Tutorial on AI Knowledge Base

Get Started

Mon, 01 Jan 0001 00:00:00 +0000

API key setup, first API call, and quickstart for the Anthropic platform.

Implement Tool Use

Mon, 01 Jan 0001 00:00:00 +0000

Step-by-step guide to implementing the tool use loop: define tools, handle tool_use responses, send tool_result.

Add Tools to Agents

Mon, 01 Jan 0001 00:00:00 +0000

Add tool calling capabilities to agents with automatic schema inference from Python functions.

Advanced setup

Mon, 01 Jan 0001 00:00:00 +0000

Advanced Tool Use

Mon, 01 Jan 0001 00:00:00 +0000

Agent Evaluation Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Agent team

Mon, 01 Jan 0001 00:00:00 +0000

Agentic IDEs and CLIs

Mon, 01 Jan 0001 00:00:00 +0000

Use Pinecone with agentic IDEs and CLIs like Claude Code, Gemini CLI, Cursor, and more.

Architecture

Mon, 01 Jan 0001 00:00:00 +0000

Learn how Pinecone’s architecture enables fast, relevant vector search at any scale.

Async

Mon, 01 Jan 0001 00:00:00 +0000

Audio

Mon, 01 Jan 0001 00:00:00 +0000

Bienvenue to Mistral AI Documentation

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Mistral AI offers open-source and commercial LLMs, APIs, and tools for developers and enterprises to build AI-powered applications

Build a SQL Agent with Cohere's LLM Platform

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a tutorial on how to build a SQL agent with Cohere’s LLM platform.

Build a streaming agent

Mon, 01 Jan 0001 00:00:00 +0000

Build an evaluation

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to build an evaluation pipeline with Weave Models and Evaluations

Build an MCP App

Mon, 01 Jan 0001 00:00:00 +0000

Getting started guide for building interactive UI applications with MCP Apps

Build applications

Mon, 01 Jan 0001 00:00:00 +0000

Build agentic applications utilizing compatible event AG-UI event streams

Build clients

Mon, 01 Jan 0001 00:00:00 +0000

Showcase: build a conversational CLI agent from scratch using AG-UI and Mastra

Build with Fireworks AI

Mon, 01 Jan 0001 00:00:00 +0000

Fast inference and fine-tuning for open source models

Build your agent with ADK

Mon, 01 Jan 0001 00:00:00 +0000

Build Your First Crew

Mon, 01 Jan 0001 00:00:00 +0000

Step-by-step tutorial to create a collaborative AI team that works together to solve complex problems.

Building a Creative Text-Based AI Game

Mon, 01 Jan 0001 00:00:00 +0000

Building Agentic RAG with Cohere

Mon, 01 Jan 0001 00:00:00 +0000

Hands-on tutorials on building agentic RAG applications with Cohere

Building AI Agents with DSPy

Mon, 01 Jan 0001 00:00:00 +0000

Building AI Applications by Customizing DSPy Modules

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Building RAG as Agent

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Cache

Mon, 01 Jan 0001 00:00:00 +0000

Chroma Cloud

Mon, 01 Jan 0001 00:00:00 +0000

Classification

Mon, 01 Jan 0001 00:00:00 +0000

Classification Finetuning

Mon, 01 Jan 0001 00:00:00 +0000

CLI quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Cline with W&B Inference

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to configure the Cline coding agent to use W&B Inference.

Code Generation for Unfamiliar Libraries

Mon, 01 Jan 0001 00:00:00 +0000

Coding with AI

Mon, 01 Jan 0001 00:00:00 +0000

Cohere Text Generation Tutorial

Mon, 01 Jan 0001 00:00:00 +0000

This page walks through how Cohere’s generation models work and how to use them.

Community Tutorials

Mon, 01 Jan 0001 00:00:00 +0000

Concepts

Mon, 01 Jan 0001 00:00:00 +0000

This document outlines basic Fireworks AI concepts.

Concepts

Mon, 01 Jan 0001 00:00:00 +0000

Understand concepts in Pinecone and how they relate to each other.

Creating a fine-tuned LoRA

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to create a fine-tuned LoRA to use with W&B Inference.

CrewAI Cookbooks

Mon, 01 Jan 0001 00:00:00 +0000

Feature-focused quickstarts and notebooks for learning patterns fast.

