Deployment on AI Knowledge Base

Claude with Amazon Bedrock

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

Learn to deploy Claude through AWS Bedrock — covers provisioned throughput, fine-tuning, and enterprise deployment patterns. Essential for teams evaluating how to access Claude in an enterprise AWS environment. This is the deployment-focused complement to the API-focused courses: the API course teaches you how to call Claude, this course teaches you how to run Claude in your cloud infrastructure.

Claude with Google Cloud's Vertex AI

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

Learn to deploy Claude through Google Cloud’s Vertex AI — covers model garden access, API integration, and enterprise deployment patterns. The Google Cloud counterpart to the Bedrock course. If your organization uses GCP, this is the path to accessing Claude within your existing cloud infrastructure. Useful for the AI Vendor & Platform Evaluation learning path’s deployment topology assessment.

Elixir Reference Implementation

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

Setup and usage guide for Symphony’s experimental Elixir/BEAM reference implementation, leveraging OTP supervision trees for fault-tolerant agent orchestration.

Google Cloud ML Engineer Learning Path

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

Google Cloud’s professional ML certification path — the most technically rigorous cloud AI certification available. Covers ML model development, MLOps, deployment, and monitoring on Google Cloud. Includes hands-on labs with Vertex AI, BigQuery ML, and TensorFlow. The learning path is free; certification exam is $200. Requires significant ML experience — this is not a beginner credential.

Deployment to Production

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

Take AI applications from prototype to production. This path covers the full deployment journey across providers: production checklists, rate limit management, batch processing for cost reduction, and agent-specific deployment patterns.

The key cross-provider insight: every provider has rate limits, batch APIs, and deployment recommendations, but the specifics differ meaningfully. Learning both OpenAI and Anthropic patterns helps you design resilient systems, and understanding framework deployment (LangGraph, CrewAI) is essential for agent-based applications.

Access BYOB using pre-signed URLs

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

Access management

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

Advanced IAM configuration

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

Agent Builder webhooks

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

Integrate agent publishing with external systems, CI/CD pipelines, or custom deployment workflows.

Agent Frameworks

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

Build production-ready AI agents with Fireworks and leading open-source frameworks

Agent Server API reference for LangSmith Deployment

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

Agent Starter Pack

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

API deployment checklist

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

Review commonly underused Responses API design choices that improve deployment quality, speed, cost, and reliability.

App development in LangSmith Deployment

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

Architecture

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

Chroma is designed with a modular architecture that prioritizes performance and ease of use. It scales seamlessly from local development to large-scale production, while exposing a consistent API across all deployment modes.

Architecture Overview

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

How Chroma is structured across local, single-node, and distributed deployments.

Automate user and team management

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

Automations

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

Manage, deploy, and monitor your live crews (automations) in one place.

Autoscaling

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

Configure how your deployment scales based on traffic

AWS

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

Deploy Chroma on AWS using CloudFormation.

AWS Bedrock

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

Deploy and query Mistral AI models on AWS Bedrock with fully managed, serverless endpoints

AWS Private Deployment Guide (EC2 and EKS)

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

Deploying Cohere models in AWS via EC2 or EKS for enhanced security, compliance, and control.

Azure

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

Deploy Chroma on Azure using Terraform.

Azure AI

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

Deploy and query Mistral AI models on Azure AI via serverless MaaS or GPU-based endpoints

Basic authentication with email and password

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

Bedrock

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

Track and monitor Amazon Bedrock LLM calls with Weave, capturing foundation model interactions, converse API usage, and multi-provider model deployments through AWS’s unified API for comprehensive observability.

Bring your own bucket (BYOB)

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

Bring your own cloud (BYOC)

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

Deploy Pinecone in your own cloud account (AWS, GCP, or Azure), with full control over your infrastructure

Checkpoints and Resume

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

Save training progress, resume from failures, and promote checkpoints to deployable models — driven by the recipe.

Chroma Configuration

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

Environment variables when self-hosting a Chroma server.

Chroma's Thin-Client

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

CI/CD with Pinecone Local and GitHub Actions

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

Test Pinecone integration with CI/CD workflows.

Claude Code with GitHub Enterprise Server

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

Connect Claude Code to your self-hosted GitHub Enterprise Server instance for web sessions, code review, and plugin marketplaces.

