On /v1/messages, AnthropicStreamWrapper synthesizes the content_block_start for
the first content block, queues it, then hits a bare `continue` when that same
upstream chunk's translated delta is empty. The queue is only drained at the top
of the next __next__ / __anext__, so the queued content_block_start waits for a
further upstream chunk to arrive.
An empty delta on the opening chunk is the normal tool-call shape: Bedrock
Converse's contentBlockStart carries the tool id and name with no arguments, and
OpenAI-format streams send arguments: "" on the chunk that names the function.
So a client learns a tool call started one upstream event late, and when the
provider delivers argument fragments as a trailing burst it sees nothing at all
after message_start for the whole generation.
Flush the queued event before continuing, in both the sync and async paths. The
sibling block-transition path already returns from the queue, so only the
first-block-open case changed.
* fix(model_map): flag native structured outputs on Anthropic-direct claude-sonnet-5 and claude-haiku-4-5
The Bedrock twins of both models already carry
supports_native_structured_output, but the Anthropic-direct entries do not,
so response_format requests to anthropic/claude-sonnet-5 and
anthropic/claude-haiku-4-5 fall back to the json_tool_call emulation and
inherit its nested-envelope failure modes (#8898) despite the API supporting
output_format natively.
Verified live against the Anthropic API on 2026-08-05: both models accept
output_format (structured outputs beta header) and return exact schema
instances, including a large nested production schema validated with
pydantic. Same two lines applied to the bundled backup map.
* fix(model_map): cover the versioned claude-haiku-4-5-20251001 alias
Exact-match capability lookup of anthropic/claude-haiku-4-5-20251001
resolved the versioned entry, which lacked the flag, so response_format
for that identifier still took the tool-emulation path. Flag it in both
the root and bundled maps, matching its unversioned alias.
* fix(anthropic): bound $defs inlining in output_format with the shared schema-bomb budget
map_response_format_to_anthropic_output_format called unpack_defs with
no max_inlined_bytes, so an authenticated caller could send a compact
schema whose repeated $refs expand without bound before reaching the
provider. Reuse the existing 10MB inlining budget (renamed from
_LEGACY_DEFS_MAX_INLINED_BYTES to DEFS_MAX_INLINED_BYTES now that two
call sites share it); overflow raises ValueError instead of
materialising the expansion.
Regression tests: a compact schema bomb is rejected, a normal $defs
schema still resolves; the bomb test fails when the bound is removed.
* chore: retrigger CI (benchmarks job flaked on a PyPI download timeout)
---------
Co-authored-by: Anmol Jaiswal <anmolg1997@users.noreply.github.com>
Images nested inside an Anthropic `tool_result` block were dropped when the
request was adapted for an OpenAI-compatible provider, because the OpenAI tool
message shape only carried text. Hoist those images out of the tool result and
into a following user message so the model can still see them, and widen the
tool message content type to accept image parts.
Anthropic's Models API declares max_input_tokens and max_tokens as nullable, not
optional, and the live vendor endpoint returns both keys on every entry. The
merged Anthropic-native listing dropped either key whenever LiteLLM could not
resolve a limit, so a client validating against a nullable-but-required schema
saw a malformed entry for any model the cost map does not know.
The two new `translate_tools_to_responses_api` calls carried
`# type: ignore[arg-type]`, which CLAUDE.md bans as LIT009: pyrightconfig.json
sets enableTypeIgnoreComments to false, so the comment silently does nothing and
the reportArgumentType error stands. Annotating the fixtures as
list[AllAnthropicToolsValues] makes both calls check clean with no suppression
at all.
Translating Anthropic tools left the outbound function-tool `strict` unset,
which the Responses API does not read as non-strict. OpenAI's function-calling
docs say strict mode requires every field in `properties` to be marked
required, and with `strict` omitted the schema gets normalized to satisfy that
instead of being rejected. What users see is a tool whose `required` lists
every property, so models fill optional Anthropic tool arguments with empty
values. Send `strict` explicitly so an unset value stays non-strict and an
explicit `strict: true` still reaches the provider
On the Chat Completions adapter, `strict` was also missing from
`mapped_tool_params`, so a tool-level `strict` was merged into the OpenAI
function `parameters` schema (mutating the caller's `input_schema` along the
way) instead of being set on the function. Map it to `function.strict` and
leave it unset when the caller omits it, since Chat Completions already
defaults to non-strict
* feat(proxy): serve Anthropic-native /v1/models for Claude Code gateway discovery
* refactor(proxy): move Anthropic model-list formatter into llms/anthropic/common_utils
* fix(proxy): make model_list request param optional for direct callers
* style: apply ruff format to changed lines
* style: satisfy ruff strict-rule budget (UP006, I001)
* style: satisfy type-discipline budget (LIT002 mutable-ok, LIT009 pyright ignore)
* style: satisfy LIT001/LIT010 and drop explanatory comment per contributor rules
* fix(proxy): translate team model names in the Anthropic /v1/models response
* ci: trigger buildkite status report
* feat(proxy): carry token limits into the Anthropic-native /v1/models entries
* fix(proxy): cast the injected request so the anthropic-version guard is a real comparison
* fix(proxy): explain the model listing casts so the type-discipline gate passes
---------
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
Python keeps only the last binding for a name, so when a file defines the same
test twice the earlier one is unreachable. pytest cannot collect a function that
no longer exists, so nothing reports it and the file still looks like it covers
the scenario.
