mirror of
https://github.com/BerriAI/litellm.git
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Merge remote-tracking branch 'origin/main' into litellm_/release-version-bump-940c92
This commit is contained in:
Yuneng Jiang
commit
56685ddeae
33 changed files with 699 additions and 52 deletions
|
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@ -343,6 +343,7 @@ _anthropic_prompt_caching_ttl_env: Optional[str] = os.getenv("LITELLM_ANTHROPIC_
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anthropic_prompt_caching_ttl: Optional[Literal["5m", "1h"]] = (
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"1h" if _anthropic_prompt_caching_ttl_env == "1h" else "5m" if _anthropic_prompt_caching_ttl_env == "5m" else None
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)
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openai_system_messages_first: bool = False
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disable_vertex_batch_output_transformation: bool = False
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extra_spend_tag_headers: Optional[List[str]] = None
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in_memory_llm_clients_cache: "LLMClientCache"
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@ -1776,6 +1776,7 @@ DEFAULT_PROMPT_INJECTION_SIMILARITY_THRESHOLD = float(os.getenv("DEFAULT_PROMPT_
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LENGTH_OF_LITELLM_GENERATED_KEY: Final = int(os.getenv("LENGTH_OF_LITELLM_GENERATED_KEY", 16))
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MINIMUM_CUSTOM_KEY_LENGTH: Final = int(os.getenv("MINIMUM_CUSTOM_KEY_LENGTH", 16))
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SECRET_MANAGER_REFRESH_INTERVAL: Final = int(os.getenv("SECRET_MANAGER_REFRESH_INTERVAL", 86400))
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OPENAI_SYSTEM_MESSAGES_FIRST_PROVIDERS: Final = frozenset({"openai", "azure"})
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LITELLM_SETTINGS_SAFE_DB_OVERRIDES: Final = [
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"default_internal_user_params",
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"default_team_params",
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@ -1793,6 +1794,7 @@ LITELLM_SETTINGS_SAFE_DB_OVERRIDES: Final = [
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# test_general_settings_ui_fields_are_db_overridable enforces that pairing.
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"enable_anthropic_prompt_caching",
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"anthropic_prompt_caching_ttl",
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"openai_system_messages_first",
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"max_ui_session_budget",
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"budget_rollover",
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"mcp_tool_search",
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@ -2256,6 +2256,22 @@ def drop_tool_reference_parts_from_tool_messages(
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return [_drop_tool_reference_parts(message) for message in messages] # mutable-ok: pipelines mutate message lists
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INSTRUCTION_MESSAGE_ROLES: Final = frozenset({"system", "developer"})
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def _is_instruction_message(message: AllMessageValues) -> bool:
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return message.get("role") in INSTRUCTION_MESSAGE_ROLES
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def system_messages_first(
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messages: list[AllMessageValues], # mutable-ok: message pipelines type messages as mutable lists
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) -> list[AllMessageValues]: # mutable-ok: message pipelines type messages as mutable lists
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return [ # mutable-ok: pipelines mutate message lists
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*(message for message in messages if _is_instruction_message(message)),
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*(message for message in messages if not _is_instruction_message(message)),
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]
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def _attempt_json_repair(s: str) -> object | None:
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"""
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Attempt to repair truncated JSON produced by LLM tool calls.
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@ -9,6 +9,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import (
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drop_tool_reference_parts_from_tool_messages,
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flatten_combinators_and_drop_non_python_regex_patterns,
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hoist_images_from_tool_messages,
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system_messages_first,
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tool_with_sanitized_parameters,
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)
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from litellm.litellm_core_utils.prompt_templates.factory import (
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@ -276,7 +277,8 @@ class AzureOpenAIConfig(BaseConfig):
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litellm_params: dict,
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headers: dict,
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) -> dict:
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stripped_messages: Final = drop_tool_reference_parts_from_tool_messages(messages)
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ordered_messages: Final = system_messages_first(messages) if litellm.openai_system_messages_first else messages
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stripped_messages: Final = drop_tool_reference_parts_from_tool_messages(ordered_messages)
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azure_messages: Final = convert_to_azure_openai_messages(hoist_images_from_tool_messages(stripped_messages))
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return {
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"model": model,
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@ -12,6 +12,7 @@ from urllib.parse import urlparse
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import httpx
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import litellm
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from litellm.constants import OPENAI_SYSTEM_MESSAGES_FIRST_PROVIDERS
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from litellm.litellm_core_utils.core_helpers import map_finish_reason
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from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response import (
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_extract_reasoning_content,
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@ -24,6 +25,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import (
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flatten_combinators_and_drop_non_python_regex_patterns,
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get_tool_call_names,
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hoist_images_from_tool_messages,
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system_messages_first,
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tool_with_sanitized_parameters,
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)
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from litellm.litellm_core_utils.prompt_templates.image_handling import (
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@ -463,6 +465,15 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
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]
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return MappingProxyType({"tools": sanitized})
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def _prompt_cache_ordered_messages(
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self, messages: list[AllMessageValues], litellm_params: Mapping[str, object]
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) -> list[AllMessageValues]:
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if not litellm.openai_system_messages_first:
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return messages
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if litellm_params.get("custom_llm_provider") not in OPENAI_SYSTEM_MESSAGES_FIRST_PROVIDERS:
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return messages
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return system_messages_first(messages)
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def transform_request(
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self,
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model: str,
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@ -477,7 +488,9 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
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Returns:
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dict: The transformed request. Sent as the body of the API call.
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"""
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messages = self._transform_messages(messages=messages, model=model)
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messages = self._transform_messages(
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messages=self._prompt_cache_ordered_messages(messages, litellm_params), model=model
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)
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if not self._should_preserve_cache_control_for_endpoint(
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litellm_params.get("custom_llm_provider"), litellm_params.get("api_base")
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):
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@ -506,7 +519,9 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
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litellm_params: dict,
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headers: dict,
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) -> dict:
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transformed_messages = await self._transform_messages(messages=messages, model=model, is_async=True)
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transformed_messages = await self._transform_messages(
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messages=self._prompt_cache_ordered_messages(messages, litellm_params), model=model, is_async=True
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)
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if not self._should_preserve_cache_control_for_endpoint(
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litellm_params.get("custom_llm_provider"), litellm_params.get("api_base")
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):
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@ -17465,6 +17465,16 @@ _GENERAL_SETTINGS_UI_LITELLM_FIELDS: Final[dict[str, GeneralSettingsUILiteLLMFie
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"tab": "prompt_caching",
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"description": "Empty uses Anthropic's 5m default. 1h suits long sessions but doubles the cache write cost.",
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},
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"openai_system_messages_first": {
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"type": "Boolean",
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"tab": "prompt_caching",
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"description": (
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"Moves system and developer messages to the front of the messages array on OpenAI and "
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"Azure OpenAI chat completions requests, keeping their relative order. OpenAI's prompt cache "
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"matches on the exact prefix, so a system message that arrives mid-conversation otherwise "
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"breaks the cached prefix on every turn."
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),
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},
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"budget_rollover": { # mutable-ok: registry literal, frozen with its siblings below
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"type": "Boolean",
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"description": (
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|
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@ -23,6 +23,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import (
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responses_reasoning_items_from_thinking_blocks,
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split_concatenated_json_objects,
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strip_encrypted_reasoning_from_messages,
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system_messages_first,
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update_messages_with_model_file_ids,
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)
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@ -1107,6 +1108,38 @@ def test_drop_tool_reference_parts_leaves_non_tool_messages_alone():
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assert result[2]["content"] == ""
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class TestSystemMessagesFirst:
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def test_stable_partition_keeps_order_within_each_group(self):
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messages = [
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{"role": "user", "content": "u1"},
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{"role": "system", "content": "s1"},
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{"role": "assistant", "content": "a1"},
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{"role": "developer", "content": "d1"},
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{"role": "tool", "tool_call_id": "c1", "content": "t1"},
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{"role": "system", "content": "s2"},
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]
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result = system_messages_first(messages)
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assert [m["content"] for m in result] == ["s1", "d1", "s2", "u1", "a1", "t1"]
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assert [m["content"] for m in messages] == ["u1", "s1", "a1", "d1", "t1", "s2"]
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assert all(
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result_message is original for result_message, original in zip(result[3:], messages[::2], strict=True)
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)
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@pytest.mark.parametrize(
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"messages",
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[
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[],
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[{"role": "user", "content": "u1"}, {"role": "assistant", "content": "a1"}],
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[{"role": "system", "content": "s1"}, {"role": "user", "content": "u1"}],
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[{"role": "system", "content": "s1"}, {"role": "system", "content": "s2"}],
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],
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)
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def test_already_ordered_messages_come_back_unchanged(self, messages):
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assert system_messages_first(messages) == messages
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class TestFlattenTopLevelSchemaCombinators:
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def _customer_anyof_schema(self):
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return {
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|
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@ -132,6 +132,32 @@ def test_transform_request_drops_tool_reference_parts():
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assert request["messages"][2]["content"] == ""
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@pytest.mark.parametrize(
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"enabled, expected", [(False, ("hi", "sys", "reply", "more")), (True, ("sys", "hi", "reply", "more"))]
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)
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def test_transform_request_system_messages_first_follows_global_flag(monkeypatch, enabled, expected):
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"""Azure OpenAI shares OpenAI's prefix-matched prompt cache, so the same flag moves
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system messages ahead of the conversation on the Azure request body."""