Debugging

Mon, 01 Jan 0001 00:00:00 +0000

A comprehensive guide to debugging Agent User Interaction Protocol (AG-UI) integrations

Debugging & Observability

Mon, 01 Jan 0001 00:00:00 +0000

DeepSeek R1 Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

How to get the most out of reasoning models like DeepSeek-R1.

DeepSeek V3.1 QuickStart

Mon, 01 Jan 0001 00:00:00 +0000

How to get started with DeepSeek V3.1

Deploy your app to Cloud

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Deployment

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Deployments Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Deploy models on dedicated GPUs in minutes

Developer quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to use the OpenAI API to generate human-like responses to natural language prompts, analyze images with computer vision, use powerful built-in tools, and more.

Developing with Cursor

Mon, 01 Jan 0001 00:00:00 +0000

Use Cursor to build AG-UI implementations faster

Development

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Development

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Development

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Email Information Extraction

Mon, 01 Jan 0001 00:00:00 +0000

End-to-end RAG using Elasticsearch and Cohere

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a basic tutorial on how to get Cohere and ElasticSearch to work well together.

Entity Extraction

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Evals In Prod

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Evals In Prod

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Evals In Prod

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Evaluate a chatbot

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Evaluate a prompt

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Evaluate a RAG application

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Evaluate a simple RAG system

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This is the practical RAG evaluation walkthrough and the page most teams should run first when they need to measure a retrieval pipeline rather than guess at it. Pay attention to the distinction between retrieval metrics like context precision and recall and generation metrics like faithfulness and answer relevancy, because a RAG system can fail at either stage and the fix differs entirely. A common mistake is optimizing answer quality while ignoring context recall, leaving the model fluent but ungrounded. Start with the simple-evals page first if you are new to RAGAS.

Evaluate an AI Agent

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Evaluate an AI Workflow

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Evaluate RAG applications

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Build and evaluate RAG applications using Weave with LLM judges

Evaluation

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Evaluation

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Evaluation

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Evaluation quickstart

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This is the fastest path into LangSmith evaluation and the right starting point before the deeper evaluator guides. The key takeaway is the dataset to target-function to evaluator to run loop, which is the mental model every other LangSmith eval feature builds on. Pay attention to how examples and the evaluation client are wired up, since that boilerplate carries over to LLM-as-judge work. A common beginner mistake is evaluating against a dataset that does not represent production traffic, which produces reassuring but meaningless scores.

Financial Analysis with Yahoo Finance

Mon, 01 Jan 0001 00:00:00 +0000

Fine-tuning Guide

Mon, 01 Jan 0001 00:00:00 +0000

Learn the basics and best practices of fine-tuning large language models.

Finetuning Agents

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Generating llms.txt

Mon, 01 Jan 0001 00:00:00 +0000

GEPA for AIME (Math)

Mon, 01 Jan 0001 00:00:00 +0000

GEPA for Code Backdoor Classification (AI control)

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GEPA for Privacy-Conscious Delegation

Mon, 01 Jan 0001 00:00:00 +0000

GEPA for Structured Information Extraction for Enterprise Tasks

Mon, 01 Jan 0001 00:00:00 +0000

Get started

Mon, 01 Jan 0001 00:00:00 +0000

Get started with Studio

Mon, 01 Jan 0001 00:00:00 +0000

Get started with the desktop app

Mon, 01 Jan 0001 00:00:00 +0000

Install Claude Code on desktop and start your first coding session

Get Started with W&B Models

Mon, 01 Jan 0001 00:00:00 +0000

Get Started with Weights & Biases

Mon, 01 Jan 0001 00:00:00 +0000

Choose the right W&B product for your use case and learn how to get started

Getting Started

Mon, 01 Jan 0001 00:00:00 +0000

Chroma is an open-source search engine for AI. It comes with everything you need to get started built-in, and runs on your machine.

Getting Started

Mon, 01 Jan 0001 00:00:00 +0000

This five-minute quickstart is the fastest way into DeepEval: install it, write a test case, pick a metric, and run deepeval test run, which feels like pytest for LLM outputs. The critical thing to set up first is an OPENAI_API_KEY, because nearly all DeepEval metrics are LLM-as-a-judge evaluators that call a model under the hood. If a run appears stuck, suspect rate limits or quota rather than a framework bug, the most common early gotcha. DeepEval covers similar ground to RAGAS but with a pytest-style assertion workflow; read the metrics introduction next.

