting
top_logprobs	int	❌	Number of log probabilities to return per token
top_p	float	❌	Nucleus sampling parameter
tool_choice	string/object	❌	ResponsesToolChoice strategy
tools	array	❌	ResponsesTool objects (docs)
truncation	string	❌	Truncation strategy (auto or off)
user	string	❌	Truncated to 64 chars

---

Special Message Handling (gpt-oss vs other models):

OpenAI models handle reasoning differently depending on the model family:

• Non-gpt-oss models (GPT-4o, o1, etc.): Send reasoning as summaries. Reasoning-only messages (with no summary and only content blocks) are filtered out since these models don’t support reasoning content blocks in the request format.
• gpt-oss models: Send reasoning as content blocks. Reasoning summaries in the request are converted to content blocks since gpt-oss expects reasoning as structured blocks, not summaries.

This conversion ensures compatibility across different model architectures for the structured Responses API. See Bifrost reasoning docs for detailed reasoning handling.

Token & Parameter Enforcement:

• max_output_tokens is enforced to have a minimum of 16. Values below 16 are automatically set to 16.
• reasoning.max_tokens field is automatically removed from JSON output (OpenAI Responses API doesn’t accept it).

Other conversions:

• Action types zoom and region are converted to screenshot
• cache_control fields are stripped from messages and tools
• Unsupported tool types are silently filtered (only these are supported: function, file_search, computer_use_preview, web_search, mcp, code_interpreter, image_generation, local_shell, custom, web_search_preview)

Response: Includes id, status (completed, incomplete, pending, error), output array with message content, and token usage.

Streaming: Server-Sent Events. stream_options: { include_usage: true } is set by default for all streaming calls. Each event carries a type field (ResponsesStreamResponseType) with one of the following values:

Category	Event Types
Response lifecycle	response.created, response.queued, response.in_progress, response.completed, response.failed, response.incomplete
Output items & content	response.output_item.added, response.output_item.done, response.content_part.added, response.content_part.done, response.output_text.delta, response.output_text.done
Refusals & annotations	response.refusal.delta, response.refusal.done, response.output_text.annotation.added, response.output_text.annotation.done
Function & custom tool calls	response.function_call_arguments.delta, response.function_call_arguments.done, response.custom_tool_call_input.delta, response.custom_tool_call_input.done
File search	response.file_search_call.in_progress, response.file_search_call.searching, response.file_search_call.results.added, response.file_search_call.results.completed
Web search	response.web_search_call.in_progress, response.web_search_call.searching, response.web_search_call.completed, response.web_search_call.results.added, response.web_search_call.results.completed
Web fetch	response.web_fetch_call.in_progress, response.web_fetch_call.fetching, response.web_fetch_call.completed
Reasoning summaries	response.reasoning_summary_part.added, response.reasoning_summary_part.done, response.reasoning_summary_text.delta, response.reasoning_summary_text.done
Image generation	response.image_generation_call.in_progress, response.image_generation_call.generating, response.image_generation_call.partial_image, response.image_generation_call.completed
MCP	response.mcp_call_arguments.delta, response.mcp_call_arguments.done, response.mcp_call.in_progress, response.mcp_call.completed, response.mcp_call.failed, response.mcp_list_tools.in_progress, response.mcp_list_tools.completed, response.mcp_list_tools.failed
Code interpreter	response.code_interpreter_call.in_progress, response.code_interpreter_call.interpreting, response.code_interpreter_call.completed, response.code_interpreter_call_code.delta, response.code_interpreter_call_code.done
Keepalive & errors	response.ping (sent by few providers, e.g. Anthropic), error

Response Lifecycle

Manage stored and background responses after creation (requests made with store: true or background: true). All lifecycle operations accept an optional provider query parameter (defaults to openai); providers that do not implement these operations return an unsupported operation error.