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monkeypatch.setattr(litellm, "openai_system_messages_first", enabled)
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messages = [
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{"role": "user", "content": "hi"},
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{"role": "system", "content": "sys"},
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{"role": "assistant", "content": "reply"},
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{"role": "user", "content": "more"},
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]
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request = AzureOpenAIConfig().transform_request(
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model="gpt-4o",
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messages=messages,
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optional_params={},
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litellm_params={"custom_llm_provider": "azure"},
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headers={},
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)
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assert tuple(m["content"] for m in request["messages"]) == expected
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assert [m["content"] for m in messages] == ["hi", "sys", "reply", "more"]
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@pytest.mark.parametrize(
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"model, emitted_key, absent_key",
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[
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|
|
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|
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@ -68,3 +68,24 @@ def test_azure_o_series_transform_request_flattens_top_level_anyof():
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assert parameters["required"] == ["id"]
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assert "anyOf" in tool["function"]["parameters"]
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assert optional_params["tools"][0] is tool
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def test_azure_o_series_transform_request_moves_system_messages_first(monkeypatch):
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monkeypatch.setattr(litellm, "openai_system_messages_first", True)
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messages = [
|
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{"role": "user", "content": "hi"},
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{"role": "developer", "content": "dev"},
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{"role": "assistant", "content": "reply"},
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{"role": "user", "content": "more"},
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]
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request = AzureOpenAIO1Config().transform_request(
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model="o3-mini",
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messages=messages,
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optional_params={},
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litellm_params={"custom_llm_provider": "azure"},
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headers={},
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)
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assert [m["content"] for m in request["messages"]] == ["dev", "hi", "reply", "more"]
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assert [m["content"] for m in messages] == ["hi", "dev", "reply", "more"]
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|
|
|
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|
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@ -1124,6 +1124,80 @@ class TestToolReferenceStripping:
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assert request["messages"][2]["content"] == ""
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|
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|
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class TestSystemMessagesFirst:
|
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"""With litellm.openai_system_messages_first on, requests bound for OpenAI put system and
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developer messages ahead of the conversation, keeping each group's order, so the instruction
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prefix stays byte-stable for OpenAI's prefix-matched prompt cache."""
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MESSAGES: Final = (
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{"role": "user", "content": "first turn"},
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{"role": "system", "content": "sys 1"},
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{"role": "assistant", "content": "reply"},
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{"role": "developer", "content": "dev"},
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{"role": "user", "content": "second turn"},
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{"role": "system", "content": "sys 2"},
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)
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ORIGINAL_ORDER: Final = ("first turn", "sys 1", "reply", "dev", "second turn", "sys 2")
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ORDERED: Final = ("sys 1", "dev", "sys 2", "first turn", "reply", "second turn")
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|
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def setup_method(self):
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self.config = OpenAIGPTConfig()
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|
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def _messages(self):
|
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return [dict(m) for m in self.MESSAGES]
|
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|
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def _transform(self, provider):
|
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return self.config.transform_request(
|
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model="gpt-4.1",
|
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messages=self._messages(),
|
||||
optional_params={},
|
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litellm_params={"custom_llm_provider": provider},
|
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headers={},
|
||||
)
|
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|
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def test_default_off_keeps_caller_order(self, monkeypatch):
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monkeypatch.setattr(litellm, "openai_system_messages_first", False)
|
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assert tuple(m["content"] for m in self._transform("openai")["messages"]) == self.ORIGINAL_ORDER
|
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|
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def test_moves_system_and_developer_messages_first_for_openai(self, monkeypatch):
|
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monkeypatch.setattr(litellm, "openai_system_messages_first", True)
|
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assert tuple(m["content"] for m in self._transform("openai")["messages"]) == self.ORDERED
|
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|
||||
def test_leaves_openai_compatible_providers_alone(self, monkeypatch):
|
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monkeypatch.setattr(litellm, "openai_system_messages_first", True)
|
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assert tuple(m["content"] for m in self._transform("deepseek")["messages"]) == self.ORIGINAL_ORDER
|
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|
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def test_does_not_mutate_caller_messages(self, monkeypatch):
|
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monkeypatch.setattr(litellm, "openai_system_messages_first", True)
|
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messages = self._messages()
|
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self.config.transform_request(
|
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model="gpt-4.1",
|
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messages=messages,
|
||||
optional_params={},
|
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litellm_params={"custom_llm_provider": "openai"},
|
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headers={},
|
||||
)
|
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assert tuple(m["content"] for m in messages) == self.ORIGINAL_ORDER
|
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|
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@pytest.mark.asyncio
|
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async def test_async_transform_request_moves_system_messages_first(self, monkeypatch):
|
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class UninstantiatedOpenAIGPTConfig(OpenAIGPTConfig):
|
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_is_base_class = True
|
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|
||||
def __init__(self) -> None:
|
||||
pass
|
||||
|
||||
monkeypatch.setattr(litellm, "openai_system_messages_first", True)
|
||||
request = await UninstantiatedOpenAIGPTConfig().async_transform_request(
|
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model="gpt-4.1",
|
||||
messages=self._messages(),
|
||||
optional_params={},
|
||||
litellm_params={"custom_llm_provider": "openai"},
|
||||
headers={},
|
||||
)
|
||||
assert tuple(m["content"] for m in request["messages"]) == self.ORDERED
|
||||
|
||||
|
||||
class TestOpenAIPromptCacheBreakpointChatPath:
|
||||
"""Chat-path shape for OpenAI explicit prompt caching (#37509)."""