Getting Started

Mon, 01 Jan 0001 00:00:00 +0000

Quick start guide

Getting Started Agents

Mon, 01 Jan 0001 00:00:00 +0000

Getting Started Chatbots

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Getting Started Llm Arena

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Getting Started Mcp

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Getting Started Rag

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Getting started with datasets

Mon, 01 Jan 0001 00:00:00 +0000

Introduction to evaluation datasets — the foundation for systematic AI testing and the first step in eval-driven development.

Getting started with GPT Actions

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to set up and test GPT actions from scratch with the OpenAI API.

GLM-5 Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

How to get the most out of GLM-5 for reasoning and agentic tasks.

Glossary

Mon, 01 Jan 0001 00:00:00 +0000

Definitions for key terms used across Fireworks AI documentation.

Glossary

Mon, 01 Jan 0001 00:00:00 +0000

Glossary of key AI and LLM terms, including LLMs, text generation, tokens, MoE, RAG, fine-tuning, function calling, embeddings, and temperature

Go

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Go

Mon, 01 Jan 0001 00:00:00 +0000

Go

Mon, 01 Jan 0001 00:00:00 +0000

Grounded Summarization Using Command R

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a basic tutorial on how to do grounded summarization with Cohere’s models.

Guides Homepage

Mon, 01 Jan 0001 00:00:00 +0000

Quickstarts and step-by-step guides for building with Together AI.

Host Your Agent

Mon, 01 Jan 0001 00:00:00 +0000

Deploy agents to Azure Functions, custom hosts, or local environments.

Image Generation Prompt iteration

Mon, 01 Jan 0001 00:00:00 +0000

Improvement

Mon, 01 Jan 0001 00:00:00 +0000

Improvement

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Improvement

Mon, 01 Jan 0001 00:00:00 +0000

Installation

Mon, 01 Jan 0001 00:00:00 +0000

A guide for installing the Cohere SDK, supported in 4 different languages – Python, TypeScript, Java, and Go.

Integrations

Mon, 01 Jan 0001 00:00:00 +0000

Introduction

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to get started building an AG-UI integration

Introduction

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Introduction

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Introduction

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Japanese documentation

Mon, 01 Jan 0001 00:00:00 +0000

Localized overview and quickstart for Japanese-speaking developers.

Java

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Java

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Java

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Java

Mon, 01 Jan 0001 00:00:00 +0000

Judge Alignment Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Kimi K2 QuickStart

Mon, 01 Jan 0001 00:00:00 +0000

How to get the most out of models like Kimi K2.

Kimi K2 Thinking QuickStart

Mon, 01 Jan 0001 00:00:00 +0000

How to get the most out of reasoning models like Kimi K2 Thinking.

Kimi K2.5 Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

How to get the most out of Kimi’s new K2.5 model.

Leaderboard Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to use leaderboard quickstart with W&B Weave

Learn

Mon, 01 Jan 0001 00:00:00 +0000

Tutorials, conceptual guides, and resources to help you get started.

Learn

Mon, 01 Jan 0001 00:00:00 +0000

Tutorials, conceptual guides, and resources to help you get started.

Learn How Cohere's Rerank Models Work

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a basic tutorial on how Cohere’s ReRank models work and how to use them.

Learn Weave with W&B Inference

Mon, 01 Jan 0001 00:00:00 +0000

Llama 4 Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

How to get the most out of the new Llama 4 models.

LlamaIndex Agent Evaluation Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

LLM Benchmarking Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Managing Conversation History

Mon, 01 Jan 0001 00:00:00 +0000

Master Reranking with Cohere Models

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a tutorial on using Cohere’s ReRank models.

Math Reasoning

Mon, 01 Jan 0001 00:00:00 +0000

Meeting minutes

Mon, 01 Jan 0001 00:00:00 +0000

Create an automated meeting minutes generator with Whisper and GPT-4.

Memory-Enabled ReAct Agents

Mon, 01 Jan 0001 00:00:00 +0000

Middleware

Mon, 01 Jan 0001 00:00:00 +0000

Connect to existing protocols, in process agents or custom solutions via AG-UI

Migrating away from create_csv_agent in langchain-cohere

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a tutorial on how to build a CSV agent without the deprecated create_csv_agent abstraction in langchain-cohere v0.3.5 and beyond.

