rayhpeng 39a575617b refactor(gateway): restructure gateway with new dependency injection and services
Reorganize app/gateway/ with:
- common/ - lifespan management
- dependencies/ - FastAPI dependency injection (db, checkpointer, repositories, stream_bridge)
- services/runs/ - run execution services (facade_factory, input adapters, store operations)
- registrar.py - router registration
- router.py - main router setup

Simplify app.py to use the new modular structure.
Remove deprecated utils.py.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-04-22 11:27:08 +08:00

255 lines
9.8 KiB
Python

"""App-owned RunSpec builder."""
from __future__ import annotations
import re
import uuid
from langchain_core.messages import HumanMessage
from deerflow.runtime.runs.types import CheckpointRequest, RunScope, RunSpec
from deerflow.runtime.stream_bridge import JSONValue
from .request_adapter import AdaptedRunRequest
type JSONMapping = dict[str, JSONValue]
type GraphInput = dict[str, object]
type RunnableConfigDict = dict[str, object]
class UnsupportedRunFeatureError(ValueError):
"""Raised when a phase1-unsupported feature is requested."""
pass
class RunSpecBuilder:
"""
Build RunSpec from AdaptedRunRequest.
Phase 1 rules:
1. messages-tuple normalized to messages
2. enqueue not supported
3. rollback not supported
4. after_seconds not supported
5. stream_resumable accepted
6. stateless auto-generates temporary thread
"""
# Phase 1 unsupported features
UNSUPPORTED_MULTITASK_STRATEGIES = {"enqueue"}
UNSUPPORTED_ACTIONS = {"rollback"}
# Default stream modes
DEFAULT_STREAM_MODES = ["values", "messages"]
CONTEXT_CONFIGURABLE_KEYS = frozenset({
"model_name",
"mode",
"thinking_enabled",
"reasoning_effort",
"is_plan_mode",
"subagent_enabled",
"max_concurrent_subagents",
})
DEFAULT_ASSISTANT_ID = "lead_agent"
@staticmethod
def _as_json_mapping(value: JSONValue | None) -> JSONMapping | None:
return value if isinstance(value, dict) else None
@staticmethod
def _as_string_list(value: JSONValue | None) -> list[str] | None:
if not isinstance(value, list):
return None
return [item for item in value if isinstance(item, str)]
def build(self, request: AdaptedRunRequest) -> RunSpec:
"""Build RunSpec from adapted request."""
body = request.body
# Validate phase1 constraints
self._validate_constraints(body)
# Build scope
scope = self._build_scope(request)
# Normalize stream modes
stream_modes = self._normalize_stream_modes(body.get("stream_mode"))
# Build checkpoint request
checkpoint_request = self._build_checkpoint_request(body)
config = self._build_runnable_config(
thread_id=scope.thread_id,
request_config=self._as_json_mapping(body.get("config")),
metadata=self._as_json_mapping(body.get("metadata")),
assistant_id=body.get("assistant_id"),
context=self._as_json_mapping(body.get("context")),
)
return RunSpec(
intent=request.intent,
scope=scope,
assistant_id=body.get("assistant_id") if isinstance(body.get("assistant_id"), str) else None,
input=self._normalize_input(self._as_json_mapping(body.get("input"))),
command=self._as_json_mapping(body.get("command")),
runnable_config=config,
context=self._as_json_mapping(body.get("context")),
metadata=self._as_json_mapping(body.get("metadata")) or {},
stream_modes=stream_modes,
stream_subgraphs=bool(body.get("stream_subgraphs", False)),
stream_resumable=bool(body.get("stream_resumable", False)),
on_disconnect=body.get("on_disconnect", "cancel") if body.get("on_disconnect") in {"cancel", "continue"} else "cancel",
on_completion=body.get("on_completion", "keep") if body.get("on_completion") in {"delete", "keep"} else "keep",
multitask_strategy=body.get("multitask_strategy", "reject") if body.get("multitask_strategy") in {"reject", "interrupt"} else "reject",
interrupt_before="*" if body.get("interrupt_before") == "*" else self._as_string_list(body.get("interrupt_before")),
interrupt_after="*" if body.get("interrupt_after") == "*" else self._as_string_list(body.get("interrupt_after")),
checkpoint_request=checkpoint_request,
follow_up_to_run_id=body.get("follow_up_to_run_id") if isinstance(body.get("follow_up_to_run_id"), str) else None,
webhook=body.get("webhook") if isinstance(body.get("webhook"), str) else None,
feedback_keys=self._as_string_list(body.get("feedback_keys")),
)
def _validate_constraints(self, body: JSONMapping) -> None:
