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Add simple app & query functionality - #1
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This commit enables anyone to create a app and add 3 types of data sources: * pdf file * youtube video * website It exposes a function called query which first gets similar docs from vector db and then passes it to LLM to get the final answer.
Adds a base chunker from which any chunker can inherit. Existing chunkers are refactored to inherit from this base chunker.
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Add simple app & query functionality
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[TicketNo.] US20251217073371 mem0ai#1 [Binary Source] NA
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- Add user identity to extraction preamble so memories are attributed to the correct user instead of cross-referencing cached patterns (OPE-6 #1) - Skip mem0.add() when no user messages remain after noise filtering, avoiding wasted API calls on assistant-only payloads (OPE-6 #2) - Raise auto-recall threshold to 0.6 (vs 0.5 for explicit search) and add dynamic thresholding that drops memories below 50% of the top result's score to reduce irrelevant context injection (OPE-6 #3) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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- Add user identity to extraction preamble so memories are attributed to the correct user instead of cross-referencing cached patterns (OPE-6 #1) - Skip mem0.add() when no user messages remain after noise filtering, avoiding wasted API calls on assistant-only payloads (OPE-6 #2) - Raise auto-recall threshold to 0.6 (vs 0.5 for explicit search) and add dynamic thresholding that drops memories below 50% of the top result's score to reduce irrelevant context injection (OPE-6 #3) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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- Add user identity to extraction preamble so memories are attributed to the correct user instead of cross-referencing cached patterns (OPE-6 #1) - Skip mem0.add() when no user messages remain after noise filtering, avoiding wasted API calls on assistant-only payloads (OPE-6 #2) - Raise auto-recall threshold to 0.6 (vs 0.5 for explicit search) and add dynamic thresholding that drops memories below 50% of the top result's score to reduce irrelevant context injection (OPE-6 #3) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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…operations # Fixes mem0ai#4490: Preserve original `actor_id` during memory UPDATE operations Fixes mem0ai#4490 ## Summary This PR attempts to fix an issue where `actor_id` metadata gets overwritten during UPDATE operations, breaking actor-level memory isolation in multi-actor scenarios. I've tested this fix locally and it seems to resolve the problem, but I would greatly appreciate maintainer review to ensure it aligns with the project's design goals. **Changes**: - Modified `_update_memory()` in `mem0/memory/main.py` (lines 1251-1252 and 2347-2349) - Changed conditional preservation to unconditional preservation of original `actor_id` ## Problem Statement Please see issue mem0ai#4490 for full details on the problem. **Quick summary**: When using `metadata={"actor_id": ...}` with shared `user_id` in multi-actor scenarios, the `actor_id` field appears to be overwritten when a different actor triggers an UPDATE event: ```python # Actor A creates memory m.add([{"role": "user", "content": "I am player mem0ai#1"}], user_id="team", metadata={"actor_id": "Alice"}) # ✓ Memory created with actor_id="Alice" # Actor B updates A's memory m.add([{"role": "user", "content": "Player mem0ai#1 is a good person"}], user_id="team", metadata={"actor_id": "Bob"}) # ❌ Memory updated but actor_id becomes "Bob" # Query fails m.search(query="", filters={"actor_id": "Alice"}) # Returns empty! ``` **Impact**: 1. Cannot query by original creator after UPDATE 2. Memory ownership tracking lost 3. Actor isolation fails in shared `user_id` scenarios ## Changes Made ### Code Changes **File**: `mem0/memory/main.py` **Location**: - Lines 1251-1252 (sync version of `_update_memory`) - Lines 2347-2348 (async version of `_update_memory`) **Before**: ```python if "actor_id" not in new_metadata and "actor_id" in existing_memory.payload: new_metadata["actor_id"] = existing_memory.payload["actor_id"] ``` **After**: ```python if "actor_id" in existing_memory.payload: new_metadata["actor_id"] = existing_memory.payload["actor_id"] ``` **Rationale**: Based on my investigation, it appears the condition check always evaluates to `False` because `new_metadata` contains the current actor's ID (passed from line 1668/1662). Removing this condition seems to make `actor_id` preservation work as (I believe) intended. This change treats `actor_id` as **"memory owner"** rather