Checkpointers and Native Parent Child Retrievers with LangChain and MongoDB
Blog post from MongoDB
MongoDB has developed a new partnership with LangChain, a company known for its large language model application framework, to enhance their collaboration and provide developers with easier tools to build cutting-edge AI solutions. Two additional enhancements have been added to the LangChain codebase, including checkpointers that allow developers to persist graph state in MongoDB, providing a persistence layer and advantages such as human-in-the-loop interaction and memory between interactions. Additionally, a native parent child retriever has been implemented, enhancing performance by providing a broader context for LLMs to consider, allowing developers to store both parent and child documents in a single collection while only computing and indexing embedding vectors for the chunks. These new tools aim to provide a developer-friendly experience and improve the overall performance of AI solutions built on MongoDB.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 5 | 3,081 | 500 | 165 | -9% |
| AI Agents | 2 | 1,271 | 187 | 84 | +42% |
| RAG | 2 | 1,581 | 239 | 69 | -19% |
| Vector Search | 2 | 4,345 | 322 | 102 | +56% |
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