Add an aws_textract OCR provider on the Rust route, with no Python path. The
detect-document-text model returns plain lines and analyze-document renders
layout and tables as markdown. Both use Textract's synchronous API, so a
multi-page PDF or TIFF is rejected with an error that names the single-page
limit. A call with no region fails instead of falling back to Bedrock's default
SigV4 covers the request body, and host hooks can rewrite that body before it
is sent. litellm-http now has OutboundRequest, which serializes the body once,
shows those bytes to a RequestSigner and is the only thing a route can send.
Chat, audio transcription and OCR build it after their hooks ran, so a callback
that redacts the body still produces a valid Bedrock or Textract signature
ChatCompletionsAuth and AudioTranscriptionAuth are replaced by
litellm_auth::RequestAuth, and one helper in core turns it into a signed or
unsigned request. Audio transcription now signs only the AWS header set and
rejects a forwarded header that SigV4 computes, the same as chat
The OCR catalog routes aws_textract as Rust required, and the dispatch context
reads the provider from the model prefix so a provider scoped rule can match
EnvironmentProxies holds raw proxy URLs, which can carry user:password, and
it sits inside HttpSettings and HttpClientConfig, so any {:?} of those would
print the password. Derive veil's Redact like the auth crate does. NO_PROXY
stays readable because it holds no credentials.
The media fetcher also rebuilt the hyper-util matcher for every URL and
redirect hop. Build it once when the fetcher is created
Python resolves the Vertex project and location as call params, then the
litellm.vertex_project / litellm.vertex_location globals, then env, and
Azure AD token refresh from litellm.enable_azure_ad_token_refresh alone.
Native OCR skipped the globals, so a config.yaml litellm_settings value
silently fell through to the credential's project and us-central1, and a
managed identity setup without an API key failed. The bridge now reads
them through a provider_defaults settings group into OcrSettings, and
VertexConfig / AzureAuthInputs slot them in at Python's precedence.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
custom_httpx mirrored a Python module that mixes transport plumbing with
OCR orchestration. The transport half (media fetcher, transport errors,
request and header helpers) now lives in litellm-http next to the pool,
TLS, proxies and settings, and the OCR request handler moves to
base_llm/ocr/handler.rs. Drops the unused deserialize_optional_param and
stale dead_code allows.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Settings sources beyond HTTP (media fetch, Azure Document Intelligence,
Vertex, timeouts) need the same env lookup and precedence merge, so move
them out of litellm-http into core_utils::settings. Lookup readers name the
Python idiom they mirror: get keeps a present empty value like
os.getenv(X, fallback), truthy drops it like an `or` chain, enabled only
switches on for "true". SSL_CERT_FILE now reads through truthy, matching
Python's `if ssl_cert_file and ...` check.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
litellm-http now builds the rustls config itself, so one route-neutral place covers roots, the client certificate, ALPN, ssl_ecdh_curve and ssl_security_level. A curve picks the single key exchange group. A cipher string restricts the TLS 1.2 suites it names, and entries rustls cannot express, such as @SECLEVEL=1, are logged once and skipped.
user_url_validation and user_url_allowed_hosts are applied by the media fetcher. Document downloads honor the environment proxy whenever provider calls do, keeping the per-hop address check, and stay on the pinned resolver when no proxy applies.
AIOHTTP_SO_KEEPALIVE, AIOHTTP_TCP_KEEPIDLE, AIOHTTP_TCP_KEEPINTVL, AIOHTTP_TCP_KEEPCNT and AIOHTTP_KEEPALIVE_TIMEOUT map onto the client. A client= argument and a live SSLContext are ignored
Every legacy callback call from callbacks-legacy now goes through one typed
Python shim, litellm.rust_bridge.legacy_callbacks, the only Python module
the crate reaches. Before, the crate called Logging methods, litellm.utils
hooks, the logging worker, the executor and several litellm globals
directly, and its tests retyped those signatures by hand, so an outdated
fake could accept a call the real code rejects. python_contract.json lists
each shim function's parameters: a Python test pins it to the real
signatures and a Rust test pins it to the Rust enum.
The lifecycle contract changes to match the Python @client wrapper:
- the driver emits CallEvent::Started before begin, so every host sees one
start time
- RequestContext carries the route-resolved api_key, so legacy pre_call and
post_call receive it, and post_call's additional_args match the Python OCR
path
- Passthrough and its re-aliasing are gone
- async deployment hooks always run, and the "no callbacks" shortcut that
skipped the logging payload is removed, as in the Python path
The OCR api_key is a SecretValue from the wire request onward, so Debug
output upstream of the callback contract cannot leak it.
host-python's RouteHost now classifies native failures once through
classify, and host ops return HostOpError. The OCR route host keeps main's
public errors by sending both through the existing Python map_failure.
