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feat(messages): apply prompt caching injection on rust

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narmstrong-berry 2026-11-10 20:05:34 +00:00
parent f0d234c4c6
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22 changed files with 539 additions and 80 deletions
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2
litellm-rust/crates/inference-messages/src/handler.rs
View file

@ -129,7 +129,7 @@ async fn provider_call(
let sanitized = config.shape_request(
MessagesRequest { model, ..body },
shaping.settings.reasoning_auto_summary,
shaping.settings.shape_options(),
)?;
let transform_context =
MessagesTransformContext::new(shaping.capabilities, shaping.settings.drop_params);

17
litellm-rust/crates/inference-messages/src/types.rs
View file

@ -2,7 +2,10 @@ use std::time::Duration;
use bytes::Bytes;
use litellm_host::call::CallOutput;
use litellm_llms::{ErrorDetail, base_llm::messages::context::MessagesModelCapabilities};
use litellm_llms::{
ErrorDetail,
base_llm::messages::context::{MessagesModelCapabilities, MessagesShapeOptions},
};
use litellm_llms_types::{
formats::messages::{MessagesRequest, MessagesResponse},
headers::ProviderSpecificHeaders,
@ -71,9 +74,20 @@ pub struct MessagesSettings {
pub additional_drop_params: Vec<String>,
#[serde(default)]
pub request_timeout: Option<f64>,
/// The host already normalized the messages, as Python's handler does before it injects
/// prompt-cache breakpoints.
#[serde(default)]
pub presanitized: bool,
}
impl MessagesSettings {
pub fn shape_options(&self) -> MessagesShapeOptions {
MessagesShapeOptions {
reasoning_auto_summary: self.reasoning_auto_summary,
presanitized: self.presanitized,
}
}
pub fn request_timeout(&self) -> Option<Duration> {
self.request_timeout
.and_then(|secs| Duration::try_from_secs_f64(secs).ok())
@ -148,6 +162,7 @@ mod tests {
reasoning_auto_summary: true,
additional_drop_params: vec!["metadata.user_id".to_string(), "thinking".to_string()],
request_timeout: Some(1800.0),
presanitized: false,
},
capabilities: MessagesModelCapabilities {
supports_reasoning: true,

42
litellm-rust/crates/llms/src/anthropic/messages/handler.rs
View file

@ -13,14 +13,19 @@ use crate::{
flatten_unencrypted_web_search_results, sanitize_tool_use_ids, strip_empty_content_blocks,
strip_provider_specific_fields,
},
base_llm::messages::context::MessagesShapeOptions,
};
pub fn shape_anthropic_messages_request(
request: MessagesRequest,
reasoning_auto_summary: bool,
options: MessagesShapeOptions,
) -> Result<MessagesRequest, Error> {
Ok(MessagesRequest {
messages: sanitize_anthropic_messages(request.messages),
messages: if options.presanitized {
strip_provider_specific_fields(request.messages)
} else {
sanitize_anthropic_messages(request.messages)
},
params: MessagesOptionalParams {
metadata: request
.params
@ -28,7 +33,10 @@ pub fn shape_anthropic_messages_request(
.as_ref()
.map(validate_anthropic_api_metadata)
.transpose()?,
thinking: with_reasoning_auto_summary(request.params.thinking, reasoning_auto_summary),
thinking: with_reasoning_auto_summary(
request.params.thinking,
options.reasoning_auto_summary,
),
..request.params
},
..request
@ -299,7 +307,10 @@ mod tests {
"thinking": {"type": "enabled", "budget_tokens": 1024},
"safeguards": [{"type": "dangerous_tool_use"}]
})),
true,
MessagesShapeOptions {
reasoning_auto_summary: true,
presanitized: false,
},
)
.unwrap();
assert_eq!(
@ -315,4 +326,27 @@ mod tests {
})
);
}
#[test]
fn presanitized_shaping_keeps_blocks_and_strips_only_provider_fields() {
let messages = json!([{"role": "user", "content": [
{"type": "text", "text": " ", "cache_control": {"type": "ephemeral"}},
{"type": "tool_result", "tool_use_id": "functions.Bash:0", "content": "ok", "provider_specific_fields": {"x": 1}}
]}]);
let sanitized = shape_anthropic_messages_request(
request(json!({"model": "m", "messages": messages})),
MessagesShapeOptions {
reasoning_auto_summary: false,
presanitized: true,
},
)
.unwrap();
assert_eq!(
serde_json::to_value(sanitized).unwrap(),
json!({"model": "m", "messages": [{"role": "user", "content": [
{"type": "text", "text": " ", "cache_control": {"type": "ephemeral"}},
{"type": "tool_result", "tool_use_id": "functions.Bash:0", "content": "ok"}
]}]})
);
}
}

6
litellm-rust/crates/llms/src/anthropic/messages/transformation.rs
View file

@ -11,7 +11,7 @@ use litellm_router_types::LitellmParams;
use serde_json::{Map, Value, json};
use super::{handler::shape_anthropic_messages_request, thinking::translate_thinking};
use crate::base_llm::messages::context::MessagesTransformContext;
use crate::base_llm::messages::context::{MessagesShapeOptions, MessagesTransformContext};
use crate::{
Error,
anthropic::common_utils::{
@ -35,9 +35,9 @@ impl BaseMessagesConfig for AnthropicMessagesConfig {
fn shape_request(
&self,
request: MessagesRequest,
reasoning_auto_summary: bool,
options: MessagesShapeOptions,
) -> Result<MessagesRequest, Error> {
shape_anthropic_messages_request(request, reasoning_auto_summary)
shape_anthropic_messages_request(request, options)
}
fn get_complete_url(