Model customization

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to customize LLMs for your application with system prompts, fine-tuning, and moderation layers

Model selection

Mon, 01 Jan 0001 00:00:00 +0000

Guide to selecting Mistral models based on performance, cost, and use case complexity.’ (99 characters)

Model weights

Mon, 01 Jan 0001 00:00:00 +0000

Open-source pre-trained and instruction-tuned models with various licenses, download links, and usage guidelines

Models Benchmarks

Mon, 01 Jan 0001 00:00:00 +0000

Mistral’s benchmarked models excel in reasoning, multilingual tasks, coding, and multimodal capabilities, outperforming competitors in key benchmarks

Models Overview

Mon, 01 Jan 0001 00:00:00 +0000

Mistral offers open and premier models for various tasks, including text, code, audio, and multimodal processing

Multi-Hop RAG

Mon, 01 Jan 0001 00:00:00 +0000

Multi-tool agent

Mon, 01 Jan 0001 00:00:00 +0000

Multi-Turn Conversations

Mon, 01 Jan 0001 00:00:00 +0000

Build agents that maintain conversation context across multiple turns with session-based state management.

Multilingual Search with Cohere and Langchain

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a basic tutorial on how to do search across different languages with Cohere’s LLM platform.

OpenAI GPT-OSS Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Get started with OpenAI’s GPT-OSS, open-source reasoning model duo.

Output Refinement

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to build, customize, and optimize your CrewAI applications with comprehensive guides and tutorials

Overview

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Overview

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Mon, 01 Jan 0001 00:00:00 +0000

Overview

Mon, 01 Jan 0001 00:00:00 +0000

PEFT configurations and models

Mon, 01 Jan 0001 00:00:00 +0000

PEFT integrations

Mon, 01 Jan 0001 00:00:00 +0000

Pinecone Assistant: n8n quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Create an n8n workflow to chat with documents using Pinecone Assistant and OpenAI.

Pinecone Assistant: SDK quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Use a Pinecone SDK to create an assistant, upload documents, and chat with the assistant.

Pinecone documentation

Mon, 01 Jan 0001 00:00:00 +0000

Pinecone is the leading vector database for building accurate and performant AI applications at scale in production.

Pondr, Fostering Connection through Good Conversation

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a basic tutorial on how tplay an AI-powered version of the icebreaking game ‘Pondr’.

Privacy-Conscious Delegation

Mon, 01 Jan 0001 00:00:00 +0000

Program Of Thought

Mon, 01 Jan 0001 00:00:00 +0000

Prompt engineering quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Prompt Evaluation Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Python

Mon, 01 Jan 0001 00:00:00 +0000

Python

Mon, 01 Jan 0001 00:00:00 +0000

Python

Mon, 01 Jan 0001 00:00:00 +0000

Python

Mon, 01 Jan 0001 00:00:00 +0000

Quick Start

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Quick Start

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Quickstart

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Welcome to Claude Code!

Quickstart

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This is the fastest path to a running agent and the best starting point before diving into advanced SDK features. Focus on the AgentConfig pattern, which is the central abstraction for defining agent behavior, tools, and instructions. Pay attention to how the SDK handles the agentic loop automatically – understanding what happens behind the scenes here will save you debugging time later. Read this before the Python or TypeScript language-specific guides so you have the conceptual model in place first.

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

This quickstart walks you through building your first agent skill end-to-end, from definition to invocation within a Claude-powered agent. Focus on the skill registration pattern and how the runtime discovers and exposes skills to the model — getting this wiring right is foundational for everything else. Be aware that the quickstart uses simplified error handling; production skills need retry logic and graceful degradation as covered in the best practices guide. Work through this hands-on before reading the enterprise or best practices docs to build concrete intuition first.

Quickstart

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Build your first AI agent with CrewAI in under 5 minutes.

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Get a custom training loop running in minutes with the Fireworks Training API.

Quickstart

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Build an agent from a template

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Build an agent from a template

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Build your first deep agent in minutes

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Quickstart

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Quickstart

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Build your first deep agent in minutes

Quickstart

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Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Quickstart guide for setting up a Mistral AI account, configuring billing, and using the API for models and embeddings

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Step-by-step setup for installing the package, configuring API keys, and running your first agent locally.

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Build your first agent with the OpenAI Agents SDK, add tools and handoffs, and understand where to go next.

