docs.json

.changeset/tiny-doors-cover.md

@@ -0,0 +1,5 @@
+---
+"claude-dev": minor
+---
+
+Migrate custom model config section to new docs

docs/custom-model-configs/aws-bedrock-with-credentials-authentication.mdx

@@ -0,0 +1,121 @@
+---
+title: "AWS Bedrock"
+description: "Learn how to set up AWS Bedrock with Cline using credentials authentication. This guide covers AWS environment setup, regional access verification, and secure integration with the Cline VS Code extension."
+---
+
+### Overview
+
+-   **AWS Bedrock:** A fully managed service that offers access to leading generative AI models (e.g., Anthropic Claude, Amazon Titan) through AWS.\
+    [Learn more about AWS Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
+-   **Cline:** A VS Code extension that acts as a coding assistant by integrating with AI models—empowering developers to generate code, debug, and analyze data.
+-   **Enterprise Focus:** This guide is tailored for organizations with established AWS environments (using IAM roles, AWS SSO, AWS Organizations, etc.) to ensure secure and compliant usage.
+
+---
+
+### Step 1: Prepare Your AWS Environment
+
+#### 1.1 Create or Use an IAM Role/User
+
+1. **Sign in to the AWS Management Console:**\
+   [AWS Console](https://aws.amazon.com/console/)
+2. **Access IAM:**
+    - Search for **IAM (Identity and Access Management)** in the AWS Console.
+    - Either create a new IAM user or use your enterprise's AWS SSO to assume a dedicated role for Bedrock access.
+    - [AWS IAM User Guide](https://docs.aws.amazon.com/IAM/latest/UserGuide/introduction.html)
+
+#### 1.2 Attach the Required Policies
+
+1. **Attach the Managed Policy:**
+    - Attach the **`AmazonBedrockFullAccess`** managed policy to your user/role.\
+      [View AmazonBedrockFullAccess Policy Details](https://docs.aws.amazon.com/bedrock/latest/userguide/security-iam.html)
+2. **Confirm Additional Permissions:**
+    - Ensure your policy includes permissions for model invocation (e.g., `bedrock:InvokeModel` and `bedrock:InvokeModelWithResponseStream`), model listing, and AWS Marketplace actions (like `aws-marketplace:Subscribe`).
+    - _Enterprise Tip:_ Apply least-privilege practices by scoping resource ARNs and using [Service Control Policies (SCPs)](https://docs.aws.amazon.com/organizations/latest/userguide/orgs_manage_policies_scps.html) to restrict access where necessary.
+
+---
+
+### Step 2: Verify Regional and Model Access
+
+#### 2.1 Choose and Confirm a Region
+
+1. **Select a Region:**\
+   AWS Bedrock is available in multiple regions (e.g., US East, Europe, Asia Pacific). Choose the region that meets your latency and compliance needs.\
+   [AWS Global Infrastructure](https://aws.amazon.com/about-aws/global-infrastructure/regions_az/)
+2. **Verify Model Access:**
+    - In the AWS Bedrock console, confirm that the models your team requires (e.g., Anthropic Claude, Amazon Titan) are marked as "Access granted."
+    - **Note:** Some advanced models might require an [Inference Profile](https://docs.aws.amazon.com/bedrock/latest/userguide/inference-profiles-prereq.html) if not available on-demand.
+
+#### 2.2 Set Up AWS Marketplace Subscriptions (if needed)
+
+1. **Subscribe to Third-Party Models:**
+    - Navigate to the AWS Bedrock console and locate the model subscription section.
+    - For models from third-party providers (e.g., Anthropic), accept the terms to subscribe.
+    - [AWS Marketplace](https://aws.amazon.com/marketplace/)
+2. **Enterprise Tip:**
+    - Model subscriptions are often managed centrally. Confirm with your cloud team if a standard subscription process is in place.
+
+---
+
+### Step 3: Configure the Cline VS Code Extension
+
+#### 3.1 Install and Open Cline
+
+1. **Install VS Code:**\
+   Download from the [VS Code website](https://code.visualstudio.com/).
+2. **Install the Cline Extension:**
+    - Open VS Code.
+    - Go to the Extensions Marketplace (`Ctrl+Shift+X` or `Cmd+Shift+X`).
+    - Search for **Cline** and install it.
+
+#### 3.2 Configure Cline Settings
+
+1. **Open Cline Settings:**
+    - Click on the settings ⚙️ to select your API Provider.
+2. **Select AWS Bedrock as the API Provider:**
+    - From the API Provider dropdown, choose **AWS Bedrock**.
+3. **Enter Your AWS Credentials:**
+    - Input your **Access Key** and **Secret Key** (or use temporary credentials if using AWS SSO).
+    - Specify the correct **AWS Region** (e.g., `us-east-1` or your enterprise-approved region).
+4. **Select a Model:**
+    - Choose an on-demand model (e.g., **anthropic.claude-3-5-sonnet-20241022-v2:0**).
+5. **Save and Test:**
+    - Click **Done/Save** to apply your settings.
+    - Test the integration by sending a simple prompt (e.g., "Generate a Python function to check if a number is prime.").
+
+---
+
+### Step 4: Security, Monitoring, and Best Practices
+
+1. **Secure Access:**
+    - Prefer AWS SSO/federated roles over long-lived IAM credentials.
+    - [AWS IAM Best Practices](https://docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html)
+2. **Enhance Network Security:**
+    - Consider setting up [AWS PrivateLink](https://docs.aws.amazon.com/vpc/latest/userguide/endpoint-services-overview.html) to securely connect to Bedrock.
+3. **Monitor and Log Activity:**
+    - Enable AWS CloudTrail to log Bedrock API calls.
+    - Use CloudWatch to monitor metrics like invocation count, latency, and token usage.
+    - Set up alerts for abnormal activity.
+4. **Handle Errors and Manage Costs:**
+    - Implement exponential backoff for throttling errors.
+    - Use AWS Cost Explorer and set billing alerts to track usage.\
+      [AWS Cost Management](https://docs.aws.amazon.com/cost-management/latest/userguide/what-is-aws-cost-management.html)
+5. **Regular Audits and Compliance:**
+    - Periodically review IAM roles and CloudTrail logs.
+    - Follow internal data privacy and governance policies.
+
+---
+
+### Conclusion
+
+By following these steps, your enterprise team can securely integrate AWS Bedrock with the Cline VS Code extension to accelerate development:
+
+1. **Prepare Your AWS Environment:** Create or use a secure IAM role/user, attach the `AmazonBedrockFullAccess` policy, and ensure necessary permissions.
+2. **Verify Region and Model Access:** Confirm that your selected region supports your required models and subscribe via AWS Marketplace if needed.
+3. **Configure Cline in VS Code:** Install and set up Cline with your AWS credentials and choose an appropriate model.
+4. **Implement Security and Monitoring:** Use best practices for IAM, network security, monitoring, and cost management.
+
+For further details, consult the [AWS Bedrock Documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html) and coordinate with your internal cloud team. Happy coding!
+
+---
+
+_This guide will be updated as AWS Bedrock and Cline evolve. Always refer to the latest documentation and internal policies for up-to-date practices._