6
litellm-rust/crates/llms/src/azure_ai/messages/transformation.rs
View file

@ -21,7 +21,7 @@ use crate::{
base_llm::{
auth::{AuthScheme, Headers, ValidatedEnvironment},
messages::{
context::MessagesTransformContext,
context::{MessagesShapeOptions, MessagesTransformContext},
normalization::{normalize_system_role_messages, strip_cache_control_scope},
transformation::BaseMessagesConfig,
},
@ -39,9 +39,9 @@ impl BaseMessagesConfig for AzureAnthropicMessagesConfig {
fn shape_request(
&self,
request: MessagesRequest,
reasoning_auto_summary: bool,
options: MessagesShapeOptions,
) -> Result<MessagesRequest, Error> {
shape_anthropic_messages_request(request, reasoning_auto_summary)
shape_anthropic_messages_request(request, options)
}
fn get_complete_url(

10
litellm-rust/crates/llms/src/base_llm/messages/context.rs
View file

@ -23,6 +23,16 @@ impl SupportedEffortTiers {
}
}
/// What an adapter's `shape_request` reads from the call's settings.
#[derive(Clone, Copy, Debug, Default, PartialEq, Eq)]
pub struct MessagesShapeOptions {
/// Marks active thinking as summarized, as Python's `is_reasoning_auto_summary_enabled` asks.
pub reasoning_auto_summary: bool,
/// The host already normalized the messages, as Python's handler does before it injects
/// prompt-cache breakpoints, so shaping only strips provider-specific fields.
pub presanitized: bool,
}
#[derive(Clone, Copy, Debug, PartialEq, Eq, Serialize, Deserialize)]
pub struct MessagesModelCapabilities {
#[serde(default)]

19
litellm-rust/crates/llms/src/base_llm/messages/transformation.rs
View file

@ -4,7 +4,7 @@ use litellm_llms_types::formats::messages::{
use litellm_router_types::LitellmParams;
use serde_json::Value;
use super::context::MessagesTransformContext;
use super::context::{MessagesShapeOptions, MessagesTransformContext};
pub use crate::base_llm::auth::{Headers, ValidatedEnvironment};
use crate::{Error, base_llm::messages::streaming::StreamDecoder};
@ -13,7 +13,7 @@ pub trait BaseMessagesConfig: Sync {
fn shape_request(
&self,
request: MessagesRequest,
_reasoning_auto_summary: bool,
_options: MessagesShapeOptions,
) -> Result<MessagesRequest, Error> {
Ok(request)
}
@ -149,9 +149,10 @@ mod tests {
}
#[rstest]
#[case::disabled(false)]
#[case::enabled(true)]
fn default_shaping_preserves_provider_policy_inputs(#[case] reasoning_auto_summary: bool) {
fn default_shaping_preserves_provider_policy_inputs(
#[values(false, true)] reasoning_auto_summary: bool,
#[values(false, true)] presanitized: bool,
) {
let request: MessagesRequest = serde_json::from_value(serde_json::json!({
"model": "test-model",
"metadata": {"user_id": 7, "extra": "keep"},
@ -160,7 +161,13 @@ mod tests {
}))
.unwrap();
assert_eq!(
DefaultsConfig.shape_request(request.clone(), reasoning_auto_summary),
DefaultsConfig.shape_request(
request.clone(),
MessagesShapeOptions {
reasoning_auto_summary,
presanitized
}
),
Ok(request)
);
assert_eq!(

9
litellm-rust/crates/llms/src/bedrock/claude_platform/messages/transformation.rs
View file

@ -21,7 +21,10 @@ use crate::{
},
base_llm::{
auth::{AuthScheme, Headers, ValidatedEnvironment},
messages::{context::MessagesTransformContext, transformation::BaseMessagesConfig},
messages::{
context::{MessagesShapeOptions, MessagesTransformContext},
transformation::BaseMessagesConfig,
},
},
bedrock::common_utils::validated_region,
};
@ -53,9 +56,9 @@ impl BaseMessagesConfig for BedrockClaudePlatformMessagesConfig {
fn shape_request(
&self,
request: MessagesRequest,
reasoning_auto_summary: bool,
options: MessagesShapeOptions,
) -> Result<MessagesRequest, Error> {
shape_anthropic_messages_request(request, reasoning_auto_summary)
shape_anthropic_messages_request(request, options)
}
fn validate_environment(

6
litellm-rust/crates/llms/src/bedrock/messages/invoke_transformations/anthropic_claude_transformation.rs
View file

@ -3,7 +3,7 @@ use std::convert::Infallible;
use crate::{
anthropic::messages::handler::shape_anthropic_messages_request,
base_llm::messages::context::MessagesTransformContext,
base_llm::messages::context::{MessagesShapeOptions, MessagesTransformContext},
};
use futures_util::StreamExt;
use litellm_auth::AwsParams;
@ -106,9 +106,9 @@ impl BaseMessagesConfig for AmazonAnthropicClaudeMessagesConfig {
fn shape_request(
&self,
request: MessagesRequest,
reasoning_auto_summary: bool,
options: MessagesShapeOptions,
) -> Result<MessagesRequest, Error> {
shape_anthropic_messages_request(request, reasoning_auto_summary)
shape_anthropic_messages_request(request, options)
}
fn get_complete_url(

6
litellm-rust/crates/llms/src/bedrock_mantle/messages/transformation.rs
View file