Cleanup and Teardown

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

Delete trainer jobs and deployments after experiments to avoid leaked resources.

Client-side performance optimization

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

Optimize your client code for maximum performance with dedicated deployments

Cloud

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

Access Mistral AI models via Azure, AWS, Google Cloud, Snowflake, IBM, and Outscale using cloud credits

Cloud Run

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

Composio Tool

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

Composio provides 250+ production-ready tools for AI agents with flexible authentication management.

Configuration

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

Tune model selection, retry logic, rate limits, and runner policies for production workloads.

Configure audit logs

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

Enable audit logging to Amazon S3 for compliance

Configure custom TLS certificates

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

Configure customer-managed encryption keys

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

Use customer-managed encryption keys with AWS KMS.

Configure environment variables

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

How to configure the W&B Server installation

Configure IP allowlisting for Dedicated Cloud

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

Configure LangSmith for scale

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

Configure private connectivity to Dedicated Cloud

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

Configure Private Endpoints for AWS PrivateLink

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

Secure Pinecone with private VPC endpoints.

Configure Slack alerts

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

Configure SSO with LDAP

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

Configure SSO with OIDC

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

Configure SSO with Okta

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

Configure SAML SSO with Okta for enterprise.

Connect to an external ClickHouse database

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

Connect to an external PostgreSQL database

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

Connect to an external Redis database

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

Control plane API reference for LangSmith Deployment

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

Create an assistant

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

Create and deploy a Pinecone Assistant for your knowledge base.

Create an Ingress for installations (Kubernetes)

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

CrewAI AMP

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

Deploy, monitor, and scale your AI agent workflows

CrewAI Documentation

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

Build collaborative AI agents, crews, and flows — production ready from day one.

Custom Models

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

Upload, verify, and deploy your own models from Hugging Face or elsewhere

Customize the error support message

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

Customize support contact information in the LangSmith frontend for self-hosted deployments.

Customize user management

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

Data deletion on Pinecone

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

Understand Pinecone’s secure data deletion process.

Data encryption in Dedicated Cloud

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

Dedicated Cloud

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

Deploy W&B Dedicated Cloud in production

Dedicated Inference

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

Deploy models on your own custom endpoints for improved reliability at scale

Deploy an observability stack for your LangSmith deployment

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

Deploy Finetuned Command Models from AWS Marketplace

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

This document provides a guide for bringing your own finetuned models to Amazon SageMaker.

Deploy on Air-Gapped Kubernetes

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

Deploy W&B Platform in air-gapped and disconnected Kubernetes environments

Deploy on Cloud

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

Deploy other frameworks

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

Deploy to AMP

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

Deploy your Crew or Flow to CrewAI AMP

Deploy to Vertex AI Agent Engine

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

Deploy W&B with Kubernetes Operator

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

Deploy W&B Platform with Kubernetes Operator on cloud or on-premises

Deploy with Cerebrium

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

Deploy AI apps effortlessly with Cerebrium’s serverless GPU infrastructure and auto-scaling." (99 characters)

Deploy with Cloudflare Workers AI

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

Deploy AI models on Cloudflare’s global network with Workers AI for serverless GPU-powered LLMs

Deploy with control plane

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

Deploy with SkyPilot

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

Deploy AI models on any cloud with SkyPilot for cost savings, high GPU availability, and managed execution

Deploy your app to Cloud

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

Deploy your finetuned model on AWS Marketplace

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

Learn how to deploy your finetuned model on AWS Marketplace.

Deploying a Fine-tuned Model

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

Once your fine-tune job completes, you should see your new model in your models dashboard.

Deploying Dedicated Endpoints

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

Guide to creating dedicated endpoints via the web UI.

Deploying Fine Tuned Models

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

Deploy one or multiple LoRA models fine tuned on Fireworks using live merge or multi-LoRA

Deploying Models in Private Environments

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

Learn how to pull and test Cohere’s container images using a license with Docker and Kubernetes.

Deploying Your Agent

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

Deployment

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

Deployment Options - Overview

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

This page provides an overview of the available options for deploying Cohere’s models.

Deployment Options Overview

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

Compare Together AI’s deployment options: fully-managed cloud service vs. secure VPC deployment for enterprises.

DeploymentManager (Compatibility)

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

Legacy SDK reference for direct deployment lifecycle and weight-sync management.