|
||||
|
||||
|
|
|
|||
|
|
@ -10750,6 +10750,7 @@ def test_get_config_list_includes_anthropic_prompt_caching_fields(monkeypatch):
|
|||
monkeypatch.setattr(ps, "prisma_client", mock_prisma)
|
||||
monkeypatch.setattr(litellm, "enable_anthropic_prompt_caching", True)
|
||||
monkeypatch.setattr(litellm, "anthropic_prompt_caching_ttl", "1h")
|
||||
monkeypatch.setattr(litellm, "openai_system_messages_first", False)
|
||||
app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth(
|
||||
user_id="admin", user_role=LitellmUserRoles.PROXY_ADMIN
|
||||
)
|
||||
|
|
@ -10771,6 +10772,10 @@ def test_get_config_list_includes_anthropic_prompt_caching_fields(monkeypatch):
|
|||
assert fields["enable_anthropic_prompt_caching"]["field_tab"] == "prompt_caching"
|
||||
assert fields["anthropic_prompt_caching_ttl"]["field_tab"] == "prompt_caching"
|
||||
assert fields["budget_exceeded_throttle_percentage"]["field_tab"] is None
|
||||
|
||||
assert fields["openai_system_messages_first"]["field_type"] == "Boolean"
|
||||
assert fields["openai_system_messages_first"]["field_value"] is False
|
||||
assert fields["openai_system_messages_first"]["field_tab"] == "prompt_caching"
|
||||
finally:
|
||||
app.dependency_overrides.clear()
|
||||
|
||||
|
|
@ -10887,6 +10892,7 @@ def test_general_settings_ui_defaults_unchanged_for_existing_fields():
|
|||
[
|
||||
("enable_anthropic_prompt_caching", True),
|
||||
("anthropic_prompt_caching_ttl", "1h"),
|
||||
("openai_system_messages_first", True),
|
||||
],
|
||||
)
|
||||
def test_prompt_caching_settings_propagate_on_config_reload(monkeypatch, field_name, db_value):
|
||||
|
|
@ -10945,6 +10951,8 @@ def test_get_config_list_marks_untouched_prompt_caching_flag_as_not_set(monkeypa
|
|||
("enable_anthropic_prompt_caching", False),
|
||||
("anthropic_prompt_caching_ttl", "5m"),
|
||||
("anthropic_prompt_caching_ttl", "1h"),
|
||||
("openai_system_messages_first", True),
|
||||
("openai_system_messages_first", False),
|
||||
],
|
||||
)
|
||||
@pytest.mark.asyncio
|
||||
|
|
@ -10993,6 +11001,8 @@ async def test_update_config_field_prompt_caching_persists_to_litellm_settings(m
|
|||
("anthropic_prompt_caching_ttl", "10m"),
|
||||
("anthropic_prompt_caching_ttl", "1H"),
|
||||
("anthropic_prompt_caching_ttl", 3600),
|
||||
("openai_system_messages_first", "yes"),
|
||||
("openai_system_messages_first", 1),
|
||||
],
|
||||
)
|
||||
@pytest.mark.asyncio
|
||||
|
|
@ -11032,6 +11042,7 @@ async def test_update_config_field_prompt_caching_rejects_invalid(monkeypatch, f
|
|||
[
|
||||
("enable_anthropic_prompt_caching", False),
|
||||
("anthropic_prompt_caching_ttl", None),
|
||||
("openai_system_messages_first", False),
|
||||
("budget_exceeded_throttle_percentage", None),
|
||||
],
|
||||
)
|
||||
|
|
|
|||
|
|
@ -35,10 +35,12 @@ beforeEach(() => {
|
|||
Element.prototype.scrollIntoView = () => {};
|
||||
});
|
||||
|
||||
const CHAT_REQUEST_ARG_COUNT = 26;
|
||||
const CHAT_REQUEST_ARG_COUNT = 27;
|
||||
const STREAMING_ENABLED_ARG_INDEX = 25;
|
||||
const MESSAGES_REQUEST_ARG_COUNT = 19;
|
||||
const CHAT_CUSTOM_HEADERS_ARG_INDEX = 26;
|
||||
const MESSAGES_REQUEST_ARG_COUNT = 20;
|
||||
const MESSAGES_STREAMING_ENABLED_ARG_INDEX = 18;
|
||||
const MESSAGES_CUSTOM_HEADERS_ARG_INDEX = 19;
|
||||
|
||||
async function openComboboxByPlaceholder(placeholder: string) {
|
||||
const user = userEvent.setup();
|
||||
|
|
@ -447,6 +449,63 @@ describe("ChatUI", () => {
|
|||
expect(requestArgs[MESSAGES_STREAMING_ENABLED_ARG_INDEX]).toBe(false);
|
||||
});
|
||||
|
||||
it("should send custom headers entered in the sidebar with /v1/chat/completions and /v1/messages requests", async () => {
|
||||
const user = userEvent.setup();
|
||||
render(
|
||||
<ChatUI
|
||||
accessToken="1234567890"
|
||||
token="1234567890"
|
||||
userRole="user"
|
||||
userID="1234567890"
|
||||
disabledPersonalKeyCreation={false}
|
||||
/>,
|
||||
);
|
||||
|
||||
await waitFor(() => {
|
||||
expect(screen.getByText("Test Key")).toBeInTheDocument();
|
||||
});
|
||||
|
||||
await selectComboboxOption("Select a Model", "Model 1");
|
||||
await user.click(screen.getByRole("button", { name: "Add Header" }));
|
||||
await user.click(screen.getByRole("button", { name: "Add Header" }));
|
||||
const [firstName] = screen.getAllByPlaceholderText("Header Name");
|
||||
const [firstValue, secondValue] = screen.getAllByPlaceholderText("Header Value");
|
||||
fireEvent.change(firstName, { target: { value: "anthropic-beta" } });
|
||||
fireEvent.change(firstValue, { target: { value: "context-1m-2025-08-07" } });
|
||||
fireEvent.change(secondValue, { target: { value: "ignored because the name is blank" } });
|
||||
|
||||
const messageInput = screen.getByPlaceholderText("Type your message... (Shift+Enter for new line)");
|
||||
await act(async () => {
|
||||
fireEvent.change(messageInput, { target: { value: "hello" } });
|
||||
});
|
||||
await act(async () => {
|
||||
fireEvent.keyDown(messageInput, { key: "Enter", code: "Enter" });
|
||||
});
|
||||
|
||||
await waitFor(() => {
|
||||
expect(makeOpenAIChatCompletionRequest).toHaveBeenCalledTimes(1);
|
||||
});
|
||||
const chatArgs = vi.mocked(makeOpenAIChatCompletionRequest).mock.calls[0];
|
||||
expect(chatArgs).toHaveLength(CHAT_REQUEST_ARG_COUNT);
|
||||
expect(chatArgs[CHAT_CUSTOM_HEADERS_ARG_INDEX]).toEqual({ "anthropic-beta": "context-1m-2025-08-07" });
|
||||
|
||||
await selectComboboxOption("Select an endpoint", "/v1/messages");
|
||||
await selectComboboxOption("Select a Model", "Model 1");
|
||||
await act(async () => {
|
||||
fireEvent.change(messageInput, { target: { value: "hello again" } });
|
||||
});
|
||||
await act(async () => {
|
||||
fireEvent.keyDown(messageInput, { key: "Enter", code: "Enter" });
|
||||
});
|
||||
|
||||
await waitFor(() => {
|
||||
expect(makeAnthropicMessagesRequest).toHaveBeenCalledTimes(1);
|
||||
});
|
||||
const messagesArgs = vi.mocked(makeAnthropicMessagesRequest).mock.calls[0];
|
||||
expect(messagesArgs).toHaveLength(MESSAGES_REQUEST_ARG_COUNT);
|
||||
expect(messagesArgs[MESSAGES_CUSTOM_HEADERS_ARG_INDEX]).toEqual({ "anthropic-beta": "context-1m-2025-08-07" });
|
||||
});
|
||||
|
||||
it("should force streaming in simplified mode even when the playground setting is off", async () => {
|
||||
sessionStorage.setItem("streamingEnabled", "false");
|
||||
|
||||
|
|
|
|||
|
|
@ -9,6 +9,7 @@ import {
|
|||
Info,
|
||||
Key,
|
||||
Link2,
|
||||
ListPlus,
|
||||
Loader2,
|
||||
Settings,
|
||||
Shield,
|
||||
|
|
@ -40,6 +41,8 @@ import { makeAnthropicMessagesRequest } from "../../llm_calls/anthropic_messages
|
|||
import { makeOpenAIAudioSpeechRequest } from "../../llm_calls/audio_speech";
|
||||
import { makeOpenAIAudioTranscriptionRequest } from "../../llm_calls/audio_transcriptions";
|
||||
import { makeOpenAIChatCompletionRequest } from "@/components/llm_calls/chat_completion";
|
||||
import { customHeadersFromPairs, parseStoredHeaderPairs } from "@/components/llm_calls/request_headers";
|
||||
import KeyValueInput, { type KeyValuePair } from "@/components/key_value_input";
|
||||
import { makeOpenAIEmbeddingsRequest } from "../../llm_calls/embeddings_api";
|
||||
import { Agent, fetchAvailableAgents } from "../../llm_calls/fetch_agents";
|
||||
import { fetchAvailableModels, ModelGroup } from "@/components/llm_calls/fetch_models";
|
||||
|
|
@ -220,6 +223,10 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
return [];
|
||||
}
|
||||
});
|
||||
const [customHeaderPairs, setCustomHeaderPairs] = useState<readonly KeyValuePair[]>(() =>
|
||||
parseStoredHeaderPairs(getSecureItem("customHeaders")),
|
||||
);
|
||||
const customHeaders = useMemo(() => customHeadersFromPairs(customHeaderPairs), [customHeaderPairs]);
|
||||
const [selectedVoice, setSelectedVoice] = useState<OpenAIVoice>(() => {
|
||||
const saved = sessionStorage.getItem("selectedVoice");
|
||||
if (!saved) return "alloy";
|
||||
|
|
@ -346,6 +353,7 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
selectedSdk,
|
||||
selectedVoice,
|
||||
proxySettings,
|
||||
customHeaders,
|
||||
});
|
||||
setGeneratedCode(code);
|
||||
}
|
||||
|
|
@ -367,12 +375,14 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
endpointType,
|
||||
selectedModel,
|
||||
proxySettings,
|
||||
customHeaders,
|
||||
]);
|
||||
|
||||
useEffect(() => {
|
||||
try {
|
||||
setSecureItem("apiKeySource", JSON.stringify(apiKeySource));
|
||||
setSecureItem("apiKey", apiKey);
|
||||
setSecureItem("customHeaders", JSON.stringify(customHeaderPairs));
|
||||
} catch {
|
||||
// Storage full or unavailable — non-critical, skip persisting.
