dongarandClaude Opus 5.5
2b26f0cff5
remember(name, description, fact) and forget(name, why): control tools for the driver (before the go-ahead too) and conversations, writing only the agent's own vault folder, one note per fact with its provenance. No one agrees first; each change is a line in the thread. The harness keeps the index and puts it into the transcript once per item, with a hash. At an item's close, completed or abandoned, a bounded memory pass (the driver's model, its own transcript and view) records what was decided and learned; it never holds the close up (tuning.memory.max_turns). With the operator: corrections may be paraphrased (L6 changed), the model forgets on its own, and nothing limits what may prompt a note. The walk remembers and forgets, and checks nothing lands outside the agent's folder. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01J5Utyfzw7gF7UhjRDEtjTk
373 lines
13 KiB
Python
373 lines
13 KiB
Python
"""Composition root: the one place that knows how the whole agent fits
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together. Every component is unit-tested in isolation; this is where they meet,
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which is what keeps a built piece from being reachable only from its own tests
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(the delegation harness and the comment poller once were)."""
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import threading
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from collections.abc import Callable
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from dataclasses import dataclass
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from nisse_dev.cancel import Cancel
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from nisse_dev.catalog import ModelCatalog, select_client
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from nisse_dev.config import AgentConfig, ConfigError
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from nisse_dev.config import Project as ProjectEntry
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from nisse_dev.context import BudgetedClient
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from nisse_dev.delegation import Caps
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from nisse_dev.execution import SSHHost
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from nisse_dev.git import GitRepo, HTTPSToken, PushCredential, SSHKey
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from nisse_dev.gitea import GiteaClient
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from nisse_dev.llm import AnthropicPassthroughClient, LiteLLMClient
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from nisse_dev.loop.agent import LoopAgent, Project
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from nisse_dev.loop.classifier import ActionClassifier
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from nisse_dev.loop.driver import Driver
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from nisse_dev.loop.help import Helpers
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from nisse_dev.loop.milestones import Milestones
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from nisse_dev.loop.reader import GoAheadReader
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from nisse_dev.matrix import MatrixTransport
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from nisse_dev.memory import Memory
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from nisse_dev.oplog import OpLog
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from nisse_dev.state import StateStore
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from nisse_dev.tools import Workspace
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from nisse_dev.vault import Vault
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from nisse_dev.worker import SerialWorker
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# How long shutdown waits for running work before leaving the store to the
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# durability layer (L8). A milestone can run far longer than a service
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# manager allows for a stop, and a hard exit mid-work is already safe.
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SHUTDOWN_WAIT_S = 10.0
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TOOL_DRIVING_ROLES = ("driver", "helper")
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MEMORY_FOLDER = "memory/nisse-dev" # L10: the agent's own, in its vault
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def discover_models(config: AgentConfig, oplog: OpLog) -> ModelCatalog:
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"""Resolve every configured role against LiteLLM before anything runs.
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Refusing to boot is the whole point: a role pointed at a model this key
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cannot see is a misconfiguration, and the cheapest place to learn that is
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here rather than ten minutes into a milestone. An unreachable proxy is
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reported separately -- it is an outage, not a mistake, and telling them
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apart is what lets an operator know whether to edit config or wait.
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"""
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catalog = ModelCatalog.discover(config.llm_base_url, config.llm_token)
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catalog.validate(config.roles.pinned())
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# Every role's context window must be known before a request is built
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# against it (L6): a guess that is too large reaches a server that may
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# silently cut the prompt.
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catalog.require_limits(config.roles.pinned())
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for role in TOOL_DRIVING_ROLES:
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facts = catalog.facts(config.roles.resolve(role))
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if facts.supports_tools is False:
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# A warning, not a refusal: models LiteLLM declares tool-less are
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# observed driving tool loops anyway, and L9 expects weak local
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# models to be accommodated rather than excluded.
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oplog.emit(
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"model_tools_unsupported",
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cause="startup",
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role=role,
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model=facts.alias,
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backing=facts.backing,
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)
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return catalog
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@dataclass
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class RunningLoop:
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config: AgentConfig
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account: str
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loop: LoopAgent
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store: StateStore
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transport: MatrixTransport
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gitea: GiteaClient
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worker: SerialWorker
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_stopped: threading.Event
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def start(self) -> None:
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self.loop.start()
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self.transport.post(
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f"nisse-dev up as {self.account} on "
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f"{', '.join(p.repo for p in self.config.projects)}; "
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f"{self.loop_status()}"
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)
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def loop_status(self) -> str:
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return self.worker.call(self.loop.status)
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def stop(self) -> None:
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self.loop.stop()
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self.transport.close()
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self.gitea.close()
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try:
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self.worker.call(self.store.close, timeout=SHUTDOWN_WAIT_S)
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except TimeoutError:
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pass # still working; L8 covers exiting mid-work
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self.worker.stop(timeout=SHUTDOWN_WAIT_S)
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self._stopped.set()
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def wait(self) -> None:
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self._stopped.wait()
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def make_llm_clients(
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config: AgentConfig, catalog: ModelCatalog
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) -> tuple[BudgetedClient, BudgetedClient]:
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"""The two LLM routes, as every model call in the agent uses them.