Rebuild exception_type around text rules per provider family and one shared
status table. The mapper takes the context, an injected redactor and the
original failure, and returns a PublicError with the message, the real
upstream response and the debug text. Every divergence from the Python
mapper and every known gap is listed in the module header
Match Python on a standalone 429 with an unknown status and on Cohere's
rules for failures without a status. Drop python_repr and the unread
public_failures fixtures
Adds a Rust port of litellm_core_utils/exception_mapping_utils.exception_type
with its provider rule tables (OpenAI-compatible, Cohere, Vertex AI), the
secret redaction patterns from secret_redaction.py, and a Python repr helper
for messages that quote caller values.
The public failure shapes are pinned by golden JSON fixtures under
tests/test_litellm/rust_bridge/fixtures/public_failures, which the Python
side reads too once the bridge is wired to this module. Nothing calls the
port yet.
OCR transformations, BaseOcrConfig with its response and connection types,
the OCR error, and the HTTP pieces (custom_httpx: http_handler, transport,
media, llm_http_handler with OcrClient and the request/response handler)
now live in litellm-llms at their Python paths. Provider code no longer
reaches into the route: it gets the caller's hooks through a route-neutral
CallHooks trait that core implements over its host, and core dispatches to
llm_http_handler::ocr with the concrete config, the way Python calls
base_llm_http_handler.ocr(provider_config=...).
Core keeps the route: entrypoint, request types, credential fallback,
provider dispatch, the machine and hook glue. ocr/mod.rs no longer
re-exports anything, provider constants moved next to their only users,
and provider tests that drive the whole route moved to core's route test
files. Twenty-two of those were exact copies of tests already there and
were dropped; every one still runs once.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
litellm-providers becomes litellm-llms, mirroring litellm/llms. The Anthropic
batches, count_tokens, Messages stream iterator and chat stream handler, the
OpenAI Responses websocket config and its base trait (with URL and model
helpers), and the StreamTransformer base iterator now live at their Python
paths in that crate. Anthropic stream decode errors move with the iterator,
and core drops its duplicate OAuth prefix constant and the unused framing
dependency.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
litellm-types mirrors litellm/types (chat, Anthropic Messages and Responses
websocket data) and litellm-core-utils mirrors litellm/litellm_core_utils
(provider resolution, prompt factory, core helpers, call arguments). Route
request types move up to their core route module, the transform contracts
move into base_llm, and the three duplicated provider error enums become one
Error in base_llm/chat/transformation.rs, mirroring BaseLLMException.
The empty-text placeholder goes back to the value Python's factory.py uses;
the provider extraction had changed it to a single space.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Extracted from #41733 without the router loop, the cache machine layer, streaming, or the
error, timeout and route-pruning work that moved to #41745
litellm-callbacks holds the contract a native call and its host share: Machine, HostOp,
CallEvent, the in-process run loop, and Passthrough, which is built only by comparing the
caller's inputs with the body the route sends, so a route can never mark a key it rewrote.
litellm-host-python (formerly python-interop) owns the CPython driver and the Execution
handle, and litellm-callbacks-legacy is the @client wrapper as the native call sees it:
function_setup, the deployment hooks, pre_call and post_call, the success and failure fan-out
and the deferred proxy release. OCR is the one route on it, and the old core and bridge
lifecycles are gone
The passthrough rule is the structural fix for the bug #41719 patched in core and #41716
reworks: an inlined remote document no longer counts as the caller's value, so the legacy
adapter never hands the caller's URL back into the body. core/tests/ocr/passthrough.rs pins
it for every route and document source, including that unchanged values stay passthrough,
and callbacks-legacy/tests/payload.rs pins the adapter side with a real pre_call callback
Python OCR integration tests that only exercised core behavior now live as Rust tests, so
tests/test_litellm_rust keeps the cases that need the full Python stack
Delete litellm/ocr/input.py and the native _ocr_file_document, _ocr_upload_document
and _ocr_mime_type helpers. File documents now project to a typed OcrDocumentInput
and the core lifecycle reads local paths, encodes bytes and asks the host to read
file-like objects through a ReadDocument operation before the provider request
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(rust): count tiktoken cl100k_base admission tokens in Rust
The Rust admission token counter only had the Anthropic tokenizer, so every
other model (OpenAI gpt-4 family, Azure, Gemini, Bedrock non-Claude, Mistral)
tokenized with tiktoken on the Python inference worker.
Add an exact cl100k_base counter to litellm-token-counter: the vendored rank
file (base64 token / rank lines, the bytes Python's tiktoken uses) is parsed
into a byte-level BPE model and the cl100k split pattern is a handwritten
scanner over the shared Unicode classes, so no regex engine runs per request.
Both tokenizers share the message, tool and reply-priming accounting.