|
||||
}
|
||||
|
|
@ -410,6 +420,7 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
mcpServerToolRestrictions,
|
||||
selectedVoice,
|
||||
streamingEnabled,
|
||||
customHeaderPairs,
|
||||
]);
|
||||
|
||||
useEffect(() => {
|
||||
|
|
@ -921,6 +932,7 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
mockTestFallbacks,
|
||||
mcpToolsets,
|
||||
streamingEnabled,
|
||||
customHeaders,
|
||||
);
|
||||
} else if (endpointType === EndpointType.IMAGE) {
|
||||
// For image generation
|
||||
|
|
@ -932,6 +944,7 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
selectedTags,
|
||||
signal,
|
||||
customProxyBaseUrl || undefined,
|
||||
customHeaders,
|
||||
);
|
||||
} else if (endpointType === EndpointType.SPEECH) {
|
||||
// For audio speech
|
||||
|
|
@ -946,6 +959,7 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
undefined, // responseFormat
|
||||
undefined, // speed
|
||||
customProxyBaseUrl || undefined,
|
||||
customHeaders,
|
||||
);
|
||||
} else if (endpointType === EndpointType.IMAGE_EDITS) {
|
||||
// For image edits
|
||||
|
|
@ -959,6 +973,7 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
selectedTags,
|
||||
signal,
|
||||
customProxyBaseUrl || undefined,
|
||||
customHeaders,
|
||||
);
|
||||
}
|
||||
} else if (endpointType === EndpointType.RESPONSES) {
|
||||
|
|
@ -1004,6 +1019,7 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
mcpToolsets,
|
||||
streamingEnabled,
|
||||
updateTotalLatency,
|
||||
customHeaders,
|
||||
);
|
||||
} else if (endpointType === EndpointType.ANTHROPIC_MESSAGES) {
|
||||
const apiChatHistory = [
|
||||
|
|
@ -1033,6 +1049,7 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
mcpServerToolRestrictions,
|
||||
mcpToolsets,
|
||||
streamingEnabled,
|
||||
customHeaders,
|
||||
);
|
||||
} else if (endpointType === EndpointType.EMBEDDINGS) {
|
||||
await makeOpenAIEmbeddingsRequest(
|
||||
|
|
@ -1042,6 +1059,7 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
effectiveApiKey,
|
||||
selectedTags,
|
||||
customProxyBaseUrl || undefined,
|
||||
customHeaders,
|
||||
);
|
||||
} else if (endpointType === EndpointType.TRANSCRIPTION) {
|
||||
// For audio transcriptions
|
||||
|
|
@ -1058,6 +1076,7 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
undefined, // responseFormat
|
||||
undefined, // temperature
|
||||
customProxyBaseUrl || undefined,
|
||||
customHeaders,
|
||||
);
|
||||
}
|
||||
} else if (endpointType === EndpointType.INTERACTIONS) {
|
||||
|
|
@ -1069,6 +1088,8 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
selectedTags,
|
||||
signal,
|
||||
customProxyBaseUrl || undefined,
|
||||
undefined,
|
||||
customHeaders,
|
||||
);
|
||||
}
|
||||
}
|
||||
|
|
@ -1086,13 +1107,10 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
resolvedServerId = toolEntry?.server_id ?? rawSelected;
|
||||
}
|
||||
if (resolvedServerId && !resolvedServerId.startsWith("toolset:") && selectedMCPDirectTool) {
|
||||
const result = await callMCPTool(
|
||||
effectiveApiKey,
|
||||
resolvedServerId,
|
||||
selectedMCPDirectTool,
|
||||
mcpToolArguments,
|
||||
selectedGuardrails.length > 0 ? { guardrails: selectedGuardrails } : undefined,
|
||||
);
|
||||
const result = await callMCPTool(effectiveApiKey, resolvedServerId, selectedMCPDirectTool, mcpToolArguments, {
|
||||
...(selectedGuardrails.length > 0 ? { guardrails: selectedGuardrails } : {}),
|
||||
customHeaders,
|
||||
});
|
||||
const resultText =
|
||||
result?.content?.length > 0
|
||||
? JSON.stringify(
|
||||
|
|
@ -1118,6 +1136,7 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
updateA2AMetadata,
|
||||
customProxyBaseUrl || undefined,
|
||||
selectedGuardrails.length > 0 ? selectedGuardrails : undefined,
|
||||
customHeaders,
|
||||
);
|
||||
}
|
||||
} catch (error) {
|
||||
|
|
@ -1485,6 +1504,18 @@ const ChatUI: React.FC<ChatUIProps> = ({
|
|||
/>
|
||||
</div>
|
||||
|
||||
{endpointType !== EndpointType.REALTIME && (
|
||||
<div>
|
||||
<label className="mb-2 flex items-center text-sm font-medium text-foreground">
|
||||
<ListPlus className="mr-2 size-4" aria-hidden="true" /> Custom Headers
|
||||
</label>
|
||||
<KeyValueInput value={customHeaderPairs} onChange={setCustomHeaderPairs} />
|
||||
<p className="mt-2 text-xs text-muted-foreground">
|
||||
Sent with every playground request, e.g. provider-specific headers like anthropic-beta.
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
|
||||
<div>
|
||||
<div className="mb-2 flex items-center gap-1 text-sm font-medium text-foreground">
|
||||
<Wrench className="mr-1 size-4" aria-hidden="true" />
|
||||
|
|
|
|||
|
|
@ -3,6 +3,7 @@
|
|||
|
||||
import { v4 as uuidv4 } from "uuid";
|
||||
import { getProxyBaseUrl, getGlobalLitellmHeaderName } from "@/components/networking";
|
||||
import { type CustomHeaders, withRequiredHeaders } from "@/components/llm_calls/request_headers";
|
||||
import { A2ATaskMetadata } from "@/components/chat_ui/types";
|
||||
|
||||
interface A2AMessagePart {
|
||||
|
|
@ -116,6 +117,7 @@ export const makeA2ASendMessageRequest = async (
|
|||
onA2AMetadata?: (metadata: A2ATaskMetadata) => void,
|
||||
customBaseUrl?: string,
|
||||
guardrails?: string[],
|
||||
customHeaders?: CustomHeaders,
|
||||
): Promise<void> => {
|
||||
const proxyBaseUrl = customBaseUrl || getProxyBaseUrl();
|
||||
const url = proxyBaseUrl ? `${proxyBaseUrl}/a2a/${agentId}/message/send` : `/a2a/${agentId}/message/send`;
|
||||
|
|
@ -146,10 +148,10 @@ export const makeA2ASendMessageRequest = async (
|
|||
try {
|
||||
const response = await fetch(url, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
headers: withRequiredHeaders(customHeaders ?? {}, {
|
||||
[getGlobalLitellmHeaderName()]: `Bearer ${accessToken}`,
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
}),
|
||||
body: JSON.stringify(jsonRpcRequest),
|
||||
signal,
|
||||
});
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
import { afterEach, describe, expect, it, vi } from "vitest";
|
||||
import Anthropic from "@anthropic-ai/sdk";
|
||||
import { makeAnthropicMessagesRequest } from "./anthropic_messages";
|
||||
import type { TokenUsage } from "@/components/chat_ui/ResponseMetrics";
|
||||
|
||||
|
|
@ -122,4 +123,26 @@ describe("anthropic_messages non-streaming", () => {
|
|||
expect(mockMessagesCreate).not.toHaveBeenCalled();
|
||||
expect(mockMessagesStream.mock.calls[0][0]).toMatchObject({ stream: true });
|
||||
});
|
||||
|
||||
it("sends custom headers alongside the tags header on the Anthropic client", async () => {
|
||||
mockMessagesCreate.mockResolvedValue({ content: [{ type: "text", text: "OK" }], usage: {} });
|
||||
|
||||
await makeAnthropicMessagesRequest(
|
||||
[{ role: "user", content: "Hello" }],
|
||||
vi.fn(),
|
||||
"claude-haiku-4-5",
|
||||
"test-token",
|
||||
["team-a"],
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
...NON_STREAMING_ARGS,
|
||||
{ "anthropic-beta": "context-1m-2025-08-07" },
|
||||
);
|
||||
|
||||
expect(vi.mocked(Anthropic).mock.calls[0][0]).toMatchObject({
|
||||
defaultHeaders: { "x-litellm-tags": "team-a", "anthropic-beta": "context-1m-2025-08-07" },
|
||||
});