When multiple API keys are configured for the provider, pin key selection on lifecycle calls (for example, with the x-bf-api-key-id header, see Request Options) so they hit the same upstream account as the create call that produced the response_id.

Retrieve Response

GET /v1/responses/{response_id} - Retrieve a stored response (docs)

Query Parameters

Parameter	Type	Required	Notes
include	array	❌	Additional fields to include (repeat the parameter for multiple values)
starting_after	int	❌	Sequence number of the event after which to start the response
include_obfuscation	bool	❌	Whether to include obfuscation on the response

Response: The full response object, same shape as POST /v1/responses.

Delete Response

DELETE /v1/responses/{response_id} - Delete a stored response (docs)

Response: BifrostResponsesDeleteResponse with id, object, and deleted: true.

Cancel Response

POST /v1/responses/{response_id}/cancel - Cancel an in-flight response (docs). Only responses created with background: true can be cancelled.

Response: The full response object, same shape as POST /v1/responses.

List Input Items

GET /v1/responses/{response_id}/input_items - List the input items of a response (docs)

Query Parameters

Parameter	Type	Required	Notes
after	string	❌	Pagination cursor (item ID to list items after)
include	array	❌	Additional fields to include (repeat the parameter for multiple values)
limit	int	❌	Results per page
order	string	❌	asc or desc

Response: BifrostResponsesInputItemsResponse with object: "list", data (array of input items), has_more, first_id, last_id. Cursor-based pagination with has_more flag.

---

3. Text Completions (Legacy)

Text Completions is a legacy API. Use Chat Completions for new implementations.

Request Parameters

Parameter	Type	Required	Notes
model	string	✅	Model identifier
prompt	string/array	✅	Completion prompt(s)
max_tokens	int	❌	Maximum output tokens
temperature	float	❌	Sampling temperature
top_p	float	❌	Nucleus sampling
stop	string/array	❌	Stop sequences
user	string	❌	Truncated to 64 chars

---

• Array prompts generate multiple completions. Finish reasons: stop or length. Streaming uses SSE format. stream_options: { include_usage: true } is set by default for streaming calls.
• user field is truncated to 64 characters or set to nil if it exceeds the limit.

---

4. Embeddings

Request Parameters

Parameter	Type	Required	Notes
model	string	✅	Model identifier
input	string/array	✅	Text(s) to embed (docs)
encoding_format	string	❌	float or base64
dimensions	int	❌	Output embedding dimensions
user	string	❌	NOT truncated (unlike chat/text)

---

• No streaming support. Returns embedding array with usage counts.

---

5. Speech (Text-to-Speech)

Request Parameters

Parameter	Type	Required	Notes
model	string	✅	tts-1 or tts-1-hd
input	string	✅	Text to convert to speech
voice	string	✅	alloy, echo, fable, onyx, nova, shimmer
response_format	string	❌	mp3, opus, aac, flac, wav, pcm
speed	float	❌	0.25 to 4.0 (default 1.0)

---

• Returns raw binary audio. Streaming supported in SSE format (base64 chunks), but not all models support streaming. stream_options: { include_usage: true } is set by default for streaming calls.

---

6. Transcriptions (Speech-to-Text)

Requests use multipart/form-data, not JSON.

Request Parameters

Parameter	Type	Required	Notes
file	binary	✅	Audio file (multipart form-data)
model	string	✅	whisper-1
language	string	❌	ISO-639-1 language code
prompt	string	❌	Optional prompt for context
temperature	float	❌	Sampling temperature
response_format	string	❌	json, text, srt, vtt, verbose_json

---

• Supported audio formats: mp3, mp4, mpeg, mpga, m4a, wav, webm
• Response: Includes text, task, language, duration, and optionally word-level timing. Streaming supported in SSE format. stream_options: { include_usage: true } is set by default for streaming calls.