docs/custom-model-configs/aws-bedrock-with-profile-authentication.mdx

@@ -0,0 +1,42 @@
+---
+title: "AWS Bedrock w/ Profile Authentication"
+description: "Learn how to configure AWS Bedrock to use AWS Profiles for authentication with Cline, focusing on SSO/Federated roles for secure access."
+---
+
+### Overview
+
+Cline offers the option of utilizing AWS credentials or AWS profiles to access AWS Bedrock services. SSO/Federated roles are suggested over Legacy IAM configuration; this guide describes how to configure your environment so that Cline uses SSO roles for authentication.
+
+---
+
+### Configuration Steps
+
+1. Install the [latest version](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html) of AWS CLI
+
+    - Follow the AWS docs to install your OS-specific version of AWS CLI
+
+2. [Configure IAM authentication](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-sso.html) with the AWS CLI
+
+    - If you do not already have AWS access through the IAM Identity Center, follow the [IAM User Guide](https://docs.aws.amazon.com/singlesignon/latest/userguide/getting-started.html) to set up IAM users and roles. Ensure you have a `PowerUserAccess` role.
+    - If you have access to AWS through your employer, open your AWS access portal and find the appropriate account. Ensure you have `PowerUserAccess` permissions.
+    - Open the `Access keys` link and note the `SSO start URL` and `SSO region`, which are needed in the next step
+
+3. Continue configuring your profile using [the `aws configure sso` CLI wizard](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-sso.html#cli-configure-sso-configure)
+
+    - Once configured, use the following command to authenticate the AWS CLI: `aws sso login --profile <AWS-profile-name>`
+    - Note which profile name you attach to your AWS account, this is needed to configure Cline in the following steps
+
+4. If you haven't already done so, install VSCode and the Cline extension. Consult the [Getting Started](/getting-started) page for guidance.
+
+5. Open the Cline extension, then click on the settings button ⚙️ to select your API Provider.
+    - From the API Provider dropdown, select AWS Bedrock
+    - Select the AWS Profile radio button, then enter the AWS Profile Name from step 3
+    - Select your AWS Region from the dropdown menu
+    - Selecting the cross-region inference checkbox is required for some models
+
+<Frame>
+	<img
+		src="/assets/robot_panel_dark.png"
+		alt="AWS Bedrock configuration in Cline settings showing profile authentication setup"
+	/>
+</Frame>

