File size: 1,799 Bytes
76962bf b1198f0 76962bf b1198f0 76962bf b1198f0 cb505ff b1198f0 76962bf b1198f0 76962bf cb505ff | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 | from typing import TypedDict, Annotated, List, Union
from langchain_core.messages import BaseMessage
import operator
class AgentState(TypedDict):
# Standard message history
messages: Annotated[List[BaseMessage], operator.add]
# Metadata for routing
user_role: str # patient, clinician, researcher
intent_type: str # diagnosis, treatment, monitoring, general
trace_id: str
# CDM / FHIR Data
session_id: str
patient_id: str
fhir_data: List[dict]
trend_analysis: str
trend_data: dict
cdm_trend_analysis: dict
current_medications: List[dict]
# Validation status
is_valid: bool
is_safe: bool
# Intermediate outputs
patient_response: str
clinician_outputs: List[str]
research_output: str
# Recovery loop counter
attempts: int
# Sources for information
sources: Annotated[List[str], operator.add]
# Evidence citations for clinical recommendations (Bug 12.3)
evidence_citations: Annotated[List[dict], operator.add]
# Execution logs
logs: Annotated[List[str], operator.add]
# Metrics (tokens, time)
metrics: Annotated[List[dict], operator.add]
# Phase 0 skill runtime metadata
active_skill_id: str
active_skill_version: str
manager_route: dict
skill_plan: List[dict]
skill_trace: List[dict]
request_id: str
authorization_subject: str
data_access_scope: List[str]
consent_status: str
response_artifacts: List[dict]
retrieved_sources: Annotated[List[dict], operator.add]
memory_context: List[dict]
memory_proposals: Annotated[List[dict], operator.add]
memory_commit_results: Annotated[List[dict], operator.add]
gates: dict
termination_reason: str
runtime_mode: str
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