---

7. Image Generation

Request Parameters

Parameter	Type	Required	Notes
model	string	✅	Model identifier (e.g., dall-e-3)
prompt	string	✅	Text description of the image to generate
n	int	❌	Number of images to generate (1-10)
size	string	❌	Image size: "256x256", "512x512", "1024x1024", "1792x1024", "1024x1792", "1536x1024", "1024x1536", "auto"
quality	string	❌	Image quality: "auto", "high", "medium", "low", "hd", "standard"
style	string	❌	Image style: "natural", "vivid"
response_format	string	❌	Response format: "url" or "b64_json"
background	string	❌	Background: "transparent", "opaque", "auto"
output_format	string	❌	Output format: "png", "webp", "jpeg"
output_compression	int	❌	Compression level (0-100%)
partial_images	int	❌	Number of partial images (0-3)
moderation	string	❌	Moderation level: "low", "auto"
user	string	❌	User identifier

---

Request Conversion

OpenAI is the baseline schema for image generation. Parameters are passed through with minimal conversion:

• Model & Prompt: bifrostReq.Model → req.Model, bifrostReq.Prompt → req.Prompt
• Parameters: All fields from bifrostReq (ImageGenerationParameters) are embedded directly into the OpenAI request struct via struct embedding. No field mapping or transformation is performed.
• Streaming: When streaming is requested, stream: true is set in the request body.

Response Conversion

• Non-streaming: OpenAI responses are unmarshaled directly into BifrostImageGenerationResponse since Bifrost’s response schema is a superset of OpenAI’s format. All fields are passed through as-is.

• Streaming: OpenAI streaming responses use Server-Sent Events (SSE) format with event types:

  • image_generation.partial_image: Intermediate image chunks with b64_json data
  • image_generation.completed: Final chunk for each image with usage information
  • error: Error events

  Each chunk includes:

  • type: Event type
  • sequence_number: Sequence number of the chunk
  • partial_image_index: Image index (0-N) for partial images
  • b64_json: Base64-encoded image data (pointer, may be nil)
  • usage: Token usage (only in completed events)
  • created_at, size, quality, background, output_format: Additional metadata

  Bifrost converts these to BifrostImageGenerationStreamResponse chunks with:

  • Per-image chunkIndex tracking for proper ordering within each image
  • Index field indicating which image (0-N) the chunk belongs to
  • PartialImageIndex set only for partial images (not completed events)
  • Usage information attached to completed chunks
  • Latency tracking per chunk

Endpoint: /v1/images/generations

---

8. Image Edit

Requests use multipart/form-data, not JSON.

Request Parameters

Parameter	Type	Required	Notes
model	string	✅	Model identifier
prompt	string	✅	Text description of the edit
image[]	binary	✅	Image file(s) to edit (multipart form-data, supports multiple images)
mask	binary	❌	Mask image file (multipart form-data)
n	int	❌	Number of images to generate (1-10)
size	string	❌	Image size: "256x256", "512x512", "1024x1024", "1536x1024", "1024x1536", "auto"
quality	string	❌	Image quality: "auto", "high", "medium", "low", "standard"
response_format	string	❌	Response format: "url" or "b64_json"
background	string	❌	Background: "transparent", "opaque", "auto"
input_fidelity	string	❌	Input fidelity: "low", "high"
partial_images	int	❌	Number of partial images (0-3)
output_format	string	❌	Output format: "png", "webp", "jpeg"
output_compression	int	❌	Compression level (0-100%)
user	string	❌	User identifier
stream	bool	❌	Enable streaming response

