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https://github.com/tiennm99/litellm.git
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add tutorial as well
This commit is contained in:
Sameer Kankute
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---
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sidebar_label: "Cursor IDE"
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---
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import Tabs from '@theme/Tabs';
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import TabItem from '@theme/TabItem';
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# Cursor IDE Integration with LiteLLM
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This tutorial shows you how to integrate Cursor IDE with LiteLLM Proxy, allowing you to use any LiteLLM-supported model through Cursor's interface with BYOK (Bring Your Own Key) and custom base URL.
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## Benefits of using Cursor with LiteLLM
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When you use Cursor IDE with LiteLLM you get the following benefits:
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**Developer Benefits:**
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- Universal Model Access: Use any LiteLLM supported model (Anthropic, OpenAI, Vertex AI, Bedrock, etc.) through the Cursor IDE interface.
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- Higher Rate Limits & Reliability: Load balance across multiple models and providers to avoid hitting individual provider limits, with fallbacks to ensure you get responses even if one provider fails.
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- Streaming Support: Full streaming support with proper response transformation for Cursor's expected format.
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**Proxy Admin Benefits:**
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- Centralized Management: Control access to all models through a single LiteLLM proxy instance without giving your developers API Keys to each provider.
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- Budget Controls: Set spending limits and track costs across all Cursor usage.
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- Request Logging: Track all requests made through Cursor for debugging and monitoring.
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## Prerequisites
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Before you begin, ensure you have:
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- Cursor IDE installed
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- A running LiteLLM Proxy instance with **HTTPS enabled** (HTTP is not supported)
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- A valid LiteLLM Proxy API key
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- An HTTPS domain for your LiteLLM Proxy (required by Cursor)
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## Quick Start Guide
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### Step 1: Install LiteLLM
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Install LiteLLM with proxy support:
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```bash
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pip install litellm[proxy]
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```
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### Step 2: Configure LiteLLM Proxy
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Create a `config.yaml` file with your model configurations:
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```yaml showLineNumbers title="config.yaml"
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model_list:
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- model_name: gpt-4o
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litellm_params:
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model: gpt-4o
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api_key: os.environ/OPENAI_API_KEY
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- model_name: claude-3-5-sonnet
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litellm_params:
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model: anthropic/claude-3-5-sonnet-20241022
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api_key: os.environ/ANTHROPIC_API_KEY
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general_settings:
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master_key: sk-1234567890 # Change this to a secure key
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```
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### Step 3: Start LiteLLM Proxy
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Start the proxy server with HTTPS enabled:
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```bash
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litellm --config config.yaml --port 4000
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```
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:::warning HTTPS Required
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**Important**: Cursor IDE requires HTTPS connections. HTTP (`http://`) will not work. You must:
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- Deploy your LiteLLM Proxy with HTTPS enabled
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- Use a valid SSL certificate
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- Access the proxy via an HTTPS domain (e.g., `https://your-proxy-domain.com`)
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For local development, you'll need to set up HTTPS (e.g., using a reverse proxy like nginx with SSL, or deploying to a cloud service with HTTPS).
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:::
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### Step 4: Configure Cursor IDE
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Configure Cursor IDE to use your LiteLLM proxy with the `/cursor/chat/completions` endpoint:
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1. Open Cursor IDE
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2. Go to **Settings** → **Features** → **AI**
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3. Enable **"Use Custom API"** or **"Bring Your Own Key"**
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4. Set the following:
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- **Base URL**: `https://your-proxy-domain.com/cursor` (⚠️ **Important**: Must use HTTPS and include `/cursor`)
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- **API Key**: Your LiteLLM Proxy API key (e.g., `sk-1234567890`)
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:::warning HTTPS Required
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Cursor IDE **requires HTTPS** connections. HTTP (`http://`) will not work. You must:
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- Use an HTTPS URL for your base URL (e.g., `https://your-proxy-domain.com/cursor`)
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- Ensure your LiteLLM Proxy is accessible via HTTPS
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- Have a valid SSL certificate configured
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:::
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**Example Configuration:**
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```
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Base URL: https://your-proxy-domain.com/cursor
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API Key: sk-1234567890
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```
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Replace `your-proxy-domain.com` with your actual HTTPS domain where LiteLLM Proxy is running.
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:::info Why `/cursor` in the base URL?
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Cursor automatically appends `/chat/completions` to the base URL you provide. By setting the base URL to `https://your-proxy-domain.com/cursor`, Cursor will send requests to `/cursor/chat/completions`, which is the special endpoint that handles Cursor's Responses API input format and transforms it to Chat Completions output format.
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If you set the base URL to just `https://your-proxy-domain.com`, Cursor would send requests to `/chat/completions`, which won't work correctly with Cursor's request format.
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:::
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### Step 5: Test the Integration
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1. Restart Cursor IDE to apply the settings
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2. Open a code file and try using Cursor's AI features (completions, chat, etc.)
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3. Your requests will now be routed through LiteLLM Proxy
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You can verify it's working by:
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- Checking the LiteLLM Proxy logs for incoming requests
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- Using Cursor's chat feature and seeing responses stream correctly
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- Checking your LiteLLM dashboard for request logs and cost tracking
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## How It Works
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The `/cursor/chat/completions` endpoint is specifically designed to handle Cursor's unique request format:
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1. **Input**: Cursor sends requests in OpenAI Responses API format (with `input` field)
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2. **Processing**: LiteLLM processes the request through its internal `/responses` flow
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3. **Output**: The response is transformed to OpenAI Chat Completions format (with `choices` field) that Cursor expects
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This transformation happens automatically for both streaming and non-streaming responses.