docs/custom-model-configs/gcp-vertex-ai.mdx

@@ -0,0 +1,206 @@
+---
+title: "GCP Vertex AI"
+description: "Configure GCP Vertex AI with Cline to access leading generative AI models like Claude 3.5 Sonnet v2. This guide covers GCP environment setup, authentication, and secure integration for enterprise teams."
+---
+
+### Overview
+
+**GCP Vertex AI:**\
+A fully managed service that provides access to leading generative AI models—such as Anthropic's Claude 3.5 Sonnet v2—through Google Cloud.\
+[Learn more about GCP Vertex AI](https://cloud.google.com/vertex-ai).
+
+This guide is tailored for organizations with established GCP environments (leveraging IAM roles, service accounts, and best practices in resource management) to ensure secure and compliant usage.
+
+---
+
+### Step 1: Prepare Your GCP Environment
+
+#### 1.1 Create or Use a GCP Project
+
+-   **Sign in to the GCP Console:**\
+    [Google Cloud Console](https://console.cloud.google.com/)
+-   **Select or Create a Project:**\
+    Use an existing project or create a new one dedicated to Vertex AI.
+
+#### 1.2 Set Up IAM Permissions and Service Accounts
+
+-   **Assign Required Roles:**
+
+    -   Grant your user (or service account) the **Vertex AI User** role (`roles/aiplatform.user`)
+    -   For service accounts, also attach the **Vertex AI Service Agent** role (`roles/aiplatform.serviceAgent`) to enable certain operations
+    -   Consider additional predefined roles as needed:
+        -   Vertex AI Platform Express Admin
+        -   Vertex AI Platform Express User
+        -   Vertex AI Migration Service User
+
+-   **Cross-Project Resource Access:**
+    -   For BigQuery tables in different projects, assign the **BigQuery Data Viewer** role
+    -   For Cloud Storage buckets in different projects, assign the **Storage Object Viewer** role
+    -   For external data sources, refer to the [GCP Vertex AI Access Control documentation](https://cloud.google.com/vertex-ai/docs/general/access-control)
+
+---
+
+### Step 2: Verify Regional and Model Access
+
+#### 2.1 Choose and Confirm a Region
+
+Vertex AI supports eight regions. Select a region that meets your latency, compliance, and capacity needs. Examples include:
+
+-   **us-east5 (Columbus, Ohio)**
+-   **us-east1 (South Carolina)**
+-   **us-east4 (Northern Virginia)**
+-   **us-central1 (Iowa)**
+-   **us-west1 (The Dalles, Oregon)**
+-   **us-west4 (Las Vegas, Nevada)**
+-   **europe-west1 (Belgium)**
+-   **asia-southeast1 (Singapore)**
+
+#### 2.2 Enable the Claude 3.5 Sonnet v2 Model
+
+-   **Open Vertex AI Model Garden:**\
+    In the Cloud Console, navigate to **Vertex AI → Model Garden**
+-   **Enable Claude 3.5 Sonnet v2:**\
+    Locate the model card for Claude 3.5 Sonnet v2 and click **Enable**
+
+---
+
+### Step 3: Configure the Cline VS Code Extension
+
+#### 3.1 Install and Open Cline
+
+-   **Download VS Code:**\
+    [Download Visual Studio Code](https://code.visualstudio.com/)
+-   **Install the Cline Extension:**
+    -   Open VS Code
+    -   Navigate to the Extensions Marketplace (Ctrl+Shift+X or Cmd+Shift+X)
+    -   Search for **Cline** and install the extension
+
+<Frame>
+	<img src="/assets/robot_panel_dark.png" alt="Cline extension in VS Code" />
+</Frame>
+
+#### 3.2 Configure Cline Settings
+
+-   **Open Cline Settings:**\
+    Click the settings ⚙️ icon within the Cline extension
+-   **Set API Provider:**\
+    Choose **GCP Vertex AI** from the API Provider dropdown
+-   **Enter Your Google Cloud Project ID:**\
+    Provide the project ID you set up earlier
+-   **Select the Region:**\
+    Choose one of the supported regions (e.g., `us-east5`)
+-   **Select the Model:**\
+    From the available list, choose **Claude 3.5 Sonnet v2**
+-   **Save and Test:**\
+    Save your settings and test by sending a simple prompt (e.g., "Generate a Python function to check if a number is prime.")
+
+---
+
+### Step 4: Authentication and Credentials Setup
+
+#### Option A: Using Your Google Account (User Credentials)
+
+1. **Install the Google Cloud CLI:**\
+   Follow the [installation guide](https://cloud.google.com/sdk/docs/install)
+2. **Initialize and Authenticate:**