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Shared with the benchmark, so that what it measures is exactly what the
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agent would do: the same context budget, the same declared limits, and
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tool_choice asked only of models declared to enforce it.
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"""
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tuning = config.tuning
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def limits_for(model: str) -> tuple[int, int | None]:
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facts = catalog.facts(model)
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assert facts.max_input_tokens is not None # require_limits checked
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return facts.max_input_tokens, facts.max_output_tokens
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def budgeted(client: object) -> BudgetedClient:
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# Every request, on either route, is fitted to its model's window.
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return BudgetedClient(
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client,
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limits_for,
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max_output_tokens=config.max_output_tokens,
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keep_recent_turns=tuning.context.keep_recent_turns,
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safety_margin=tuning.context.safety_margin,
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enforces_tool_choice=lambda m: (
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catalog.facts(m).supports_tool_choice is True
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),
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)
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normalized = budgeted(
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LiteLLMClient(
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config.llm_base_url,
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config.llm_token,
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max_tokens=config.max_output_tokens,
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timeout_s=config.request_timeout_s,
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)
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)
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# Delegations prefer the vendor-native route; fidelity is cheap
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# elsewhere (L9). Which route a given model gets is decided by
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# select_client, not by where the caller happens to sit.
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passthrough = budgeted(
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AnthropicPassthroughClient(
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config.llm_base_url,
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config.llm_token,
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max_tokens=config.max_output_tokens,
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timeout_s=config.request_timeout_s,
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)
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)
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return normalized, passthrough
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def build_host(config: AgentConfig, project: ProjectEntry) -> SSHHost:
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"""A project's build VM (L13). Its known-hosts file and connection socket
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live beside the state store."""
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host = project.build_host
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return SSHHost(
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host.address,
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key=host.key,
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user=host.user,
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port=host.port,
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state_dir=config.state_db.parent / "ssh",
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)
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def push_credential(project: ProjectEntry) -> PushCredential | None:
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"""What a project's pushes go by: a push-only account's token over
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HTTPS, or a deploy key over SSH (D4)."""
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if project.push_user and project.push_token:
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return HTTPSToken(project.push_user, project.push_token)
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if project.push_key is None:
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return None
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try:
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return SSHKey(project.push_key.read_text())
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except OSError as exc:
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raise RuntimeError(
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f"cannot read the push key {project.push_key}: {exc}"
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) from exc
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def remote_url(gitea: GiteaClient, repo: str, credential: PushCredential | None) -> str:
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"""The credential-free URL the workspace clones from and pushes to."""
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if isinstance(credential, SSHKey):
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return gitea.ssh_url(repo)
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return gitea.clone_url(repo)
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def prepare_workspace(
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host: SSHHost,
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config: AgentConfig,
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account: str,
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remote: str,
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credential: PushCredential | None,
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project: ProjectEntry,
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) -> GitRepo:
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"""Ensure the workspace on the build VM is a clone of the project repo.
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The clone uses the repository's SSH URL, so no credential is ever stored
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in it (#89); the push credential is handed to the clone and nothing else.
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"""
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repo = GitRepo(host, project.workspace)
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if not repo.exists():
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repo.clone(remote, credential=credential)
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repo.configure_identity(account, f"{account}@users.noreply.local")
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repo.install_excludes() # build artifacts are never the work (#80)
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return repo
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def project_runtime(
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config: AgentConfig,
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entry: ProjectEntry,
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store: StateStore,
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gitea: GiteaClient,
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account: str,
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) -> Project:
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"""One project's part of the loop: its clone on its build VM, workspace
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(with the secrets its commands may see, redacted on return), push
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credential and milestones."""
