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* feat: port LangSmith LLM Gateway routing from upstream (#1671, #1673, #1674, #1678) Ports four upstream commits that add opt-in LLM call routing through the LangSmith Gateway, preserving fork conventions (Bedrock/Fireworks model IDs, no-agent-attribution, bun toolchain). - #1671 (e9dc6e01): opt-in gateway routing — new gateway.py, team-settings toggle, admin UI section, wired into make_model for all graph entrypoints - #1673 (702ef908): dedicated LANGSMITH_GATEWAY_API_KEY precedence over platform LANGSMITH_API_KEY - #1674 (5f7c2f46): fix Fireworks gateway base URL to /fireworks (bare host, SDK appends /v1/chat/completions) + SanitizeFireworksMessagesMiddleware - #1678 (73b7d1c0): fix OpenAI Responses reasoning replay — SanitizeOpenAIResponsesMiddleware, store/include config for encrypted reasoning content, reasoning_effort coercion for Chat Completions fallback Refs #134 * fix: downgrade gateway not-routed log to debug, add Bedrock UI note, add sanitizer parity - Downgrade logger.warning to logger.debug in gateway_overrides for not-routed providers and missing API key (Bedrock is the default provider in this fork, so these are expected steady states) - Add Bedrock to the LLMGatewaySection route-toggle description so admins know it is not routed through the gateway - Add SanitizeOpenAIResponsesMiddleware to chat.py for parity with server.py and reviewer.py - Restore the Bedrock region comment in model.py that explains the AWS_REGION / AWS_DEFAULT_REGION precedence Refs #138 --------- Co-authored-by: amoussa1229 <166072409+amoussa1229@users.noreply.github.com>
85 lines
2.6 KiB
Python
85 lines
2.6 KiB
Python
"""Middleware that removes stale OpenAI Responses reasoning references."""
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from __future__ import annotations
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import logging
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from collections.abc import Awaitable, Callable
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from typing import Any
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from langchain.agents.middleware import AgentMiddleware
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from langchain.agents.middleware.types import ModelCallResult, ModelRequest, ModelResponse
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from langchain_core.messages import AIMessage
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try:
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from langchain_openai import ChatOpenAI
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except ImportError: # pragma: no cover
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ChatOpenAI = None # type: ignore[assignment, misc]
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logger = logging.getLogger(__name__)
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def _is_chat_openai(model: object) -> bool:
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if ChatOpenAI is None:
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return False
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seen: set[int] = set()
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current = model
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for _ in range(10):
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if isinstance(current, ChatOpenAI):
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return True
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current_id = id(current)
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if current_id in seen:
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return False
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seen.add(current_id)
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bound = getattr(current, "bound", None)
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if bound is None or bound is current:
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return False
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current = bound
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return False
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def _is_stale_reasoning_reference(block: dict[str, Any]) -> bool:
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if block.get("type") != "reasoning":
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return False
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if block.get("encrypted_content"):
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return False
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block_id = block.get("id")
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return isinstance(block_id, str) and block_id.startswith("rs_")
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def _sanitize_messages(messages: list[Any]) -> None:
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removed = 0
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for message in messages:
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if not isinstance(message, AIMessage) or not isinstance(message.content, list):
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continue
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content = []
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for block in message.content:
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if isinstance(block, dict) and _is_stale_reasoning_reference(block):
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removed += 1
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continue
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content.append(block)
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if len(content) != len(message.content):
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message.content = content
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if removed:
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logger.warning("Removed %d stale OpenAI Responses reasoning reference(s)", removed)
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class SanitizeOpenAIResponsesMiddleware(AgentMiddleware):
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"""Drop non-replayable OpenAI Responses reasoning item references."""
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def wrap_model_call(
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self,
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request: ModelRequest,
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handler: Callable[[ModelRequest], ModelResponse],
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) -> ModelCallResult:
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if _is_chat_openai(request.model):
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_sanitize_messages(request.messages)
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return handler(request)
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async def awrap_model_call(
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self,
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request: ModelRequest,
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handler: Callable[[ModelRequest], Awaitable[ModelResponse]],
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) -> Any:
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if _is_chat_openai(request.model):
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_sanitize_messages(request.messages)
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return await handler(request)
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