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chore: update changelog, bump SDK versions to Python 2.0.12 and TypeScript 3.1.0 (#6281)

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Kartik
2026-07-13 22:11:51 +05:30
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parent d89793b666
commit 42cf18c4e6
7 changed files with 82 additions and 5 deletions
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cli/node/package.json
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@@ -1,6 +1,6 @@
{
"name": "@mem0/cli",
"version": "0.2.10",
"version": "0.2.11",
"description": "The official CLI for mem0 — the memory layer for AI agents",
"type": "module",
"bin": {
cli/python/pyproject.toml
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@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
[project]
name = "mem0-cli"
version = "0.2.9"
version = "0.2.10"
description = "The official CLI for mem0 — the memory layer for AI agents"
readme = "README.md"
license = "Apache-2.0"
cli/python/src/mem0_cli/__init__.py
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@@ -1,3 +1,3 @@
"""mem0 CLI — the command-line interface for the mem0 memory layer."""
__version__ = "0.2.9"
__version__ = "0.2.10"
docs/changelog/highlights.mdx
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@@ -4,6 +4,22 @@ description: "Major product launches, headline features, and milestones for Mem0
mode: "wide"
---
<Update label="2026-07-13" description="TypeScript provider expansion">
**TypeScript OSS SDK: 26 New Providers, Reranking, and Zero-Dependency Imports**
TypeScript SDK v3.1.0 is the largest provider release for the OSS SDK so far, closing most of the remaining gap with the Python SDK. Python SDK v2.0.12 ships alongside it with fixes and security patches.
- **17 new vector stores:** Pinecone, Weaviate, Milvus, Chroma, MongoDB, Elasticsearch, OpenSearch, Databricks, AWS Neptune Analytics, S3 Vectors, Azure MySQL, Google Vertex AI Vector Search, Turbopuffer, Upstash Vector, Valkey, Cassandra, and Baidu Mochow.
- **5 new LLM providers:** AWS Bedrock, xAI Grok, Together, vLLM, and Sarvam.
- **4 new embedding providers:** Vertex AI, HuggingFace, FastEmbed, and Together.
- **Reranking in TypeScript:** Four rerankers (Cohere, ZeroEntropy, cross-encoder, and LLM-based) with per-search rerank via a `rerank` option on `search()`.
- **Install only what you use:** Importing `mem0ai/oss` no longer pulls in any provider SDK. Provider packages are resolved lazily on first use, so an app that configures only OpenAI and Qdrant does not need the other provider SDKs installed.
See [SDK & Tools](/changelog/sdk) for version details and PR links.
</Update>
<Update label="2026-06-27" description="SDK memory expiration">
**SDK Memory Expiration: Expiring Memories Across Python and TypeScript**
docs/changelog/sdk.mdx
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@@ -7,6 +7,34 @@ mode: "wide"
<Tabs>
<Tab title="Python">
<Update label="2026-07-13" description="v2.0.12">
**New Features:**
- **Memory (OSS):** Accept `text` in `Memory.update()` and `AsyncMemory.update()`. `data` still works but is now deprecated, so prefer `text` in new code ([#6044](https://github.com/mem0ai/mem0/pull/6044))
**Bug Fixes:**
- **Core:** Coerce non-string entity IDs (`user_id`, `agent_id`, `run_id`) instead of crashing on `.strip()`, so passing an integer ID no longer raises `AttributeError` ([#6206](https://github.com/mem0ai/mem0/pull/6206))