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host = build_host(config, entry)
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credential = push_credential(entry)
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remote = remote_url(gitea, entry.repo, credential)
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git = prepare_workspace(host, config, account, remote, credential, entry)
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return Project(
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name=entry.name,
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repo=entry.repo,
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labels=entry.labels,
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base=entry.base_branch,
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merge=entry.merge,
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workspace=Workspace(
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host,
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entry.workspace,
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timeout_s=config.tuning.tools.command_timeout_s,
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max_output_chars=config.tuning.tools.max_output_chars,
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secrets=entry.command_secrets(),
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),
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milestones=Milestones(
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store,
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git,
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gitea,
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repo=entry.repo,
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remote=remote,
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credential=credential,
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base=entry.base_branch,
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),
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)
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def build_loop_agent(
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config: AgentConfig, load: Callable[[], AgentConfig] | None = None
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) -> RunningLoop:
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"""``load`` reads the configuration again, for a new project's entry
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(D8); by default from the file this one came from."""
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oplog = OpLog("nisse-dev")
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worker = SerialWorker(
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on_error=lambda exc: oplog.emit(
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"worker.job_failed", cause="unhandled exception", error=repr(exc)
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)
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)
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worker.start()
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store = worker.call(lambda: StateStore(config.state_db, oplog=oplog))
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catalog = discover_models(config, oplog)
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gitea = GiteaClient(config.gitea_url, config.gitea_token)
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account = gitea.whoami()
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# D8: each project its own build VM, clone, push credential and milestones.
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projects = [
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project_runtime(config, entry, store, gitea, account)
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for entry in config.projects
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]
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normalized, passthrough = make_llm_clients(config, catalog)
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cancel = Cancel()
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# The configured driver; each work item runs on the one it pinned (L9).
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driver = Driver(
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normalized,
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config.roles.resolve("driver"),
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max_turns=config.tuning.driver.max_turns,
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cancel=cancel,
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failure_limit=config.tuning.driver.failure_limit,
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)
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tuning = config.tuning
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helpers = Helpers(
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client=normalized,
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roles=config.roles,
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client_for=lambda model: select_client(model, normalized, passthrough, catalog),
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backing=lambda model: catalog.facts(model).backing,
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caps=Caps(
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turns=tuning.delegation.max_turns,
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tokens=tuning.delegation.max_tokens,
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wall_clock_s=tuning.delegation.wall_clock_s,
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),
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expert_budget=tuning.expert.consult_budget,
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profiles=config.profiles,
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)
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transport = MatrixTransport(config.matrix)
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vault = (
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Vault(config.vault.root, config.vault.folders, ignore=config.vault.ignore)
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if config.vault
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else None
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)
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loop = LoopAgent(
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store,
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transport,
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gitea,
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projects=projects,
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account=account,
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operators=config.operators,
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gitea_operators=config.gitea_operators,
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driver=driver,
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worker=worker,
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cancel=cancel,
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oplog=oplog,
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roles=config.roles.pinned(),
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# The classifier role reads plain-language go-aheads (L5, L9).
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reader=GoAheadReader(normalized, config.roles.resolve("classifier")),
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# L4: what the fast path doesn't know, judged on the classifier role.
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classifier=ActionClassifier(
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normalized,
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config.roles.resolve("classifier"),
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backing=lambda model: catalog.facts(model).backing,
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),
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helpers=helpers,
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reload=lambda known: [
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project_runtime(config, entry, store, gitea, account)
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for entry in (load or _from_file(config))().projects
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if entry.name not in known
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],
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# D3, M4.1: the build VM checked, and the toolchain set up, before
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# the driver plans.
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preflight=True,
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preflight_turns=config.tuning.preflight.max_turns,
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preflight_timeout_s=config.tuning.preflight.command_timeout_s,
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bug_grace_s=config.tuning.loop.bug_grace_s,
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general_idle_s=config.tuning.loop.general_idle_s,
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vm_retry_s=config.tuning.build_vm.retry_s,
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vm_settle_s=config.tuning.build_vm.settle_s,
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# L10: the knowledge vault, when configured; L6.4: the agent's
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# memory, when its own folder in it is read-write.
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vault=vault,
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memory=(
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Memory(vault, MEMORY_FOLDER)
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if vault and vault.folders().get(MEMORY_FOLDER) == "rw"
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else None
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),
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memory_turns=config.tuning.memory.max_turns,
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)
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return RunningLoop(
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config=config,
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account=account,
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loop=loop,
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store=store,
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transport=transport,
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gitea=gitea,
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worker=worker,
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_stopped=threading.Event(),
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)
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def _from_file(config: AgentConfig) -> Callable[[], AgentConfig]:
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def load() -> AgentConfig:
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if config.config_file is None:
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raise ConfigError("this agent wasn't started from a config file")
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return AgentConfig.from_file(config.config_file)
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return load
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