pi-think is a fork of the pi coding agent that adds one feature on top of an otherwise untouched upstream: a startup-selected think-tool reasoning mode. With it, the model's chain-of-thought is externalized into a plaintext scratchpad tool call, so the full reasoning becomes visible — live in the TUI, and persisted in the session file — even for models whose native thinking is hidden, summarized, or encrypted. Everything below the separator is upstream pi documentation.
Frontier-model APIs increasingly conceal chain-of-thought: summarized thinking, or
fully encrypted thinking blocks (opaque signature, empty text). pi-think
operationalizes the scratchpad-tool injection method inside a full coding agent:
- A benign free-text scratchpad tool (default name
think, parameterthoughts) is registered. Tool arguments are plaintext-visible to the API caller by protocol necessity — function calling cannot work otherwise. - The model is steered (system prompt + a forced first call per user prompt) to write
its step-by-step reasoning into
thoughts, and the TUI renders it like native thinking. The CoT persists in the session transcript as ordinary tool calls, so it stays readable across/modelswitches and is saved in the session file.
The mechanism is dialect-generic: request shaping keys off the model's API family
(anthropic-messages / openai-completions / openai-responses), never a specific
provider, so it works with any tool-calling model on those dialects — including
Anthropic-compatible gateways and OpenAI-compatible endpoints configured in
~/.pi/agent/models.json. No provider is hardcoded.
git clone https://github.com/ict-agent/pi-think.git
cd pi-think
npm install
npm run build
# run from the repo:
node packages/coding-agent/dist/cli.js --reasoning-mode think-tool
# or put the `pi` binary on your PATH:
(cd packages/coding-agent && npm link)
pi --reasoning-mode think-toolRequires Node.js (see upstream pi's prerequisites). All stock pi configuration
(~/.pi/agent, providers, models, themes, extensions) works unchanged — pi-think
only adds the reasoning-mode flags.
pi --reasoning-mode think-tool --model <provider>/<model> # CoT visible, live
pi --reasoning-mode think-tool --think-tool-name deep_think # custom scratchpad name
pi --reasoning-mode native # stock pi (default)
PI_WIRE_LOG=/tmp/wire.jsonl pi --reasoning-mode think-tool # + raw request/response log--reasoning-modeis fixed at startup; there is no runtime switching.nativeis unmodified pi.- In think-tool mode, Anthropic-dialect reasoning models get
thinking: {"type": "disabled"}pinned on the wire, and the scratchpad call is forced viatool_choiceon fresh user prompts (continuation turns runauto, so thinking interleaves with real tool use). The same forcing applies on the OpenAI Chat and Responses dialects. - A scratchpad call truncated by the output token limit is recorded with its salvaged partial arguments and the model is asked to continue — reasoning length is unbounded.
- If a model writes its visible reply into the scratchpad and ends the turn with an empty message (observed with haiku-class models), the harness enqueues a one-shot nudge telling it to write the actual reply.
PI_WIRE_LOGappends every raw LLM request/response body (JSONL; SSE responses reassembled) — the on-the-wire ground truth for exactly what thinking/tool payloads were sent and received.
packages/agent:AgentTool.salvageTruncatedArgs+ truncated-message salvage path in the agent loop.packages/ai: anthropic compat flagsupportsPromptCaching(providers whose non-Claude upstreams rejectcache_control).packages/coding-agent:core/tools/think.ts(scratchpad tool + TUI renderer),core/think-tool-mode.ts(dialect-generic payload shaping),core/wire-log.ts(PI_WIRE_LOG), empty-answer nudge inagent-session.ts,--reasoning-mode/--think-tool-nameCLI flags, sdk wiring.
New issues and PRs from new contributors are auto-closed by default. Maintainers review auto-closed issues daily. See CONTRIBUTING.md.
This is the home of the Pi agent harness project including our self extensible coding agent.