@ -26,7 +26,7 @@ use crate::{
base_llm::{
auth::AuthScheme,
messages::{
context::MessagesTransformContext,
context::{MessagesShapeOptions, MessagesTransformContext},
transformation::{BaseMessagesConfig, Headers, ValidatedEnvironment},
},
},
@ -129,9 +129,9 @@ impl BaseMessagesConfig for BedrockMantleAnthropicMessagesConfig {
fn shape_request(
&self,
request: MessagesRequest,
reasoning_auto_summary: bool,
options: MessagesShapeOptions,
) -> Result<MessagesRequest, Error> {
shape_anthropic_messages_request(request, reasoning_auto_summary)
shape_anthropic_messages_request(request, options)
}
fn wire_body(&self, body: Value) -> Value {

9
litellm-rust/crates/llms/src/deepseek/messages/transformation.rs
View file

@ -21,7 +21,10 @@ use crate::{
},
base_llm::{
auth::{AuthScheme, Headers, ValidatedEnvironment},
messages::{context::MessagesTransformContext, transformation::BaseMessagesConfig},
messages::{
context::{MessagesShapeOptions, MessagesTransformContext},
transformation::BaseMessagesConfig,
},
},
};
@ -45,9 +48,9 @@ impl BaseMessagesConfig for DeepSeekAnthropicMessagesConfig {
fn shape_request(
&self,
request: MessagesRequest,
reasoning_auto_summary: bool,
options: MessagesShapeOptions,
) -> Result<MessagesRequest, Error> {
shape_anthropic_messages_request(request, reasoning_auto_summary)
shape_anthropic_messages_request(request, options)
}
fn get_complete_url(

9
litellm-rust/crates/llms/src/minimax/messages/transformation.rs
View file

@ -19,7 +19,10 @@ use crate::{
},
base_llm::{
auth::{AuthScheme, Headers, ValidatedEnvironment},
messages::{context::MessagesTransformContext, transformation::BaseMessagesConfig},
messages::{
context::{MessagesShapeOptions, MessagesTransformContext},
transformation::BaseMessagesConfig,
},
},
};
@ -34,9 +37,9 @@ impl BaseMessagesConfig for MinimaxMessagesConfig {
fn shape_request(
&self,
request: MessagesRequest,
reasoning_auto_summary: bool,
options: MessagesShapeOptions,
) -> Result<MessagesRequest, Error> {
shape_anthropic_messages_request(request, reasoning_auto_summary)
shape_anthropic_messages_request(request, options)
}
fn validate_environment(

9
litellm-rust/crates/llms/src/tencent/messages/transformation.rs
View file

@ -19,7 +19,10 @@ use crate::{
},
base_llm::{
auth::{AuthScheme, Headers, ValidatedEnvironment},
messages::{context::MessagesTransformContext, transformation::BaseMessagesConfig},
messages::{
context::{MessagesShapeOptions, MessagesTransformContext},
transformation::BaseMessagesConfig,
},
},
};
@ -35,9 +38,9 @@ impl BaseMessagesConfig for TencentAnthropicMessagesConfig {
fn shape_request(
&self,
request: MessagesRequest,
reasoning_auto_summary: bool,
options: MessagesShapeOptions,
) -> Result<MessagesRequest, Error> {
shape_anthropic_messages_request(request, reasoning_auto_summary)
shape_anthropic_messages_request(request, options)
}
fn validate_environment(

6
litellm-rust/crates/llms/src/vertex_ai/messages/transformation.rs
View file

@ -24,7 +24,7 @@ use crate::{
base_llm::{
auth::{AuthScheme, Headers, ValidatedEnvironment},
messages::{
context::MessagesTransformContext,
context::{MessagesShapeOptions, MessagesTransformContext},
normalization::{normalize_system_role_messages, strip_cache_control_scope},
transformation::BaseMessagesConfig,
},
@ -50,9 +50,9 @@ impl BaseMessagesConfig for VertexAiPartnerModelsAnthropicMessagesConfig {
fn shape_request(
&self,
request: MessagesRequest,
reasoning_auto_summary: bool,
options: MessagesShapeOptions,
) -> Result<MessagesRequest, Error> {
shape_anthropic_messages_request(request, reasoning_auto_summary)
shape_anthropic_messages_request(request, options)
}
fn get_complete_url(

