mirror of
https://github.com/BerriAI/litellm.git
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f81e657903
* feat(volcengine): add Doubao-Seedance video generation via the OpenAI /v1/videos surface
New VolcEngineVideoConfig maps litellm's OpenAI Videos API onto Volcengine
Ark's contents/generations task API: create hits
/api/v3/contents/generations/tasks and returns a cgt-... task id, status and
content poll /api/v3/contents/generations/tasks/{id}, list maps the same
collection (limit -> page_size, Ark's filter.* through extra_query), delete
maps DELETE on the task URL, and edit/extension reuse create with a
reference_video content item since Ark models both as ordinary generation
tasks. Ark's own edit and extension require ratio adaptive (edit also
duration -1), so those are pinned unless the caller overrides them. Remix has
no Ark equivalent and raises.
The body is flat apart from a typed content array: the prompt is a text item
and every image/video/audio input is a url item carrying a role, which is the
only way to express reference-to-video, edit and extension jobs, so a
caller-supplied content array wins outright. input_reference becomes a
first_frame item, base64 encoded into a data URI for file inputs.
OpenAI params translate per Ark's contract: seconds becomes duration and size
yields both a ratio and a named resolution tier, with the ratio snapped onto
the set Ark accepts (854x480 reduces to 427:240, which Ark rejects) and the
tier taken from the shortest side. Emitting only the ratio leaves the request
on the model default and bills at that default's rate.
Billing reads the delivered duration and resolution rather than the requested
ones, because duration -1 and ratio adaptive both let Ark deliver something
else. Ark bills per output token (tokens = width * height * 24 * seconds /
1024), so the cost map carries per-second rates by resolution tier, derived
from the console's CNY per million token list rates (2.5 70, 2.0 46, 2.0-fast
37, 2.0-mini 23 without a video input) at the repo's 7.0 CNY/USD convention.
Requests that do carry a video input bill at the lower rate instead, which
litellm's per-second tiers cannot express, so those are overestimated.
usage.total_tokens rides along for invoice reconciliation.
Ark echoes the delivered geometry only as a resolution tier plus a ratio, and
the 2.0 family's rendered frame does not follow the tier name: its 16:9 "480p"
canvas is 864x496, not the 854x480 the tier implies, and its other ratios
differ from the tier's nominal shortest side too. A size reconstructed from
the tier alone therefore reports pixels the model never produces and scales
the 480p rate against the wrong pixel count, so both the reported size and
the 2.0 480p rates come from the measured frame (a per-family table, sourced
from the Seedance 2.0 Mini model card and re-verified against a live gateway).
The create response reports the requested duration and resolution, since only
the create, edit and remix calls are costed and Ark's create response carries
no usage block, so without it every video logs zero spend. A caller that
leaves seconds off is not free either: Ark runs its own default length, which
is 5s for the 2.0 family, so that is what the create response bills, while
the 2.5 family's default is -1 (Ark picks) and stays unbilled until the
status response. The create response also echoes the requested seconds and
the frame the job will be rendered at.
Editing and extending need the source video as a URL: Ark's task query is a
GET while litellm's edit prefetch hook only POSTs, so a task id cannot be
resolved into one. The model comes from an explicit extra_body.model, else
the encoded video id, else the model the router already resolved, with
litellm's provider prefix dropped.
The credential's api_base is the Anthropic-compat surface
(/api/compatible), so the base is cut at the first /api/ marker rather than
by a /api/v3 suffix before the video paths append their own version.
The cost-map schema test's exception list gains the 2.0 4K tier, whose
$1.28/second rate exceeds its $1 sanity bound, alongside the existing
runwayml/seedance2 entry.
* fix(volcengine): answer 4xx when a Seedance video is downloaded before it finishes
Downloading a task that is still queued or running raised a bare ValueError, which the
video content handler synthesizes into a 500. The proxy then retried the same poll twice
and reported the caller's own early download as a gateway fault, and the router went
looking for a model group fallback for a job that was simply unfinished
The download path now raises VolcEngineVideoError carrying the status the OpenAI videos
API documents for content that is not ready (404), 400 for a task the provider reported
as failed, 404 for an expired task record, and 502 for a succeeded task with no artifact.
