LangChain Templates

LangChain · Beginner ·🤖 AI Agents & Automation ·2y ago

Key Takeaways

LangChain Templates provide easily deployable reference architectures for developers to quickly get to production, featuring a collection of templates for chains and agents in a standard format, deployable with LangServe.

Original Description

Introduction and overview of LangChain Templates LangChain Templates offers a collection of easily deployable reference architectures that anyone can use. We've worked with some of our partners to create a set of easy-to-use templates to help developers get to production more quickly. We will continue to add to this over time. This is a new way to create, share, maintain, download, and customize chains and agents. They are all in a standard format with allows them to easily be deployed with LangServe, allowing you to easily get production-ready APIs and a playground for free. Key Links Quick Start: Go here for a guide on how to get started with LangChain Templates. https://github.com/langchain-ai/langchain/blob/master/templates/README.md Featured Templates: Explore the many templates available to use - from advanced RAG to agents. https://github.com/langchain-ai/langchain/blob/master/templates/docs/INDEX.md All Templates: Explore all templates available. https://github.com/langchain-ai/langchain/tree/master/templates Contributing: Want to contribute your own template? It's pretty easy! These instructions walk through how to do that. https://github.com/langchain-ai/langchain/blob/master/templates/docs/CONTRIBUTING.md LangServe: Learn more about the best way to deploy LangChain chains and agents. https://github.com/langchain-ai/langserve Hosted LangServe: We will be releasing a hosted version of LangServe for one-click deployments of LangChain applications. Sign up here: https://airtable.com/app0hN6sd93QcKubv/shrAjst60xXa6quV2
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Playlist

