mirror of
https://github.com/bytedance/deer-flow.git
synced 2026-11-12 14:00:35 +00:00
1fbc06279a
* feat(benchmark): add offline memory vs project-context comparison suite (part of #7884) * fix(benchmark): route prompts through DynamicContextMiddleware, flatten rows, and share test run * refactor(benchmark): run through local Gateway and simplify first-pass suite (#7884) * docs(agents): keep context memory benchmark guidance within chain budget * fix(benchmark): verify DeerMem scope rejection --------- Co-authored-by: Totoro <msy626836554@gmail.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
1.9 KiB
1.9 KiB
Offline memory and project context comparison
This synthetic benchmark for #7884 starts a disposable Gateway in process with SQLite. It creates projects, shelf documents, threads and memory through the real API. A fixed model records the messages passed to it, and DeerMem receives scripted extraction responses.
Run this command from the backend directory of a Git checkout.
uv run python -m scripts.benchmark.context_memory_comparison run-offline --output-dir /tmp/context-memory
The command runs the committed fixtures and writes one report.json with
the source revision, benchmark and fixture hashes, and the observations below.
- Two projects and an unassigned thread must see only their own context and
the default memory bucket. A custom agent must see its own memory bucket.
The project-only check requires a successful update with exactly one fact
rejected for scope (
scope_rejectionsin the report). The fact must also be absent from default memory and from the other thread's prompt. - Replacement and deletion are observed in the store, in the original thread's next turn, and in a fresh thread. A first-turn canary verifies checkpoint reuse. The fresh thread is a control. If the original thread keeps a memory block from its checkpoint, the report records the stale fact and marks that check failed.
- Each recorded turn includes character-based token estimates for the
<memory>,<project>and<documents>blocks in its actual model request. The default and custom-agent observations identify the memory bucket being measured. These are estimates for the injected blocks.
The exit code is 0 when all behavioral checks pass and 1 when any fail. The benchmark uses synthetic data and fixed model responses. Gateway state is temporary, and the report contains canary IDs and counts rather than full prompts.