None of them are 5xx, so the router stops retrying them
Regression tests drive avideo_content and assert the caller sees NotFoundError or
BadRequestError instead of an internal server error
* fix(volcengine): clear the type-discipline and override findings on the Seedance video path
The module annotated four mutable collections and carried five `# mutable-ok` markers on
lines that suppressed nothing, so the type-discipline gate counted LIT001 x4 and LIT013
x5 against the PR. The content-item and task-dump helpers hand back read-only views of
what they build, so they now say Mapping. VideoObject.error is declared as a dict by the
type it feeds, so that one marker moves onto the annotation it actually suppresses
transform_video_status_retrieve_response also dropped the client keyword the base class
declares, which basedpyright reported as an incompatible override
* fix(volcengine): bill every Seedance video at create and keep its polls on the deployment that made it
Ark bills a task when it finishes while litellm bills it at create, so a request
whose cost is not known then is rejected: Ark-picked length (duration -1), frames,
a video input, and with it edit and extension. An omitted length is sent as 5s,
since the 2.5 family otherwise lets Ark pick it and logged $0.
Video ids now carry the requested and the served model group, read from
litellm_metadata, so polls and downloads go back to the deployment that created
the task. The routing and input_reference helpers move out of the DashScope
config into a shared module both providers use.
A download before the render finishes answers 400, unreadable or unmapped task
bodies answer 502, malformed seconds, size, parameters and Ark fields raise
unless drop_params is set, an unpriced resolution tier is refused, and the
rendered frame table moves into the cost map.
Co-Authored-By: AaronHowell <111272993+AaronHowell@users.noreply.github.com>
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
* fix(volcengine): reject a text item in content so the guarded prompt is the only text sent
Input guardrails scan data["prompt"], so a caller could pass a harmless prompt
for scanning and a different, unscanned text item in content, which this branch
kept and the guarded prompt was dropped. The prompt now always leads the content
array and a second text item answers 400.
Co-Authored-By: AaronHowell <111272993+AaronHowell@users.noreply.github.com>
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
* fix(volcengine): route video to VOLCENGINE_API_BASE when the deployment sets no api_base
* fix(volcengine): let a model with no tier prices keep its resolution instead of rejecting every tier
* fix(volcengine): answer 400 for malformed or unknown create fields, send a 720p default tier, and stop the list cursor
* fix(volcengine): map size to the closest tier by pixel count, reject draft, remix and list cursors, map user to safety_identifier, read ARK_API_BASE
* fix(volcengine): drop unsupported create values under drop_params, take OpenAI's object input_reference, default to 4 seconds, price endpoint ids by base_model
* fix(videos): unwrap nested file tuples without recursion
* fix(volcengine): price Seedance tiers at Ark's own per-resolution token rates
Ark prices 1080p and 4k per token above and below the 480p/720p rate, so the
single 46 CNY per million tokens the rows were derived from billed 2.0 1080p
and 2.5 1080p about 10% low and 2.0 4k 77% high. Ark's per-resolution table
and its own 16:9 examples agree: 1080p 2.48 CNY/s, 4k 5.05 CNY/s for 2.0 and
3.74 CNY/s for 2.5 1080p, which is 51, 26 and 77 CNY per million tokens.
Rewrites the tier test to check each rate against the rendered pixels at that
tier's own price instead of assuming every tier scales from the base rate,
and drops the 4k cost exception that only existed for the old rate.
Co-Authored-By: Bytechoreographer <noreply@bytechoreographer.com>
Co-Authored-By: AaronHowell <111272993+AaronHowell@users.noreply.github.com>
* fix(volcengine): unpack Ark parameters sent through extra_body
* fix(volcengine): ignore the extra_body keys litellm maps itself
The shared request builder merges the caller's raw extra_body back over the
mapped params, so a key this adapter maps itself comes back a second time as a
field of its own, and the unknown field check turned the supported request
into a 400. 2aefc18b0a covered parameters; size, seconds and user still failed
that way.
