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https://github.com/MODSetter/SurfSense.git
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fix: summarization middleware usage
This commit is contained in:
parent
5353d4587f
commit
bd2d6c07ff
5 changed files with 206 additions and 114 deletions
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@ -24,7 +24,6 @@ from deepagents.backends import StateBackend
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from deepagents.graph import BASE_AGENT_PROMPT
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from deepagents.middleware.patch_tool_calls import PatchToolCallsMiddleware
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from deepagents.middleware.subagents import GENERAL_PURPOSE_SUBAGENT
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from deepagents.middleware.summarization import create_summarization_middleware
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from langchain.agents import create_agent
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from langchain.agents.middleware import TodoListMiddleware
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from langchain_anthropic.middleware import AnthropicPromptCachingMiddleware
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@ -41,6 +40,9 @@ from app.agents.new_chat.middleware import (
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MemoryInjectionMiddleware,
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SurfSenseFilesystemMiddleware,
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)
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from app.agents.new_chat.middleware.safe_summarization import (
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create_safe_summarization_middleware,
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)
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from app.agents.new_chat.system_prompt import (
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build_configurable_system_prompt,
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build_surfsense_system_prompt,
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@ -442,7 +444,7 @@ async def create_surfsense_deep_agent(
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created_by_id=user_id,
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thread_id=thread_id,
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),
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create_summarization_middleware(llm, StateBackend),
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create_safe_summarization_middleware(llm, StateBackend),
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PatchToolCallsMiddleware(),
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AnthropicPromptCachingMiddleware(unsupported_model_behavior="ignore"),
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]
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@ -472,7 +474,7 @@ async def create_surfsense_deep_agent(
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thread_id=thread_id,
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),
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SubAgentMiddleware(backend=StateBackend, subagents=[general_purpose_spec]),
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create_summarization_middleware(llm, StateBackend),
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create_safe_summarization_middleware(llm, StateBackend),
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PatchToolCallsMiddleware(),
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DedupHITLToolCallsMiddleware(agent_tools=tools),
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AnthropicPromptCachingMiddleware(unsupported_model_behavior="ignore"),
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@ -0,0 +1,125 @@
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"""Safe wrapper around deepagents' SummarizationMiddleware.
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Upstream issue
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--------------
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`deepagents.middleware.summarization.SummarizationMiddleware._aoffload_to_backend`
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(and its sync counterpart) call
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``get_buffer_string(filtered_messages)`` before writing the evicted history
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to the backend file. In recent ``langchain-core`` versions, ``get_buffer_string``
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accesses ``m.text`` which iterates ``self.content`` — this raises
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``TypeError: 'NoneType' object is not iterable`` whenever an ``AIMessage``
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has ``content=None`` (common when a model returns *only* tool_calls, seen
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frequently with Azure OpenAI ``gpt-5.x`` responses streamed through
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LiteLLM).
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The exception aborts the whole agent turn, so the user just sees "Error during
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chat" with no assistant response.
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Fix
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---
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We subclass ``SummarizationMiddleware`` and override
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``_filter_summary_messages`` — the only call site that feeds messages into
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``get_buffer_string`` — to return *copies* of messages whose ``content`` is
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``None`` with ``content=""``. The originals flowing through the rest of the
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agent state are untouched.
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We also expose a drop-in ``create_safe_summarization_middleware`` factory
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that mirrors ``deepagents.middleware.summarization.create_summarization_middleware``
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but instantiates our safe subclass.
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"""
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from __future__ import annotations
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import logging
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from typing import TYPE_CHECKING
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from deepagents.middleware.summarization import (
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SummarizationMiddleware,
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compute_summarization_defaults,
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)
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if TYPE_CHECKING:
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from deepagents.backends.protocol import BACKEND_TYPES
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from langchain_core.language_models import BaseChatModel
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from langchain_core.messages import AnyMessage
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logger = logging.getLogger(__name__)
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def _sanitize_message_content(msg: "AnyMessage") -> "AnyMessage":
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"""Return ``msg`` with ``content`` coerced to a non-``None`` value.
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``get_buffer_string`` reads ``m.text`` which iterates ``self.content``;
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when a provider streams back an ``AIMessage`` with only tool_calls and
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no text, ``content`` can be ``None`` and the iteration explodes. We
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replace ``None`` with an empty string so downstream consumers that only
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care about text see an empty body.
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The original message is left untouched — we return a copy via
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pydantic's ``model_copy`` when available, otherwise we fall back to
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re-setting the attribute on a shallow copy.
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"""
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if getattr(msg, "content", "not-missing") is not None:
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return msg
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try:
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return msg.model_copy(update={"content": ""})
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except AttributeError:
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import copy
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new_msg = copy.copy(msg)
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try:
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new_msg.content = ""
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except Exception: # pragma: no cover - defensive
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logger.debug(
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"Could not sanitize content=None on message of type %s",
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type(msg).__name__,
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)
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return msg
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return new_msg
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class SafeSummarizationMiddleware(SummarizationMiddleware):
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"""`SummarizationMiddleware` that tolerates messages with ``content=None``.
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Only ``_filter_summary_messages`` is overridden — this is the single
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helper invoked by both the sync and async offload paths immediately
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before ``get_buffer_string``. Normalising here means we get coverage
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for both without having to copy the (long, rapidly-changing) offload
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implementations from upstream.
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"""
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def _filter_summary_messages(
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self, messages: "list[AnyMessage]"
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) -> "list[AnyMessage]":
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filtered = super()._filter_summary_messages(messages)
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return [_sanitize_message_content(m) for m in filtered]
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def create_safe_summarization_middleware(
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model: "BaseChatModel",
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backend: "BACKEND_TYPES",
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) -> SafeSummarizationMiddleware:
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"""Drop-in replacement for ``create_summarization_middleware``.
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Mirrors the defaults computed by ``deepagents`` but returns our
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``SafeSummarizationMiddleware`` subclass so the
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``content=None`` crash in ``get_buffer_string`` is avoided.
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"""
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defaults = compute_summarization_defaults(model)
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return SafeSummarizationMiddleware(
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model=model,
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backend=backend,
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trigger=defaults["trigger"],
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keep=defaults["keep"],
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trim_tokens_to_summarize=None,
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truncate_args_settings=defaults["truncate_args_settings"],
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)
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__all__ = [
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"SafeSummarizationMiddleware",
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"create_safe_summarization_middleware",
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]
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@ -74,7 +74,7 @@ dependencies = [
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"deepagents>=0.4.12",
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"stripe>=15.0.0",
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"azure-ai-documentintelligence>=1.0.2",
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"litellm>=1.83.0",
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"litellm>=1.83.4",
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"langchain-litellm>=0.6.4",
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]
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2
surfsense_backend/uv.lock
generated
2
surfsense_backend/uv.lock
generated
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@ -8070,7 +8070,7 @@ requires-dist = [
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{ name = "langgraph", specifier = ">=1.1.3" },
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{ name = "langgraph-checkpoint-postgres", specifier = ">=3.0.2" },
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{ name = "linkup-sdk", specifier = ">=0.2.4" },
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{ name = "litellm", specifier = ">=1.83.0" },
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{ name = "litellm", specifier = ">=1.83.4" },
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{ name = "llama-cloud-services", specifier = ">=0.6.25" },
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{ name = "markdown", specifier = ">=3.7" },
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{ name = "markdownify", specifier = ">=0.14.1" },
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