These ten are cases where the two definitions have different bodies, meaning a
real test was replaced rather than duplicated. Each is renamed to say what it
actually covers, which makes it reachable again:
- test_gemini_frequency_penalty: the dead copy checks the parameter is listed in
get_supported_openai_params for vertex_ai; the survivor checks get_optional_params
maps a value for gemini. Different function and different provider.
- test_async_log_success_event_adds_to_queue and the failure variant: the dead
copies run without mocking asyncio.create_task, so they exercise the real task
path the survivors mock out.
- test_async_send_batch_triggers_tasks: the dead copy asserts send is not awaited
directly; the survivor asserts create_task was called.
- test_model_id_in_required_metrics: the dead copy checks the model_id label on
twelve further metrics the survivor dropped.
- test_anthropic_messages_pt_file_block_preserves_cache_control: the dead copy
passes model and llm_provider explicitly and uses real base64 PDF content.
- test_translate_streaming_openai_chunk_to_anthropic_with_thinking: the dead copy
covers thinking_delta; the survivor covers signature_delta.
- test_client_initialization and test_client_without_api_key: the dead copies
assert the resource clients are wired with the right base URL and key; the
survivors only construct the object.
- test_client_initialization_strips_trailing_slash: the dead copy constructs
ModelsManagementClient directly rather than going through Client.
Verification: collecting the seven touched files gives 401 node IDs before and
411 after, the ten new names and nothing else, with nothing lost. All ten pass.
Running the touched files in full gives 299 passed, and test_optional_params.py
goes from 111 passed to 112.
Two further shadowed definitions were left alone rather than renamed: the dead
copies of test_prompt_caching and test_cost_calculator_with_base_model_with_router
have no assertions at all, one being a bare pass and the other a lone import, so
restoring them would add tests that cannot fail.
Claude Code drives Opus 4.7 with thinking {"type": "adaptive"} plus
output_config {"effort": "max"}. The anthropic-to-openai adapter
forwarded thinking verbatim for Claude models but dropped output_config,
and Bedrock Converse streams zero reasoningContent blocks for adaptive
thinking without an effort tier. Forward the effort subset of
output_config for Bedrock targets, accept it in the converse supported
params, and map it with the model's effort ceiling applied. Re-enable
the skipped e2e compat cell that catches this
The iterations branch in AnthropicConfig.calculate_usage summed
cache_creation_input_tokens but never aggregated the per-iteration
cache_creation 5m/1h breakdown, leaving cache_creation_token_details
as None. As a result all cache-creation tokens fell back to the flat
5m write rate, underbilling 1h cache writes by up to 2x.
Aggregate the ephemeral_5m/ephemeral_1h split across iterations so 1h
writes are priced at the 1h rate.
Fixes LIT-4868
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(websearch): restore snippet text in native web_search_tool_result blocks (LIT-5315)
The build_web_search_tool_result_block method copied url/title/page_age but
hardcoded encrypted_content to empty string, never reading SearchResult.snippet.
This left every native block content-free, forcing clients to web_fetch each
result to recover evidence—the reported symptom.
The Anthropic spec carries page text only in encrypted_content (an opaque
server-issued blob we cannot mint), so snippet is emitted as an additive key
alongside the spec fields. encrypted_content stays empty rather than holding
plaintext, which would assert encryption semantics that don't hold.
The anthropic SDK's BaseModel sets extra='allow', so the additive snippet key
survives SDK parsing. litellm has no typed model for web_search_result at all,
so nothing drops it internally. Turn-2 replay behavior is unaffected: the
empty encrypted_content already exists today.
Tests:
- Updated test_shape_with_results to assert snippet present
- Added test_snippet_carried_for_every_result to cover multi-result ordering
- Added test_missing_snippet_degrades_to_empty_string for edge case
- Mutation check: reverting source-only yields 3 test failures, restored to 117 passed
Fixes: LIT-5315
Co-Authored-By: Claude <noreply@anthropic.com>
* fix(websearch): make synthesized web_search blocks replayable by native clients
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
* fix(websearch): flatten a resultless replayed search block so Bedrock accepts the next turn
The flatten added for LIT-5315 bails when the replayed web_search_tool_result
carries an empty content list, but that is exactly what the interceptor emits
when a search legitimately returns nothing and when a search raises. The block
survived into the outbound body, Bedrock rejected the tag, and the conversation
died on the following turn just as it did before the flatten existed.