All three are already mapped from the top-level copy the same builder writes,
so the leftover is ignored rather than rejected. characters and image stay
rejected, since Ark has no equivalent and accepting them would hide a
parameter that never took effect.
Co-Authored-By: Bytechoreographer <noreply@bytechoreographer.com>
Co-Authored-By: AaronHowell <111272993+AaronHowell@users.noreply.github.com>
* fix(volcengine): reject litellm request fields inside parameters and accept litellm's own controls
A seconds, size, user, prompt or nested parameters inside an Ark parameters object, and an extra_body copy of
prompt, model or extra_headers, answer 400 again unless drop_params is on, instead of being ignored. A user that
is not a string answers 400 the same way. drop_params, additional_drop_params and a forwarded organization are
no longer rejected as unknown Ark fields, and additional_drop_params removes the fields it names.
* fix(volcengine): apply additional_drop_params before mapping request fields
A drop list naming user, seconds, size, parameters or an unsupported field such as image had no effect, because
the fields were already mapped to Ark names before the list was applied. The list now removes them first, so the
request sends what it would send if those fields were never set
---------
Co-authored-by: AaronHowell <111272993+AaronHowell@users.noreply.github.com>
Co-authored-by: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: zijie.zhou <zijie.zhou@momenta.ai>
Co-authored-by: Bytechoreographer <noreply@bytechoreographer.com>
3533 lines
103 KiB
JSON
3533 lines
103 KiB
JSON
{
|
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"_comment": "This file defines which endpoints are supported by each LiteLLM provider",
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"_schema": {
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"provider_slug": {
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"display_name": "Display name shown in README (e.g., 'OpenAI (`openai`)')",
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"url": "Link to provider documentation",
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"endpoints": {
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"chat_completions": "Supports /chat/completions endpoint",
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"systemone": "Supports native System One typed decisions",
|
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"messages": "Supports /messages endpoint (Anthropic format)",
|
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"responses": "Supports /responses endpoint (OpenAI/Anthropic unified)",
|
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"embeddings": "Supports /embeddings endpoint",
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"image_generations": "Supports /image/generations endpoint",
|
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"audio_transcriptions": "Supports /audio/transcriptions endpoint",
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"audio_speech": "Supports /audio/speech endpoint",
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"moderations": "Supports /moderations endpoint",
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"batches": "Supports /batches endpoint",
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"rerank": "Supports /rerank endpoint",
|
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"ocr": "Supports /ocr endpoint",
|
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"search": "Supports /search endpoint",
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"skills": "Supports /skills endpoint",
|
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"interactions": "Supports /interactions endpoint (Google AI Interactions API)",
|
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"a2a_(Agent Gateway)": "Supports /a2a/{agent}/message/send endpoint (A2A Protocol)",
|
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"container": "Supports OpenAI's /containers endpoint",
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"container_file": "Supports OpenAI's /containers/{id}/files endpoint",
|
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"compact": "Supports /responses/compact endpoint",
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"files": "Supports /files endpoint for file operations",
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"image_edits": "Supports /images/edits endpoint for image editing",
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"vector_stores_create": "Supports creating a new vector store via /vector_stores endpoint",
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"vector_stores_search": "Supports searching a vector store via /vector_stores/{id}/search endpoint",
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"video_generations": "Supports /videos/generations endpoint for video generation"
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}
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}
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},
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"providers": {
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"a2a": {
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"display_name": "A2A (Agent-to-Agent) (`a2a`)",
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"url": "https://docs.litellm.ai/docs/providers/a2a",
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": false,
|
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"responses": false,
|
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"embeddings": false,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": false,
|
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"rerank": false,
|
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"a2a": false
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}
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},
|
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"abliteration": {
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"display_name": "Abliteration (`abliteration`)",
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"url": "https://docs.litellm.ai/docs/providers/abliteration",
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": false,
|
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"responses": false,
|
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"embeddings": false,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
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"moderations": false,
|
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"batches": false,
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"rerank": false,
|
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"a2a": false
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}
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},
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"aiml": {
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"display_name": "AI/ML API (`aiml`)",
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"url": "https://docs.litellm.ai/docs/providers/aiml",
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": true,
|
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"responses": true,
|
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"embeddings": true,
|
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"image_generations": true,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": false,
|
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"rerank": false,