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -2,6 +2,7 @@ import Anthropic from "@anthropic-ai/sdk";
|
|||
import { MessageType } from "@/components/chat_ui/types";
|
||||
import { TokenUsage } from "@/components/chat_ui/ResponseMetrics";
|
||||
import { buildMcpToolBlocks } from "@/components/llm_calls/mcp_tool_blocks";
|
||||
import { buildPlaygroundHeaders, type CustomHeaders } from "@/components/llm_calls/request_headers";
|
||||
import { MCPServer, MCPToolset } from "@/components/mcp_tools/types";
|
||||
import { getProxyBaseUrl } from "@/components/networking";
|
||||
import { toast } from "@/lib/toast";
|
||||
|
|
@ -34,6 +35,7 @@ export async function makeAnthropicMessagesRequest(
|
|||
mcpServerToolRestrictions?: Record<string, string[]>,
|
||||
mcpToolsets?: MCPToolset[],
|
||||
streamingEnabled: boolean = true,
|
||||
customHeaders?: CustomHeaders,
|
||||
) {
|
||||
if (!accessToken) {
|
||||
throw new Error("Virtual Key is required");
|
||||
|
|
@ -46,11 +48,7 @@ export async function makeAnthropicMessagesRequest(
|
|||
|
||||
const proxyBaseUrl = customBaseUrl || getProxyBaseUrl();
|
||||
|
||||
// Prepare headers with tags and trace ID
|
||||
const headers: Record<string, string> = {};
|
||||
if (tags && tags.length > 0) {
|
||||
headers["x-litellm-tags"] = tags.join(",");
|
||||
}
|
||||
const headers = buildPlaygroundHeaders(tags, customHeaders);
|
||||
|
||||
const client = new Anthropic({
|
||||
apiKey: accessToken,
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
import openai from "openai";
|
||||
import { getProxyBaseUrl } from "@/components/networking";
|
||||
import { buildPlaygroundHeaders, type CustomHeaders } from "@/components/llm_calls/request_headers";
|
||||
import { toast } from "@/lib/toast";
|
||||
import type { OpenAIVoice } from "../components/chat_ui/chatConstants";
|
||||
|
||||
|
|
@ -14,6 +15,7 @@ export async function makeOpenAIAudioSpeechRequest(
|
|||
responseFormat?: string,
|
||||
speed?: number,
|
||||
customBaseUrl?: string,
|
||||
customHeaders?: CustomHeaders,
|
||||
) {
|
||||
// base url should be the current base_url
|
||||
const isLocal = process.env.NODE_ENV === "development";
|
||||
|
|
@ -25,7 +27,7 @@ export async function makeOpenAIAudioSpeechRequest(
|
|||
apiKey: accessToken,
|
||||
baseURL: proxyBaseUrl,
|
||||
dangerouslyAllowBrowser: true,
|
||||
defaultHeaders: tags && tags.length > 0 ? { "x-litellm-tags": tags.join(",") } : undefined,
|
||||
defaultHeaders: buildPlaygroundHeaders(tags, customHeaders),
|
||||
});
|
||||
|
||||
try {
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
import openai from "openai";
|
||||
import { getProxyBaseUrl } from "@/components/networking";
|
||||
import { buildPlaygroundHeaders, type CustomHeaders } from "@/components/llm_calls/request_headers";
|
||||
import { toast } from "@/lib/toast";
|
||||
|
||||
export async function makeOpenAIAudioTranscriptionRequest(
|
||||
|
|
@ -14,6 +15,7 @@ export async function makeOpenAIAudioTranscriptionRequest(
|
|||
responseFormat?: string,
|
||||
temperature?: number,
|
||||
customBaseUrl?: string,
|
||||
customHeaders?: CustomHeaders,
|
||||
) {
|
||||
// base url should be the current base_url
|
||||
const isLocal = process.env.NODE_ENV === "development";
|
||||
|
|
@ -26,7 +28,7 @@ export async function makeOpenAIAudioTranscriptionRequest(
|
|||
apiKey: accessToken,
|
||||
baseURL: proxyBaseUrl,
|
||||
dangerouslyAllowBrowser: true,
|
||||
defaultHeaders: tags && tags.length > 0 ? { "x-litellm-tags": tags.join(",") } : undefined,
|
||||
defaultHeaders: buildPlaygroundHeaders(tags, customHeaders),
|
||||
});
|
||||
|
||||
try {
|
||||
|
|
|
|||
|
|
@ -76,4 +76,42 @@ describe("embeddings_api", () => {
|
|||
input: "Sample text",
|
||||
});
|
||||
});
|
||||
|
||||
it("sends custom headers on the fetch request, letting them override the tags header", async () => {
|
||||
await makeOpenAIEmbeddingsRequest(
|
||||
"Sample text",
|
||||
mockUpdateEmbeddingsUI,
|
||||
"text-embedding-3-small",
|
||||
"abcdef",
|
||||
["team-a"],
|
||||
undefined,
|
||||
{ "x-litellm-tags": "team-b", "x-request-source": "playground" },
|
||||
);
|
||||
|
||||
expect(mockFetch.mock.calls[0][1]).toMatchObject({
|
||||
headers: {
|
||||
Authorization: "Bearer abcdef",
|
||||
"x-litellm-tags": "team-b",
|
||||
"x-request-source": "playground",
|
||||
},
|
||||
});
|
||||
});
|
||||
|
||||
it("does not let custom headers replace the gateway auth or content-type headers", async () => {
|
||||
await makeOpenAIEmbeddingsRequest(
|
||||
"Sample text",
|
||||
mockUpdateEmbeddingsUI,
|
||||
"text-embedding-3-small",
|
||||
"abcdef",
|
||||
undefined,
|
||||
undefined,
|
||||
{ authorization: "Bearer stolen", "Content-Type": "text/plain", "x-request-source": "playground" },
|
||||
);
|
||||
|
||||
expect(mockFetch.mock.calls[0][1].headers).toEqual({
|
||||
Authorization: "Bearer abcdef",
|
||||
"Content-Type": "application/json",
|
||||
"x-request-source": "playground",
|
||||
});
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -1,5 +1,10 @@
|
|||
import { toast } from "@/lib/toast";
|
||||
import { getProxyBaseUrl, getGlobalLitellmHeaderName } from "@/components/networking";
|
||||
import {
|
||||
buildPlaygroundHeaders,
|
||||
type CustomHeaders,
|
||||
withRequiredHeaders,
|
||||
} from "@/components/llm_calls/request_headers";
|
||||
|
||||
export async function makeOpenAIEmbeddingsRequest(
|
||||
input: string,
|
||||
|
|
@ -8,6 +13,7 @@ export async function makeOpenAIEmbeddingsRequest(
|
|||
accessToken: string,
|
||||
tags?: string[],
|
||||
customBaseUrl?: string,
|
||||
customHeaders?: CustomHeaders,
|
||||
) {
|
||||
if (!accessToken) {
|
||||
throw new Error("Virtual Key is required");
|
||||
|
|
@ -20,11 +26,10 @@ export async function makeOpenAIEmbeddingsRequest(
|
|||
}
|
||||
|
||||
const proxyBaseUrl = customBaseUrl || getProxyBaseUrl();
|
||||
// Prepare headers with tags and trace ID
|
||||
const headers: Record<string, string> = {};
|
||||
if (tags && tags.length > 0) {
|
||||
headers["x-litellm-tags"] = tags.join(",");
|
||||
}
|
||||
const headers = withRequiredHeaders(buildPlaygroundHeaders(tags, customHeaders), {
|
||||
"Content-Type": "application/json",
|
||||
[getGlobalLitellmHeaderName()]: `Bearer ${accessToken}`,
|
||||
});
|
||||
|
||||
try {
|
||||
const normalizedBaseUrl = proxyBaseUrl.endsWith("/") ? proxyBaseUrl.slice(0, -1) : proxyBaseUrl;
|
||||
|
|
@ -32,11 +37,7 @@ export async function makeOpenAIEmbeddingsRequest(
|
|||
|
||||
const response = await fetch(requestUrl, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
[getGlobalLitellmHeaderName()]: `Bearer ${accessToken}`,
|
||||
...headers,
|
||||
},
|
||||
headers,
|
||||
body: JSON.stringify({
|
||||
model: selectedModel,
|
||||
input,
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
import openai from "openai";
|
||||
import { getProxyBaseUrl } from "@/components/networking";
|
||||
import { buildPlaygroundHeaders, type CustomHeaders } from "@/components/llm_calls/request_headers";
|
||||
import { toast } from "@/lib/toast";
|
||||
|
||||
export async function makeOpenAIImageEditsRequest(
|
||||
