pie

pie is a Rust rewrite of the original pi project (pi-coding-agent). pie is a terminal-based AI coding agent, run it inside a project, ask it to inspect files, make edits, run shell commands, remember preferences, and continue previous sessions.

Install / build

git clone https://github.com/c4pt0r/pie.git
cd pie
cargo build --release

The CLI binary will be at ./target/release/pie.

Configure a model

pie auto-detects the first available provider credential. Set an API key before starting:

export ANTHROPIC_API_KEY=sk-ant-...
# or: OPENAI_API_KEY, OPENROUTER_API_KEY, GROQ_API_KEY,
#     MISTRAL_API_KEY, GEMINI_API_KEY, GOOGLE_API_KEY

You can also store a key from inside pie:

/login anthropic sk-ant-...

Local OpenAI-compatible models

pie can also use local OpenAI-compatible servers. Add a model definition to ~/.pie/models.json (user-global) or <project>/.pie/models.json (project-local, higher precedence), then select it with --provider and --model.

Example for DS4, the DeepSeek V4 Flash local server. The Responses endpoint is the preferred OpenAI-compatible API for Codex-style clients; chat completions also works for simpler integrations.

# In the DS4 checkout:
./ds4-server --ctx 100000 --kv-disk-dir /tmp/ds4-kv --kv-disk-space-mb 8192
# If launching from another directory, add: --chdir /path/to/ds4

{
  "models": [
    {
      "id": "deepseek-v4-flash",
      "name": "DeepSeek V4 Flash (local DS4)",
      "api": "openai-responses",
      "provider": "ds4",
      "baseUrl": "http://127.0.0.1:8000/v1",
      "reasoning": true,
      "thinkingLevelMap": {
        "off": null,
        "minimal": "low",
        "low": "low",
        "medium": "medium",
        "high": "high",
        "xhigh": "xhigh"
      },
      "input": ["text"],
      "cost": { "input": 0, "output": 0, "cacheRead": 0, "cacheWrite": 0 },
      "contextWindow": 100000,
      "maxTokens": 384000,
      "compat": {
        "supportsStore": false,
        "supportsDeveloperRole": false,
        "supportsReasoningEffort": true,
        "supportsUsageInStreaming": true,
        "maxTokensField": "max_tokens",
        "supportsStrictMode": false,
        "thinkingFormat": "deepseek",
        "requiresReasoningContentOnAssistantMessages": true
      }
    }
  ]
}

Then run:

export DS4_API_KEY=dsv4-local
./target/release/pie --provider ds4 --model deepseek-v4-flash

DS4 is local and accepts placeholder bearer tokens. You can also store the same local placeholder with /login ds4 dsv4-local. Using the ds4 provider keeps local model credentials separate from real OPENAI_API_KEY credentials.

Quick start

# Start in the current project
./target/release/pie

# Choose a specific provider/model
./target/release/pie --provider anthropic --model claude-haiku-4-5

# Enable extended thinking where supported
./target/release/pie --thinking high

# Resume the most recent session for this project
./target/release/pie --resume

Once the REPL opens, type a request such as:

summarize this repository
fix the failing tests
add a README example and run the relevant checks
when ~/build.done appears, run cargo test and show me the result

Useful commands

Inside pie, slash commands control the session:

Command	What it does
/help	Show all commands
/model [provider:model-id]	Show or switch model
/thinking	Show or set thinking level, off, minimal, low, medium, high, xhigh
/sessions	List sessions for the current project
/save [path]	Export the transcript to Markdown
/compact [instructions]	Compact long context
/undo	Remove the most recent user/assistant turn
/cost	Show token and cost totals
/login <provider> <api-key>	Store an API key
/logout <provider>	Remove a stored API key
/triggers	Show trigger rules, sources, running actions, and audit
/triggers rules	List dynamic trigger ids and state
/triggers enable <id> / /triggers disable <id>	Resume or pause a trigger
/triggers remove <id>	Delete a trigger
/quit	Exit

CLI helpers:

./target/release/pie --help
./target/release/pie --list-sessions
./target/release/pie --list-all-sessions
./target/release/pie --delete-session <id>
./target/release/pie --image screenshot.png

What pie can do

The agent has tools for common coding workflows:

• read, write, and edit files
• list files and search with grep/find
• run shell commands
• manage persistent memory
• delegate focused sub-tasks
• resume JSONL-backed sessions per project
• attach images to the first prompt with --image
• create session-scoped natural-language triggers that run actions when local checks or MCP push events match
• run local command hooks or HTTP webhooks on agent lifecycle events; see docs/hooks.md

Triggers

Triggers let you describe an automation in normal chat:

when $HOME/helloworld exists, print its contents

pie turns that request into a dynamic trigger rule. Rules are stored next to the active session, so a new session starts cleanly and --resume brings that session's rules back. Dynamic triggers fire once by default; ask for a repeating trigger when you want it to keep running.

Trigger actions run in a separate sub-agent. The sub-agent inherits the parent model, tools, tool hooks, thinking level, and skill catalog, but it does not receive the full parent conversation by default. Trigger output is shown in the TUI and written to trigger audit records. If you explicitly ask for the result to be visible to future turns, the rule is created with promote_to_chat=true and successful trigger output is inserted into the main chat context with a [Trigger ...] prefix.

Local dynamic checks poll every 60 seconds by default, and only emit checks while at least one enabled dynamic rule exists. Configure the interval in ~/.pie/config.toml:

[triggers]
poll_interval_secs = 60

For one run, override it with:

./target/release/pie --trigger-poll-secs 10

MCP notifications are treated as trigger sources too: a configured MCP server can push an event into the same trigger runtime, where the same rules, audit, deduping, and output behavior apply.

Files and storage

By default, pie stores local state under ~/.pie:

Path	What
~/.pie/sessions/<cwd-hash>/<uuidv7>.jsonl	Session history for each project
~/.pie/memory/*.md	Cross-session memory injected into future sessions
~/.pie/auth.json	Stored API keys from /login
~/.pie/models.json	User-global local/custom model definitions
~/.pie/history	Prompt history
~/.pie/hooks.toml	Optional command/webhook hooks
~/.pie/config.toml	Optional user config, including trigger poll interval

Set PIE_DIR to use a different base directory.

Development

cargo build --workspace
cargo test --workspace
cargo clippy --workspace --all-targets -- -D warnings
cargo fmt --all --check

License

MIT