|
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"a2a": true,
|
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"interactions": true
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}
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},
|
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"ai21": {
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"display_name": "AI21 (`ai21`)",
|
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"url": "https://docs.litellm.ai/docs/providers/ai21",
|
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": true,
|
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"responses": true,
|
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"embeddings": false,
|
|
"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": false,
|
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"rerank": false,
|
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"a2a": true,
|
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"interactions": true
|
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}
|
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},
|
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"ai21_chat": {
|
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"display_name": "AI21 Chat (`ai21_chat`)",
|
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"url": "https://docs.litellm.ai/docs/providers/ai21",
|
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": true,
|
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"responses": true,
|
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"embeddings": false,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": false,
|
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"rerank": false,
|
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"a2a": true,
|
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"interactions": true
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}
|
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},
|
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"amazon_nova": {
|
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"display_name": "Amazon Nova (`amazon_nova`)",
|
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"url": "https://docs.litellm.ai/docs/providers/amazon_nova",
|
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": true,
|
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"responses": true,
|
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"embeddings": false,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": false,
|
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"rerank": false,
|
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"a2a": true,
|
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"interactions": true
|
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}
|
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},
|
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"anthropic": {
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"display_name": "Anthropic (`anthropic`)",
|
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"url": "https://docs.litellm.ai/docs/providers/anthropic",
|
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": true,
|
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"responses": true,
|
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"embeddings": false,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": true,
|
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"rerank": false,
|
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"skills": true,
|
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"a2a": true,
|
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"interactions": true,
|
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"count_tokens": true
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}
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},
|
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"anthropic_text": {
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"display_name": "Anthropic Text (`anthropic_text`)",
|
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"url": "https://docs.litellm.ai/docs/providers/anthropic",
|
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": true,
|
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"responses": true,
|
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"embeddings": false,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": true,
|
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"rerank": false,
|
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"skills": true,
|
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"a2a": true,
|
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"interactions": true
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}
|
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},
|
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"apertis": {
|
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"display_name": "Apertis (`apertis`)",
|
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": false,
|
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"responses": false,
|
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"embeddings": true,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": false,
|
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"rerank": false,
|
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"a2a": false
|
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}
|
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},
|
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"aihubmix": {
|
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"display_name": "AIHubMix (`aihubmix`)",
|
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"url": "https://docs.litellm.ai/docs/providers/aihubmix",
|
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": true,
|
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"responses": true,
|
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"embeddings": true,
|
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"image_generations": true,
|
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"audio_transcriptions": true,
|
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"audio_speech": true,
|
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"moderations": true,
|
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"batches": false,
|
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"rerank": true,
|
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"a2a": false
|
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}
|
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},
|
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"assemblyai": {
|
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"display_name": "AssemblyAI (`assemblyai`)",
|
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"url": "https://docs.litellm.ai/docs/pass_through/assembly_ai",
|
|
"endpoints": {
|
|
"chat_completions": true,
|
|
"messages": true,
|
|
"responses": true,
|
|
"embeddings": false,
|
|
"image_generations": false,
|
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"audio_transcriptions": true,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": false,
|
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"rerank": false,
|
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"a2a": true,
|
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"interactions": true
|
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}