---

Request Conversion

• Model & Input: bifrostReq.Model → req.Model, bifrostReq.Input.Images → req.Input.Images, bifrostReq.Input.Prompt → req.Input.Prompt
• Parameters: All fields from bifrostReq.Params (ImageEditParameters) are embedded directly into the OpenAI request struct via struct embedding. No field mapping or transformation is performed.
• Multipart Form Data: The request is serialized as multipart/form-data:
  • Model & Prompt: Written as form fields (model, prompt)
  • Images: Each image in Input.Images is written as a separate image[] field with proper MIME type detection (image/jpeg, image/webp, image/png) and Content-Type headers
  • Mask: If present, written as a mask field with MIME type detection and appropriate filename (mask.png, mask.jpg, mask.webp)
  • Optional Parameters: All optional parameters (n, size, quality, response_format, background, input_fidelity, partial_images, output_format, output_compression, user) are written as form fields
  • Integer Conversion: Integer fields (n, partial_images, output_compression) are converted to strings using strconv.Itoa
  • Streaming: When streaming is requested, stream: "true" is written as a form field

Response Conversion

• Non-streaming: OpenAI responses are unmarshaled directly into BifrostImageGenerationResponse since Bifrost’s response schema is a superset of OpenAI’s format. All fields are passed through as-is.

• Streaming: OpenAI streaming responses use Server-Sent Events (SSE) format with event types:

  • image_edit.partial_image: Intermediate image chunks with b64_json data
  • image_edit.completed: Final chunk for each image with usage information
  • error: Error events

  Each chunk includes:

  • type: Event type (image_edit.partial_image or image_edit.completed)
  • sequence_number: Sequence number of the chunk
  • partial_image_index: Image index (0-N) for partial images
  • b64_json: Base64-encoded image data (pointer, may be nil)
  • usage: Token usage (only in completed events)

  Bifrost converts these to BifrostImageGenerationStreamResponse chunks with:

  • Per-image chunkIndex tracking for proper ordering within each image
  • Index field indicating which image (0-N) the chunk belongs to
  • PartialImageIndex set only for partial images (not completed events)
  • Usage information attached to completed chunks
  • Latency tracking per chunk
  • Robust handling of interleaved chunks using incomplete image tracking

Endpoint: /v1/images/edits

---

9. Image Variation

Requests use multipart/form-data, not JSON.

Request Parameters

Parameter	Type	Required	Notes
model	string	✅	Model identifier
image	binary	✅	Image file to create variations from (multipart form-data)
n	int	❌	Number of images to generate (1-10)
size	string	❌	Image size: "256x256", "512x512", "1024x1024", "1792x1024", "1024x1792", "1536x1024", "1024x1536", "auto"
response_format	string	❌	Response format: "url" or "b64_json"
user	string	❌	User identifier

---

Request Conversion

• Model & Input: bifrostReq.Model → req.Model, bifrostReq.Input.Image.Image → req.Input.Image.Image
• Parameters: All fields from bifrostReq.Params (ImageVariationParameters) are embedded directly into the OpenAI request struct via struct embedding. No field mapping or transformation is performed.
• Multipart Form Data: The request is serialized as multipart/form-data:
  • Model: Written as form field (model)
  • Image: The image is written as an image field with proper MIME type detection (image/jpeg, image/webp, image/png) and Content-Type headers. If MIME type cannot be detected, defaults to image/png
  • Optional Parameters: All optional parameters (n, size, response_format, user) are written as form fields
  • Integer Conversion: Integer field (n) is converted to string using strconv.Itoa
• Multiple Images: Additional images beyond the first one (if present in ExtraParams["images"]) are stored in ExtraParams but only the first image is sent to OpenAI (OpenAI API only supports single image input)

Response Conversion

• Non-streaming: OpenAI responses are unmarshaled directly into BifrostImageVariationResponse (which is a type alias for BifrostImageGenerationResponse). All fields are passed through as-is.
• Streaming: Not supported for image variation requests.

Endpoint: /v1/images/variations

---

10. Files API

Upload

Request Parameters

Parameter	Type	Required	Notes
file	binary	✅	File to upload (multipart form-data)
purpose	string	✅	batch, fine-tune, or assistants
filename	string	❌	Custom filename (defaults to file.jsonl)

Response: FileObject with id, bytes, created_at, filename, purpose, status (docs)

List Files

Query Parameters

Parameter	Type	Required	Notes
purpose	string	❌	Filter by purpose
limit	int	❌	Results per page
after	string	❌	Pagination cursor
order	string	❌	asc or desc

Cursor-based pagination with has_more flag.