35
litellm-rust/crates/python-bridge/src/routes/messages/host.rs
View file

@ -2,7 +2,7 @@ use crate::cache::{CacheCall, Cached, PythonCache, Selection};
use litellm_host_python::{PythonHostCalls, PythonOwned};
use bytes::Bytes;
use litellm_host_python::{InvokeError, PythonBinding, from_py, to_py};
use litellm_host_python::{InvokeError, PythonBinding, effective_py_args, from_py, to_py};
use litellm_inference_messages::{
Error, MessagesCall, MessagesSettings, MessagesShaping, litellm_params, messages_body,
route::{Messages, MessagesStreamHead},
@ -72,6 +72,7 @@ fn project_litellm_params<'py>(
pub(super) struct MessagesPythonHost {
view: RequestView,
cache: PythonCache,
asynchronous: bool,
}
impl MessagesPythonHost {
@ -79,9 +80,25 @@ impl MessagesPythonHost {
Self {
view,
cache: PythonCache::new(asynchronous),
asynchronous,
}
}
/// The body fields `body_params` keeps from the keywords the call would send. Python's
/// sync and async entries prepare prompt caching differently, so it is told which ran.
fn body_params(
&self,
py: Python<'_>,
arguments: &Bound<'_, PyDict>,
) -> PyResult<Map<String, Value>> {
let request = effective_py_args(self.view.request(py)?, arguments)?;
from_py(
&py.import(ROUTE_HOST_MODULE)?
.getattr("body_params")?
.call1((request, self.asynchronous))?,
)
}
fn projection(
&self,
py: Python<'_>,
@ -93,10 +110,19 @@ impl MessagesPythonHost {
};
let model = string("model")?.ok_or(ArgumentError::Required("model"))?;
let messages = argument("messages")?.ok_or(ArgumentError::Required("messages"))?;
let fields = self.view.body_params(py, arguments, ROUTE_HOST_MODULE)?;
let mut fields = self.body_params(py, arguments)?;
// `body_params` answers `messages` only when it prepared them as Python's handler does,
// normalized and with prompt-cache breakpoints injected, so shaping must not sanitize
// them again.
let prepared = fields.remove("messages");
let presanitized = prepared.is_some();
let messages = match prepared {
Some(messages) => messages,
None => from_py(&messages)?,
};
let body = [
("model".to_string(), Value::String(model.clone())),
("messages".to_string(), from_py(&messages)?),
("messages".to_string(), messages),
]
.into_iter()
.chain(fields)
@ -117,7 +143,8 @@ impl MessagesPythonHost {
.call1((&model, api_base.as_deref()))?
.extract()?,
};
let shaping = self.shaping(py, &model, custom_llm_provider.as_deref(), arguments)?;
let mut shaping = self.shaping(py, &model, custom_llm_provider.as_deref(), arguments)?;
shaping.settings.presanitized = presanitized;
let extra_headers = self.merged_headers(py, arguments)?;
let provider_specific_header = self.provider_specific_header(py, arguments)?;
let litellm_params = project_litellm_params(argument, |name| module_global(py, name))?;

61
litellm/llms/anthropic/messages/native/handler.py
View file

@ -458,6 +458,48 @@ def _short_circuit_safeguards_evaluator(
return request_safeguards_evaluator(kwargs, messages)
def provider_after_pre_request_hooks(
model: str, custom_llm_provider: str | None, request_kwargs: Mapping[str, object]
) -> str | None:
"""The provider ``anthropic_messages`` hands its handler: the caller's, else the one the
pre-request hooks derived, else ``get_llm_provider``'s.
The litellm_params dict may have been overwritten by ``**kwargs`` in
``_execute_pre_request_hooks``, hence the last fallback.
"""
if custom_llm_provider:
return custom_llm_provider
hook_params: Final = request_kwargs.get("litellm_params")
hooked: Final = (
cast(Mapping[str, object], hook_params).get("custom_llm_provider") # cast-ok: the hooks' own params dict
if isinstance(hook_params, Mapping)
else None
)
derived: Final = hooked if isinstance(hooked, str) else None
if derived:
return derived
try:
_, resolved, _, _ = litellm.get_llm_provider(model=model)
except Exception: # noqa: BLE001 # an unknown model keeps the provider the hooks left
return derived
return resolved
def tools_marked_for_cache_points(
tools: object,
request_kwargs: dict[str, object], # mutable-ok: pops the points and records the mark in the handler's kwargs
) -> Sequence[object] | None:
"""Pops the injection points the message pass left for the tool config, marks the tool they
name and records the gateway's mark. Returns ``None`` when no tool is marked."""
marked: Final = tools_marked_for_a_tool_config_point(
tools, request_kwargs.pop("cache_control_injection_points", None)
)
if marked is None:
return None
AnthropicCacheControlHook.record_gateway_injection(request_kwargs, 1)
return list(marked)
@client
async def anthropic_messages(
max_tokens: int,
@ -518,16 +560,7 @@ async def anthropic_messages(
tool_choice = request_kwargs.pop("tool_choice", tool_choice)
top_k = request_kwargs.pop("top_k", top_k)
top_p = request_kwargs.pop("top_p", top_p)
# Propagate the provider derived inside pre-request hooks, if not already set.
# The litellm_params dict may have been overwritten by **kwargs in
# _execute_pre_request_hooks, so fall back to get_llm_provider() if needed.
if not custom_llm_provider:
custom_llm_provider = request_kwargs.get("litellm_params", {}).get("custom_llm_provider")
if not custom_llm_provider:
try:
_, custom_llm_provider, _, _ = litellm.get_llm_provider(model=model)
except Exception:
pass
custom_llm_provider = provider_after_pre_request_hooks(model, custom_llm_provider, request_kwargs)
# Remove litellm_params from kwargs (only needed for hooks)
request_kwargs.pop("litellm_params", None)
# Merge back any other modifications
@ -834,12 +867,8 @@ def anthropic_messages_handler(
)
request_kwargs: Final = cast(dict[str, object], kwargs) # cast-ok: **kwargs of the handler is untyped
marked_tools: Final = tools_marked_for_a_tool_config_point(
local_vars.get("tools"), request_kwargs.pop("cache_control_injection_points", None)
)
if marked_tools is not None:
AnthropicCacheControlHook.record_gateway_injection(request_kwargs, 1)
local_vars.update({**request_kwargs, **({"tools": list(marked_tools)} if marked_tools is not None else {})})
marked_tools: Final = tools_marked_for_cache_points(local_vars.get("tools"), request_kwargs)
local_vars.update({**request_kwargs, **({"tools": marked_tools} if marked_tools is not None else {})})
anthropic_messages_optional_request_params: Final = (
AnthropicMessagesRequestUtils.get_requested_anthropic_messages_optional_param(
params=local_vars,