|
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},
|
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"auto_router": {
|
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"display_name": "Auto Router (`auto_router`)",
|
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"url": "https://docs.litellm.ai/docs/proxy/auto_routing",
|
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": true,
|
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"responses": true,
|
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"embeddings": false,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": false,
|
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"rerank": false,
|
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"a2a": true,
|
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"interactions": true
|
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}
|
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},
|
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"bedrock": {
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"display_name": "AWS - Bedrock (`bedrock`)",
|
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"url": "https://docs.litellm.ai/docs/providers/bedrock",
|
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": true,
|
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"responses": true,
|
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"embeddings": true,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": false,
|
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"rerank": true,
|
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"a2a": true,
|
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"interactions": true,
|
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"bedrock_invoke": true,
|
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"bedrock_converse": true,
|
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"vector_stores_search": true,
|
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"count_tokens": true,
|
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"rag_ingest": true,
|
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"rag_query": true
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}
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},
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"s3_vectors": {
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"display_name": "AWS S3 Vectors (`s3_vectors`)",
|
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"url": "https://docs.litellm.ai/docs/providers/s3_vectors",
|
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"endpoints": {
|
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"chat_completions": false,
|
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"messages": false,
|
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"responses": false,
|
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"embeddings": false,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
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"batches": false,
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"rerank": false,
|
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"a2a": false,
|
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"interactions": false,
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"vector_stores_create": true,
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"vector_stores_search": true
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}
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},
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"sagemaker": {
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"display_name": "AWS - Sagemaker (`sagemaker`)",
|
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"url": "https://docs.litellm.ai/docs/providers/aws_sagemaker",
|
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"endpoints": {
|
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"chat_completions": true,
|
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"messages": true,
|
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"responses": true,
|
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"embeddings": true,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": false,
|
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"moderations": false,
|
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"batches": false,
|
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"rerank": false,
|
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"a2a": true,
|
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"interactions": true
|
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}
|
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},
|
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"aws_polly": {
|
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"display_name": "AWS - Polly (`aws_polly`)",
|
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"url": "https://docs.litellm.ai/docs/providers/aws_polly",
|
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"endpoints": {
|
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"chat_completions": false,
|
|
"messages": false,
|
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"responses": false,
|
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"embeddings": false,
|
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"image_generations": false,
|
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"audio_transcriptions": false,
|
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"audio_speech": true,
|
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"moderations": false,
|
|
"batches": false,
|
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"rerank": false
|
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}
|
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|
"text_completion": {
|
|
"docs_label": "text_completion",
|
|
"display_name": "OpenAI Completions API",
|
|
"leftnav_label": "/completions",
|
|
"provider_json_field": "text_completion",
|
|
"url": "https://docs.litellm.ai/docs/text_completion",
|
|
"bridges_to_chat_completion": true
|
|
},
|
|
"text_to_speech": {
|
|
"docs_label": "text_to_speech",
|
|
"display_name": "OpenAI Text-to-Speech API",
|
|
"leftnav_label": "/audio/speech",
|
|
"provider_json_field": "audio_speech",
|
|
"url": "https://docs.litellm.ai/docs/text_to_speech"
|
|
},
|
|
"vector_store_files": {
|
|
"docs_label": "vector_store_files",
|
|
"display_name": "OpenAI Vector Store Files API",
|
|
"leftnav_label": "/vector_stores/files",
|
|
"provider_json_field": "vector_store_files",
|
|
"url": "https://docs.litellm.ai/docs/vector_store_files"
|
|
},
|
|
"vector_stores_create": {
|
|
"docs_label": "vector_stores_create",
|
|
"display_name": "OpenAI Vector Stores Create API",
|
|
"leftnav_label": "/vector_stores/create",
|
|
"provider_json_field": "vector_stores_create",
|
|
"url": "https://docs.litellm.ai/docs/vector_stores/create"
|
|
},
|
|
"vector_stores_search": {
|
|
"docs_label": "vector_stores_search",
|
|
"display_name": "OpenAI Vector Stores Search API",
|
|
"leftnav_label": "/vector_stores/search",
|
|
"provider_json_field": "vector_stores_search",
|
|
"url": "https://docs.litellm.ai/docs/vector_stores/search"
|
|
},
|
|
"videos": {
|
|
"docs_label": "videos",
|
|
"display_name": "OpenAI Videos API",
|
|
"leftnav_label": "/videos",
|
|
"provider_json_field": "video_generations",
|
|
"url": "https://docs.litellm.ai/docs/videos"
|
|
}
|
|
}
|
|
}
|