|
|
@ -11,6 +12,7 @@ export async function makeOpenAIImageEditsRequest(
|
|||
tags?: string[],
|
||||
signal?: AbortSignal,
|
||||
customBaseUrl?: string,
|
||||
customHeaders?: CustomHeaders,
|
||||
) {
|
||||
// base url should be the current base_url
|
||||
const isLocal = process.env.NODE_ENV === "development";
|
||||
|
|
@ -23,7 +25,7 @@ export async function makeOpenAIImageEditsRequest(
|
|||
apiKey: accessToken,
|
||||
baseURL: proxyBaseUrl,
|
||||
dangerouslyAllowBrowser: true,
|
||||
defaultHeaders: tags && tags.length > 0 ? { "x-litellm-tags": tags.join(",") } : undefined,
|
||||
defaultHeaders: buildPlaygroundHeaders(tags, customHeaders),
|
||||
});
|
||||
|
||||
try {
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
import openai from "openai";
|
||||
import { getProxyBaseUrl } from "@/components/networking";
|
||||
import { buildPlaygroundHeaders, type CustomHeaders } from "@/components/llm_calls/request_headers";
|
||||
import { toast } from "@/lib/toast";
|
||||
|
||||
export async function makeOpenAIImageGenerationRequest(
|
||||
|
|
@ -10,6 +11,7 @@ export async function makeOpenAIImageGenerationRequest(
|
|||
tags?: string[],
|
||||
signal?: AbortSignal,
|
||||
customBaseUrl?: string,
|
||||
customHeaders?: CustomHeaders,
|
||||
) {
|
||||
// base url should be the current base_url
|
||||
const isLocal = process.env.NODE_ENV === "development";
|
||||
|
|
@ -21,7 +23,7 @@ export async function makeOpenAIImageGenerationRequest(
|
|||
apiKey: accessToken,
|
||||
baseURL: proxyBaseUrl,
|
||||
dangerouslyAllowBrowser: true,
|
||||
defaultHeaders: tags && tags.length > 0 ? { "x-litellm-tags": tags.join(",") } : undefined,
|
||||
defaultHeaders: buildPlaygroundHeaders(tags, customHeaders),
|
||||
});
|
||||
|
||||
try {
|
||||
|
|
|
|||
|
|
@ -1,5 +1,10 @@
|
|||
import { toast } from "@/lib/toast";
|
||||
import { getGlobalLitellmHeaderName, getProxyBaseUrl } from "@/components/networking";
|
||||
import {
|
||||
buildPlaygroundHeaders,
|
||||
type CustomHeaders,
|
||||
withRequiredHeaders,
|
||||
} from "@/components/llm_calls/request_headers";
|
||||
|
||||
export async function makeInteractionsRequest(
|
||||
input: string,
|
||||
|
|
@ -10,6 +15,7 @@ export async function makeInteractionsRequest(
|
|||
signal?: AbortSignal,
|
||||
customBaseUrl?: string,
|
||||
previousInteractionId?: string,
|
||||
customHeaders?: CustomHeaders,
|
||||
): Promise<void> {
|
||||
if (!accessToken) {
|
||||
throw new Error("Virtual Key is required");
|
||||
|
|
@ -24,13 +30,10 @@ export async function makeInteractionsRequest(
|
|||
const normalizedBaseUrl = proxyBaseUrl.endsWith("/") ? proxyBaseUrl.slice(0, -1) : proxyBaseUrl;
|
||||
const requestUrl = `${normalizedBaseUrl}/v1beta/interactions`;
|
||||
|
||||
const headers: Record<string, string> = {
|
||||
const headers: Record<string, string> = withRequiredHeaders(buildPlaygroundHeaders(tags, customHeaders), {
|
||||
"Content-Type": "application/json",
|
||||
[getGlobalLitellmHeaderName()]: `Bearer ${accessToken}`,
|
||||
};
|
||||
if (tags && tags.length > 0) {
|
||||
headers["x-litellm-tags"] = tags.join(",");
|
||||
}
|
||||
});
|
||||
|
||||
const body: Record<string, unknown> = {
|
||||
model: selectedModel,
|
||||
|
|
|
|||
|
|
@ -45,6 +45,15 @@ const SETTINGS_FIXTURE = [
|
|||
field_tab: "prompt_caching",
|
||||
field_default_value: null,
|
||||
},
|
||||
{
|
||||
field_name: "openai_system_messages_first",
|
||||
field_type: "Boolean",
|
||||
field_value: false,
|
||||
field_description: "openai system first toggle",
|
||||
stored_in_db: null,
|
||||
field_tab: "prompt_caching",
|
||||
field_default_value: false,
|
||||
},
|
||||
{
|
||||
field_name: "max_ui_session_budget",
|
||||
field_type: "Dollar",
|
||||
|
|
@ -101,6 +110,39 @@ describe("GeneralSettings General tab", () => {
|
|||
});
|
||||
});
|
||||
|
||||
describe("GeneralSettings Prompt Caching tab", () => {
|
||||
beforeEach(() => {
|
||||
vi.mocked(getGeneralSettingsCall).mockResolvedValue([...SETTINGS_FIXTURE.map((s) => ({ ...s }))]);
|
||||
vi.mocked(updateConfigFieldSetting).mockClear();
|
||||
vi.mocked(deleteConfigFieldSetting).mockClear();
|
||||
});
|
||||
|
||||
it("persists openai_system_messages_first when its switch is turned on", async () => {
|
||||
const user = userEvent.setup();
|
||||
renderWithProviders(<GeneralSettings accessToken="token" userRole="Admin" userID="user" />);
|
||||
|
||||
await user.click(await screen.findByRole("tab", { name: "Prompt Caching" }));
|
||||
const toggle = await screen.findByRole("switch", { name: "System messages first for OpenAI" });
|
||||
expect(toggle).not.toBeChecked();
|
||||
|
||||
await user.click(toggle);
|
||||
|
||||
expect(toggle).toBeChecked();
|
||||
expect(updateConfigFieldSetting).toHaveBeenCalledWith("token", "openai_system_messages_first", true);
|
||||
expect(deleteConfigFieldSetting).not.toHaveBeenCalled();
|
||||
});
|
||||
|
||||
it("keeps the prompt caching rows off the General tab table", async () => {
|
||||
const user = userEvent.setup();
|
||||
renderWithProviders(<GeneralSettings accessToken="token" userRole="Admin" userID="user" />);
|
||||
|
||||
await user.click(screen.getByText("General"));
|
||||
await settingsRow("max_ui_session_budget");
|
||||
|
||||
expect(screen.queryByText("openai_system_messages_first")).not.toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
// The five tabs here are proxy-wide settings. Auto-routers moved to Models + Endpoints.
|
||||
describe("GeneralSettings tabs", () => {
|
||||
beforeEach(() => {
|
||||
|
|
|
|||
|
|
@ -18,6 +18,9 @@ import RoutingGroups from "@/components/routing_groups";
|
|||
const PROMPT_CACHING_TAB = "prompt_caching";
|
||||
const ENABLE_ANTHROPIC_PROMPT_CACHING = "enable_anthropic_prompt_caching";
|
||||
const ANTHROPIC_PROMPT_CACHING_TTL = "anthropic_prompt_caching_ttl";
|
||||
const OPENAI_SYSTEM_MESSAGES_FIRST = "openai_system_messages_first";
|
||||
|
||||
const isOn = (value: unknown) => value === true || value === "true";
|
||||
|
||||
interface GeneralSettingsPageProps {
|
||||
accessToken: string | null;
|
||||
|
|
@ -117,14 +120,15 @@ export const PromptCachingPanel: React.FC<{
|
|||
}> = ({ accessToken, settings, onChange }) => {
|
||||
const enableSetting = settings.find((s) => s.field_name === ENABLE_ANTHROPIC_PROMPT_CACHING);
|
||||
const ttlSetting = settings.find((s) => s.field_name === ANTHROPIC_PROMPT_CACHING_TTL);
|
||||
const systemFirstSetting = settings.find((s) => s.field_name === OPENAI_SYSTEM_MESSAGES_FIRST);
|
||||
|
||||
// The two rows come from the same registry the General tab reads; if they
|
||||
// The rows come from the same registry the General tab reads; if they
|
||||
// are not loaded yet there is nothing to render.
|
||||
if (!enableSetting) {
|
||||
return null;
|
||||
}
|
||||
|
||||
const enabled = enableSetting.field_value === true || enableSetting.field_value === "true";
|
||||
const enabled = isOn(enableSetting.field_value);
|
||||
|
||||
// Apply immediately: a toggle and a dropdown are direct controls, so there is
|
||||
// no separate Update button. Clearing the ttl resets it to the provider default.