1
litellm/messages/dispatch.py
View file

@ -141,7 +141,6 @@ _FEATURES: Final[detectors.Detectors] = MappingProxyType(
Feature.RESPONSE_CACHE: detectors.response_cache,
Feature.MODIFY_PARAMS: detectors.modify_params,
Feature.WORKLOAD_IDENTITY: route_detectors.anthropic_workload_identity,
Feature.CACHE_CONTROL_INJECTION: detectors.cache_control_injection,
Feature.STREAM_COST_INJECTION: route_detectors.stream_cost_injection,
Feature.THINKING_SIGNATURE_RETRY: route_detectors.thinking_signature_retry,
Feature.TOOL_CUSTOM_FIELD: route_detectors.tool_custom_field,

1
litellm/rust_bridge/catalog.py
View file

@ -182,7 +182,6 @@ MESSAGES_PYTHON_FEATURES: Final = (COMMON_PYTHON_FEATURES - {Feature.TIMEOUT_VAR
Feature.RESPONSE_CACHE,
Feature.MODIFY_PARAMS,
Feature.WORKLOAD_IDENTITY,
Feature.CACHE_CONTROL_INJECTION,
Feature.STREAM_COST_INJECTION,
Feature.THINKING_SIGNATURE_RETRY,
Feature.TOOL_CUSTOM_FIELD,

110
litellm/rust_bridge/host/routes/messages.py
View file

@ -2,6 +2,7 @@ from __future__ import annotations
import datetime
import errno
import inspect
import ipaddress
import os
import socket
@ -11,7 +12,7 @@ from typing import Final, TypeAlias, cast # noqa: TID251 # narrows native payl
import httpx
from aiohttp.http_exceptions import ContentLengthError, TransferEncodingError
from pydantic import TypeAdapter, ValidationError
from pydantic import JsonValue, TypeAdapter, ValidationError
import litellm
from litellm.litellm_core_utils import exception_mapping_utils
@ -27,12 +28,13 @@ from litellm.llms.anthropic.messages.native.handler import (
from litellm.llms.anthropic.messages.native.handler import (
_with_deployment_output_effort as _deployment_output_effort, # pyright: ignore[reportPrivateUsage] # the handler's own effort rounding
)
from litellm.llms.anthropic.messages.native.utils import prepare_native_messages
from litellm.llms.anthropic.messages.utils import is_reasoning_auto_summary_enabled
from litellm.llms.base_llm.chat.transformation import BaseLLMException
from litellm.llms.custom_httpx.http_handler import get_ssl_configuration
from litellm.rust_bridge import failures
from litellm.rust_bridge import detectors, failures
from litellm.rust_bridge.host import callbacks_legacy_python, http_transport
from litellm.rust_bridge.public_call import known_params, optional_str
from litellm.rust_bridge.public_call import NativeCall, known_params, optional_str
from litellm.types.llms.anthropic_messages.anthropic_response import AnthropicMessagesResponse
_METADATA: Final = TypeAdapter(dict[str, object])
@ -90,13 +92,30 @@ def inferred_provider(model: str, api_base: str | None) -> str | None:
return provider
def body_params(request: Mapping[str, object]) -> Mapping[str, object]:
def _body_fields(request: Mapping[str, object]) -> Mapping[str, object]:
params: Final = known_params(_BODY_FIELDS.difference(handler.additional_drop_paths(request)), request)
if deployment_reasoning_effort_levels(request.get("model_info")) is None:
return params
return _with_deployment_effort(params, request)
def body_params(request: Mapping[str, object], asynchronous: bool) -> Mapping[str, object]:
"""The body fields Python's handler sends. For a call that asks for prompt caching they
also hold the handler's ``messages``, normalized and with its breakpoints injected, and
its ``system`` and ``tools`` after injection; ``messages`` is here only then, which tells
the native route not to normalize them again."""
fields: Final = _body_fields(request)
if not detectors.cache_control_injection(NativeCall(args=(), kwargs=request, base={})):
return fields
messages, system, tools = _prompt_cached(request, asynchronous)
return {
**fields,
"messages": messages,
**({"system": system} if "system" in fields else {}),
**({"tools": tools} if tools is not None and "tools" in fields else {}),
}
def _with_deployment_effort(params: Mapping[str, object], request: Mapping[str, object]) -> Mapping[str, object]:
"""Python's handler rounds the requested effort to the levels the deployment declares in
`model_info.reasoning_effort_levels`, the one place a deployment, not the model, decides."""
@ -116,6 +135,85 @@ def _with_deployment_effort(params: Mapping[str, object], request: Mapping[str,
)
_ENTRY: Final = cast( # cast-ok: only the untyped handler's signature is read
Callable[..., object],
handler.anthropic_messages, # noqa: TID251 # reads the handler's signature, never calls it
)
_HANDLER: Final = cast( # cast-ok: only the untyped handler's signature is read
Callable[..., object],
handler.anthropic_messages_handler, # noqa: TID251 # reads the handler's signature, never calls it
)
_ENTRY_PARAMS: Final = frozenset(inspect.signature(_ENTRY).parameters) - {"kwargs"}
_HANDLER_PARAMS: Final = frozenset(inspect.signature(_HANDLER).parameters) - {"kwargs"}
_JsonBlocks: TypeAlias = list[dict[str, JsonValue]]
_Prepared: TypeAlias = tuple[_JsonBlocks, str | _JsonBlocks | None, Sequence[object] | None]
def _prompt_cached(request: Mapping[str, object], asynchronous: bool) -> _Prepared:
"""What Python's handler sends after injecting prompt-cache breakpoints. The sync handler
prepares the messages once; the async entry prepares them, then hands them to the handler,
which prepares them again as already normalized for the provider the pre-request hooks
leave. The ``**kwargs`` each function sees is the call minus its named params."""
model: Final = str(request["model"])
provider: Final = optional_str(request.get("custom_llm_provider"))
api_base: Final = optional_str(request.get("api_base"))
tools: Final = cast(_JsonBlocks | None, request.get("tools")) # cast-ok: handed on unchecked, as the handler does
messages: Final = cast(_JsonBlocks, request["messages"]) # cast-ok: handed on unchecked, as the handler does
system: Final = cast( # cast-ok: handed on unchecked, as the handler does
str | _JsonBlocks | None, request.get("system")
)
if not asynchronous:
return _handler_prepared(
request,
messages,
system,
model=model,
provider=provider,
tools=tools,
api_base=api_base,
presanitized=False,
)
entry_kwargs: Final = {name: value for name, value in request.items() if name not in _ENTRY_PARAMS}
entry_messages, entry_system = prepare_native_messages(
messages, system, entry_kwargs, model=model, custom_llm_provider=provider, tools=tools, api_base=api_base
)
return _handler_prepared(
entry_kwargs,
entry_messages,
entry_system,
model=model,
provider=handler.provider_after_pre_request_hooks(model, provider, entry_kwargs),
tools=tools,
api_base=api_base,
presanitized=True,
)
def _handler_prepared(
call: Mapping[str, object],
messages: _JsonBlocks,
system: str | _JsonBlocks | None,
*,
model: str,
provider: str | None,
tools: _JsonBlocks | None,
api_base: str | None,
presanitized: bool,
) -> _Prepared:
handler_kwargs: Final = {name: value for name, value in call.items() if name not in _HANDLER_PARAMS}
prepared_messages, prepared_system = prepare_native_messages(
messages,
system,
handler_kwargs,
model=model,
custom_llm_provider=provider,
tools=tools,
api_base=api_base,
presanitized=presanitized,
)
return prepared_messages, prepared_system, handler.tools_marked_for_cache_points(tools, handler_kwargs)
def stream_hidden_params(headers: Sequence[tuple[str, str]]) -> Mapping[str, object]:
from litellm.llms.anthropic.messages.native.streaming_iterator import (
anthropic_messages_stream_hidden_params,
@ -331,8 +429,8 @@ def _log_resolved_call(request: Mapping[str, object], request_provider: str) ->
logger,
kwargs={name: value for name, value in request.items() if name != "metadata"},
model=str(request["model"]).removeprefix(f"{request_provider}/"),
optional_params=dict(body_params(request)),
litellm_params={"model_info": request.get("model_info"), **body_params(request)},
optional_params=dict(_body_fields(request)),
litellm_params={"model_info": request.get("model_info"), **_body_fields(request)},
custom_llm_provider=request_provider,
)

