Phase 2 architecture rule: VM management code lives in
litellm/managed_agents/vms/, not litellm/proxy/. The proxy is control
plane only.
Tracks LIT-2879.
Phase 2 architecture rule: VM management code lives in
litellm/managed_agents/vms/, not litellm/proxy/. The proxy is control
plane only.
Tracks LIT-2879.
Phase 2 architecture rule: VM management code lives in
litellm/managed_agents/vms/, not litellm/proxy/. The proxy is control
plane only.
Tracks LIT-2879.
Phase 2 architecture rule: VM management code lives in
litellm/managed_agents/vms/, not litellm/proxy/. The proxy is control
plane only.
Tracks LIT-2879.
Phase 2 architecture rule: VM management code lives in
litellm/managed_agents/vms/, not litellm/proxy/. The proxy is control
plane only.
Tracks LIT-2879.
Phase 2 architecture rule: VM management code lives in
litellm/managed_agents/vms/, not litellm/proxy/. The proxy is control
plane only.
Tracks LIT-2879.
Phase 2 architecture rule: VM management code lives in
litellm/managed_agents/vms/, not litellm/proxy/. The proxy is control
plane only.
Tracks LIT-2879.
The package __init__ now re-exports AgentRuntime/AgentConfig/SessionState
plus both runtime implementations (ClaudeSDKAgentRuntime and the new
LiteLLMAgentRuntime) so callers can do
'from litellm.managed_agents.agent_runtime import LiteLLMAgentRuntime'
without poking into submodules.
Required for the package-level __init__.py re-exports to resolve.
Real Prisma translates {agent: {connect: {id: X}}} into the underlying
agent_id FK column at write time. The in-memory FakePrismaClient we
share with the proxy tests stores the dict verbatim, so the agent_id
column was None on every row our managed_agents code wrote. Tests
asserting session.agent_id == 'agent_1' (and the same for session_id /
run_id) all failed at the same boundary.
Fix: wrap each table's create() in a small adapter that unwraps the
relation-syntax keys into bare FK columns before delegating. Local to
this test conftest so the change does not leak into the proxy tests
that re-use the same fake.
The package __init__ now re-exports the public surface so SDK callers
can do a single 'from litellm.managed_agents import Agent, Session, ...'
instead of digging into submodules.
Also pins what's public — anything not in __all__ is implementation
detail and may move.
Session is the unit of work in the managed-agents API. send(prompt)
mirrors what the HTTP create_run + event_stream pair does on the proxy:
1. INSERT LiteLLM_AgentRun (status=queued, prompt={text}).
2. Flip session status ready -> busy and run status queued -> running.
3. async for event in self.runtime.run(...) — persist each event to
LiteLLM_AgentRunEvent and yield it back to the consumer.
4. On exit (clean or error), set the run terminal status and restore
session to ready in a finally block so a single failed send never
locks the session forever.
Also adds get_run/list_runs/conversation read helpers — same wire shape
the corresponding HTTP endpoints serve.
Agent is the SDK-side handle for one LiteLLM_Agent row. It wraps:
* the static agent definition (name, model, system_prompt, tools_config)
* the AgentRuntime + Sandbox that spawned sessions will use
* session lifecycle helpers (create_session, get_session, list_sessions,
delete)
create_session inserts the LiteLLM_AgentSession row directly in 'ready'
status, mints a daemon JWT (same shape the proxy mints in /v2/sessions),
and returns a Session ready to send() prompts.
The HTTP /v2/sessions path uses 'provisioning' because it kicks off a
remote VM provider call; the managed_agents Python layer owns the sandbox
in-process and is ready immediately.
Run is the read-only Python accessor for one LiteLLM_AgentRun row. It is
the SDK-side counterpart to GET /v2/sessions/{sid}/runs/{rid} and to the
SSE event stream.
Two entry points:
* Run.from_db_row(row, db) — build from a Prisma row.
* await run.stream(starting_seq=N) — async iterator over persisted
events ordered by seq, paginated through the DB to bound memory on
chatty runs.
Stream is snapshot-based; live tailing remains the SSE endpoint's job.