than **"last updater"**. The history table already tracks all contributors via `db.add_history()`, so update history is preserved. ## Testing ### Test Methodology I've attempted to validate this fix using a monkey patch approach that applies the proposed change to my local codebase without modifying source files. This allowed me to test the behavior before submitting the PR. ### Before Fix (Bug Demonstration) **Test scenario**: Alice creates a memory, Bob updates it with different `actor_id` **Result**: ``` === State AFTER Bob's UPDATE === Event: UPDATE This actor_id: 'Bob' ← Overwritten! ISOLATION TEST: Query Alice's memories: 0 found ❌ BUG: Alice's memory lost! ``` ### After Fix (Monkey Patch Validation) **Applied patch**: ```python from mem0.memory.main import Memory as MemoryClass def _patched_update_memory(self, memory_id, data, existing_embeddings, metadata=None): # ... (identical to original except actor_id handling) # ===== FIX ===== if "actor_id" in existing_memory.payload: new_metadata["actor_id"] = existing_memory.payload["actor_id"] # =============== # ... (rest unchanged) MemoryClass._update_memory = _patched_update_memory ``` **Result**: ``` === State AFTER Bob's UPDATE === Event: UPDATE This actor_id: 'Alice' ← Preserved! ISOLATION TEST: Query Alice's memories: 1 found ✅ SUCCESS: Alice's memory preserved! ``` ### Key Verification Points ✅ UPDATE event correctly triggered (not ADD) ✅ Memory content correctly updated ✅ `actor_id` preserved as original creator ✅ Query filtering by `actor_id` works correctly ✅ No side effects on other metadata fields ## Backward Compatibility To the best of my understanding, this change should not introduce breaking changes: - Existing code should continue to work without modification - API signature remains unchanged - Only affects behavior in multi-actor UPDATE scenarios - History table continues to track all contributors However, I may be missing some edge cases, so maintainer review would be greatly appreciated! ### Behavior Change Details **Before this fix:** When calling `add()` with a different `actor_id` that triggers an UPDATE event, the `actor_id` would be overwritten to the new actor. **After this fix:** The original `actor_id` (memory creator) is preserved during UPDATE operations. **Scenarios NOT affected:** - ✅ Calling `update()` method directly (already preserves `actor_id` correctly) - ✅ Updating memories without `actor_id` field (behavior unchanged) - ✅ Adding new memories (no UPDATE event triggered) **If you were relying on UPDATE to change `actor_id`:** You should use this pattern instead: ```python # Delete the old memory m.delete(memory_id) # Add a new memory with new actor m.add(..., metadata={"actor_id": "new_actor"}) ``` This change aligns with the semantic meaning of `actor_id` as the **memory creator** (immutable), not the **last updater** (tracked in history table). ## Additional Context ### Design Consistency This fix aligns with how other session identifiers are handled: ```python # Lines 1245-1250 already preserve these unconditionally (if not in new_metadata): if "user_id" not in new_metadata and "user_id" in existing_memory.payload: new_metadata["user_id"] = existing_memory.payload["user_id"] if "agent_id" not in new_metadata and "agent_id" in existing_memory.payload: new_metadata["agent_id"] = existing_memory.payload["agent_id"] if "run_id" not in new_metadata and "run_id" in existing_memory.payload: new_metadata["run_id"] = existing_memory.payload["run_id"] ``` The fix makes `actor_id` follow the same preservation pattern, but removes the always-false condition. ### Alternative Approaches I Considered I also thought about these alternatives, but decided against them (open to feedback though!): 1. **Track both `created_by` and `updated_by`** - Would require more complex schema changes - Less backward-compatible - Might not be necessary since history table already tracks updates 2. **Make preservation configurable** - Would add API complexity - I couldn't think of a clear use case for wanting `actor_id` to change - Seems to go against the semantic meaning of "actor" If either of these approaches seems better, I'm happy to revise the PR! ### Affected Implementations - ✅ Sync: `_update_memory()` (lines 1251-1252) - ✅ Async: `async _update_memory()` (lines 2347-2349) ## Checklist - [x] Code changes implemented (both sync and async) - [x] Tested with before/after comparison (monkey patch validation) - [x] Verified backward compatibility (to the best of my understanding) - [x] No breaking changes to existing API (as far as I can tell) - [x] Documented in PR description - [ ] Unit tests added (awaiting maintainer guidance on test location/structure) --- **Environment**: - Mem0 version: v1.0.7 - Python: 3.13 - Vector Store: Qdrant (local) Happy to make any adjustments based on maintainer feedback. Thanks for the great library!