- **Core:** Stop requiring `langchain-core` for the default async procedural memory path. The optional dependency is now only imported when you pass a custom LangChain LLM, matching the sync behavior ([#6209](https://github.com/mem0ai/mem0/pull/6209))
- **Client:** Encode dynamic URL path segments so IDs containing special characters no longer produce malformed requests ([#5963](https://github.com/mem0ai/mem0/pull/5963))
- **LLMs:** Skip `temperature` and `top_p` for newer Anthropic models that reject sampling parameters. Detection is automatic per model family and version, and the new `enable_sampling_parameters` config flag overrides it ([#6211](https://github.com/mem0ai/mem0/pull/6211))
- **Vector Stores:** Stop writing internal `OutputData` model fields as properties on Weaviate `update()` ([#6149](https://github.com/mem0ai/mem0/pull/6149))
- **Vector Stores:** Improve wildcard search handling in Milvus ([#6187](https://github.com/mem0ai/mem0/pull/6187))
- **Vector Stores:** Keep env-resolved Upstash Vector credentials after config validation. An env-var-only config previously passed validation and then failed to build ([#5811](https://github.com/mem0ai/mem0/pull/5811))
- **Vector Stores:** Restore the previous payload when a Neptune Analytics vector upsert fails inside `update()`, so a partial write can no longer leave the payload and embedding out of sync ([#5824](https://github.com/mem0ai/mem0/pull/5824))
**Changes:**
- **LLMs:** The Together default model is now `MiniMaxAI/MiniMax-M3` (was `mistralai/Mixtral-8x7B-Instruct-v0.1`) ([#6049](https://github.com/mem0ai/mem0/pull/6049))
- **LLMs:** The xAI default model is now `grok-4.3` (was `grok-2-latest`) ([#6115](https://github.com/mem0ai/mem0/pull/6115))
- **Embeddings:** The Together default embedding model is now `intfloat/multilingual-e5-large-instruct` at 1024 dimensions (was `togethercomputer/m2-bert-80M-8k-retrieval` at 768). If you use the Together embedder without pinning `model`, existing vectors were written at the old dimension: either re-embed them, or pin `model` and `embedding_dims` to the old values ([#5989](https://github.com/mem0ai/mem0/pull/5989))
- **Rerankers:** The Cohere default rerank model is now `rerank-v3.5` (was `rerank-english-v3.0`) ([#6055](https://github.com/mem0ai/mem0/pull/6055))
**Security:**
- **Vector Stores:** Fix SQL and Cypher injection vulnerabilities in the PGVector, Azure MySQL, and Neptune providers ([#4878](https://github.com/mem0ai/mem0/pull/4878))
- **Vector Stores:** Validate Elasticsearch filter keys and values to prevent term query injection ([#5980](https://github.com/mem0ai/mem0/pull/5980))
- **Dependencies:** Require `transformers>=5.3.0` to remediate GHSA-29pf-2h5f-8g72 (CVE-2026-4372) ([#6110](https://github.com/mem0ai/mem0/pull/6110))
</Update>
<Update label="2026-07-01" description="v2.0.11">
**Bug Fixes:**
@@ -1100,6 +1128,32 @@ See the [OSS v2 to v3 migration guide](https://docs.mem0.ai/migration/oss-v2-to-
<Tab title="TypeScript">
<Update label="2026-07-13" description="v3.1.0">
The largest provider release for the TypeScript OSS SDK so far: 17 new vector stores, 5 new LLM providers, 4 new embedders, and reranking support. Importing `mem0ai/oss` no longer pulls in any provider SDK, so you only install what you actually configure.