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## Advanced Configuration
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### Using Different Models
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You can configure Cursor to use different models by updating your `config.yaml`:
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```yaml showLineNumbers title="config.yaml"
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model_list:
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- model_name: gpt-4o
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litellm_params:
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model: gpt-4o
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api_key: os.environ/OPENAI_API_KEY
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- model_name: claude-3-5-sonnet
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litellm_params:
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model: anthropic/claude-3-5-sonnet-20241022
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api_key: os.environ/ANTHROPIC_API_KEY
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- model_name: gemini-pro
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litellm_params:
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model: gemini/gemini-1.5-pro
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api_key: os.environ/GEMINI_API_KEY
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```
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Then in Cursor, you can specify which model to use in your requests.
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### Rate Limiting and Budgets
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Set up rate limits and budgets in your `config.yaml`:
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```yaml showLineNumbers title="config.yaml"
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general_settings:
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master_key: sk-1234567890
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litellm_settings:
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# Set max budget per user
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max_budget: 100.0
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# Set rate limits
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rate_limit: 100 # requests per minute
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```
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### Request Logging
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All requests from Cursor will be logged by LiteLLM Proxy. You can:
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- View logs in the LiteLLM Admin UI
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- Export logs to your preferred logging service
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- Track costs per user/team
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## Troubleshooting
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### Cursor shows no output
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- **Check base URL**: Ensure it uses HTTPS and includes `/cursor` (e.g., `https://your-proxy-domain.com/cursor`, not `http://` or without `/cursor`)
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- **Verify HTTPS**: Cursor requires HTTPS - HTTP connections will not work
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- **Check API key**: Verify your LiteLLM Proxy API key is correct
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- **Check proxy logs**: Look for errors in the LiteLLM Proxy logs
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### Requests failing
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- **Verify HTTPS is enabled**: Cursor requires HTTPS connections. Ensure your LiteLLM Proxy is accessible via HTTPS with a valid SSL certificate
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- **Verify proxy is running**: Check that LiteLLM Proxy is accessible at your HTTPS base URL
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- **Check SSL certificate**: Ensure your SSL certificate is valid and not expired
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- **Check model configuration**: Ensure the model you're trying to use is configured in `config.yaml`
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- **Check API keys**: Verify provider API keys are set correctly in environment variables
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### HTTP not working
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If you're trying to use HTTP (`http://`) and it's not working:
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- **This is expected**: Cursor IDE requires HTTPS connections
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- **Solution**: Deploy your LiteLLM Proxy with HTTPS enabled (use a reverse proxy like nginx, or deploy to a cloud service that provides HTTPS)
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### Streaming not working
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The `/cursor/chat/completions` endpoint automatically handles streaming. If streaming isn't working:
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- Check that your model supports streaming
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- Verify the proxy logs for any transformation errors
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- Ensure Cursor IDE is up to date
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## Related Documentation
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- [Cursor Endpoint Documentation](/docs/proxy/cursor) - Detailed endpoint documentation
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- [LiteLLM Proxy Setup](/docs/proxy/quick_start) - General proxy setup guide
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- [Model Configuration](/docs/proxy/configs) - How to configure models
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@@ -105,6 +105,7 @@ const sidebars = {
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items: [
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"tutorials/claude_responses_api",
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"tutorials/cost_tracking_coding",
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"tutorials/cursor_integration",
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"tutorials/github_copilot_integration",
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"tutorials/litellm_gemini_cli",
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"tutorials/litellm_qwen_code_cli",
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@@ -129,16 +130,6 @@ const sidebars = {
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},
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items: [
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"proxy/docker_quick_start",
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{
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type: "link",
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label: "A2A Agent Gateway",
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href: "https://docs.litellm.ai/docs/a2a",
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},
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{
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type: "link",
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label: "MCP Gateway",
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href: "https://docs.litellm.ai/docs/mcp",
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},
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{
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"type": "category",
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"label": "Config.yaml",
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@@ -195,7 +186,6 @@ const sidebars = {
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label: "Architecture",
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items: [
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"proxy/architecture",
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"proxy/multi_tenant_architecture",
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"proxy/control_plane_and_data_plane",
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"proxy/db_deadlocks",
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"proxy/db_info",
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@@ -327,14 +317,6 @@ const sidebars = {
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slug: "/supported_endpoints",
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},
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items: [
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{
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type: "category",
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label: "/a2a - A2A Agent Gateway",
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items: [
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"a2a",
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"a2a_agent_permissions",
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],
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},
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"assistants",
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{
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type: "category",
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@@ -448,7 +430,6 @@ const sidebars = {
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"realtime",
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"rerank",
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"response_api",
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"proxy/cursor",
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{
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type: "category",
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label: "/search",
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@@ -491,11 +472,6 @@ const sidebars = {
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id: "provider_registration/index",
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label: "Integrate as a Model Provider",
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},
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{
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type: "doc",
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id: "contributing/adding_openai_compatible_providers",
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label: "Add OpenAI-Compatible Provider (JSON)",
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},
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{
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type: "doc",
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id: "provider_registration/add_model_pricing",
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@@ -820,7 +796,6 @@ const sidebars = {
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type: "category",
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label: "Adding Providers",
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items: [
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"contributing/adding_openai_compatible_providers",
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"adding_provider/directory_structure",
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"adding_provider/new_rerank_provider",
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]
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