Agents
An agent is an AI entity with a role, a model, and tools. It persists memory across sessions and executes tasks autonomously.- name — unique identifier
- role — what the agent does
- model — LLM provider and model (e.g.
anthropic/claude-sonnet-4-5) - tools — what the agent can do (read, write, bash, http_fetch, etc.)
- memory — persistent context across sessions (shared + per-agent)
- identity — persona, responsibilities, communication style
- skills — installable knowledge packs that teach new domains
Teams
Agents are organized into teams. Teams are just grouping — they don’t restrict what agents can do. A project can have multiple teams with different specializations.Tasks
A task is a unit of work assigned to an agent. The agent executes it in an isolated sandbox with access to its configured tools. Tasks have a lifecycle:pending → assigned → in_progress → review → done or failed.
When a task fails, Polpo can automatically retry, fix, or escalate based on your retry policy.
Missions
A mission is a multi-step workflow composed of tasks. Missions define:- Tasks with dependencies (task B waits for task A)
- Checkpoints — pause for human review before continuing
- Quality gates — automated pass/fail based on assessment scores
- Delays — timed waits between task groups
- Volatile agents — temporary specialists created for the mission
Assessment
Every task result is automatically assessed:- Agent completes the task
- Assessment runs expectations (tests, file checks, LLM review)
- G-Eval scoring across weighted dimensions
- Pass → done. Fail → fix prompt → retry
Memory
Two levels:- Shared memory — accessible by all agents in the project
- Agent memory — private to a single agent, persists across sessions
Tools
Agents interact with the real world through tools: read/write files, run commands, fetch URLs, send emails, browse the web, analyze images, and more. Tools run inside the agent’s sandbox with access to the project volume.Volumes
A volume is a FUSE-based persistent filesystem for a project. Every project gets one automatically. All agents share the same volume — when one agent writes a file, the next agent sees it. Memory, skills, and shared context live on the volume.Apps
An app is the main unit of infrastructure for coding agents. It bundles a codebase, servers, and ports into a managed environment. One call gives you a live preview, IDE, and terminal. Apps can hibernate (stop compute, keep files) and wake instantly.Codebases
A codebase is the code layer inside an app — project source, git history, dependencies, and builds. Unlike volumes (FUSE-based, shared), codebases use local block storage suitable for running dev servers and builds.Servers
A server is a long-running process inside an app — dev servers, terminals, IDEs. Servers stay alive between agent sessions and restart automatically after hibernation.Templates
A template is a pre-built snapshot that apps are created from. It includes a runtime, project code, installed dependencies, and default server definitions. Apps boot from templates in seconds.Chat Completions
Every agent is accessible via an OpenAI-compatible API. Send messages, get streaming responses. Pass anappId to run the agent inside a persistent app. Works with any OpenAI client library.