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* docs: add xAI Grok and Mistral AI provider configs * docs: add Anthropic Claude model configuration guide - Add comprehensive documentation for configuring Anthropic Claude models with Cline - Include API key setup, supported models list, and configuration steps - Cover advanced features like prompt caching and rate limits - Update navigation to include new Anthropic page in custom model configs section * docs: add DeepSeek, Ollama, OpenAI, OpenAI Compatible pages and update Plan & Act * docs: add Extended Thinking section to Anthropic configuration guide * docs: update vscode language model api page * docs: update vscode language model api docs * Add model documentation pages and update navigation structure - Add new documentation pages for model overviews (Claude, Gemini, OpenAI, XAI) - Add general models overview page - Update docs.json to include new model documentation in navigation - Update OpenAI-compatible model documentation * Remove Notes column from model documentation tables for consistency * Fix table formatting in Gemini models documentation * added 5 new model configurations and updated existing ones * Update AWS Bedrock documentation with minimal IAM permissions * modified: docs/get-to-know-the-models/claude-models.mdx * Renamed 'custom model configuration' to 'provider configuation' to avoid providers being confused with models * Fix dollar sign rendering in model documentation - Escape dollar signs in pricing tables to prevent MDX parsing issues - Fixes disappearing dollar signs in gemini-models.mdx and other model docs - Dollar signs now display correctly as literal currency symbols * Add feature descriptions to OpenAI and XAI model docs - Added 'Diverse Performance for Different Tasks Across Model Tiers' section to OpenAI models - Added 'Real-time Information Access' section to XAI models - Maintains consistency with existing Claude and Gemini documentation format - Highlights valuable features for agentic AI coding workflows * removing these files due to name change in header. they're in the new docs/provider configs folder * added 2 new issues per model page + formatting * Update model documentation files * Fix: Correct paths in docs.json for provider configs * docs: update docs.json and apply formatting * docs: fix broken links, add OpenRouter & Requesty pages * docs: remove 'get to know the models' section and files * Update docs/provider-config/openai-compatible.mdx Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com> --------- Co-authored-by: kevinneung <94151024+kevinneung@users.noreply.github.com> Co-authored-by: Dennise Bartlett <bartlett.dc.1@gmail.com> Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
40 lines
2.9 KiB
Plaintext
40 lines
2.9 KiB
Plaintext
---
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title: "Cloud Provider Integration"
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---
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Cline supports major cloud providers like AWS Bedrock and Google's Cloud Vertex; whichever your team currently uses is appropriate, and there's no need to change providers to utilize Cline's features.
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For the purpose of this document, we assume your organization will use cloud-based frontier models. Cloud inference providers offer cutting-edge capabilities and the flexibility to select models which best suit your needs.
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Certain scenarios may warrant using local models, including handling highly sensitive data, applications requiring consistent low-latency responses, or compliance with strict data sovereignty requirements. If your team needs to utilize local models, see [Running Local Models ](/running-models-locally/read-me-first.mdx)with Cline.
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---
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## AWS Bedrock Setup Guides
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#### [IAM Security Best Practices](https://docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html) (For administrators)
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#### [AWS Bedrock setup for Legacy IAM (AWS Credentials)](/provider-config/aws-bedrock-with-credentials-authentication)
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#### [AWS Bedrock setup for SSO token (AWS Profile)](/provider-config/aws-bedrock-with-profile-authentication)
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#### VPC Endpoint Setup
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To protect your team's data, Cline supports VPC (Virtual Private Cloud) endpoints, which create private connections between your data and AWS Bedrock. AWS VPCs enhance security by eliminating the need for public IP addresses, network gateways, or complex firewall rules—essentially creating a private highway for data that bypasses the public internet entirely. By keeping traffic within AWS's private network, teams also benefit from lower latency and more predictable performance when accessing services like AWS Bedrock or custom APIs. For those working with confidential information or operating in highly regulated industries like healthcare or finance, VPCs offers the perfect balance between the accessibility of cloud services and the security of private infrastructure.
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---
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1. Consult the [AWS guide](https://docs.aws.amazon.com/bedrock/latest/userguide/vpc-interface-endpoints.html) to creating VPC endpoints. This document specifies pre-requisites and describes the syntax used for creating VPC endpoints.
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2. Follow the directions for [creating a VPC endpoint](https://docs.aws.amazon.com/vpc/latest/privatelink/create-interface-endpoint.html#create-interface-endpoint-aws) in the AWS console. The image below pertains to steps 4 and 5 of the AWS guide linked above.
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<Frame>
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<img src="https://storage.googleapis.com/cline_public_images/docs/assets/vpc-console.png" alt="VPC Console" />
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</Frame>
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3. Note the IP address of your VPC endpoint, open Cline's settings menu, and select `AWS Bedrock`from the API Provider dropdown.
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4. Click the `Use Custom VPC endpoint`checkbox and enter the IP address of your VPC endpoint
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<Frame>
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<img src="https://storage.googleapis.com/cline_public_images/docs/assets/vpc-settings-menu.png" alt="VPC Settings Menu" />
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</Frame>
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