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Deepnote | Case study

What is Langtail?

Getting started

Main concepts in Langtail

Overview

Concepts and Examples Overview

Playground Overview

Use Handlebars to add conditions to your templates

Prompt Templating

Assistants & Threads

Variables

Use Tools to test if your functions and external APIs are used correctly

Tools

Tests Overview

Basic Tests

Utilize Configs to evaluate your prompts across diverse scenarios and observe the outcomes.

Advanced tests

Deployments Overview

Deploy Prompt

API keys and Env Variables

Logs and Metrics Overview

Integrate via Langtail SDK

Integrate via OpenAI library

Integrate via REST API

Integrate via Langchain

TypeScript SDK

Get completion for stored prompt. The response format is the same as [OpenAI Chat completion response](https://platform.openai.com/docs/api-reference/chat/object).

Invoke Deployed Prompt

Get completion for a stored assistant. This endpoint invokes the assistant and returns its response. It uses chat completions on the backend and maintains OpenAI-compatible format. Assistants are stateful AI agents that can leverage various model providers and tools, access persistent conversation threads, and execute multiple tools in parallel.

Invoke Assistant

Get a list of threads within your project.

List Threads

Create a new thread. This endpoint allows you to initialize a conversation thread, optionally providing metadata or an initial log.

Create a Thread

Thread by ID

Delete a Thread by ID

Update a Thread by ID

Retrieves a list of messages for a specific thread.

List Thread Messages

Create Thread Message

Retrieves a specific message from a thread.

Get Thread Message

Updates the metadata of a specific message within a thread.

Update Thread Message

Want to build better chatbots?  We feel you.

Introduction

Concepts and Examples

References

Media & Presentations

Support & Community

Deepnote | Case study