155
tests/rust-python-harness/strategies/e2e_parity/sdk/messages/test_native_parity.py
View file

@ -346,7 +346,6 @@ F_MOCK: Final = "F: mock_response is Python-only (detector mock_response)"
F_THINKING_RETRY: Final = (
"F: retry without thinking after a rejected signature is Python-only (detector thinking_signature_retry)"
)
F_CACHE_INJECTION: Final = "F: prompt cache_control injection is Python-only (detector cache_control_injection)"
F_TOOL_CUSTOM: Final = "F: hoisting a tool's custom field is Python-only (detector tool_custom_field)"
F_STREAM_COST: Final = "F: cost injection into streamed usage is Python-only (detector stream_cost_injection)"
@ -380,10 +379,8 @@ KNOWN_GAPS: Final[Mapping[str, Mapping[str, str | None]]] = MappingProxyType(
logged_metadata=F_THINKING_RETRY,
logged_response_headers=F_THINKING_RETRY,
),
"cache_control_injection_points": _gaps(request=F_CACHE_INJECTION),
"tool_custom_field": _gaps(request=F_TOOL_CUSTOM),
"stream_cost_injection": _gaps(outcome=F_STREAM_COST),
"enable_prompt_caching": _gaps(request=F_CACHE_INJECTION),
}
)
@ -729,6 +726,142 @@ SYNC_CASES: Final = (
Case("sync_upstream_429", upstream=(_failure(429, "rate_limit_error", "slow down"),), sync=True),
)
SYSTEM_POINT: Final[Mapping[str, JsonValue]] = MappingProxyType({"location": "message", "role": "system"})
LAST_MESSAGE_POINT: Final[Mapping[str, JsonValue]] = MappingProxyType({"location": "message", "index": -1})
SYSTEM_BLOCKS: Final[tuple[JsonValue, ...]] = (
{"type": "text", "text": "Answer in one word."},
{"type": "text", "text": "Be terse."},
)
MARKED_TURNS: Final[tuple[JsonValue, ...]] = (
{"role": "user", "content": [{"type": "text", "text": "One.", "cache_control": {"type": "ephemeral"}}]},
{"role": "assistant", "content": [{"type": "text", "text": "Two.", "cache_control": {"type": "ephemeral"}}]},
{"role": "user", "content": [{"type": "text", "text": "Three.", "cache_control": {"type": "ephemeral"}}]},
)
PROMPT_CACHING_CASES: Final = (
Case(
"cache_control_injection_points",
_kw(system="Answer in one word.", cache_control_injection_points=[dict(SYSTEM_POINT)]),
),
Case("enable_prompt_caching", _kw(system="Answer in one word.", enable_prompt_caching=True)),
Case(
"enable_prompt_caching_without_system",
_kw(messages=list(TOOL_TURNS), tools=[dict(WEATHER_TOOL)], enable_prompt_caching=True),
),
Case(
"global_prompt_caching_with_ttl",
_kw(system=list(SYSTEM_BLOCKS)),
settings=MappingProxyType({"enable_anthropic_prompt_caching": True, "anthropic_prompt_caching_ttl": "1h"}),
),
Case(
"global_prompt_caching_stands_down_on_client_marks",
_kw(system=[{"type": "text", "text": "Answer in one word.", "cache_control": {"type": "ephemeral"}}]),
settings=MappingProxyType({"enable_anthropic_prompt_caching": True}),
),
Case(
"global_prompt_caching_stands_down_on_marked_tools",
_kw(tools=[{**WEATHER_TOOL, "cache_control": {"type": "ephemeral"}}]),
settings=MappingProxyType({"enable_anthropic_prompt_caching": True}),
),
Case(
"enable_prompt_caching_false_overrides_nothing",
_kw(system="Answer in one word.", enable_prompt_caching=False),
),
Case(
"injection_point_negative_index",
_kw(
messages=list(TOOL_TURNS),
cache_control_injection_points=[
{"location": "message", "index": -2, "control": {"type": "ephemeral", "ttl": "1h"}}
],
),
),
Case(
"injection_point_string_index",
_kw(messages=list(TOOL_TURNS), cache_control_injection_points=[{"location": "message", "index": "1"}]),
),
Case(
"injection_point_out_of_range_index",
_kw(messages=list(TOOL_TURNS), cache_control_injection_points=[{"location": "message", "index": 7}]),
