mirror of
https://github.com/multica-ai/multica.git
synced 2026-07-05 13:29:44 +02:00
8c518c350a
* feat(agent): add Pi agent runtime support
Add Pi as a new agent runtime provider, following the established adapter
pattern. Pi CLI outputs JSONL events which are parsed for messages, tool
calls, and usage tracking.
Backend:
- New piBackend implementing the Backend interface (pi.go)
- Pi CLI discovery via MULTICA_PI_PATH env var or PATH lookup
- JSONL event stream parsing (agent_start, message_update, thinking_update,
tool_execution_start/end, agent_end)
- Usage scanner for ~/.pi/sessions/*.jsonl files
- Runtime config injection via AGENTS.md
- Skill injection to .pi/agent/skills/
Frontend:
- Pi provider logo (teal π icon)
- Pi label in transcript dialog
Docs:
- Updated all provider lists in README, CLI_INSTALL, and docs
* fix(agent): filter Pi usage scanner to agent_end events only
Address review feedback: restrict usage parsing to agent_end events
which contain cumulative totals, preventing potential inaccuracy if
Pi adds usage fields to other event types in the future.
* fix(agent): align Pi runtime with real CLI flags, event schema, and custom_args
- Flags: Pi's CLI uses `--mode json` (not `--output-format jsonl`), has no
`--yolo` (explicit `--tools` allowlist instead), takes the prompt as a
positional argument (not `-p <prompt>`), splits model as
`--provider <name> --model <id>`, and treats `--session` as a file path
that must exist before spawn.
- Event parsing: rewrite the stream event struct to match Pi's actual
JSON event schema (`message_update.assistantMessageEvent.delta`,
`turn_end.message.usage.{input,output,cacheRead,cacheWrite}`, etc.).
- Sessions: generate/persist session files under ~/.multica/pi-sessions/
and use the file path as the opaque SessionID returned to the daemon.
- Usage scanner: read assistant `message` events from the same session
files (Pi's session-file schema, distinct from the stdout stream).
- Custom args: consume `ExecOptions.CustomArgs` via `filterCustomArgs`
with a Pi-specific blocked set (`-p`, `--print`, `--mode`, `--session`)
so Pi matches the pattern shared by every other agent backend.
65 lines
2.3 KiB
Plaintext
65 lines
2.3 KiB
Plaintext
---
|
|
title: Cloud Quickstart
|
|
description: Get started with Multica Cloud — no setup required.
|
|
---
|
|
|
|
The fastest way to get started with Multica — no setup required.
|
|
|
|
## 1. Sign up
|
|
|
|
Go to [multica.ai](https://multica.ai) and create an account.
|
|
|
|
## 2. Install the CLI and start the daemon
|
|
|
|
Give this instruction to your AI agent (Claude Code, Codex, Gemini CLI, OpenClaw, OpenCode, etc.):
|
|
|
|
```
|
|
Fetch https://github.com/multica-ai/multica/blob/main/CLI_INSTALL.md and follow the instructions to install Multica CLI, log in, and start the daemon on this machine.
|
|
```
|
|
|
|
Or install manually:
|
|
|
|
### macOS / Linux (Homebrew - recommended)
|
|
|
|
```bash
|
|
brew install multica-ai/tap/multica
|
|
```
|
|
|
|
### macOS / Linux (install script)
|
|
|
|
```bash
|
|
# Install the CLI
|
|
curl -fsSL https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.sh | bash
|
|
```
|
|
|
|
### Windows (PowerShell)
|
|
|
|
```powershell
|
|
irm https://raw.githubusercontent.com/multica-ai/multica/main/scripts/install.ps1 | iex
|
|
```
|
|
|
|
Then configure, authenticate, and start the daemon:
|
|
|
|
```bash
|
|
# Configure, authenticate, and start the daemon
|
|
multica setup
|
|
```
|
|
|
|
The daemon auto-detects available agent CLIs (`claude`, `codex`, `gemini`, `openclaw`, `opencode`, `hermes`, `pi`) on your PATH. When an agent is assigned a task, the daemon creates an isolated environment, runs the agent, and reports results back.
|
|
|
|
## 3. Verify your runtime
|
|
|
|
Open your workspace in the Multica web app. Navigate to **Settings → Runtimes** — you should see your machine listed as an active **Runtime**.
|
|
|
|
> **What is a Runtime?** A Runtime is a compute environment that can execute agent tasks. It can be your local machine (via the daemon) or a cloud instance. Each runtime reports which agent CLIs are available, so Multica knows where to route work.
|
|
|
|
## 4. Create an agent
|
|
|
|
Go to **Settings → Agents** and click **New Agent**. Pick the runtime you just connected and choose a provider (Claude Code, Codex, Gemini CLI, OpenClaw, OpenCode, or Hermes). Give your agent a name — this is how it will appear on the board, in comments, and in assignments.
|
|
|
|
## 5. Assign your first task
|
|
|
|
Create an issue from the board (or via `multica issue create`), then assign it to your new agent. The agent will automatically pick up the task, execute it on your runtime, and report progress — just like a human teammate.
|
|
|
|
That's it! Your agent is now part of the team.
|