+
+    ```bash
+    gcloud init
+    gcloud auth application-default login
+    ```
+
+    - This sets up Application Default Credentials (ADC) using your Google account
+
+3. **Restart VS Code:**\
+   Ensure VS Code is restarted so that the Cline extension picks up the new credentials
+
+#### Option B: Using a Service Account (JSON Key)
+
+1. **Create a Service Account:**
+
+    - In the GCP Console, navigate to **IAM & Admin > Service Accounts**
+    - Create a new service account (e.g., "vertex-ai-client")
+
+2. **Assign Roles:**
+
+    - Attach **Vertex AI User** (`roles/aiplatform.user`)
+    - Attach **Vertex AI Service Agent** (`roles/aiplatform.serviceAgent`)
+    - Optionally, add other roles as required
+
+3. **Generate a JSON Key:**
+
+    - In the Service Accounts section, manage keys for your service account and download the JSON key
+
+4. **Set the Environment Variable:**
+
+    ```bash
+    export GOOGLE_APPLICATION_CREDENTIALS="/path/to/your/service-account-key.json"
+    ```
+
+    - This instructs Google Cloud client libraries (and Cline) to use this key
+
+5. **Restart VS Code:**\
+   Launch VS Code from a terminal where the `GOOGLE_APPLICATION_CREDENTIALS` variable is set
+
+---
+
+### Step 5: Security, Monitoring, and Best Practices
+
+#### 5.1 Enforce Least Privilege
+
+-   **Principle of Least Privilege:**\
+    Only grant the minimum necessary permissions. Custom roles can offer finer control compared to broad predefined roles
+-   **Best Practices:**\
+    Refer to [GCP IAM Best Practices](https://cloud.google.com/iam/docs/best-practices)
+
+#### 5.2 Manage Resource Access
+
+-   **Project vs. Resource-Level Access:**\
+    Access can be managed at both levels. Note that resource-level permissions (e.g., for BigQuery or Cloud Storage) add to, but do not override, project-level policies
+
+#### 5.3 Monitor Usage and Quotas
+
+-   **Model Observability Dashboard:**
+
+    -   In the Vertex AI Console, navigate to the **Model Observability** dashboard
+    -   Monitor metrics such as request throughput, latency, and error rates (including 429 quota errors)
+
+-   **Quota Management:**
+    -   If you encounter 429 errors, check the **IAM & Admin > Quotas** page
+    -   Request a quota increase if necessary\
+        [Learn more about GCP Vertex AI Quotas](https://cloud.google.com/vertex-ai/docs/quotas)
+
+#### 5.4 Service Agents and Cross-Project Considerations
+
+-   **Service Agents:**\
+    Be aware of the different service agents:
+
+    -   Vertex AI Service Agent
+    -   Vertex AI RAG Data Service Agent
+    -   Vertex AI Custom Code Service Agent
+    -   Vertex AI Extension Service Agent
+
+-   **Cross-Project Access:**\
+    For resources in other projects (e.g., BigQuery, Cloud Storage), ensure that the appropriate roles (BigQuery Data Viewer, Storage Object Viewer) are assigned
+
+---
+
+### Conclusion
+
+By following these steps, your enterprise team can securely integrate GCP Vertex AI with the Cline VS Code extension to harness the power of **Claude 3.5 Sonnet v2**:
+
+-   **Prepare Your GCP Environment:**\
+    Create or use a project, configure IAM with least privilege, and ensure necessary roles (including the Vertex AI Service Agent role) are attached
+-   **Verify Regional and Model Access:**\
+    Confirm that your chosen region supports Claude 3.5 Sonnet v2 and that the model is enabled
+-   **Configure Cline in VS Code:**\
+    Install Cline, enter your project ID, select the appropriate region, and choose the model
+-   **Set Up Authentication:**\
+    Use either user credentials (via `gcloud auth application-default login`) or a service account with a JSON key
+-   **Implement Security and Monitoring:**\
+    Adhere to best practices for IAM, manage resource access carefully, and monitor usage with the Model Observability dashboard
+
+For further details, please consult the [GCP Vertex AI Documentation](https://cloud.google.com/vertex-ai/docs) and your internal security policies.\
+Happy coding!
+
+_This guide will be updated as GCP Vertex AI and Cline evolve. Always refer to the latest documentation for current practices._