),
Case(
"injection_point_by_role",
_kw(messages=list(TOOL_TURNS), cache_control_injection_points=[{"location": "message", "role": "user"}]),
),
Case(
"injection_points_capped_by_client_marks",
_kw(
messages=list(MARKED_TURNS),
system=list(SYSTEM_BLOCKS),
tools=[{**WEATHER_TOOL, "cache_control": {"type": "ephemeral"}}],
cache_control_injection_points=[dict(SYSTEM_POINT), dict(LAST_MESSAGE_POINT)],
),
),
Case(
"injection_points_beside_client_marks",
_kw(
messages=[*MARKED_TURNS[:2], {"role": "user", "content": "Three."}],
cache_control_injection_points=[dict(SYSTEM_POINT), dict(LAST_MESSAGE_POINT)],
system="Answer in one word.",
),
),
Case(
"tool_config_point_marks_the_last_tool",
_kw(
tools=[dict(WEATHER_TOOL), {**WEATHER_TOOL, "name": "get_time"}],
cache_control_injection_points=[{"location": "tool_config"}, dict(LAST_MESSAGE_POINT)],
),
),
Case(
"tool_config_point_without_tools",
_kw(cache_control_injection_points=[{"location": "tool_config"}]),
),
Case(
"injection_marks_the_gateway_deployment",
_kw(
system="Answer in one word.",
enable_prompt_caching=True,
litellm_metadata={"user_api_key": "hashed"},
model_info={"id": "deployment-1"},
),
),
Case(
"injection_into_whitespace_only_turn",
_kw(
messages=[dict(USER), {"role": "assistant", "content": "Paris"}, {"role": "user", "content": " "}],
cache_control_injection_points=[dict(LAST_MESSAGE_POINT)],
),
upstream=(_failure(400, "invalid_request_error", "messages: text content blocks must be non-empty"),),
),
Case(
"injection_after_empty_blocks_are_stripped",
_kw(
messages=[
dict(USER),
{"role": "assistant", "content": [{"type": "text", "text": ""}]},
{"role": "user", "content": "And Germany?"},
],
cache_control_injection_points=[{"location": "message", "index": 1}],
),
),
Case(
"stream_with_prompt_caching",
_kw(stream=True, system="Answer in one word.", enable_prompt_caching=True),
upstream=(_stream(TEXT_STREAM),),
),
Case(
"global_prompt_caching_beside_an_unmatched_point",
_kw(
system="Answer in one word.", cache_control_injection_points=[{"location": "message", "role": "assistant"}]
),
settings=MappingProxyType({"enable_anthropic_prompt_caching": True}),
),
)
SYNC_PROMPT_CACHING_CASES: Final = tuple(
replace(case, name=f"sync_{case.name}", sync=True) for case in PROMPT_CACHING_CASES
)
FALLBACK_CASES: Final = (
Case("mock_response", _kw(mock_response="Hi from the mock"), upstream=()),
Case("mock_response_rate_limit", _kw(mock_response="litellm.RateLimitError"), upstream=()),
@ -744,10 +877,6 @@ FALLBACK_CASES: Final = (
_ok(),
),
),
Case(
"cache_control_injection_points",
_kw(system="Answer in one word.", cache_control_injection_points=[{"location": "message", "role": "system"}]),
),
Case("tool_custom_field", _kw(tools=[{**WEATHER_TOOL, "custom": {"defer_loading": True}}])),
Case(
"strict_tools_rejected_then_retried",
@ -764,12 +893,20 @@ FALLBACK_CASES: Final = (
upstream=(_stream(TEXT_STREAM),),
settings=MappingProxyType({"include_cost_in_streaming_usage": True}),
),
Case("enable_prompt_caching", _kw(system="Answer in one word.", enable_prompt_caching=True)),
Case("request_timeout_kwarg", _kw(request_timeout=30)),
Case("stream_timeout_kwarg", _kw(stream=True, stream_timeout=30), upstream=(_stream(TEXT_STREAM),)),
)
CASES: Final = (*REQUEST_CASES, *RESPONSE_CASES, *FAILURE_CASES, *STREAM_CASES, *SYNC_CASES, *FALLBACK_CASES)
CASES: Final = (
*REQUEST_CASES,
*PROMPT_CACHING_CASES,
*SYNC_PROMPT_CACHING_CASES,
*RESPONSE_CASES,
*FAILURE_CASES,
*STREAM_CASES,
*SYNC_CASES,
*FALLBACK_CASES,
)
@dataclass(frozen=True, slots=True)