Deployments

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

Configure and manage on-demand deployments on dedicated GPUs

Deployments Quickstart

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

Deploy models on dedicated GPUs in minutes

DeploymentSampler

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

Client-side tokenized sampling from inference deployments for training and evaluation.

Different Types of API Keys and Rate Limits

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

This page describes Cohere API rate limits for production and evaluation keys.

Disable automatic updates for W&B Server

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

Learn how to disable automatic updates for W&B Server.

Distributed tracing with Agent Server

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

Unify traces when calling your deployed Agent Server from another service using RemoteGraph or the SDK.

Distributed/Cloud Performance

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

How to think about performance in distributed Chroma deployments.

Docker

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

Run Chroma in a Docker Container

Egress for billing and operational telemetry

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

Enable blob storage

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

Enable Insights

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

Enable LangSmith Deployment

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

Enable Polly

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

Enable TTL and data retention

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

Error handling

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

Handle errors with retry logic and best practices.

Evaluation best practices

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

Advanced evaluation patterns for production AI systems — handling ambiguous cases, scaling eval suites, avoiding eval gaming, and integrating evals into CI/CD pipelines.

Export data from Dedicated Cloud

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

Export data from Dedicated Cloud

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

Export runs, metrics, artifacts, and reports from a W&B Dedicated Cloud instance using the Python SDK API.

Exporting Metrics

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

Export metrics from your dedicated deployments to your observability stack

Fireworks Agent Overview

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

Describe what you want, approve the plan and cost, get a deployed fine-tuned model.

Fireworks Agent: Supervised Fine-Tuning

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

Run end-to-end SFT with Fireworks Agent — dataset inspection, hyperparameter sweep, evaluator-guided selection, and a deployed winner.

Fleet webhooks

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

Integrate agent publishing with external systems, CI/CD pipelines, or custom deployment workflows.

GCP

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

Deploy Chroma on Google Cloud Platform using Terraform.

General

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

How to improve Chroma performance across single-node and distributed deployments.

GKE

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

Going Live with a Cohere Model

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

Learn to upgrade from a Trial to a Production key; understand the limitations and benefits of each and go live with Cohere.

Going to production

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

Take your Deep Agent to production with persistent memory, sandboxes, resilience middleware, and deployment options

Going to production

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

Take your Deep Agent to production with persistent memory, sandboxes, resilience middleware, and deployment options

Host Your Agent

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

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

How Does Cohere's Pricing Work?

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

This page details Cohere’s pricing model. Our models can be accessed directly through our API, allowing for the creation of scalable production workloads.

How to add semantic search to your agent deployment

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

How to interact with a deployment using RemoteGraph

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

How to Start with the Cohere Toolkit

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

Build and deploy RAG applications quickly with the Cohere Toolkit, which offers pre-built front-end and back-end components.

How to use a custom checkpointer

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

Replace the built-in Postgres checkpointer with a custom BaseCheckpointSaver implementation in your agent deployment.

How to use a custom store

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

Replace the built-in Postgres store with a custom BaseStore implementation in your agent deployment.

IBM watsonx.ai

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

Mistral AI’s Large model on IBM watsonx.ai: SaaS & on-premise deployment with setup, API access, and usage guides

Identity and access management (IAM)

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

Image Generation with Flux2

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

Deploy a Flux2 image generation model on Together’s managed GPU infrastructure using Dedicated Containers.

Implement a CI/CD pipeline using LangSmith Deployment and Evaluation

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

Inference for RL Rollouts

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

Session affinity, weight-swap behavior, and MoE Router Replay for rollout traffic on Fireworks inference deployments.

Integrations

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

Pinecone integrations enable you to build and deploy AI applications faster and more efficiently. Integrate Pinecone with your favorite frameworks, data sources, and infrastructure providers.

Interact with your self-hosted instance of LangSmith

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

Introduction

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

Deploy custom containers on Together’s managed GPU infrastructure with automatic scaling, job queues, and built-in observability.

Jig CLI

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

Build, push, and deploy containers to Together’s managed GPU infrastructure.

La Plateforme

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

Mistral AI’s La Plateforme offers pay-as-you-go API access to its latest models with flexible deployment options

LangSmith Deployment

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

Deploy and manage agents with durable execution, real-time streaming, and horizontal scaling.

LangSmith Deployment

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

Deploy and manage agents with durable execution, real-time streaming, and horizontal scaling.