|
||||
|
|
@ -175,6 +179,20 @@ export const PromptCachingPanel: React.FC<{
|
|||
</Select>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{systemFirstSetting && (
|
||||
<div className="mt-6 flex items-start justify-between gap-8">
|
||||
<div className="min-w-0 max-w-2xl">
|
||||
<p className="font-medium">System messages first for OpenAI</p>
|
||||
<p className="mt-1 break-words text-xs text-muted-foreground">{systemFirstSetting.field_description}</p>
|
||||
</div>
|
||||
<Switch
|
||||
aria-label="System messages first for OpenAI"
|
||||
checked={isOn(systemFirstSetting.field_value)}
|
||||
onCheckedChange={(checked) => persist(OPENAI_SYSTEM_MESSAGES_FIRST, checked)}
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
</CardContent>
|
||||
</Card>
|
||||
);
|
||||
|
|
|
|||
|
|
@ -48,6 +48,28 @@ describe("CodeSnippets", () => {
|
|||
expect(code).toContain("print(response.data[0].embedding)");
|
||||
});
|
||||
|
||||
describe("custom headers", () => {
|
||||
const customHeaders = { "anthropic-beta": "context-1m-2025-08-07", "x-request-source": "playground" };
|
||||
|
||||
it("passes configured headers as default_headers on the OpenAI client", () => {
|
||||
const code = generateCodeSnippet({ ...baseParams, endpointType: EndpointType.CHAT, customHeaders });
|
||||
expect(code).toContain('base_url="http://localhost:4000",\n\tdefault_headers={');
|
||||
expect(code).toContain('"anthropic-beta": "context-1m-2025-08-07"');
|
||||
expect(code).toContain('"x-request-source": "playground"');
|
||||
});
|
||||
|
||||
it("passes configured headers as default_headers on the Azure client", () => {
|
||||
const code = generateCodeSnippet({ ...baseParams, selectedSdk: "azure", customHeaders });
|
||||
expect(code).toContain('api_version="2024-02-01",\n\tdefault_headers={');
|
||||
expect(code).toContain('"anthropic-beta": "context-1m-2025-08-07"');
|
||||
});
|
||||
|
||||
it("omits default_headers when no custom headers are configured", () => {
|
||||
expect(generateCodeSnippet(baseParams)).not.toContain("default_headers");
|
||||
expect(generateCodeSnippet({ ...baseParams, customHeaders: {} })).not.toContain("default_headers");
|
||||
});
|
||||
});
|
||||
|
||||
describe("base URL selection", () => {
|
||||
it("should use LITELLM_UI_API_DOC_BASE_URL when provided", () => {
|
||||
const customBaseUrl = "https://custom-doc.example.com";
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
import { MessageType } from "./types";
|
||||
import { EndpointType } from "./mode_endpoint_mapping";
|
||||
import { MCPServer } from "@/components/mcp_tools/types";
|
||||
import type { CustomHeaders } from "@/components/llm_calls/request_headers";
|
||||
|
||||
interface CodeGenMetadata {
|
||||
tags?: string[];
|
||||
|
|
@ -30,6 +31,7 @@ interface GenerateCodeParams {
|
|||
PROXY_BASE_URL?: string;
|
||||
LITELLM_UI_API_DOC_BASE_URL?: string | null;
|
||||
};
|
||||
customHeaders?: CustomHeaders;
|
||||
}
|
||||
|
||||
export const generateCodeSnippet = (params: GenerateCodeParams): string => {
|
||||
|
|
@ -48,6 +50,7 @@ export const generateCodeSnippet = (params: GenerateCodeParams): string => {
|
|||
selectedModel,
|
||||
selectedSdk,
|
||||
proxySettings,
|
||||
customHeaders,
|
||||
} = params;
|
||||
const effectiveApiKey = apiKeySource === "session" ? accessToken : apiKey;
|
||||
|
||||
|
|
@ -76,6 +79,11 @@ export const generateCodeSnippet = (params: GenerateCodeParams): string => {
|
|||
|
||||
const modelNameForCode = selectedModel || "your-model-name";
|
||||
|
||||
const defaultHeadersCode =
|
||||
customHeaders && Object.keys(customHeaders).length > 0
|
||||
? `,\n\tdefault_headers=${JSON.stringify(customHeaders, null, 2).replace(/\n/g, "\n\t")}`
|
||||
: "";
|
||||
|
||||
const clientInitialization =
|
||||
selectedSdk === "azure"
|
||||
? `import openai
|
||||
|
|
@ -83,13 +91,13 @@ export const generateCodeSnippet = (params: GenerateCodeParams): string => {
|
|||
client = openai.AzureOpenAI(
|
||||
api_key="${effectiveApiKey || "YOUR_LITELLM_API_KEY"}",
|
||||
azure_endpoint="${apiBase}",
|
||||
api_version="2024-02-01"
|
||||
api_version="2024-02-01"${defaultHeadersCode}
|
||||
)`
|
||||
: `import openai
|
||||
|
||||
client = openai.OpenAI(
|
||||
api_key="${effectiveApiKey || "YOUR_LITELLM_API_KEY"}",
|
||||
base_url="${apiBase}"
|
||||
base_url="${apiBase}"${defaultHeadersCode}
|
||||
)`;
|
||||
|
||||
let endpointSpecificCode;
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
import { afterEach, beforeEach, describe, expect, it, vi } from "vitest";
|
||||
import openai from "openai";
|
||||
import { makeOpenAIChatCompletionRequest } from "./chat_completion";
|
||||
import type { TokenUsage } from "../chat_ui/ResponseMetrics";
|
||||
|
||||
|
|
@ -615,3 +616,47 @@ describe("chat_completion response cache", () => {
|
|||
expect(onUsageData).toHaveBeenCalledWith(expect.not.objectContaining({ servedFromResponseCache: true }));
|
||||
});
|
||||
});
|
||||
|
||||
describe("chat_completion custom headers", () => {
|
||||
afterEach(() => {
|
||||
vi.clearAllMocks();
|
||||
});
|
||||
|
||||
it("sends custom headers alongside the tags header on the OpenAI client", async () => {
|
||||
mockCreate.mockReturnValueOnce(nonStreamingResponse({ choices: [{ message: { content: "Hi" } }] }));
|
||||
|
||||
await makeOpenAIChatCompletionRequest(
|
||||
[{ role: "user", content: "Hello" }],
|
||||
vi.fn(),
|
||||
"gpt-4",
|
||||
"test-token",
|
||||
["team-a"],
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
false,
|
||||
{ "anthropic-beta": "context-1m-2025-08-07", "x-litellm-tags": "overridden" },
|
||||
);
|
||||
|
||||
expect(vi.mocked(openai.OpenAI).mock.calls[0][0]).toMatchObject({
|
||||
defaultHeaders: { "anthropic-beta": "context-1m-2025-08-07", "x-litellm-tags": "overridden" },
|
||||
});
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -6,6 +6,7 @@ import { getProxyBaseUrl } from "@/components/networking";
|
|||
import { MCPServer, MCPToolset, type MCPEvent } from "@/components/mcp_tools/types";
|
||||
import { extractPromptCacheTokens } from "@/utils/promptCacheUsage";
|
||||
import { parseUsageCost } from "./usage_cost";
|
||||
import { buildPlaygroundHeaders, type CustomHeaders } from "./request_headers";
|
||||
|
||||
const completionAsSingleChunk = (completion: ChatCompletion): ChatCompletionChunk =>
|
||||
({
|
||||
|
|
@ -50,6 +51,7 @@ export async function makeOpenAIChatCompletionRequest(
|
|||
mockTestFallbacks?: boolean,
|
||||
mcpToolsets?: MCPToolset[],
|
||||
streamingEnabled: boolean = true,
|
||||
customHeaders?: CustomHeaders,
|
||||
) {
|
||||
// base url should be the current base_url
|
||||
const isLocal = process.env.NODE_ENV === "development";
|
||||
|
|
@ -57,11 +59,7 @@ export async function makeOpenAIChatCompletionRequest(
|
|||
console.log = function () {};
|
||||
}
|
||||
const proxyBaseUrl = customBaseUrl || getProxyBaseUrl();
|
||||
// Prepare headers with tags and trace ID
|
||||
const headers: Record<string, string> = {};
|
||||
if (tags && tags.length > 0) {
|
||||
headers["x-litellm-tags"] = tags.join(",");
|
||||
}
|
||||
const headers = buildPlaygroundHeaders(tags, customHeaders);