1
tests/test_litellm_rust/messages/test_dispatch.py
View file

@ -485,7 +485,6 @@ STRICT_TOOL: Final = {"name": "a", "input_schema": {"type": "object"}, "strict":
{"anthropic_federation_rule_id": "rule-1", "anthropic_organization_id": "org-1"},
{},
),
(Feature.CACHE_CONTROL_INJECTION, "anthropic/claude-sonnet-4-5", {"enable_prompt_caching": True}, {}),
(
Feature.THINKING_SIGNATURE_RETRY,
"anthropic/claude-sonnet-4-5",

99
tests/unit/rust_bridge/host/routes/test_messages.py
View file

@ -170,7 +170,7 @@ def test_body_params_round_effort_to_the_levels_the_deployment_declares(
"model_info": {"id": "deployment-1", "reasoning_effort_levels": levels},
}
assert messages_host.body_params(request)["output_config"] == {"effort": expected}
assert messages_host.body_params(request, asynchronous=True)["output_config"] == {"effort": expected}
def test_body_params_keep_the_requested_effort_without_deployment_levels() -> None:
@ -181,7 +181,7 @@ def test_body_params_keep_the_requested_effort_without_deployment_levels() -> No
"output_config": {"effort": "max"},
}
assert messages_host.body_params(request)["output_config"] == {"effort": "max"}
assert messages_host.body_params(request, asynchronous=True)["output_config"] == {"effort": "max"}
@pytest.mark.parametrize(
@ -203,7 +203,7 @@ def test_body_params_derive_no_effort_from_a_param_the_deployment_lists(
"model_info": {"id": "deployment-1", "reasoning_effort_levels": ["low", "medium", "high"]},
}
assert set(messages_host.body_params(request)).difference({"messages", "model"}) == expected_keys
assert set(messages_host.body_params(request, asynchronous=True)).difference({"messages", "model"}) == expected_keys
def _marked(phase: str | None = None, *args: object) -> ValueError:
@ -445,3 +445,96 @@ def test_a_failure_before_any_response_maps_like_the_python_transport_error(
f"litellm.InternalServerError: AnthropicException - {text}. Handle with `litellm.InternalServerError`."
)
assert "This looks like a bug in LiteLLM" not in str(mapped)
def test_body_params_leave_the_messages_to_the_route_for_a_call_without_prompt_caching(
monkeypatch: pytest.MonkeyPatch,
) -> None:
monkeypatch.setattr(litellm, "enable_anthropic_prompt_caching", False)
fields: Final = messages_host.body_params(
{
"model": "anthropic/claude-sonnet-4-5",
"messages": [{"role": "user", "content": "hi"}],
"system": "Be terse.",
"enable_prompt_caching": False,
"cache_control_injection_points": [],
},
asynchronous=True,
)
assert fields == {"system": "Be terse."}
@pytest.mark.parametrize("asynchronous", [True, False])
def test_body_params_mark_the_turns_tools_and_deployment_the_handler_marks(
monkeypatch: pytest.MonkeyPatch, asynchronous: bool
) -> None:
monkeypatch.setattr(litellm, "enable_anthropic_prompt_caching", False)
gateway: Final[dict[str, object]] = {}
caller_metadata: Final = {"user_id": "u"}
tool: Final = {"name": "get_weather", "input_schema": {"type": "object"}}
fields: Final = messages_host.body_params(
{
"model": "anthropic/claude-sonnet-4-5",
"messages": [
{"role": "user", "content": "hi"},
{"role": "assistant", "content": [{"type": "text", "text": ""}]},
{"role": "user", "content": "again"},
],
"system": "Be terse.",
"tools": [tool],
"metadata": caller_metadata,
"litellm_metadata": gateway,
"model_info": {"id": "deployment-1"},
"cache_control_injection_points": [
{"location": "message", "role": "system"},
{"location": "message", "index": -1, "control": {"type": "ephemeral", "ttl": "1h"}},
{"location": "tool_config"},
],
},
asynchronous=asynchronous,
)
assert fields == {
"messages": [
{"role": "user", "content": [{"type": "text", "text": "hi"}]},
{
"role": "user",
"content": [{"type": "text", "text": "again", "cache_control": {"type": "ephemeral", "ttl": "1h"}}],
},
],
"system": [{"type": "text", "text": "Be terse.", "cache_control": {"type": "ephemeral"}}],
"tools": [{**tool, "cache_control": {"type": "ephemeral"}}],
"metadata": caller_metadata,
}
assert gateway == {"litellm_gateway_injected_cache": "deployment-1"}
assert caller_metadata == {"user_id": "u"}
@pytest.mark.parametrize(
("asynchronous", "expected_system"),
[
# The async entry spends the configured point, so the handler's own pass falls back
# to the global defaults; the sync handler prepares the messages only once.
(True, [{"type": "text", "text": "Be terse.", "cache_control": {"type": "ephemeral"}}]),
(False, "Be terse."),
],
)
def test_body_params_prepare_prompt_caching_as_the_entry_that_ran(
monkeypatch: pytest.MonkeyPatch, asynchronous: bool, expected_system: object
) -> None:
monkeypatch.setattr(litellm, "enable_anthropic_prompt_caching", True)
fields: Final = messages_host.body_params(
{
"model": "anthropic/claude-sonnet-4-5",
"messages": [{"role": "user", "content": "hi"}],
"system": "Be terse.",
"cache_control_injection_points": [{"location": "message", "role": "assistant"}],
},
asynchronous=asynchronous,
)
assert fields["system"] == expected_system