LangSmith Deployment

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

LangSmith Deployment

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

LangSmith Deployment

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

LangSmith Deployment

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

LangGraph deployment through LangSmith provides managed infrastructure for hosting graph-based agents with built-in tracing, monitoring, and versioning. This guide covers the deployment pipeline from local development to hosted execution, including environment configuration and API endpoint setup. A key consideration is that deploying to LangSmith introduces a vendor dependency that affects your architecture, so evaluate the tracing and observability benefits against the portability tradeoffs before committing. If you need self-hosted deployment or want to compare alternatives, review this alongside general containerization approaches for Python applications.

LangSmith Deployment components

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

LangSmith Deployment SDK

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

LangSmith for Enterprise

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

Deployment options, access control, data privacy, cost controls, and security compliance for Enterprise users.

Manage access control for projects

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

Manage project access using visibility scopes and project-level roles

Manage Agent Builder

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

Manage bucket storage and costs

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

Understand how W&B uses object storage, how deletion maps to bucket bytes, and how to reduce usage on self-managed, Dedicated Cloud, and bring-your-own-bucket deployments.

Manage Fleet

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

Manage users, groups, and roles with SCIM

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

Manage your organization

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

Microsoft Foundry

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

Deploy frontier open models inside your Azure subscription, billed through Azure.

Mirror images for your LangSmith installation

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

MLOps & Observability

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

Track and monitor your Fireworks AI deployments with leading MLOps and observability platforms

Model Gallery

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

Pinecone integrations enable you to build and deploy AI applications faster and more efficiently. Integrate Pinecone with your favorite frameworks, data sources, and infrastructure providers.

Monitor performance

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

Monitor performance metrics in the Pinecone console or with Prometheus or Datadog.

Multi-tenant Cloud

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

Deploy Multi-tenant Cloud in production

Observability

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

Monitor and trace your Chroma deployment with OpenTelemetry.

Observability

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

Observability for LLMs ensures visibility, debugging, and performance optimization across prototyping, testing, and production

Open Telemetry Logs

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

Understand how to capture telemetry logs from your CrewAI AMP deployments

Opik Integration

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

Learn how to use Comet Opik to debug, evaluate, and monitor your CrewAI applications with comprehensive tracing, automated evaluations, and production-ready dashboards.

Outscale

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

Deploy and query Mistral AI models on Outscale via managed VMs and REST APIs

Performance

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

Single-node Chroma performance benchmarks and limitations.

Performance benchmarking

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

Measure and optimize your deployment’s performance with load testing

Philosophy

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

LangChain exists to be the easiest place to start building with LLMs, while also being flexible and production-ready.

Philosophy

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

LangChain exists to be the easiest place to start building with LLMs, while also being flexible and production-ready.

Pinecone Assistant

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

Pinecone Assistant is a service that allow you to build production-grade chat and agent-based applications quickly.

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.

Platform Overview

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

Architecture, deployment lifecycle, and core concepts for Dedicated Container Inference.

Prepare for Deployment

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

Ensure your Crew or Flow is ready for deployment to CrewAI AMP

Pricing

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

Check the pricing page for detailed API cost information

Private Deployment – Setting Up

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

This page describes the setup required for private deployments of Cohere’s models.

Private Deployment Overview

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

This page provides an overview of private deployments of Cohere’s models.

Private Deployment Usage

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

This page describes how to use Cohere’s SDK to access privately deployed Cohere models.

Production Architecture

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

Best practices for building production-ready AI applications with CrewAI

Production best practices

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

Explore best practices for transitioning your AI projects from prototype to production, including scaling, security, and cost management.

Production checklist

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

Prepare your indexes for production with best practices.

Production notes on GPT Actions

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

Guidelines for deploying GPT Actions in a production environment, including rate limits, timeouts, and security measures.

Queue API

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

Submit, monitor, and manage asynchronous jobs for your Dedicated Container deployments.

Quickstart

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

Deploy your first container in 20 minutes.

Rate limit and usage tiers

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

Learn about Mistral’s API rate limits, usage tiers, and how to upgrade for higher capacity.’ (99 characters)

Rate limits

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

Default rate limits on Dedicated Cloud and how to request changes

Rate limits

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

Optional rate limits on Self-Managed instances for stability

Reference Architecture

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

W&B Reference Architecture

Regions

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

Fireworks runs a global fleet of hardware on which you can deploy your models.