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- require_admin: handle ADMIN_API_KEY and AUTH_DISABLED on fresh empty DB by falling through to allow bootstrap when no users exist yet, instead of raising 401 (Finding #1) - docker-compose healthcheck: use ${POSTGRES_USER:-postgres} instead of hardcoded -U postgres so custom POSTGRES_USER values work (Finding #2) - require_admin: restore request: Request param (needed for auth_type check) but now used in function body (Finding #7 resolved) - docs: sync migration guide password placeholder with README (Finding #9)
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内核 review（3 critical / 7 major / 4 minor）: - mem0ai#1 孤儿清扫改为单文档删除 + 宽限期 + 删前水位复核——不再整条 删除 entry 的已发布版本历史，且不会击中在途发布 - mem0ai#2 _state_flip 每轮 CAS 重读 head：并发 revise 后的 retire/reactivate 翻转最新状态，不再用陈旧快照回退已发布版本 - mem0ai#3 并发 revise 冲突后重算版本号：确定性 version _id 不再覆盖已发布 不可变版本（expand 证据链保持有效） - mem0ai#4 对账校验改为存在且匹配：陈旧 head 从已发布 version 重建； 事件 state_after 由水位事件推导（不再被陈旧 head 污染） - mem0ai#5 恢复路径用 version 文档的实际 scope_revision（claim 记录的是预测值） - mem0ai#6 已发布但 dedup 未落盘的 claim 补 ACTIVE 而非释放（防重复创建） - mem0ai#7 _get_doc 区分 404 与瞬时故障（防误判触发 claim 接管） - mem0ai#8 claim 接管围栏：最终 ACTIVE 写入前校验归属；reactivate 尊重 TTL - mem0ai#9 EmbeddingReconciler 条件向量写入（entry_version_id 围栏， 防 revise 竞态把旧向量盖章 ready） - mem0ai#10 purge 物理删除纳入派生重试 + 对账补齐（purged 水位触发清理） - mem0ai#11 SQL 兜底要求全部通道失败均为 UNAVAILABLE/TIMEOUT/THROTTLED （单个 400/401 类失败一票否决，防止配置错误被静默降级） - mem0ai#12 写者确定性失败时释放自己的 prepared claim（重试立即收敛） - mem0ai#14 alias 守卫改为别名级（防 v2 切换后双索引绑定） 新增 7 项并发/恢复回归测试（stale-head 翻转、双修订版本链、孤儿宽限、 陈旧 head 重建、条件向量、活 claim 补齐、兜底一票否决） 修复 FakeES NotFoundError 构造缺 body（此前被全捕获掩盖） E2E 复验: ONLY_VDB 36/36；全套件 820 通过
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…1 minor） - mem0ai#1(CRITICAL) 迁移 backfill 改 search_after 分页扫描——不再静默截断 1000 行上限（防永久数据丢失） - mem0ai#2 迁移对账改为强断言：五索引 refresh + track_total_hits 计数， scope/head/version/active-dedup 数量不一致即 ok=false - mem0ai#3 HYBRID 下 ES 探针非阻塞——ES 故障 → degraded（SQL FTS 继续服务， §10 表格语义），ONLY_VDB 保持 not_ready - mem0ai#4 /configure 构建成功后才提交 _current_config（防幻影配置） - mem0ai#5 legacy get_all 过期过滤改为日期比较（未来过期日不再隐藏记忆） - mem0ai#6 metadata/expiration-only revise 不再被 noop 吞掉；支持清除过期 （clear_expires_at 语义贯通 adapter→service→write） - mem0ai#7 legacy /search 元数据过滤改为真过滤（不再伪造命中 metadata） - mem0ai#8 vector_store shim 补全 serialize 契约（expiration_date/categories） + after_id 键集分页（/export 超 500 行不再截断） - mem0ai#9 MCP 中间件仅凭证解析在错误作用域内（传输/工具错误不再伪装 401） - mem0ai#10 挂载式 /mcp 同样套 McpAuthMiddleware（宿主收养 lifespan 时不再 暴露无鉴权服务级 API） - mem0ai#11 custom_instructions/分类体系/legacy prompt 真正贯通到抽取 LLM - mem0ai#12 /configure 拓扑拒绝 → 400（不再 500） - mem0ai#13 EntryNotActiveError(409) 替代裸 ContextError(500) - mem0ai#14 legacy add 的 updated 收敛映射为 event=UPDATE - mem0ai#15 content_hash/expires_at 补入 head/recall 输出（hash 不再恒 null） - mem0ai#16 MCP expand 空范围防护 + 单条目工具暴露完整 scope 字段 - mem0ai#17 /metrics 加鉴权（admin/内网语义 §7.6.2） - mem0ai#18 Sunset 头改为 RFC 8594 日期 - mem0ai#19 overrides 读失败跳过持久化（不再清空已存配置） - mem0ai#20 backfill 单行容错+失败清单、CAS 单次取 scope、消除 O(n²) 辅助 - mem0ai#21 legacy delete_all 循环分页（不再 5000 静默截断） - mem0ai#22 admin migrate 改后台任务 + job 轮询端点 新增 5 项 legacy 契约回归测试；全套件 825 通过；ONLY_VDB e2e 复验 36/36
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This enables anyone to create an app and add 3 types of data sources:
• pdf file
• youtube video
• website
It exposes a function called query which first gets similar docs from vector db and then passes it to LLM to get the final answer.