# Fnord
[](https://github.com/sysread/fnord/actions/workflows/run-tests.yml)
Fnord is a command line tool that uses multiple AI-powered agents and tools to
provide a conversational interface to your codebase, notes, and other
(non-binary) files.
## Features
- Code base search
- Graph search and pathfinding
- On-demand playbooks assembled from documentation and code
- Troubleshooting and debugging
- Git archaeology
- Learns about your project(s) over time
- Improves its research capabilities with each interaction
## Installation
1. Install `elixir` if necessary:
```bash
# MacOS
brew install elixir
# Debian-based
sudo apt-get install elixir
```
2. Add the mix escript path to your shell's PATH:
```bash
echo 'export PATH="$HOME/.mix/escripts:$PATH"' >> ~/.bashrc
source ~/.bashrc
```
3. Install the script:
```bash
mix escript.install github sysread/fnord
```
Use the same command to reinstall. It will offer to overwrite the existing
installation.
4. Set `OPENAI_API_KEY`
Set this in your shell environment to the OpenAI project key you wish to use
for this tool. You can create a new project and get a key
[here](https://platform.openai.com/api-keys).
## Usage
### Index
The first step is to index your project. This will scan all files in the
project directory and create a searchable database.
The initial index, especially on a large codebase, can will take a while.
Subsequent runs will be faster, re-indexing only those files which have changed
since they were last indexed.
The `--dir` option is required only for the initial indexing. Subsequent
indexing will use the directory specified in the initial index.
```bash
fnord index --project foo --dir /path/to/foo
```
You can **reindex** the project, forcing it to reindex all files.
```bash
fnord index -p foo -d /path/to/foo --reindex
```
`fnord` learns about your project over time, so every now and then it's a good
idea to **consolidate** the notes it has taken.
```bash
fnord index -p foo --defrag-notes
```
You can also watch the project for changes and reindex them as they happen
using [watchman](https://github.com/facebook/watchman). Just be sure to use
`--quiet` to suppress interactive output.
```bash
watchman-make -p '**/*' --settle 5 --run "fnord index --project $project --dir $project_root --quiet"
```
...or use the `fnord-watch` script in the [tools directory on
GitHub](https://github.com/sysread/fnord/blob/main/tools/fnord-watch).
```bash
fnord-watch -p foo -d /path/to/foo
```
### Search
Search for files in the project that match a query.
```bash
fnord search -p foo -q "some search query"
```
If you want more detail about each file matched:
```bash
fnord search -p foo -q "some search query" --detail
```
### Ask
Ask the AI assistant to answer questions about your project.
```bash
fnord ask -p foo -q "how do you run the tests for this project?"
# Pipe output to `glow` to render markdown
fnord ask -p foo -q "summarize the dependencies of this project" | glow
# Reveal tool calls and research steps
LOGGER_LEVEL=debug fnord ask -p foo -q "summarize the dependencies of this project" | glow
```
### Miscellaneous
- **List projects:** `fnord projects`
- **List files in a project:** `fnord files -p foo`
- **List learned insights and inferences:** `fnord notes -p foo`
- **List learned research strategies:** `fnord strategies`
- **Show the AI-generated summary of a file:** `fnord summary -p foo -f bar.ext`
- **Delete a project:** `fnord delete -p foo`
- **Show conversations:** `fnord conversations -p foo -q`
Note that deleting a project only deletes from the index, not the actual files.
## Tool usage
Internally, the `ask` command uses the OpenAI chat completions API to generate
a response, implementing a function tool to allow the assistant to query the
database for information.
`fnord` can be used to implement a similar tool for your own projects. While
the `ask` command severely limits the parameters that the assistant may utilize
(`query` only, with `project` being provided by the user's invocation of the
command), the following syntax includes the full set of parameters available
for the `search` command.
```json
{
"name": "search_tool",
"description": "Searches for matching files and their contents in a project.",
"parameters": {
"type": "object",
"properties": {
"project": {
"type": "string",
"description": "Project name for the search."
},
"query": {
"type": "string",
"description": "The search query string."
},
"detail": {
"type": "boolean",
"description": "Include AI-generated file summary if set to true."
},
"limit": {
"type": "integer",
"description": "Limit the number of results (default: 10)."
},
"workers": {
"type": "integer",
"description": "Number of concurrent workers to use for the search."
}
},
"required": ["project", "query"]
}
}
```
# TODO
- ask: report how old the index is
- index: option to verify and consolidate notes
