src/core/graph_cdm.py

from langgraph.graph import StateGraph, END
from src.core.state import AgentState
from src.agents.agent_instances import (
    health_coach, trend_analyzer, validator, safety_check
)
from src.tools.fhir_memory import (
    get_patient_summary_fhir, save_observation, ingest_fhir_bundle, 
    get_medications_by_patient, save_medication
)
from src.tools.web_tools import web_search_tool
from langgraph.prebuilt import ToolNode
import time
from src.utils.logger import setup_logger

logger = setup_logger("CDMPipeline")

def log_step(name: str, output: str = None):
    logger.info(f"Executing: {name}")
    log_msg = f"➔ CDM Node: {name}"
    if output:
        log_msg += f"\nOutput: {output}"
    return {"logs": [log_msg]}

async def data_fetch_node(state: AgentState):
    """
    Fetch FHIR data and medications for CDM context.
    Bug 7.3: Include medication context in CDM pipeline.
    """
    patient_id = state.get("patient_id", "unknown")
    if patient_id == "unknown":
        return log_step("Data Fetch", "No Patient ID provided.")
    
    start_time = time.time()
    
    # Fetch FHIR summary
    summary = get_patient_summary_fhir.invoke({"patient_id": patient_id})
    
    # Bug 7.3: Fetch medications for context
    medications = get_medications_by_patient.invoke({"patient_id": patient_id})
    
    # If summary has active_medications field, populate it
    if isinstance(summary, dict) and "active_medications" in summary:
        summary["active_medications"] = medications if medications else []
    
    end_time = time.time()
    
    log_output = f"Retrieved summary and medications for {patient_id}"
    if medications:
        log_output += f" ({len(medications)} active medications)"
    
    log = log_step("FHIR Data Fetch", log_output)
    
    metrics = {
        "agent": "DataFetchNode",
        "tokens": 0,
        "time": round(end_time - start_time, 3)
    }
    
    return {
        "fhir_data": [summary] if isinstance(summary, dict) else [], 
        "current_medications": medications if isinstance(medications, list) else [],
        "logs": log["logs"],
        "metrics": [metrics]
    }

async def trend_analyzer_node(state: AgentState):
    res = await trend_analyzer.run(state)
    log = log_step("Trend Analyzer", res.get("trend_analysis", ""))
    res.update(log)
    return res

async def health_coach_node(state: AgentState):
    res = await health_coach.run(state)
    last_msg = res["messages"][-1]
    content = last_msg.content if getattr(last_msg, "content", "") else "Tool calls generated."
    log = log_step("Health Coach", content)
    res.update(log)
    return res

async def validator_node(state: AgentState):
    from src.agents.agent_instances import validator
    res = await validator.run(state)
    log = log_step("Response Validator", f"Valid: {res.get('is_valid')}")
    res.update(log)
    return res

async def safety_check_node(state: AgentState):
    from src.agents.agent_instances import safety_check
    res = await safety_check.run(state)
    log = log_step("Safety Check", f"Safe: {res.get('is_safe')}")
    res.update(log)
    return res

# Tool routing
def route_health_coach(state: AgentState):
    last_message = state["messages"][-1]
    if hasattr(last_message, "tool_calls") and last_message.tool_calls:
        return "tools_node"
    return "validator"

def route_after_tools(state: AgentState):
    return "health_coach"

def route_after_validator(state: AgentState):
    if state.get("is_valid", False):
        return "safety_check"
    return "health_coach" # Simple retry

# Setup tools
cdm_tools = [web_search_tool, save_observation, ingest_fhir_bundle, get_patient_summary_fhir, get_medications_by_patient, save_medication]
tool_node = ToolNode(cdm_tools)

async def tools_node_with_metrics(state: AgentState):
    start_time = time.time()
    res = await tool_node.ainvoke(state)
    end_time = time.time()
    
    metrics = {
        "agent": "CDMToolsNode",
        "tokens": 0,
        "time": round(end_time - start_time, 3)
    }
    
    # ToolNode returns a list of messages
    return {"messages": res, "metrics": [metrics]}

# Build CDM Graph
builder = StateGraph(AgentState)

builder.add_node("data_fetch", data_fetch_node)
builder.add_node("trend_analyzer", trend_analyzer_node)
builder.add_node("health_coach", health_coach_node)
builder.add_node("tools_node", tools_node_with_metrics)
builder.add_node("validator", validator_node)
builder.add_node("safety_check", safety_check_node)

builder.set_entry_point("data_fetch")
builder.add_edge("data_fetch", "trend_analyzer")
builder.add_edge("trend_analyzer", "health_coach")

builder.add_conditional_edges("health_coach", route_health_coach, {
    "tools_node": "tools_node",
    "validator": "validator"
})

builder.add_edge("tools_node", "health_coach")

builder.add_conditional_edges("validator", route_after_validator, {
    "safety_check": "safety_check",
    "health_coach": "health_coach"
})

builder.add_conditional_edges("safety_check", lambda x: "end" if x.get("is_safe") else "health_coach", {
    "end": END,
    "health_coach": "health_coach"
})

cdm_pipeline = builder.compile()