* fix(logging): warn when drop_params drops a requested reasoning level on the remaining paths
* fix(logging): keep guardrail and token-count reads of a request from logging drop warnings
Only the real Anthropic-messages adapter request reports a dropped thinking budget. Guardrail,
shadow-eval and token-count translations of the same request now drop it silently, so one request
logs one warning. The 422 retry also no longer hashes each loc entry, so a list inside loc cannot
raise TypeError.
* fix(bedrock): keep the DeepSeek R1 Converse reasoning_effort drop at debug level
Only allowed_openai_params reaches that branch, and it puts reasoning_effort back after the provider mapping, so a warning there claimed a drop that never happened
* fix(logging): warn on Gemini non-integer budget drops and keep the auto-router baseline silent
Gemini 2.x now logs the drop of a non-integer thinking budget. The auto-router
savings baseline builds a body it never sends, so it no longer warns. Logged
values are capped with reprlib, Azure AI marks only its drop_params retry as
gated, and Bedrock Chat Completions names the model without its route prefix.
* fix(logging): warn on the Gemini 3, Magistral, Ollama, Fireworks and DeepSeek ARN reasoning drops
Gemini 3 and later now log a dropped thinking budget, Magistral logs the
level it swaps for a reasoning prompt, Ollama logs a level it maps to
think off, Fireworks logs chat_template_kwargs effort keys dropped for a
model the map does not list as reasoning, and DeepSeek on Bedrock logs a
drop when the model is addressed by an ARN that advertises the param.
* fix(logging): warn on the remaining Ollama, DeepSeek and Tencent reasoning drops
The ollama/ completion route now shares the chat route's think mapping, so
a level it turns off logs the same warning. DeepSeek warns when it drops
thinking.budget_tokens, and Tencent warns when an adaptive-only model gets a
non-integer budget. Magistral no longer warns on low, medium, high or
enabled thinking, the values its reasoning prompt stands in for. The Gemini 3
budget warning no longer claims the model uses its default level.
* fix(reasoning): warn when Claude drops a non-string reasoning_effort
Claude chat and native /v1/messages dropped a reasoning_effort like 5 or
{"effort": 5} with no log line. Both now log one warn-only WARNING. A
Magistral thinking.type sent as a list no longer raises TypeError.
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(anthropic): send /v1/messages PDF documents to OpenAI-shaped providers as file parts
* refactor(anthropic): hold the chat completions document change for a later commit
* fix(anthropic): send /v1/messages PDFs as file parts and keep file parts on azure_ai
* fix(snowflake): turn file parts into document blocks for Cortex Claude
* fix(prompt_security): sanitize chat file parts that carry file_data
* fix: answer 400 or drop PDFs for models that cannot read them
Models whose model_info or cost map entry sets supports_pdf_input to
false, and Ollama, now get the PDF dropped under drop_params and a 400
from litellm without it. GigaChat uploads file parts, SAP keeps sending
them as image_url data URLs, azure_ai passes dict content through, and
annotations other than url_citation move to provider_specific_fields
instead of failing the response.
* fix(router): scope supports_pdf_input to its deployment and keep provider annotation keys
Mark the azure_ai chat models in the cost map that cannot read PDFs, so drop_params drops the PDF and
litellm answers its own 400 without it. Keep url_citation annotations whole, move only typed provider
annotations to provider_specific_fields, and split them the same way when a stream is rebuilt.
* fix(vertex_ai): send PDF file parts to Vertex partner models as image_url
Vertex AI's OpenAI-compatible partner endpoint rejects the chat `file` part, so PDFs from /v1/messages
reach those models as the image_url data URL they took before. Mark native DeepSeek chat models as
unable to read PDFs, and treat a file part as a PDF by its format or filename when it has no data URL.
* fix(cost-map): leave native DeepSeek PDF support unset
/v1/messages reaches native DeepSeek through its own Anthropic endpoint, so the marks never applied there
and would only change chat completions, which this PR does not otherwise touch.
* fix(main): drop a user turn that held only a PDF under drop_params
Dropping the PDF from a PDF-only user turn left an empty content list, which
Foundry and OpenAI-shaped providers reject with a 400, so drop_params still
failed for that request. The emptied user turn is now removed.
* fix: read OCI PDFs, gate deployment base models, and stop empty drops
OCI generic chat sends file parts as image data URLs again, so OCI Gemini
keeps reading PDFs from /v1/messages and chat file parts.