"""Validate phase1 constraints, raise UnsupportedRunFeatureError if violated."""
# Check multitask_strategy
strategy = body.get("multitask_strategy", "reject")
if strategy in self.UNSUPPORTED_MULTITASK_STRATEGIES:
raise UnsupportedRunFeatureError(
f"multitask_strategy '{strategy}' is not supported in phase1. "
f"Supported: reject, interrupt"
)
# Check for rollback action
command = self._as_json_mapping(body.get("command")) or {}
if command.get("action") in self.UNSUPPORTED_ACTIONS:
raise UnsupportedRunFeatureError(
f"action '{command.get('action')}' is not supported in phase1"
)
# Check for after_seconds
if body.get("after_seconds") is not None:
raise UnsupportedRunFeatureError("after_seconds is not supported in phase1")
def _build_scope(self, request: AdaptedRunRequest) -> RunScope:
"""Build RunScope from request."""
if request.is_stateless:
# Stateless: generate temporary thread
return RunScope(
kind="stateless",
thread_id=str(uuid.uuid4()),
temporary=True,
)
else:
assert request.thread_id is not None
return RunScope(
kind="stateful",
thread_id=request.thread_id,
temporary=False,
)
def _normalize_stream_modes(self, stream_mode: JSONValue | None) -> list[str]:
"""Normalize stream_mode to list, convert messages-tuple to messages."""
if stream_mode is None:
return self.DEFAULT_STREAM_MODES.copy()
if isinstance(stream_mode, str):
modes = [stream_mode]
elif isinstance(stream_mode, list):
modes = [mode for mode in stream_mode if isinstance(mode, str)]
else:
return self.DEFAULT_STREAM_MODES.copy()
return ["messages" if m == "messages-tuple" else m for m in modes]
def _build_checkpoint_request(self, body: JSONMapping) -> CheckpointRequest | None:
"""Build CheckpointRequest if checkpoint data is provided."""
checkpoint_id = body.get("checkpoint_id")
checkpoint = self._as_json_mapping(body.get("checkpoint"))
if not isinstance(checkpoint_id, str) and checkpoint is None:
return None
return CheckpointRequest(
checkpoint_id=checkpoint_id if isinstance(checkpoint_id, str) else None,
checkpoint=checkpoint,
)
def _normalize_input(self, raw_input: JSONMapping | None) -> GraphInput | None:
"""Convert HTTP-friendly message dicts into LangChain message objects."""
if raw_input is None:
return None
messages = raw_input.get("messages")
if not messages or not isinstance(messages, list):
return raw_input
converted: list[object] = []
for msg in messages:
if isinstance(msg, dict):
role = msg.get("role", msg.get("type", "user"))
content = msg.get("content", "")
if role in ("user", "human"):
converted.append(HumanMessage(content=content))
else:
converted.append(HumanMessage(content=content))
else:
converted.append(msg)
return {**raw_input, "messages": converted}
def _build_runnable_config(
self,
*,
thread_id: str,
request_config: JSONMapping | None,
metadata: JSONMapping | None,
assistant_id: str | None,
context: JSONMapping | None,
) -> RunnableConfigDict:
"""Build RunnableConfig from request payload and app-side rules."""
config: RunnableConfigDict = {"recursion_limit": 100}
if request_config:
if "context" in request_config:
config["context"] = request_config["context"]
else:
configurable = {"thread_id": thread_id}
raw_configurable = request_config.get("configurable")
if isinstance(raw_configurable, dict):
configurable.update(raw_configurable)
config["configurable"] = configurable
for key, value in request_config.items():
if key not in ("configurable", "context"):
config[key] = value
else:
config["configurable"] = {"thread_id": thread_id}
configurable = config.get("configurable")
if (
assistant_id
and assistant_id != self.DEFAULT_ASSISTANT_ID
and isinstance(configurable, dict)
and "agent_name" not in configurable
):
normalized = assistant_id.strip().lower().replace("_", "-")
if not normalized or not re.fullmatch(r"[a-z0-9-]+", normalized):
raise ValueError(
f"Invalid assistant_id {assistant_id!r}: must contain only letters, digits, and hyphens after normalization."
)
configurable["agent_name"] = normalized
if metadata:
existing_metadata = config.get("metadata")
if isinstance(existing_metadata, dict):
existing_metadata.update(metadata)
else:
config["metadata"] = dict(metadata)
if context and isinstance(configurable, dict):
for key in self.CONTEXT_CONFIGURABLE_KEYS:
if key in context:
configurable.setdefault(key, context[key])
return config