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[bot] Instrument Mem0 (470,878 weekly downloads)

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評估

難度
4/5
預估耗時
3-5 天
新手友好度
68/100
Issue 類型
功能
描述清晰度
基本清楚
活躍度
活躍
技術堆疊
python
領域
observability

研究方向

Start by reading the existing files under py/src/braintrust/integrations/ and py/src/braintrust/wrappers/, then inspect py/noxfile.py and the [tool.braintrust.matrix] section of py/pyproject.toml. Trace the Mem0 Memory and AsyncMemory entry points named in the issue and identify how integrations are registered and tested. Done means add coverage for add, search, and get_all, including their internal LLM and embedding work, with the integration, cassette directory, nox session, and matrix entry described in the issue.

由索引模型根據 Issue 內容生成。

描述

new-integration

Summary

mem0ai (import name mem0, by Mem0) is a widely used persistent-memory layer for LLM agents. Its core Memory class exposes .add(messages, user_id=...) and .search(query, filters={"user_id": ...}) as the primary execution surface. Critically, Memory().add() calls an LLM internally by default (OpenAI gpt-5-mini for fact extraction/updates, plus text-embedding-3-small for embeddings) to extract and consolidate facts from conversation messages before storing them — this is a genuine LLM-driven execution step, not just a database write, and it happens invisibly to Braintrust today.

This repository has zero instrumentation for Mem0 anywhere: no py/src/braintrust/integrations/mem0* directory, no wrapper, no nox session, no cassette directory, and no entry in py/pyproject.toml's [tool.braintrust.matrix].

What's missing

  • Memory.add() / AsyncMemory.add() — stores new memories from a message list; internally triggers an LLM call for fact extraction/update plus an embedding call, both currently untraced.
  • Memory.search() / AsyncMemory.search() — retrieves relevant memories via vector search, filtered by user_id/other filters; the core "memory retrieval" step in an agent's context-assembly loop.
  • Memory.get_all() — full CRUD listing of stored memories for a given filter scope.

Weekly downloads

Weekly downloads: 470,878 (as of 2026-09-28; https://pypistats.org/api/packages/mem0ai/recent)

Braintrust docs status

not_found. Checked https://www.braintrust.dev/docs/guides/tracing and https://www.braintrust.dev/docs/guides/tracing/integrations (both checked 2026-09-28) — neither the tracing-integrations list nor the agent-framework list ("Agno, OpenAI Agents SDK, Claude Agent SDK, Pi Coding Agent SDK, Deep Agents, LangGraph, CrewAI, AutoGen, AgentScope, Google ADK, LiveKit Agents, Mastra, Pipecat, Pydantic AI, Strands Agents SDK, Cloudflare Agents, Cloudflare AI Chat") mentions Mem0.

Upstream sources

Braintrust docs sources checked

Local repo files inspected

  • py/src/braintrust/integrations/ — no mem0/ directory
  • py/src/braintrust/wrappers/ — no Mem0 wrapper
  • py/pyproject.toml [tool.braintrust.matrix] — no mem0ai entry
  • py/noxfile.py — no test_mem0 session
  • Repo-wide case-insensitive grep for import mem0/from mem0/mem0ai under py/src/braintrust/**/*.py — zero matches
主要語言
Python
星號
22
分支
27
平均合併
14 小時 49 分鐘
30 天內合併 PR
126

環境準備

  • 提供 Dockerfile 或 Docker Compose 檔案
  • 沒有 Pull Request 範本
  • 閱讀貢獻指南

從這裡開始

  1. 先讀完整個 Issue，再讀專案的貢獻指南。
  2. 在 Issue 下留言說明你要接手 —— 這能避免兩個人做同樣的事。
  3. Fork 儲存庫，在一個分支上完成修改。
  4. 送出 Pull Request，並在描述裡引用這個 Issue 編號。

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