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Get started with Pinecone manually, with AI assistance, or with no-code tools.

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Deploy your first container in 20 minutes.

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Get up to speed with our API in one minute.

Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Quickstart: Create Your First Cluster

Mon, 01 Jan 0001 00:00:00 +0000

Get started with GPU Clusters in minutes

Quickstart: Flux Kontext

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to use Flux’s new in-context image generation models

Quickstart: Flux LoRA Inference

Mon, 01 Jan 0001 00:00:00 +0000

Quickstart: FLUX.2

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to use FLUX.2, the next generation image model with advanced prompting capabilities

Quickstart: How to do OCR

Mon, 01 Jan 0001 00:00:00 +0000

A step by step guide on how to do OCR with Together AI’s vision models with structured outputs

Quickstart: How to Use OpenClaw with Together AI

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to pair OpenClaw, a powerful autonomous agent, with frontier OSS models on Together AI like Kimi K2.5 and GLM 4.7.

Quickstart: Next.Js

Mon, 01 Jan 0001 00:00:00 +0000

Build an app that can ask a single question or chat with an LLM using Next.js and Together AI.

Quickstart: Publish an MCP Server to the MCP Registry

Mon, 01 Jan 0001 00:00:00 +0000

Publishing your MCP server to the registry makes it discoverable by any MCP client, which is a critical step for adoption beyond your own projects. Focus on the metadata requirements (name, description, capabilities) because poorly described servers are effectively invisible in the registry. Note that the registry currently requires GitHub-based authentication and a specific package manifest format — read through the validation errors carefully if your first publish attempt fails, as the error messages are quite specific. Come to this doc after you have a working server from the build-server tutorial, since you need a functional server before publishing makes sense.

Quickstart: Retrieval Augmented Generation (RAG)

Mon, 01 Jan 0001 00:00:00 +0000

How to build a RAG workflow in under 5 mins!

Quickstart: Track LLM inputs & outputs

Mon, 01 Jan 0001 00:00:00 +0000

Begin debugging LLM apps by adding tracing.

Quickstart: Using Hugging Face Inference With Together

Mon, 01 Jan 0001 00:00:00 +0000

This guide will walk you through how to use Together models with Hugging Face Inference.

Quickstart: Using Mastra with Together AI

Mon, 01 Jan 0001 00:00:00 +0000

This guide will walk you through how to use Together models with Mastra.

Quickstart: Using Vercel AI SDK With Together AI

Mon, 01 Jan 0001 00:00:00 +0000

This guide will walk you through how to use Together models with the Vercel AI SDK.

Quickstart: Wan 2.7 T2V

Mon, 01 Jan 0001 00:00:00 +0000

Generate videos from text prompts with optional audio input using the Wan 2.7 T2V model.

RAG With Chat Embed and Rerank via Pinecone

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a basic tutorial on how to build a RAG-powered chatbot.

Realtime quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Stand up low-latency realtime agents with websocket transport (WebRTC is not available in the Python SDK).

Remote Agent Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Train an SVG drawing agent running in a remote environment

Reranking - quickstart

Mon, 01 Jan 0001 00:00:00 +0000

A quickstart guide for performing reranking with Cohere’s Reranking models (v2 API).

Retrieval augmented generation (RAG) - quickstart

Mon, 01 Jan 0001 00:00:00 +0000

A quickstart guide for performing retrieval augmented generation (RAG) with Cohere’s Command models (v2 API).

Retrieval evaluation using LLM-as-a-judge via Pydantic AI

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a tutorial on how to evaluate retrieval systems using LLMs as judges via Pydantic AI.

Retrieval-Augmented Generation (RAG)

Mon, 01 Jan 0001 00:00:00 +0000

RL for Multi-Hop Research

Mon, 01 Jan 0001 00:00:00 +0000

RL for Privacy-Conscious Delegation

Mon, 01 Jan 0001 00:00:00 +0000

Run your first experiment

Mon, 01 Jan 0001 00:00:00 +0000

Saving and Loading

Mon, 01 Jan 0001 00:00:00 +0000

SDK Clients

Mon, 01 Jan 0001 00:00:00 +0000

Official Python & TypeScript SDKs and community clients for Mistral AI

Security Best Practices

Mon, 01 Jan 0001 00:00:00 +0000

Security considerations, attack vectors, and best practices for MCP implementations

Semantic search - quickstart

Mon, 01 Jan 0001 00:00:00 +0000

A quickstart guide for performing text semantic search with Cohere’s Embed models (v2 API).