- @earendil-works/pi-coding-agent: Interactive coding agent CLI
- @earendil-works/pi-agent-core: Agent runtime with tool calling and state management
- @earendil-works/pi-ai: Unified multi-provider LLM API (OpenAI, Anthropic, Google, …)
To learn more about Pi:
- Visit pi.dev, the project website with demos
- Read the documentation, but you can also ask the agent to explain itself
| Package | Description |
|---|---|
| @earendil-works/pi-telemetry | Vendor-neutral telemetry contracts, reference adapter, conformance tests, and typed schemas |
| @earendil-works/pi-ai | Unified multi-provider LLM API (OpenAI, Anthropic, Google, etc.) |
| @earendil-works/pi-agent-core | Agent runtime with tool calling and state management |
| @earendil-works/pi-coding-agent | Interactive coding agent CLI |
| @earendil-works/pi-tui | Terminal UI library with differential rendering |
For Slack/chat automation and workflows see earendil-works/pi-chat.
Pi does not include a built-in permission system for restricting filesystem, process, network, or credential access. By default, it runs with the permissions of the user and process that launched it.
If you need stronger boundaries, containerize or sandbox Pi. See packages/coding-agent/docs/containerization.md for three patterns:
- Gondolin extension: keep
piand provider auth on the host while routing built-in tools and!commands into a local Linux micro-VM. - Plain Docker: run the whole
piprocess in a local container for simple isolation. - OpenShell: run the whole
piprocess in a policy-controlled sandbox.
See CONTRIBUTING.md for contribution guidelines and AGENTS.md for project-specific rules (for both humans and agents). Longer term plans for Pi can also be found in RFCs.
npm install --ignore-scripts # Install all dependencies without running lifecycle scripts
npm run build # Refresh model data, then build all packages
npm run build:offline # Rebuild using existing model data without network access
npm run check # Lint, format, and type check
./test.sh # Run tests (skips LLM-dependent tests without API keys)
./pi-test.sh # Run pi from sources (can be run from any directory)GitHub releases include a versioned source archive covered by the release's SHA256SUMS file. Extract it and run the same build script used for the official standalone binaries:
VERSION="<release-version>"
tar -xzf "pi-${VERSION}-source.tar.gz"
cd "pi-${VERSION}"
./scripts/build-binaries.sh --offline-model-data --platform linux-x64 --out "$PWD/out"The source archive includes the generated provider model data used for the release. --offline-model-data builds with that snapshot instead of refreshing it from live provider catalogs. The script still installs dependencies, builds the monorepo, compiles the Bun executable, and stages its runtime assets. Package maintainers who provide dependencies separately can pass --skip-install --skip-deps.
We treat npm dependency changes as reviewed code changes.
- Direct external dependencies are pinned to exact versions. Internal workspace packages remain version-ranged.
.npmrcsetssave-exact=trueandmin-release-age=2to avoid same-day dependency releases during npm resolution.package-lock.jsonis the dependency ground truth. Pre-commit blocks accidental lockfile commits unlessPI_ALLOW_LOCKFILE_CHANGE=1is set.npm run checkverifies pinned direct deps, native TypeScript import compatibility, and the generated coding-agent shrinkwrap.- The published CLI package includes
packages/coding-agent/npm-shrinkwrap.json, generated from the root lockfile, to pin transitive deps for npm users. - Release smoke tests use
npm run release:localto build, pack, and create isolated npm and Bun installs outside the repo before tagging a release. - Local release installs, documented npm installs, and
pi update --selfuse--ignore-scriptswhere supported. - CI installs with
npm ci --ignore-scripts, and a scheduled GitHub workflow runsnpm audit --omit=devplusnpm audit signatures --omit=dev. - Shrinkwrap generation has an explicit allowlist for dependency lifecycle scripts; new lifecycle-script deps fail checks until reviewed.
If you use Pi or other coding agents for open source work, please share your sessions.
Public OSS session data helps improve coding agents with real-world tasks, tool use, failures, and fixes instead of toy benchmarks.
For the full explanation, see this post on X.
To publish sessions, use badlogic/pi-share-hf. Read its README.md for setup instructions. All you need is a Hugging Face account, the Hugging Face CLI, and pi-share-hf.
You can also watch this video, where I show how I publish my pi-mono sessions.
I regularly publish my own pi-mono work sessions here:
MIT