The PyO3 TokenCounter gains a from_cl100k_ranks constructor; Python reads the
rank file and passes it in, the way claude_json_str already works. The bridge
selects the counter through the same predicates litellm.token_counter uses
(huggingface_tokenizer_kind, openai_tokenizer_encoding), declines o200k_base,
downloaded HuggingFace and custom tokenizers to Python, and budget reservation
counts once per distinct tokenizer a request names.
The legacy gpt-3.5-turbo-0301 message accounting (4 per message, -1 per name)
stays in Python: the selector declines it through the predicate token_counter
itself uses.
* feat(rust): count tiktoken o200k_base admission tokens in Rust (#40794)
Add a handwritten o200k_base split scanner and TokenCounter::from_o200k_ranks
next to the cl100k_base counter, sharing MergeRanks and the request
accounting. The Python bridge selects it when openai_tokenizer_encoding
names o200k_base, so gpt-4o, gpt-4.1, gpt-5, o1/o3/o4 and chatgpt-4o
requests stop tokenizing on the Python worker under LITELLM_RUST=true
Co-authored-by: yassin <yassin@berri.ai>
---------
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: devin-ai-integration[bot] <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* feat(rust_bridge): count budget-check input tokens in Rust on all LLM routes
Rust counts input tokens from the raw JSON body with the GIL released inside the existing budget reservation, covering every LLM route the auth dependency guards. It only fires for models on the Anthropic tokenizer when a budget is set, and Python counts whenever Rust is off, missing, or declines a body shape.
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* perf(rust): count byte-level BPE tokens without the GPT-2 split regex (#40594)
The oniguruma run of the ByteLevel pre-tokenizer regex is about 90% of
encode_fast on a 100k token body (100 ms of the ~110 ms Rust admission
count in the gateway pod). A hand-written scanner that yields the same
pieces, then feeds the model directly, counts the same text in 10 ms.
It only engages for tokenizers with the Anthropic shape (optional NFKC,
ByteLevel without prefix space, no post-processor) and falls back to the
full encoder when the text contains an added token. Parity with
encode_fast is tested on random texts, the pieces are compared with the
real pre-tokenizer, and the \p{L}/\p{N}/\s tables are checked against
oniguruma for every code point.
NFKC runs through unicode-normalization-alignments, the crate and
Unicode tables NormalizedString::nfkc already uses, so the fast path
normalizes exactly what the full encoder would. Using the newer
unicode-normalization crate changed the count for 171 code points that
gained compatibility decompositions after Unicode 9 (U+32FF, U+A7F1..).
The fast normalizer is compared with the tokenizer's for every scalar
value and on random texts.
The scanner is built without mutable state: byte_char and mapped_len replace the const table builders and the reusable mapped buffer, and iter::successors replaces the stateful piece iterator. byte_chars_match_the_byte_level_alphabet checks the byte mapping against ByteLevel for every scalar value.
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(rust_bridge): bound concurrent token-count encodes and share the Anthropic tokenizer predicate
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
---------
Co-authored-by: yassin <yassin@berri.ai>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Build one ClientConfig that names ring and loads the native roots once, and hand it to every tokio-tungstenite dial as its connector instead of installing a process-wide default from the dial path. Each of the three dial sites gets a wss:// test that reproduces the panic if its connector is dropped.
The gateway's dependency graph turns on two rustls crypto backends at once:
reqwest's rustls-tls pulls in ring, and litellm-core's bedrock-auth pulls in
aws-lc-rs through aws-config. rustls 0.23 refuses to guess between them, so
ClientConfig::builder panics, and that is exactly how tokio-tungstenite builds
its TLS config. Every outbound WebSocket dial killed its tokio worker and the
client saw the socket vanish with no close frame.
reqwest and the AWS SDK both pick a provider explicitly, so only the tungstenite
path was affected. Route all three dial sites through one helper that installs
ring once per process before connecting.
* refactor(python-bridge): split non-streaming bridge modules
* refactor(python-bridge): bring shared function tracing into route layer
* feat(dev): list Python route functions and call sites
* feat(dev): list Rust route functions and call sites
* docs(dev): record OCR parity gaps across Python and Rust
* feat(dev): list executed SDK calls with runtime tracing
* feat(dev): report Python vs Rust SDK pipeline steps in one CLI
* feat(dev): side-by-side pipeline step report in compare CLI
* fix(dev): drop invalid Final annotations in compare cell loop
* feat(dev): blue python-only and yellow rust-only steps in compare CLI
* feat(dev): vertical layout with section spacing in compare CLI
* fix(dev): validate SDK trace stages across sync and async routes
* refactor(rust): align SDK route call structure with Python
* refactor(python-bridge): share sync and async route call wrappers
* refactor(dev): split compare CLI into fixtures, runtime, and report modules
* fix(ci): run SDK trace tests and satisfy test lint