**New Features:**
- **Rerankers:** Add reranking to the OSS SDK with four providers (Cohere, ZeroEntropy, cross-encoder, and LLM-based), plus per-search rerank via a `rerank` option on `search()` ([#6055](https://github.com/mem0ai/mem0/pull/6055))
- **Memory (OSS):** Accept `text` in `Memory.update()`. `data` still works but is now deprecated, so prefer `text` in new code ([#6044](https://github.com/mem0ai/mem0/pull/6044))
- **Vector Stores:** Add Pinecone ([#5802](https://github.com/mem0ai/mem0/pull/5802)), Weaviate ([#5800](https://github.com/mem0ai/mem0/pull/5800)), Milvus ([#5889](https://github.com/mem0ai/mem0/pull/5889)), Chroma ([#6145](https://github.com/mem0ai/mem0/pull/6145)), MongoDB ([#5793](https://github.com/mem0ai/mem0/pull/5793)), Elasticsearch ([#5866](https://github.com/mem0ai/mem0/pull/5866)), and OpenSearch ([#5810](https://github.com/mem0ai/mem0/pull/5810))
- **Vector Stores:** Add Databricks ([#5824](https://github.com/mem0ai/mem0/pull/5824)), AWS Neptune Analytics ([#5797](https://github.com/mem0ai/mem0/pull/5797)), S3 Vectors ([#5822](https://github.com/mem0ai/mem0/pull/5822)), Azure MySQL ([#5827](https://github.com/mem0ai/mem0/pull/5827)), and Google Vertex AI Vector Search ([#5791](https://github.com/mem0ai/mem0/pull/5791))
- **Vector Stores:** Add Turbopuffer ([#5801](https://github.com/mem0ai/mem0/pull/5801)), Upstash Vector ([#5811](https://github.com/mem0ai/mem0/pull/5811)), Valkey ([#5826](https://github.com/mem0ai/mem0/pull/5826)), Cassandra ([#5823](https://github.com/mem0ai/mem0/pull/5823)), and Baidu Mochow ([#5790](https://github.com/mem0ai/mem0/pull/5790))
- **LLMs:** Add AWS Bedrock ([#5890](https://github.com/mem0ai/mem0/pull/5890)), xAI Grok ([#6115](https://github.com/mem0ai/mem0/pull/6115)), Together ([#6049](https://github.com/mem0ai/mem0/pull/6049)), vLLM ([#5805](https://github.com/mem0ai/mem0/pull/5805)), and Sarvam ([#6130](https://github.com/mem0ai/mem0/pull/6130))
- **Embeddings:** Add Vertex AI ([#5882](https://github.com/mem0ai/mem0/pull/5882)), HuggingFace ([#6027](https://github.com/mem0ai/mem0/pull/6027)), FastEmbed ([#5862](https://github.com/mem0ai/mem0/pull/5862)), and Together ([#5989](https://github.com/mem0ai/mem0/pull/5989))
**Improvements:**
- **Packaging:** Lazy-load optional provider SDKs so importing `mem0ai/oss` never requires them. Provider packages are now resolved on first use, so an app that only configures OpenAI and Qdrant does not need the other provider SDKs installed ([#6280](https://github.com/mem0ai/mem0/pull/6280))
**Bug Fixes:**
- **Memory (OSS):** Re-raise LLM extraction transport failures instead of returning `[]`, so a network error during extraction surfaces as an error rather than a silently empty result ([#6102](https://github.com/mem0ai/mem0/pull/6102))
- **Vector Stores:** Prevent an unhandled promise rejection in the Supabase and Redis constructors ([#6111](https://github.com/mem0ai/mem0/pull/6111))
- **Client:** Encode dynamic URL path segments so IDs containing special characters no longer produce malformed requests ([#5963](https://github.com/mem0ai/mem0/pull/5963))
**Security:**
- **Dependencies:** Patch the `fast-xml-parser` and `tar` transitive CVEs ([#6160](https://github.com/mem0ai/mem0/pull/6160))
</Update>
<Update label="2026-07-01" description="v3.0.13">
**Bug Fixes:**
@@ -1606,6 +1660,13 @@ See the [TypeScript SDK migration guide](https://docs.mem0.ai/migration/ts-v2-to
<Tab title="CLI">
<Update label="2026-07-13" description="Python v0.2.10 / Node v0.2.11">
**Bug Fixes:**
- **Platform backend:** Encode dynamic URL path segments so memory and entity IDs containing special characters no longer produce malformed requests (Python and Node [#5963](https://github.com/mem0ai/mem0/pull/5963))
</Update>
<Update label="2026-07-01" description="Python v0.2.9 / Node v0.2.10">
**Bug Fixes:**
mem0-ts/package.json
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{
"name": "mem0ai",
"version": "3.0.13",
"version": "3.1.0",
"description": "The Memory Layer For Your AI Apps",
"main": "./dist/index.js",
"module": "./dist/index.mjs",
pyproject.toml
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@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
[project]
name = "mem0ai"
version = "2.0.11"
version = "2.0.12"
description = "Long-term memory for AI Agents"
authors = [
{ name = "Mem0", email = "support@mem0.ai" }