The PDF gate now reads model_info.base_model, drops PDFs under drop_params
for azure_ai deployments that never declared PDF support (the old flattening
behavior), and answers 400 when dropping the PDF leaves no user message.
The cost map marks the Vertex partner text models that a live probe showed
answering without reading the PDF.
* test(integration): cover the PDF input gate, messages PDF file parts and provider annotations
Wire cells for the supports_pdf_input check on chat, chat streaming, /v1/messages and the Responses bridge, its model_info, base_model, cost map and Ollama sources, drop_params at deployment and request level, azure_ai file parts, sibling deployment isolation, Anthropic SDK PDFs reaching azure as titled file parts, Gemini and Bedrock document controls, Prompt Security sanitizing a /v1/messages PDF, and OpenRouter file annotations live, cached and streamed
* test(integration): cover Snowflake Claude and SAP in the messages PDF wire cells
* fix(azure_ai): flatten non-PDF file parts to text as before and cover the GigaChat PDF upload
* fix(main): PDF check reads the deployment's top-level base_model
* fix(main): keep roles alternating after drop_params removes a PDF-only turn
When ensure_alternating_roles is set, re-run role normalization on the messages left after the PDF check drops a turn, so two assistant turns never end up next to each other
* test: type the PDF and annotation tests the PR added
* test: type the GigaChat, SAP and Snowflake PDF tests
* fix(oci): skip non-function tools and gate reasoning_effort on models that reject it
Fixes#31449.
Two OCI GENERIC request-building defects that made Grok-on-OCI unusable
for tool-using coding-agent clients (Codex over the Responses API, Claude
Code over the Anthropic Messages API):
1. `adapt_tool_definition_to_oci_standard` raised `OCIError("OCI only
supports function tools")` for any tool whose type is not "function",
aborting the whole request when a client mixed a built-in/server tool
in with its function tools. Non-function tools are now skipped with a
warning; if none remain, `tools`/`toolChoice` are omitted from the
request instead of sending an empty array.
2. The GENERIC param map forwarded `reasoning_effort` to every non-Cohere
model, but OCI rejects it for all served xAI Grok models
(`Model grok-4.20 does not support parameter reasoningEffort`) and for
OpenAI's non-reasoning models (`Unrecognized request argument supplied:
reasoning_effort` on gpt-4o / gpt-4.1); gpt-5, the o-series, gpt-oss-*
and Meta/Google models accept it. `_model_supports_reasoning_effort`
encodes that, `get_supported_openai_params` stops advertising the param
for those models, and `map_openai_params` follows the standard
unsupported-param contract (dropped under drop_params, clear error
otherwise) so `drop_params` / `additional_drop_params` now work as
documented instead of the 400 surfacing from the service.
Behaviour verified against OCI GenAI in us-chicago-1 (2026-09-11) per model.
The two existing reasoning_effort normalisation tests move from a Grok
model to openai.gpt-5, which is the case they exercise. 21 new tests; the
OCI suite is 406 passed.
* fix(oci): drive reasoning_effort gating from the model catalog and drop tool_choice for skipped tools
Review follow-ups on #40732:
- `_model_supports_reasoning_effort` now reads the `supports_reasoning` flag
of the model's `oci/` catalog entry through `get_model_info` instead of
hardcoding xAI / gpt-oss branches. Catalogued models without the flag
(xAI Grok, Meta Llama) no longer receive `reasoningEffort`; models absent
from the catalog keep the historical pass-through.
- Catalog: flag `oci/google.gemini-2.5-{flash,pro,flash-lite}` as reasoning
models and add `oci/openai.gpt-oss-120b` / `oci/openai.gpt-oss-20b`
(pricing from Oracle's public price list, 128K context per OCI docs).
- `_model_uses_max_completion_tokens` routes on the `openai.*` prefix only.
OCI-hosted Gemini accepts `maxCompletionTokens` but ignores it (the output
cap silently disappears) and Llama rejects it with 400, so the catalog's
reasoning flag must not drive that switch.
- After tool adaptation, a `FUNCTION` tool_choice naming a tool that was
skipped (built-in / server tools) is dropped with a warning instead of
being sent to OCI, which rejects the unmatched choice.
