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"Research Assistant": Exploring UXs Besides Chat

"Research Assistant": Exploring UXs Besides Chat

TLDR: We’re excited to announce a new LangChain template for helping with research, heavily inspired by and in collaboration with the GPT Researcher team.

6 min read
LangChain Expands Collaboration with Microsoft

LangChain Expands Collaboration with Microsoft

Today, we’re thrilled to announce a collaboration between LangChain and Microsoft. LangChain helps developers build context-aware reasoning applications and powers some of the most

Case Studies 2 min read
Query Construction

Query Construction

Key Links * Text-to-metadata: Updated self-query docs and template * Text-to-SQL+semantic: Cookbook and template There's great interest in seamlessly connecting natural language with diverse

7 min read
Morningstar Intelligence Engine puts personalized investment insights at analysts' fingertips

Morningstar Intelligence Engine puts personalized investment insights at analysts' fingertips

Challenge Financial services is one of the most data-driven industries and financial professionals are always hungry for more data and better tools to drive value

Case Studies 2 min read
Parallel Function Calling for Structured Data Extraction

Parallel Function Calling for Structured Data Extraction

Important Links: * Cookbook for extraction using parallel function calling One of the biggest use cases for language models that we see is in extraction. This

4 min read
♠️ SPADE: Automatically Digging up Evals based on Prompt Refinements

♠️ SPADE: Automatically Digging up Evals based on Prompt Refinements

Written by Shreya Shankar (UC Berkeley) in collaboration with Haotian Li (HKUST), Will Fu-Hinthorn (LangChain), Harrison Chase (LangChain), J.D. Zamfirescu-Pereira (UC Berkeley), Yiming Lin

6 min read
Implementing advanced RAG strategies with Neo4j

Implementing advanced RAG strategies with Neo4j

Editor's note: We're excited to share this blogpost as it covers several of the advanced retrieval strategies we introduced in the

7 min read
Embeddings Drive the Quality of RAG: Voyage AI in Chat LangChain

Embeddings Drive the Quality of RAG: Voyage AI in Chat LangChain

Editor's Note: This post was written by the Voyage AI team. This post demonstrates that the choice of embedding models significantly impacts the

6 min read
LangChain Templates

LangChain Templates

Today we're excited to announce the release of LangChain Templates. LangChain Templates offers a collection of easily deployable reference architectures that anyone can

6 min read
Announcing Data Annotation Queues

Announcing Data Annotation Queues

💡Data Annotation Queues are a new feature in LangSmith, our developer platform aimed at helping bring LLM applications from prototype to production. Sign up for

4 min read
Query Transformations

Query Transformations

Naive RAG typically splits documents into chunks, embeds them, and retrieves chunks with high semantic similarity to a user question. But, this present a few

4 min read
LangChain's First Birthday

LangChain's First Birthday

It’s LangChain’s first birthday! It’s been a really exciting year! We worked with thousands of developers building LLM applications and tooling. We

By LangChain 15 min read

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