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@@ -4,9 +4,9 @@ import Image from '@theme/IdealImage';
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# Track Usage for Coding Tools
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This tutorial shows how to track usage and costs for AI-powered coding tools like Claude Code, Roo Code, Gemini CLI, and OpenAI Codex through LiteLLM.
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Track usage and costs for AI-powered coding tools like Claude Code, Roo Code, Gemini CLI, and OpenAI Codex through LiteLLM.
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Track requests, total costs, and user engagement metrics for each coding tool via User-Agent headers.
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Monitor requests, costs, and user engagement metrics for each coding tool using User-Agent headers.
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<Image
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img={require('../../img/agent_1.png')}
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@@ -16,24 +16,24 @@ Track requests, total costs, and user engagement metrics for each coding tool vi
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## Who This Is For
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Central AI Platform teams providing developers access to coding tools through LiteLLM. Use this to monitor tool engagement and track individual user usage patterns.
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Central AI Platform teams providing developers access to coding tools through LiteLLM. Monitor tool engagement and track individual user usage patterns.
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## What LiteLLM Tracks
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## What You Can Track
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### Summary Metrics
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- Cost per coding tool
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- Successful requests and token usage per tool
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### User Engagement Metrics
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### User Engagement Metrics
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- Daily, weekly, and monthly active users for each User-Agent
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## Quick Start
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### 1. Connect Your Coding Tool to LiteLLM
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Configure your coding tool to send requests through LiteLLM proxy with appropriate User-Agent headers.
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Configure your coding tool to send requests through the LiteLLM proxy with appropriate User-Agent headers.
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Follow these instructions to connect your coding tool to LiteLLM:
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**Setup guides:**
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- [Use LiteLLM with Claude Code](../../docs/tutorials/claude_responses_api)
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- [Use LiteLLM with Gemini CLI](../../docs/tutorials/litellm_gemini_cli)
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- [Use LiteLLM with OpenAI Codex](../../docs/tutorials/openai_codex)
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@@ -44,7 +44,7 @@ Ensure your coding tool includes identifying User-Agent headers in API requests.
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### 3. Verify Tracking in LiteLLM Logs
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Confirm that LiteLLM is properly tracking requests by checking logs for the expected User-Agent values.
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Confirm LiteLLM is properly tracking requests by checking logs for the expected User-Agent values.
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<Image
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img={require('../../img/agent_2.png')}
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@@ -57,42 +57,35 @@ Access the LiteLLM dashboard to view aggregated usage metrics and user engagemen
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#### Summary Metrics
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This shows the total cost and successful requests for each coding tool.
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<br/>
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View total cost and successful requests for each coding tool.
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<Image
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img={require('../../img/agent_3.png')}
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style={{width: '100%', display: 'block', margin: '2rem auto'}}
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/>
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#### Daily, Weekly, and Monthly Active Users
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#### DAU, WAU, MAU
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This shows the daily, weekly, and monthly active users for each coding tool.
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<br/>
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View active user metrics for each coding tool.
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<Image
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img={require('../../img/agent_4.png')}
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style={{width: '80%', display: 'block', margin: '2rem auto'}}
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/>
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## How LiteLLM Identifies Coding Tools
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LiteLLM tracks coding tools by monitoring the `User-Agent` header in incoming API requests (`/chat/completions`, `/responses`, etc.). Each unique User-Agent is tracked separately for usage analytics.
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### Example Request
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Here's an example using `claude-cli` as the User-Agent:
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Example using `claude-cli` as the User-Agent:
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```shell
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curl -X POST \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer sk-1234" \
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-H "User-Agent: claude-cli/1.0" \
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-d '{"model": "claude-3-5-sonnet-latest", "messages": [{"role": "user", "content": "Hello, how are you?"}]}' \
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http://localhost:4000/chat/completions
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer sk-1234" \
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-H "User-Agent: claude-cli/1.0" \
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-d '{"model": "claude-3-5-sonnet-latest", "messages": [{"role": "user", "content": "Hello, how are you?"}]}' \
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http://localhost:4000/chat/completions
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```
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