# Praneeth Ravuri’s developer project resources

## Using these resources

Praneeth Ravuri’s public project repositories are the source for setup instructions, implementation details, dependencies, and licensing. Follow each repository’s current README before running a project. This portfolio provides a directory and descriptions; it does not host an API, authentication service, or MCP server. Pitstop is an MCP project whose installation and configuration belong to its repository.

## Tether

Coding agents in separate terminals need a way to talk and coordinate edits. Tether gives them a shared inbox through a local CLI. Agents can send questions, wait for replies, leave handoffs, and claim files they plan to work on. A Go daemon stores messages in SQLite and connects sessions across Git worktrees. Technologies: Go, SQLite, Unix Sockets.

- [Tether source code](https://github.com/praneethravuri/tether)
- [Tether README and setup](https://github.com/praneethravuri/tether#readme)

## Gary

Gary takes a master resume and a job description and produces a tailored Word document. Three agent passes analyze the role, draft the resume, and check the result against the source material. A document template keeps the formatting consistent, and Google Sheets records the application details. Technologies: Python, CrewAI, Pydantic, docxtpl, Google Sheets API.

- [Gary source code](https://github.com/praneethravuri/gary)
- [Gary README and setup](https://github.com/praneethravuri/gary#readme)

## Pitstop

Pitstop brings Formula 1 data into an AI chat through MCP. Its tools cover race results, standings, schedules, telemetry, and news. For questions about a race, it can compare lap pace, summarize stints, and calculate how lap times change over a tire stint. It combines FastF1, Jolpica, and OpenF1 with a queryable SQLite database. Technologies: Python, FastMCP, FastF1, HTTPX, SQLite.

- [Pitstop source code](https://github.com/praneethravuri/pitstop)
- [Pitstop README and setup](https://github.com/praneethravuri/pitstop#readme)

## Smart Traffic

A university team project exploring how reinforcement learning can control a four-way intersection. A SARSA agent chooses which direction gets a green light, using accumulated vehicle delays to represent traffic conditions. Pygame shows the traffic simulation, while learning curves track the agent’s behavior during training. Technologies: Python, NumPy, Pygame, Matplotlib.

- [Smart Traffic source code](https://github.com/praneethravuri/traffic-congestion-reduction-with-SARSA)
- [Smart Traffic README and setup](https://github.com/praneethravuri/traffic-congestion-reduction-with-SARSA#readme)

## Notstuck

Upload a PDF, Word document, or text file, then ask questions about it. Notstuck splits the document into chunks, embeds them, and retrieves relevant passages from Pinecone. A chat interface shows the answer alongside document references. The assistant also has a web-search tool for questions beyond the uploaded files. Technologies: Next.js, TypeScript, FastAPI, Pinecone, CrewAI, OpenAI Embeddings.

- [Notstuck source code](https://github.com/praneethravuri/notstuck)
- [Notstuck README and setup](https://github.com/praneethravuri/notstuck#readme)

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