|
||||
|
||||
const client = new openai.OpenAI({
|
||||
apiKey: accessToken,
|
||||
|
|
|
|||
|
|
@ -0,0 +1,60 @@
|
|||
import { describe, expect, it } from "vitest";
|
||||
import {
|
||||
buildPlaygroundHeaders,
|
||||
customHeadersFromPairs,
|
||||
parseStoredHeaderPairs,
|
||||
withRequiredHeaders,
|
||||
} from "./request_headers";
|
||||
|
||||
describe("customHeadersFromPairs", () => {
|
||||
it("trims header names and drops rows without a name", () => {
|
||||
expect(
|
||||
customHeadersFromPairs([
|
||||
[" anthropic-beta ", "context-1m-2025-08-07"],
|
||||
["", "orphan value"],
|
||||
[" ", "whitespace name"],
|
||||
["x-empty", ""],
|
||||
]),
|
||||
).toEqual({ "anthropic-beta": "context-1m-2025-08-07", "x-empty": "" });
|
||||
});
|
||||
});
|
||||
|
||||
describe("parseStoredHeaderPairs", () => {
|
||||
it("round-trips pairs persisted as JSON", () => {
|
||||
const pairs = [["anthropic-beta", "context-1m-2025-08-07"]] as const;
|
||||
expect(parseStoredHeaderPairs(JSON.stringify(pairs))).toEqual(pairs);
|
||||
});
|
||||
|
||||
it("returns no pairs for missing, malformed, or wrongly shaped storage", () => {
|
||||
expect(parseStoredHeaderPairs(null)).toEqual([]);
|
||||
expect(parseStoredHeaderPairs("not json")).toEqual([]);
|
||||
expect(parseStoredHeaderPairs(JSON.stringify({ "anthropic-beta": "x" }))).toEqual([]);
|
||||
expect(parseStoredHeaderPairs(JSON.stringify([["ok", "pair"], ["one"], [1, 2], "str"]))).toEqual([["ok", "pair"]]);
|
||||
});
|
||||
});
|
||||
|
||||
describe("buildPlaygroundHeaders", () => {
|
||||
it("joins tags into x-litellm-tags and lets custom headers override it", () => {
|
||||
expect(buildPlaygroundHeaders(["a", "b"], { "x-custom": "1" })).toEqual({
|
||||
"x-litellm-tags": "a,b",
|
||||
"x-custom": "1",
|
||||
});
|
||||
expect(buildPlaygroundHeaders(["a"], { "x-litellm-tags": "b" })).toEqual({ "x-litellm-tags": "b" });
|
||||
});
|
||||
|
||||
it("omits x-litellm-tags when there are no tags", () => {
|
||||
expect(buildPlaygroundHeaders([], { "x-custom": "1" })).toEqual({ "x-custom": "1" });
|
||||
expect(buildPlaygroundHeaders(undefined, undefined)).toEqual({});
|
||||
});
|
||||
});
|
||||
|
||||
describe("withRequiredHeaders", () => {
|
||||
it("keeps required headers regardless of custom header name casing", () => {
|
||||
expect(
|
||||
withRequiredHeaders(
|
||||
{ authorization: "Bearer stolen", "content-type": "text/plain", "x-custom": "1" },
|
||||
{ Authorization: "Bearer real", "Content-Type": "application/json" },
|
||||
),
|
||||
).toEqual({ Authorization: "Bearer real", "Content-Type": "application/json", "x-custom": "1" });
|
||||
});
|
||||
});
|
||||
|
|
@ -0,0 +1,38 @@
|
|||
import type { KeyValuePair } from "@/components/key_value_input";
|
||||
|
||||
export type CustomHeaders = Readonly<Record<string, string>>;
|
||||
|
||||
export const customHeadersFromPairs = (pairs: readonly KeyValuePair[]): CustomHeaders =>
|
||||
Object.fromEntries(pairs.map(([name, value]) => [name.trim(), value]).filter(([name]) => name !== ""));
|
||||
|
||||
const isHeaderPair = (entry: unknown): entry is KeyValuePair =>
|
||||
Array.isArray(entry) && entry.length === 2 && entry.every((part) => typeof part === "string");
|
||||
|
||||
export const parseStoredHeaderPairs = (raw: string | null): readonly KeyValuePair[] => {
|
||||
if (!raw) return [];
|
||||
try {
|
||||
const parsed: unknown = JSON.parse(raw);
|
||||
return Array.isArray(parsed) ? parsed.filter(isHeaderPair) : [];
|
||||
} catch {
|
||||
return [];
|
||||
}
|
||||
};
|
||||
|
||||
export const buildPlaygroundHeaders = (
|
||||
tags?: readonly string[],
|
||||
customHeaders?: CustomHeaders,
|
||||
): Record<string, string> => ({
|
||||
...(tags && tags.length > 0 ? { "x-litellm-tags": tags.join(",") } : {}),
|
||||
...customHeaders,
|
||||
});
|
||||
|
||||
export const withRequiredHeaders = (
|
||||
headers: Readonly<Record<string, string>>,
|
||||
required: Readonly<Record<string, string>>,
|
||||
): Record<string, string> => {
|
||||
const reserved = new Set(Object.keys(required).map((name) => name.toLowerCase()));
|
||||
return {
|
||||
...Object.fromEntries(Object.entries(headers).filter(([name]) => !reserved.has(name.toLowerCase()))),
|
||||
...required,
|
||||
};
|
||||
};
|
||||
|
|
@ -1,4 +1,5 @@
|
|||
import { afterEach, beforeEach, describe, expect, it, vi } from "vitest";
|
||||
import openai from "openai";
|
||||
import { makeOpenAIResponsesRequest } from "./responses_api";
|
||||
import { MessageType } from "../chat_ui/types";
|
||||
import type { TokenUsage } from "../chat_ui/ResponseMetrics";
|
||||
|
|
@ -611,3 +612,46 @@ describe("responses_api response cache", () => {
|
|||
expect(onUsageData).toHaveBeenCalledWith(expect.not.objectContaining({ servedFromResponseCache: true }), "");
|
||||
});
|
||||
});
|
||||
|
||||
describe("responses_api custom headers", () => {
|
||||
afterEach(() => {
|
||||
vi.clearAllMocks();
|
||||
});
|
||||
|
||||
it("sends custom headers alongside the tags header on the OpenAI client", async () => {
|
||||
mockResponsesCreate.mockReturnValueOnce(nonStreamingResponse({ id: "resp_1", output: [] }));
|
||||
|
||||
await makeOpenAIResponsesRequest(
|
||||
[{ role: "user", content: "Hello" }],
|
||||
vi.fn(),
|
||||
"gpt-4",
|
||||
"test-token",
|
||||
["team-a"],
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
undefined,
|
||||
false,
|
||||
undefined,
|
||||
{ "anthropic-beta": "context-1m-2025-08-07" },
|
||||
);
|
||||
|
||||
expect(vi.mocked(openai.OpenAI).mock.calls[0][0]).toMatchObject({
|
||||
defaultHeaders: { "x-litellm-tags": "team-a", "anthropic-beta": "context-1m-2025-08-07" },
|
||||
});
|
||||
});
|
||||
});
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@ import { getProxyBaseUrl } from "@/components/networking";
|
|||
import { toast } from "@/lib/toast";
|
||||
import { extractPromptCacheTokens } from "@/utils/promptCacheUsage";
|
||||
import { parseUsageCost } from "./usage_cost";
|
||||
import { buildPlaygroundHeaders, type CustomHeaders } from "./request_headers";
|
||||
import type { MCPEvent } from "@/components/mcp_tools/types";
|
||||
import { MCPServer, MCPToolset } from "@/components/mcp_tools/types";
|
||||
import {
|
||||
|
|
@ -85,6 +86,7 @@ export async function makeOpenAIResponsesRequest(
|
|||
mcpToolsets?: MCPToolset[],
|
||||
streamingEnabled: boolean = true,
|
||||
onTotalLatency?: (latency: number) => void,
|
||||
customHeaders?: CustomHeaders,
|
||||
) {
|
||||
if (!accessToken) {
|
||||
throw new Error("Virtual Key is required");
|
||||
|
|
@ -101,11 +103,7 @@ export async function makeOpenAIResponsesRequest(
|
|||
}
|
||||
|
||||
const proxyBaseUrl = customBaseUrl || getProxyBaseUrl();
|
||||
// Prepare headers with tags and trace ID
|
||||
const headers: Record<string, string> = {};
|
||||
if (tags && tags.length > 0) {
|
||||
headers["x-litellm-tags"] = tags.join(",");
|
||||
}
|
||||
const headers = buildPlaygroundHeaders(tags, customHeaders);
|
||||
|
||||
const client = new openai.OpenAI({
|
||||
apiKey: accessToken,
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue