Wraps OpenAI and Anthropic clients transparently to log every API call to local SQLite. Provides CLI commands to break down spend by feature, detect retry waste, context bloat, duplicate calls, and model downgrade opportunities. All data stays local.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.
## 📋 Pull Request Information
**Original PR:** https://github.com/vinta/awesome-python/pull/3033
**Author:** [@BuildWithAbid](https://github.com/BuildWithAbid)
**Created:** 4/7/2026
**Status:** ❌ Closed
**Base:** `master` ← **Head:** `master`
---
### 📝 Commits (1)
- [`856039a`](https://github.com/vinta/awesome-python/commit/856039a91d15874b0a9eab8bbd916e93efdbe441) Add llm-cost-profiler to README
### 📊 Changes
**1 file changed** (+1 additions, -0 deletions)
<details>
<summary>View changed files</summary>
📝 `README.md` (+1 -0)
</details>
### 📄 Description
**llm-cost-profiler — Track, visualize, and optimize LLM API spending**
GitHub: https://github.com/BuildWithAbid/llm-cost-profiler
Install: pip install llm-spend-profiler
License: MIT
Python 3.9+, zero dependencies
Wraps OpenAI and Anthropic clients transparently to log every API call to local SQLite. Provides CLI commands to break down spend by feature, detect retry waste, context bloat, duplicate calls, and model downgrade opportunities. All data stays local.
---
<sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>
Blocking a user prevents them from interacting with repositories, such as opening or commenting on pull requests or issues. Learn more about blocking a user.
📋 Pull Request Information
Original PR: https://github.com/vinta/awesome-python/pull/3033
Author: @BuildWithAbid
Created: 4/7/2026
Status: ❌ Closed
Base:
master← Head:master📝 Commits (1)
856039aAdd llm-cost-profiler to README📊 Changes
1 file changed (+1 additions, -0 deletions)
View changed files
📝
README.md(+1 -0)📄 Description
llm-cost-profiler — Track, visualize, and optimize LLM API spending
GitHub: https://github.com/BuildWithAbid/llm-cost-profiler
Install: pip install llm-spend-profiler
License: MIT
Python 3.9+, zero dependencies
Wraps OpenAI and Anthropic clients transparently to log every API call to local SQLite. Provides CLI commands to break down spend by feature, detect retry waste, context bloat, duplicate calls, and model downgrade opportunities. All data stays local.
🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.