Retrieve / Delete / Content

Operations:

• GET /v1/files/{file_id} - Retrieve file metadata
• DELETE /v1/files/{file_id} - Delete file
• GET /v1/files/{file_id}/content - Download file content

---

11. Batch API

Create Batch

Request Parameters

Parameter	Type	Required	Notes
input_file_id	string	Conditional	File ID OR requests array (not both)
requests	array	Conditional	BatchRequestItem objects (converted to JSONL)
endpoint	string	✅	Target endpoint (e.g., /v1/chat/completions)
completion_window	string	❌	24h (default)
metadata	object	❌	Custom metadata

Response: BifrostBatchCreateResponse with id, endpoint, input_file_id, status, created_at, request_counts (docs). Statuses: BatchStatus (validating, failed, in_progress, finalizing, completed, expired, cancelling, cancelled)

List Batches

Query Parameters

Parameter	Type	Required	Notes
limit	int	❌	Results per page
after	string	❌	Pagination cursor

Retrieve / Cancel Batch

Operations:

• GET /v1/batches/{batch_id} - Get batch BifrostBatchRetrieveResponse (docs)
• POST /v1/batches/{batch_id}/cancel - Cancel batch (docs)

Get Results

1. Batch must be completed (has output_file_id)
2. Download output file via Files API
3. Parse JSONL - each BatchResultItem: {id, custom_id, response: {status_code, body}}

---

12. List Models

GET /v1/models - Lists available models with metadata. Model IDs in Bifrost responses are prefixed with openai/ (e.g., openai/gpt-4o). Results are aggregated from all configured API keys. No request body or parameters required.

---

13. Video Generation

Generate (POST /v1/videos)

Request Parameters

Parameter	Type	Required	Notes
model	string	✅	e.g., sora-2
prompt	string	✅	Text description of the video
input_reference	string	❌	Input image for image-to-video. Must be a base64 data URL (e.g., data:image/png;base64,...). Plain URLs are not accepted.
seconds	string	❌	Duration in seconds
size	string	❌	Resolution: 720x1280 (default), 1280x720, 1024x1792, 1792x1024

Response: BifrostVideoGenerationResponse - id, status, model, prompt, created_at

Job Statuses: queued → in_progress → completed / failed

Retrieve / Download / Delete / List / Remix

Operation	Endpoint	Notes
Get status	GET /v1/videos/{id}	Poll until status: completed
Download	GET /v1/videos/{id}/content	Returns raw video bytes
Delete	DELETE /v1/videos/{id}	Removes video job
List jobs	GET /v1/videos	Query params: after, limit, order
Remix	POST /v1/videos/{id}/remix	Body: {"prompt": "..."}

---

14. Context Compaction

Compresses a conversation into an opaque encrypted item that can be reused in future Responses API calls, reducing token costs for long-running conversations.

Request Parameters

Parameter	Type	Required	Notes
model	string	✅	Model identifier
input	string/array	✅*	Conversation to compact. Required unless previous_response_id is set. Accepts the same format as the Responses API input field, including prior compaction items (type: "response.compaction").
previous_response_id	string	✅*	ID of a previously stored response to compact instead of sending full input.
instructions	string	❌	System instructions preserved across the compacted context.
prompt_cache_key	string	❌	Prompt caching key.
prompt_cache_retention	string	❌	Cache retention duration.
service_tier	string	❌	Service tier preference.
fallbacks	array	❌	Bifrost fallback model list.

Endpoint: POST /v1/responses/compact

---

Common Error Codes

HTTP Status → Error Type mapping:

• 400 - invalid_request_error
• 401 - authentication_error
• 403 - permission_error
• 404 - not_found_error
• 429 - rate_limit_error
• 500 - api_error