Lokesh-Tallapaneni
Lokesh-Tallapaneni's work was selected for the XERJ Corpus Hub, the open reference memory AI coding agents search before they write code. When an agent meets the same problem, it gets this implementation back as a worked example, with the author and the repository attached.
Totals across every corpus @Lokesh-Tallapaneni appears in; a commit selected for two corpora counts once. Files and lines count the selected commits; each corpus indexes the whole repository at its pinned commit.
What an agent can do with the veloce corpus
Lokesh-Tallapaneni/veloce: Async Python web framework where one route definition drives HTTP, OpenAPI and MCP tools. ASGI-native, written from scratch, batteries…
- Look up how veloce implements asgi, async, asyncio, with answers cited to file and line.
- Reuse a worked example: the commit “elect the first-request latch with a lock no event loop owns” (5 files · Python).
- Answer from veloce's real Python source instead of memory (AI, prompts and agents).
- Where does veloce handle “elect the first-request latch with a lock no event loop owns”?
- How does veloce implement asgi?
- What does tests do in veloce?
Search the GitHub repository Lokesh-Tallapaneni/veloce with XERJ (https://hub.xerj.org/corpus/lokesh-tallapaneni--veloce). Run these in a shell, in order, and check each result before the next: 1. xerj --help (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh 2. git clone https://github.com/Lokesh-Tallapaneni/veloce veloce && git -C veloce checkout c4bfe5313b701bbab9d8856dcddaaf19ca01cc97 3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data 4. xerj autoindex ./veloce --url http://127.0.0.1:9200 --prefix veloce --progress plain 5. xerj autoindex map --url http://127.0.0.1:9200 Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt Licence: MIT. Keep the copyright notice and credit the authors.
corpus lokesh-tallapaneni--veloce · AI, prompts and agents
Related corpora: aiohttp, httpx, dymmond/ravyn, coregx/fursy
AI search and retrieval with XERJ · Case study: reference coding for agents
Selected work
Lokesh-Tallapaneni/veloce
Async Python web framework where one route definition drives HTTP, OpenAPI and MCP tools. ASGI-native, written from scratch, batteries included
The corpus is the whole repository at the pinned commit, not only the files of the selected commit.
Sign in with GitHub or Hugging Face to see more: every selected commit in full (commit date, every folder, licence review state, pin) and the pack builds of each corpus.
[](https://hub.xerj.org/contributors/Lokesh-Tallapaneni)
Included with the author's permission (email, 2026-10-29), under each repository's own licence, with attribution. Own more repositories? Sign in with GitHub and add them. Want something removed? Reply to the email, withdraw it on /add, or open an issue on xerj-org/xerj.