Verified live against OCI GenAI (us-chicago-1): Grok with mixed tools plus a
forced built-in now completes and still calls the function tool; Gemini and
gpt-oss forward reasoningEffort with maxTokens honoured; Llama drops it under
drop_params; gpt-5 keeps maxCompletionTokens.
* style(oci): use an immutable set for the tool-name lookup
Keeps the type-discipline gate (LIT002, mutable collections) within its
budget; the lookup is read-only.
* fix(oci): fail closed when a forced tool_choice names a tool OCI will not receive
Review follow-ups on #40732:
- When tool_choice forces a function that is not among the adapted tools
(a skipped built-in or a misspelled name), send `toolChoice: NONE` instead
of removing the choice. Falling back to the service default would let the
model call any other supplied function even though the caller forced a
specific one, which an agent processing untrusted content must not do.
- Move the #31449 regression tests into the mapped test module
(`test_oci_chat_transformation.py`) instead of a separate file.
Verified live against OCI GenAI: Grok and Llama with a forced skipped
built-in now complete with no tool call; a forced kept function is still
honoured.
* test(oci): point reasoning_effort comments at the in-module gating tests
The referenced module was folded into this file.
* fix(oci): drop non-function tools only under drop_params and gate reasoning_effort on declared levels
Non-function tools now follow the unsupported-param contract: a 400 naming
drop_params without it, and dropped with a warning under it, with a forced
dropped tool turning tool calls off. reasoning_effort is gated on the model's
reasoning_effort_levels catalog entry, so OCI Llama keeps forwarding it and the
Grok 4.20 models OCI serves, now in the catalog with their Oracle prices, stop
sending a param the service rejects
* fix(oci): gate reasoning_effort on oci/xai.grok-4.20, which rejects it
* fix(oci): disable tool calls when tool_choice forces a dropped custom tool by name
* fix(oci): drop tool_choice that forces a dropped tool and keep a kept function's name
* fix(oci): keep Gemini 2.5 Flash Lite unflagged for reasoning so released proxies keep its max_tokens cap
* fix(oci): answer 400 when a request depends on a dropped tool and leave Gemini max_tokens routing to its own PR
Under drop_params, non-function tools still drop when function tools remain and
tool_choice does not force a dropped tool. A request whose every tool is dropped,
or whose tool_choice forces one, now answers 400 instead of a tool-less reply the
model can fill with invented results, or a swap to another tool.
The maxTokens routing change for OCI Gemini goes back to base, since it is
outside this fix and an open PR carries it.
---------
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
* fix(params): validate stream_chunk_size once and carry it as typed control options
Checks stream_chunk_size at the top of completion() and acompletion(), accepts
digit strings, returns a 400 naming the param unless drop_params is set, and
stores the checked value under _litellm_control. Bedrock Converse and Invoke
read it from litellm_params; the Bedrock-only checker and the dead Invoke pops
are gone. Owned-kwarg filtering now runs through one helper everywhere.
Refs LIT-8317
* test(bedrock): drop tests for the removed stream_chunk_size_from helper
Refs LIT-8317
* fix(params): check stream_chunk_size before the MCP gateway branch
Refs LIT-8317
* fix(params): return assert_never in the exhaustive control-options match
Refs LIT-8317
* fix(params): address council review of the control options change
Read all_litellm_params live so names registered after import stay
LiteLLM-owned, make litellm_params a required keyword on the stream
wrapper hooks, give digit strings and ints the same 18-digit range,
share the default-chunking test table, test the Responses bridge through
litellm.responses, and revert formatting-only churn in existing tests.
Refs LIT-8317
* fix(params): address the second council review of control options
Keep the Responses bridge on its original all_litellm_params forwarding,
narrow _int_from_decimal_string inline so it type-checks, bound nested
huge ints in the error message, store _litellm_control only when a value
is set, simplify the parser to its single field, drop the one-caller
wrapper, and tighten the tests.
Refs LIT-8317
* fix(params): keep the 18-digit length check on stream_chunk_size strings
A 19-character string with leading zeros such as 0000000000000000001 would
otherwise pass as 1, although the rule and the error message say at most
18 digits.
Refs LIT-8317
* test(params): tidy control options tests after council sign-off
Move the Responses bridge test into the existing bridge test file, drop the
rebind test that pinned an implementation detail, assert through
stored_control_options instead of the storage key, and cover
drop_params="true" through Bedrock streaming.
Refs LIT-8317
* test(params): wrap a chunking test row that went past 120 characters
Refs LIT-8317