Uploads from LangChain · LangChain · 20 of 60

1 Chat With Your Documents Using LangChain + JavaScript
Chat With Your Documents Using LangChain + JavaScript
LangChain
2 LangChain SQL Webinar
LangChain SQL Webinar
LangChain
3 LangChain "OpenAI functions" Webinar
LangChain "OpenAI functions" Webinar
LangChain
4 LangSmith Launch
LangSmith Launch
LangChain
5 LangChain x Pinecone: Supercharging Llama-2 with RAG
LangChain x Pinecone: Supercharging Llama-2 with RAG
LangChain
6 LangChain Expression Language
LangChain Expression Language
LangChain
7 Building LLM applications with LangChain with Lance
Building LLM applications with LangChain with Lance
LangChain
8 Benchmarking Question/Answering Over CSV Data
Benchmarking Question/Answering Over CSV Data
LangChain
9 LangChain "RAG Evaluation" Webinar
LangChain "RAG Evaluation" Webinar
LangChain
10 Fine-tuning in Your Voice Webinar
Fine-tuning in Your Voice Webinar
LangChain
11 Tabular Data Retrieval
Tabular Data Retrieval
LangChain
12 Building an LLM Application with Audio by AssemblyAI
Building an LLM Application with Audio by AssemblyAI
LangChain
13 Superagent Deepdive Webinar
Superagent Deepdive Webinar
LangChain
14 Lessons from Deploying LLMs with LangSmith
Lessons from Deploying LLMs with LangSmith
LangChain
15 Shortwave Assistant Deepdive Webinar
Shortwave Assistant Deepdive Webinar
LangChain
16 Cognitive Architectures for Language Agents
Cognitive Architectures for Language Agents
LangChain
17 Effectively Building with LLMs in the Browser with Jacob
Effectively Building with LLMs in the Browser with Jacob
LangChain
18 Data Privacy for LLMs
Data Privacy for LLMs
LangChain
19 "Theory of Mind" Webinar with Plastic Labs
"Theory of Mind" Webinar with Plastic Labs
LangChain
LangChain Templates
LangChain Templates
LangChain
21 Using Natural Language to Query Postgres with Jacob
Using Natural Language to Query Postgres with Jacob
LangChain
22 Building a Research Assistant from Scratch
Building a Research Assistant from Scratch
LangChain
23 Benchmarking RAG over LangChain Docs
Benchmarking RAG over LangChain Docs
LangChain
24 Skeleton-of-Thought: Building a New Template from Scratch
Skeleton-of-Thought: Building a New Template from Scratch
LangChain
25 Benchmarking Methods for Semi-Structured RAG
Benchmarking Methods for Semi-Structured RAG
LangChain
26 LangSmith Highlights: Getting Started
LangSmith Highlights: Getting Started
LangChain
27 LangSmith Highlights: Debugging
LangSmith Highlights: Debugging
LangChain
28 LangSmith Highlights: Datasets
LangSmith Highlights: Datasets
LangChain
29 LangSmith Highlights: Evaluation
LangSmith Highlights: Evaluation
LangChain
30 LangSmith Highlights: Human Annotation
LangSmith Highlights: Human Annotation
LangChain
31 LangSmith Highlights: Monitoring
LangSmith Highlights: Monitoring
LangChain
32 LangSmith Highlights: Hub
LangSmith Highlights: Hub
LangChain
33 SQL Research Assistant
SQL Research Assistant
LangChain
34 Getting Started with Multi-Modal LLMs
Getting Started with Multi-Modal LLMs
LangChain
35 Build a Full Stack RAG App With TypeScript
Build a Full Stack RAG App With TypeScript
LangChain
36 Auto-Prompt Builder (with Hosted LangServe)
Auto-Prompt Builder (with Hosted LangServe)
LangChain
37 LangChain v0.1.0 Launch: Introduction
LangChain v0.1.0 Launch: Introduction
LangChain
38 LangChain v0.1.0 Launch: Observability
LangChain v0.1.0 Launch: Observability
LangChain
39 LangChain v0.1.0 Launch: Integrations
LangChain v0.1.0 Launch: Integrations
LangChain
40 LangChain v0.1.0 Launch: Composability
LangChain v0.1.0 Launch: Composability
LangChain
41 LangChain v0.1.0 Launch: Streaming
LangChain v0.1.0 Launch: Streaming
LangChain
42 LangChain v0.1.0 Launch: Output Parsing
LangChain v0.1.0 Launch: Output Parsing
LangChain
43 LangChain v0.1.0 Launch: Retrieval
LangChain v0.1.0 Launch: Retrieval
LangChain
44 LangChain v0.1.0 Launch: Agents
LangChain v0.1.0 Launch: Agents
LangChain
45 Build and Deploy a RAG app with Pinecone Serverless
Build and Deploy a RAG app with Pinecone Serverless
LangChain
46 Hosted LangServe + LangChain Templates
Hosted LangServe + LangChain Templates
LangChain
47 LangGraph: Intro
LangGraph: Intro
LangChain
48 LangGraph: Agent Executor
LangGraph: Agent Executor
LangChain
49 LangGraph: Chat Agent Executor
LangGraph: Chat Agent Executor
LangChain
50 LangGraph: Human-in-the-Loop
LangGraph: Human-in-the-Loop
LangChain
51 LangGraph: Dynamically Returning a Tool Output Directly
LangGraph: Dynamically Returning a Tool Output Directly
LangChain
52 LangGraph: Respond in a Specific Format
LangGraph: Respond in a Specific Format
LangChain
53 LangGraph: Managing Agent Steps
LangGraph: Managing Agent Steps
LangChain
54 LangGraph: Force-Calling a Tool
LangGraph: Force-Calling a Tool
LangChain
55 LangGraph: Multi-Agent Workflows
LangGraph: Multi-Agent Workflows
LangChain
56 Streaming Events: Introducing a new `stream_events` method
Streaming Events: Introducing a new `stream_events` method
LangChain
57 Building a web RAG chatbot: using LangChain, Exa (prev. Metaphor), LangSmith, and Hosted Langserve
Building a web RAG chatbot: using LangChain, Exa (prev. Metaphor), LangSmith, and Hosted Langserve
LangChain
58 OpenGPTs
OpenGPTs
LangChain
59 Open Source RAG with Nomic's New Embedding Model (and ChromaDB and Ollama)
Open Source RAG with Nomic's New Embedding Model (and ChromaDB and Ollama)
LangChain
60 LangGraph: Persistence
LangGraph: Persistence
LangChain

LangChain Templates provide a collection of easily deployable reference architectures for developers to quickly get to production, featuring a standard format for chains and agents, deployable with LangServe. This allows for rapid creation, sharing, maintenance, download, and customization of templates, enabling developers to easily get production-ready APIs and a playground for free.

Key Takeaways
  1. Explore the LangChain Templates repository
  2. Choose a template to deploy
  3. Follow the Quick Start guide
  4. Customize the template as needed
  5. Deploy the template using LangServe
💡 LangChain Templates provide a standardized way to create, share, and deploy chains and agents, enabling rapid development and deployment of AI-powered applications.

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