Reliability and Error Handling

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

Recommended patterns for timeouts, retries, and error handling when building production applications on the Fireworks API.

Reserved capacity

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

Routers

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

Distribute traffic across multiple deployments for A/B testing, traffic migration, and load distribution.

Running Chroma in Client-Server Mode

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

Safety best practices

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

Comprehensive safety practices for responsible AI deployment — covering moderation, adversarial testing, human oversight, prompt engineering for safety, and production monitoring.

Security overview

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

Understand Pinecone’s security features, including authentication, encryption, and audit logs.

Self-deployment

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

Deploy Mistral AI models on your infrastructure using vLLM, TensorRT-LLM, TGI, or tools like SkyPilot and Cerebrium

Self-host LangSmith on Kubernetes

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

Self-host LangSmith with Docker

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

Self-host standalone servers

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

Self-hosted

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

Self-hosted LangSmith

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

Self-hosted LangSmith changelog

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

Self-hosted LangSmith on AWS

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

Self-hosted LangSmith on Azure

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

Self-hosted LangSmith on GCP

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

Self-Managed infrastructure requirements

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

Infrastructure and software requirements for W&B Self-Managed deployments

Set up a self-managed W&B Weave instance

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

Deploy and manage Weave on your own infrastructure

Set up guardrails

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

Ensure LLM safety and measure output quality in production applications

Set up hybrid LangSmith

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

Set up monitors

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

Passively score production traffic to surface trends and issues

Set up SSO with OAuth2.0 and OIDC

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

Set up the LLM auth proxy

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

Deploy an Envoy-based auth proxy that validates LangSmith-signed JWTs and routes LLM requests to your upstream provider or gateway.

Snowflake Cortex

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

Access Mistral AI models on Snowflake Cortex as serverless, fully managed endpoints for SQL & Python

Speculative Decoding

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

Speed up generation with draft models and n-gram speculation

Sprocket SDK

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

A Python SDK for building inference workers that support both synchronous and asynchronous requests via Together’s platform.

Standard deployment

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

Supported Dedicated Cloud regions

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

View all supported AWS, Google Cloud, and Azure regions available for W&B Dedicated Cloud instances.

Supported Dedicated Cloud regions

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

TensorRT

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

Guide to building and deploying TensorRT-LLM engines with Triton inference server

Test deployed agents

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

Text Generation Inference

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

TGI is a toolkit for deploying and serving LLMs with high-performance text generation features like quantization and OpenAI-like API support

Track user activity with audit logs

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

Training and Sampling

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

End-to-end SDK walkthrough: bootstrap resources, train, checkpoint, and sample through a serving deployment.

Troubleshooting for self-hosted deployments

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

Understanding LoRA performance

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

Understand the performance impact of LoRA fine-tuning, optimization strategies, and deployment considerations.

Update W&B license and version

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Guide for updating W&B version and license across different installation methods.

Upgrade an installation

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Use an existing secret for your installation (Kubernetes)

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Use environment variables for model providers

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Use federated identities with SDK

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Use Prometheus monitoring

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Use server-side caching

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Cache values server-side in your agent deployment using stale-while-revalidate and key-value cache APIs.

Use service accounts to automate workflows

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Manage automated or non-interactive workflows using org and team scoped service accounts

Vertex AI

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Deploy and query Mistral AI models on Google Cloud Vertex AI as serverless endpoints

Video Generation with Wan 2.1

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Deploy a multi-GPU video generation model on Together’s managed GPU infrastructure using Dedicated Containers.

View organization activity

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View trace counts across your organization

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vLLM

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vLLM is an open-source LLM inference engine optimized for deploying Mistral models on-premise

W&B Mobile App (iOS)

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Track training runs, view line plots, and explore your W&B Models projects from your iPhone or iPad.

W&B Self-Managed deployment overview

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Deploy W&B Self-Managed on cloud or on-premises infrastructure

Weight sync

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How a trainer’s updated weights reach the serving deployment during RL training.

Welcome to LLM University!

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LLM University (LLMU) offers in-depth, practical NLP and LLM training. Ideal for all skill levels. Learn, build, and deploy Language AI with Cohere.

Workspaces

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La Plateforme workspaces enable team collaboration, access control, and shared fine-tuned models.’ (99 characters)