Semantic Search with Cohere Embed Jobs

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a basic tutorial on how to use Cohere’s Embed Jobs functionality.

Semantic Search with Cohere Models

Mon, 01 Jan 0001 00:00:00 +0000

This is a tutorial describing how to leverage Cohere’s models for semantic search.

Server

Mon, 01 Jan 0001 00:00:00 +0000

Implement AG-UI compatible servers

Serverless Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Make your first Serverless API call in minutes

Serverless Semantic Search with Cohere and Pinecone

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a basic tutorial on how to get Cohere and the Pinecone vector database to work well together.

Single-Turn Training Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Train a model to be an expert at answering GSM8K math questions

SQL Agent with Cohere and LangChain (i-5O Case Study)

Mon, 01 Jan 0001 00:00:00 +0000

This page contains a tutorial on how to build a SQL agent with Cohere and LangChain in the manufacturing industry.

Streaming

Mon, 01 Jan 0001 00:00:00 +0000

Technical Overview

Mon, 01 Jan 0001 00:00:00 +0000

Test Pinecone at scale

Mon, 01 Jan 0001 00:00:00 +0000

Test Pinecone with a real-world dataset and semantic search workload.

Text generation - quickstart

Mon, 01 Jan 0001 00:00:00 +0000

A quickstart guide for performing text generation with Cohere’s Command models (v2 API).

Text-to-SQL Evaluation Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Tool use & agents - quickstart

Mon, 01 Jan 0001 00:00:00 +0000

A quickstart guide for using tool use and building agents with Cohere’s Command models (v2 API).

Trace an LLM application tutorial

Mon, 01 Jan 0001 00:00:00 +0000

Tracing quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Track Application Logic

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to track data flow and metadata in your LLM applications

Tracking DSPy Optimizers

Mon, 01 Jan 0001 00:00:00 +0000

Tutorial Introduction

Mon, 01 Jan 0001 00:00:00 +0000

Tutorial Setup

Mon, 01 Jan 0001 00:00:00 +0000

Tutorial: App versioning

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to use Weave Model to track and version your application and its parameters

Tutorial: Create sweep job from project

Mon, 01 Jan 0001 00:00:00 +0000

Tutorial on how to create sweep jobs from a pre-existing W&B project.

Tutorial: Create, track, and use a dataset artifact

Mon, 01 Jan 0001 00:00:00 +0000

Create, track, and use a dataset artifact with W&B.

Tutorial: Define, initialize, and run a sweep

Mon, 01 Jan 0001 00:00:00 +0000

Sweeps quickstart shows how to define, initialize, and run a sweep. There are four main steps

Tutorial: Log tables, visualize and query data

Mon, 01 Jan 0001 00:00:00 +0000

Explore how to use W&B Tables with this 5 minute Quickstart.

Tutorial: Use custom charts

Mon, 01 Jan 0001 00:00:00 +0000

Tutorial of using the custom charts feature in the W&B UI

Tutorials

Mon, 01 Jan 0001 00:00:00 +0000

Tutorials Overview

Mon, 01 Jan 0001 00:00:00 +0000

TypeScript

Mon, 01 Jan 0001 00:00:00 +0000

Understanding Authorization in MCP

Mon, 01 Jan 0001 00:00:00 +0000

Learn how to implement secure authorization for MCP servers using OAuth 2.1 to protect sensitive resources and operations

Use MCP in DSPy

Mon, 01 Jan 0001 00:00:00 +0000

Vibe Coder Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Voice quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Build speech-enabled agents with streaming transcription and TTS.

W&B Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

W&B Quickstart

W&B Tutorials & Blog

Mon, 01 Jan 0001 00:00:00 +0000

Web QA with embeddings

Mon, 01 Jan 0001 00:00:00 +0000

How to build an AI that can answer questions about your website.

Workflow Evaluation Quickstart

Mon, 01 Jan 0001 00:00:00 +0000

Workflows Tutorial

Mon, 01 Jan 0001 00:00:00 +0000

Tutorial on defining graph-based multi-agent workflows with executors and edges.

Your First Agent

Mon, 01 Jan 0001 00:00:00 +0000

Step-by-step tutorial to build your first agent with the Microsoft Agent Framework.