build(deps): bump mem0ai from 0.1.117 to 2.0.12 in /sdk

[dependabot]

Bumps mem0ai from 0.1.117 to 2.0.12.

Release notes

Sourced from mem0ai's releases.

Mem0 Python SDK (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)

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)
• 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)
• Client: Encode dynamic URL path segments so IDs containing special characters no longer produce malformed requests (#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)
• Vector Stores: Stop writing internal OutputData model fields as properties on Weaviate update() (#6149)
• Vector Stores: Improve wildcard search handling in Milvus (#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)
• 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)

Changes:

• LLMs: The Together default model is now MiniMaxAI/MiniMax-M3 (was mistralai/Mixtral-8x7B-Instruct-v0.1) (#6049)
• LLMs: The xAI default model is now grok-4.3 (was grok-2-latest) (#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)
• Rerankers: The Cohere default rerank model is now rerank-v3.5 (was rerank-english-v3.0) (#6055)

Security:

• Vector Stores: Fix SQL and Cypher injection vulnerabilities in the PGVector, Azure MySQL, and Neptune providers (#4878)
• Vector Stores: Validate Elasticsearch filter keys and values to prevent term query injection (#5980)
• Dependencies: Require transformers>=5.3.0 to remediate GHSA-29pf-2h5f-8g72 (CVE-2026-4372) (#6110)

Mem0 Python SDK (v2.0.11)

Bug Fixes:

• Embeddings: Guard against an embed_batch count mismatch in the OpenAI and Azure OpenAI embedders (#5966)
• Memory: Re-raise LLM extraction failures instead of silently returning [] (#5878)
• Vector Stores: Normalize vectors for the cosine distance strategy in FAISS (#5960)

Security:

• Vector Stores: Validate OpenSearch filter values to prevent term query injection (#5986)
• Vector Stores: Validate value types and escape quotes in Azure AI Search OData filters (#5983)
• Vector Stores: Validate Databricks catalog/schema/table identifiers to prevent SQL injection (#5988)
• Graph: Escape Neptune filter values in openCypher queries to prevent injection (#5982)

Mem0 Python SDK (v2.0.10)

New Features:

• Client: Expose expiration_date on MemoryClient.update() and AsyncMemoryClient.update() — callers can now set or clear a memory's expiration date; None is preserved and forwarded to the API (#5874)

Bug Fixes:

• Memory (OSS): Apply remove_code_blocks() to the LangChain path in async _create_procedural_memory so code fences are stripped consistently (#5711)
• Rerankers: Score HuggingFace cross-encoder results with per-document sigmoid instead of set-relative min-max, preventing a single low-score document from collapsing all relevance scores to zero (#5715)
• Core: Validate and trim entity IDs (user_id, agent_id, run_id) in delete_all() for both sync and async Memory (#5735)
• Vector Stores: Use .get() for hash and created_at in the Redis insert() and update() paths so entity payloads that omit those fields no longer raise KeyError (#5709)
• Memory: Fix scale-threshold notices not firing for Redis and search-engine backends by resolving col_info() signature differences and adding num_docs to the count-extraction lookup (#5687)

... (truncated)

Commits

• 42cf18c chore: update changelog, bump SDK versions to Python 2.0.12 and TypeScript 3....
• d89793b refactor(ts-sdk): lazy-load optional provider SDKs so importing mem0ai/oss ne...
• 1783674 feat(vector-stores): add Databricks provider to TypeScript OSS SDK (#5824)
• c9af559 fix(anthropic): Remove sampling parameters when using new model. (#6211)
• f69f8dc fix(weaviate): don't write OutputData model fields as properties on update (#...
• 28e4d81 fix(ts-sdk): re-raise LLM extraction transport failures instead of returning ...
• 1d383c4 fix(vector-stores): improve milvus wildcard search (#6187)
• 8488abe docs: correct custom categories, per-call custom_categories is supported (#6218)
• 49863e9 docs: add a dedicated Memory Expiration page (#6194)
• 770ce97 fix(core): coerce non-string entity ids instead of crashing on .strip() (#6206)
• Additional commits viewable in compare view

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[JasonW404]

mem0ai 从 0.1.117 升级到 2.0.7 是 major version bump（从 0.x 到 2.x），这意味着 API 可能有大量不兼容变更。从 release notes 看，v2 重构了 vector store 接口、修复了大量 crash 问题。请确认项目中 mem0ai 的调用代码是否已适配 v2 API，特别是 Memory 初始化和 vector store 配置部分。