docs/custom-model-configs/litellm-and-cline-using-codestral.mdx

@@ -0,0 +1,65 @@
+---
+title: "LiteLLM & Cline (using Codestral)"
+description: "Learn how to set up and run LiteLLM with Cline using the Codestral model. This guide covers Docker setup, configuration, and integration with Cline."
+---
+
+### Using LiteLLM with Cline
+
+This guide demonstrates how to run a demo for LiteLLM starting with the Codestral model for use with Cline.
+
+#### Prerequisites
+
+-   [Docker CLI or Docker Desktop](https://www.docker.com/get-started/) installed to run the LiteLLM image locally
+-   For this example config: A Codestral API Key (different from the Mistral API Keys)
+
+#### Setup
+
+1. **Create a `.env` file and fill in the appropriate field**
+
+    ```bash
+    # Tip: Use the following command to generate a random alphanumeric key:
+    # openssl rand -base64 32 | tr -dc 'A-Za-z0-9' | head -c 32
+    LITELLM_MASTER_KEY=YOUR_LITELLM_MASTER_KEY
+    CODESTRAL_API_KEY=YOUR_CODESTRAL_API_KEY
+    ```
+
+    _Note: Although this is limited to localhost, it's a good practice set LITELLM_MASTER_KEY to something secure_
+
+2. **Configuration**
+
+    We'll need to create a `config.yaml` file to contain our LiteLLM configuration. In this case we'll just have one model, 'codestral-latest' and label it 'codestral'
+
+    ```yaml
+    model_list:
+        - model_name: codestral
+          litellm_params:
+              model: codestral/codestral-latest
+              api_key: os.environ/CODESTRAL_API_KEY
+    ```
+
+#### Running the Demo
+
+1. **Startup the LiteLLM docker container**
+
+    ```bash
+    docker run \
+        --env-file .env \
+        -v $(pwd)/config.yaml:/app/config.yaml \
+        -p 127.0.0.1:4000:4000 \
+        ghcr.io/berriai/litellm:main-latest \
+        --config /app/config.yaml --detailed_debug
+    ```
+
+2. **Setup Cline**
+
+    Once the LiteLLM server is up and running you can set it up in Cline:
+
+    - Base URL should be `http://0.0.0.0:4000/v1`
+    - API Key should be the one you set in `.env` for LITELLM_MASTER_KEY
+    - Model ID is `codestral` or whatever you named it under `config.yaml`
+
+#### Getting Help
+
+-   [LiteLLM Documentation](https://docs.litellm.ai/)
+-   [Mistral AI Console](https://console.mistral.ai/)
+-   [Cline Discord Community](https://discord.gg/cline)

docs/docs.json

@@ -80,6 +80,15 @@
 			{
 				"group": "Improving Your Prompting Skills",
 				"pages": ["prompting/prompt-engineering-guide", "prompting/cline-memory-bank"]
+			},
+			{
+				"group": "Custom Model Configurations",
+				"pages": [
+					"custom-model-configs/aws-bedrock-with-credentials-authentication",
+					"custom-model-configs/aws-bedrock-with-profile-authentication",
+					"custom-model-configs/gcp-vertex-ai",
+					"custom-model-configs/litellm-and-cline-using-codestral"
+				]
 			}
 		]
 	},