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nanobot/nanobot/providers/conversation_state.py
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263 lines
8.9 KiB
Python

"""Provider-owned conversation-state lifecycle coordination."""
from __future__ import annotations
from copy import deepcopy
from typing import Any, cast
from nanobot.providers.base import (
LLMProvider,
LLMResponse,
ProviderCallContext,
ProviderConversationState,
)
_PROVIDER_STATE_OUTPUT_META = "provider_state_output"
_PROVIDER_STATE_BOUNDARY_META = "provider_state_boundary"
def allows_conversation_message_merge(message: dict[str, Any]) -> bool:
"""Return whether new same-role input may merge into *message*."""
internal_meta = cast(object, message.get("_meta"))
return not (
isinstance(internal_meta, dict)
and cast(dict[str, Any], internal_meta).get(
_PROVIDER_STATE_BOUNDARY_META
) is True
)
class ProviderConversationStateController:
"""Keep provider conversation-state semantics outside the agent runner.
The runner owns the tool loop and reports lifecycle events here. This
controller owns capability checks, transcript deltas, response projections,
retry transitions, and durable snapshots for provider-private state.
"""
def __init__(
self,
*,
provider: LLMProvider,
model: str | None,
messages: list[dict[str, Any]],
state: ProviderConversationState | None = None,
) -> None:
self._provider = provider
self._model = model
self._state = (
state
if state is not None
and provider.can_resume_conversation_state(state, model)
else None
)
self._boundary = len(messages)
self._request_messages: list[dict[str, Any]] = []
def independent_request_context(
self,
*,
context_window_tokens: int | None,
) -> ProviderCallContext | None:
"""Return typed provider context for a request that does not resume state."""
if context_window_tokens is None:
return None
return ProviderCallContext(context_window_tokens=context_window_tokens)
def prepare_request(
self,
messages: list[dict[str, Any]],
*,
context_window_tokens: int | None,
model_messages: list[dict[str, Any]] | None = None,
supplemental_messages: list[dict[str, Any]] | None = None,
) -> ProviderCallContext | None:
"""Build typed context for the next request and remember its durable delta."""
independent_context = self.independent_request_context(
context_window_tokens=context_window_tokens,
)
if self._state is None:
self._request_messages = []
return independent_context
if not self._provider.can_resume_conversation_state(
self._state,
self._model,
):
self._state = None
self._request_messages = []
return independent_context
durable_messages = self._messages_after_boundary(messages)
governed_messages = (
self._model_messages_after_boundary(model_messages)
if model_messages is not None and durable_messages
else None
)
request_messages = (
governed_messages
if governed_messages is not None
else durable_messages
)
supplemental = deepcopy(supplemental_messages or [])
self._request_messages = deepcopy(request_messages)
request_state = self._state.with_pending_messages([
*self._state.pending_messages,
*request_messages,
*supplemental,
])
return ProviderCallContext(
conversation_state=request_state,
context_window_tokens=(
independent_context.context_window_tokens
if independent_context is not None
else None
),
)
def observe_response(
self,
response: LLMResponse,
messages: list[dict[str, Any]],
*,
adopt_candidate_state: bool = True,
) -> None:
"""Advance, preserve, or discard state after one provider response."""
candidate = response.provider_state if adopt_candidate_state else None
candidate_is_replayable = response.finish_reason in {
"stop",
"tool_calls",
"function_call",
}
if (
candidate is not None
and candidate_is_replayable
and self._provider.can_resume_conversation_state(
candidate,
self._model,
)
):
self._state = candidate
self._boundary = len(messages)
self._seal_boundary(messages)
elif response.finish_reason == "error" and (
response.preserve_provider_state_on_error is True
or (
response.preserve_provider_state_on_error is None
and LLMProvider.is_transient_response(response)
)
):
if self._state is not None and self._request_messages:
self._state = self._state.with_pending_messages([
*self._state.pending_messages,
*self._request_messages,
])
self._boundary = len(messages)
else:
self._state = None
self._boundary = len(messages)
self._request_messages = []
@staticmethod
def project_response_message(
message: dict[str, Any],
response: LLMResponse,
) -> dict[str, Any]:
"""Mark a Chat projection already represented by provider output."""
if response.provider_state is None:
return message
internal_meta = dict(message.get("_meta") or {})
internal_meta[_PROVIDER_STATE_OUTPUT_META] = True
message["_meta"] = internal_meta
return message
def checkpoint(
self,
messages: list[dict[str, Any]],
*,
model_messages: list[dict[str, Any]] | None = None,
) -> ProviderConversationState | None:
"""Return a durable state snapshot without changing live state."""
if self._state is None:
return None
durable_messages = self._messages_after_boundary(messages)
governed_messages = (
self._model_messages_after_boundary(model_messages)
if model_messages is not None and durable_messages
else None
)
pending_messages = (
governed_messages
if governed_messages is not None
else durable_messages
)
return self._state.with_pending_messages([
*self._state.pending_messages,
*pending_messages,
])
def finish(
self,
messages: list[dict[str, Any]],
) -> ProviderConversationState | None:
"""Return the final durable state after all runner messages are known."""
self._state = self.checkpoint(messages)
return self._state
def _messages_after_boundary(
self,
messages: list[dict[str, Any]],
) -> list[dict[str, Any]]:
pending: list[dict[str, Any]] = []
for message in messages[self._boundary:]:
internal_meta = cast(object, message.get("_meta"))
if (
isinstance(internal_meta, dict)
and cast(dict[str, Any], internal_meta).get(
_PROVIDER_STATE_OUTPUT_META
) is True
):
continue
pending.append(deepcopy(message))
return pending
@staticmethod
def _model_messages_after_boundary(
messages: list[dict[str, Any]],
) -> list[dict[str, Any]] | None:
"""Return the governed delta after the latest provider-owned boundary."""
boundary = None
for idx in range(len(messages) - 1, -1, -1):
internal_meta = cast(object, messages[idx].get("_meta"))
if (
isinstance(internal_meta, dict)
and cast(dict[str, Any], internal_meta).get(
_PROVIDER_STATE_BOUNDARY_META
) is True
):
boundary = idx
break
if boundary is None:
return None
pending: list[dict[str, Any]] = []
for message in messages[boundary + 1:]:
internal_meta = cast(object, message.get("_meta"))
if (
isinstance(internal_meta, dict)
and cast(dict[str, Any], internal_meta).get(
_PROVIDER_STATE_OUTPUT_META
) is True
):
continue
pending.append(deepcopy(message))
return pending
@staticmethod
def _seal_boundary(messages: list[dict[str, Any]]) -> None:
"""Prevent later same-role injection merging across a state boundary."""
if not messages:
return
internal_meta = dict(messages[-1].get("_meta") or {})
internal_meta[_PROVIDER_STATE_BOUNDARY_META] = True
messages[-1]["_meta"] = internal_meta