Show HN: Plandex – an AI coding engine for complex tasks

• plandex

  16 9,021 9.8 Go

  An AI coding engine for building complex, real-world software with LLMs

  

Hey HN, I'm building Plandex (https://plandex.ai), an open source, terminal-based AI coding engine for complex tasks.

I built Plandex because I was tired of copying and pasting code back and forth between ChatGPT and my projects. It can complete tasks that span multiple files and require many steps. It uses the OpenAI API with your API key (support for other models, including Claude, Gemini, and open source models is on the roadmap). You can watch a 2 minute demo here: https://player.vimeo.com/video/926634577

Here's a prompt I used to build the AWS infrastructure for Plandex Cloud (Plandex can be self-hosted or cloud-hosted): https://github.com/plandex-ai/plandex/blob/main/test/test_pr...

Something I think sets Plandex apart is a focus on working around bad outputs and iterating on tasks systematically. It's relatively easy to make a great looking demo for any tool, but the day-to-day of working with it has a lot more to do with how it handles edge cases and failures. Plandex tries to tighten the feedback loop between developer and LLM:

- Every aspect of a Plandex plan is version-controlled, from the context to the conversation itself to model settings. As soon as things start to go off the rails, you can use the `plandex rewind` command to back up and add more context or iterate on the prompt. Git-style branches allow you to test and compare multiple approaches.

- As a plan proceeds, tentative updates are accumulated in a protected sandbox (also version-controlled), preventing any wayward edits to your project files.

- The `plandex changes` command opens a diff review TUI that lets you review pending changes side-by-side like the GitHub PR review UI. Just hit the 'r' key to reject any change that doesn’t look right. Once you’re satisfied, either press ctrl+a from the changes TUI or run `plandex apply` to apply the changes.

- If you work on files you’ve loaded into context outside of Plandex, your changes are pulled in automatically so that the model always uses the latest state of your project.

Plandex makes it easy to load files and directories in the terminal. You can load multiple paths:

  plandex load components/some-component.ts lib/api.ts ../sibling-dir/another-file.ts

• openrouter-runner

  11 339 9.5 Python

  Inference engine powering open source models on OpenRouter

  

Not affiliated with the project but you could use something like OpenRouter to give users a massive list of models to choose from with fairly minimal effort

https://openrouter.ai/

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• r2ai

  1 51 9.5 Python

  local language model for radare2

  

I think Mistral-2-Pro would work really well for this, judging by the great results I've had with it on another heavy on tool calling project [1]

[1] https://github.com/radareorg/r2ai

• ollama

  203 64,536 9.9 Go

  Get up and running with Llama 3, Mistral, Gemma, and other large language models.

  

Suggest a related project