repowiseamithathreya/inference_layer

amithathreya / inference_layer

Custom inference gateway implementation for llama.cpp model deployments with standard openAI API spec

Python

github.com/amithathreya/inference_layerIndexed at 8c88c66Up to date with upstream

About this codebase

12 files and 51 symbols in 3 modules, written in Python.

Built from the index

Code health

8.6out of 10Excellent

Hotspots average 8.1, the place fixes pay off most.

Use amithathreya/inference_layer in your agent

Point Claude Code, Cursor, Codex or VS Code at this repository. Your agent gets the index this page is built from: cited answers, callers, history and health for any file.

  1. 1.In Claude, open Customize → Connectors, click +, then Add custom connector. On a Team or Enterprise plan an owner adds it first under Organization settings → Connectors.
  2. 2.Paste the server URL below as the Remote MCP server URL, then click Add.
  3. 3.Click Connect. A Repowise sign-in window opens. Approve access.
  4. 4.Repowise's tools are now available in your Claude chats.

Connect with one click. Sign in with Repowise (OAuth), no API key to copy. Works in Claude on the web, desktop, and mobile.

Docs
bash
https://api.repowise.dev/mcp/amithathreya/inference_layer
Editors need an API key: sign in to create one.Sign in to connect

This repo is public, so anyone with a Repowise account and an API key can connect.

Try asking

  • get_overview()
  • get_answer("how is inference_layer put together?")
  • get_why("why is inference_layer structured this way?")

Explore inference_layer

How amithathreya/inference_layer works

The codebase has 12 files and 51 symbols in 3 modules, led by Python. Code health is 8.6 out of 10, rated excellent.

About this page

Get a page like this for your own codebase

Repowise built this map of amithathreya/inference_layer from its source and git history. It parses every symbol, draws the dependency graph, scores each file's health from complexity, duplication, coverage and churn, finds hotspots and owners in the history, and writes documentation for every module. Your coding agent reads the same index over MCP, so its answers cite real files.

Index your repo freeSee how Repowise worksFree for 2 public repos, with a page like this one.

Prefer local? pip install repowise && repowise init indexes your own checkout, no account needed.