An empty content list has no encrypted_content to respect and no evidence to
preserve, so it flattens safely, and its paired server_tool_use goes with it.
The rendered text now says so explicitly rather than emitting a bare header.
Adds the multi-turn replay coverage that existed nowhere: the outbound Bedrock
invoke body is asserted free of both block types, parametrized over the
results-present and resultless cases, and built from the interceptor's own
builder so the fixture cannot drift from what it emits.
Resolves LIT-5320
* test(websearch): pin flatten idempotency for the agentic-loop re-entry
The agentic loop re-enters the same /v1/messages entry point for its follow-up
call and hands it the original client history, so the flatten runs again over
already-flattened messages once per iteration. Bedrock always takes that path,
since its config reports web search as natively handled and the short-circuit
is skipped.
A pass that appended the rendered text instead of replacing the block would
duplicate the evidence on every iteration and re-ship the unsupported tag, and
no existing single-pass test sees it. Mutation checked: keeping the original
block alongside the rendered text fails this test on its own.
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
OpenAI emits a reasoning output item on every reasoning turn, but only emits
reasoning_summary_text deltas when a summary was requested and actually
produced. The Anthropic /v1/messages Responses stream adapter opened the
thinking content block eagerly on response.output_item.added, so a summary-less
reasoning item surfaced as {"type": "thinking", "thinking": ""}. Clients persist
that in their session transcript and replay it on the next turn; an Anthropic
model then rejects the request with "each thinking block must contain thinking",
which is what users hit when a resumed session falls back to the default
Anthropic model.
Open the thinking block on the first non-empty summary delta instead, and only
emit content_block_stop for items that actually have an open block.
Gate the OpenAI handler's tools forwarding behind scan_only_tool_results,
matching the Anthropic handler, so a tool-results-only scan can no longer
evaluate or rewrite trusted function definitions.
When a guardrail returns a replacement structured_messages list, substitute
the returned messages back into the positions their scoped originals came
from instead of installing the scoped list as the whole conversation, so
out-of-scope messages (system prompt, prior turns) survive redaction on
both the OpenAI and Anthropic paths.
Guardrails silently skipped three surfaces on the Anthropic Messages
path, so an agent loop driven by /v1/messages ran unguarded:
- The Anthropic input translation never walked tool_result blocks, so
content returned by a local tool (a curl, a file read, an MCP call)
reached the model unscanned in both the string and list content
shapes, images inside a tool_result included.
- tool_permission only understood ModelResponse, so an Anthropic
non-streaming response or a raw SSE stream carrying tool_use blocks
passed through with no rule ever evaluated.
- ContentFilterGuardrail scanned inputs["texts"] but never
inputs["tool_calls"], so the arguments a model proposes for a tool
call went unchecked.
Tool call arguments are parsed as JSON before filtering so a MASK
action rewrites the value and leaves the payload valid JSON; non-JSON
arguments fall back to scanning the raw string. Denied tool_use blocks
are dropped from the Anthropic content array and replaced with a text
block, and stop_reason resets to end_turn when nothing tool-shaped
survives.
* fix(anthropic): split mixed reasoning stream chunks
* style: use builtin generic annotation
* fix(anthropic): split mixed stream chunks by payload kind
The mixed-chunk split cleared only the fields it knew about on each
deep-copied piece, so any other payload riding the chunk survived on
both pieces: tool_calls were emitted as two tool_use blocks with the
same id, thinking_blocks on the text piece emitted duplicated thinking
into a text block while dropping the answer text, and chunks whose
reasoning arrived only as thinking_blocks never split at all
Rebuild each piece's delta from scratch with exactly one payload kind
(reasoning, text, tool calls), ordered to match native Anthropic block
order. Fresh Delta construction keeps unset attributes deleted, which
matters because the translators branch on hasattr, and prevents future
Delta fields from riding along on every piece
* fix(anthropic): keep continuation and multi-choice chunks unsplit, emit signature-less thinking once
Adversarial verification against the merge-base found three shapes where
the payload-kind split changed behavior beyond its target: a mixed chunk
carrying a tool argument continuation was torn into a truncated block
plus a fabricated one, a multi-choice chunk lost its secondary choices'
payload, and a signature-less thinking_blocks piece inherited the
non-empty block start body so accumulators collected the thinking twice
Continuation and multi-choice chunks now pass through the splitter
untouched, matching the merge-base byte for byte, and signature-less
thinking_blocks pieces are normalized to reasoning_content so the block
start opens empty and the thinking text is emitted exactly once
---------
Co-authored-by: Napuh <naamanynadiemas@gmail.com>
