Dynavera/apps/mlstore/consumers.py

import json
from channels.generic.websocket import AsyncWebsocketConsumer
from channels.db import database_sync_to_async
from django.utils import timezone
from .models import Agent, AgentRun, AgentEvent
from .tasks import start_fine_tune_run_task, infer_run_task


class MLStoreConsumer(AsyncWebsocketConsumer):
    async def connect(self):
        self.user = self.scope["user"]
        self.agent_id = self.scope["url_route"]["kwargs"].get("agent_id")
        self.room_group_name = f"mlstore_agent_{self.agent_id}"

        if not self.user.is_authenticated:
            await self.close()
            return

        agent = await self.get_agent(self.agent_id)
        if not agent:
            await self.close()
            return

        await self.channel_layer.group_add(self.room_group_name, self.channel_name)
        await self.accept()
        await self.send(json.dumps({
            "type": "connection",
            "message": "Connected to mlstore agent stream",
            "agent_id": str(self.agent_id)
        }))

    async def disconnect(self, close_code):
        await self.channel_layer.group_discard(self.room_group_name, self.channel_name)

    async def receive(self, text_data):
        try:
            data = json.loads(text_data)
            action = data.get("action")

            if action == "fine_tune":
                await self.handle_fine_tune(data)
            elif action == "infer":
                await self.handle_infer(data)
            elif action in ("stop_agent", "stop"):
                await self.handle_stop(data)
            else:
                await self.send(json.dumps({
                    "type": "error",
                    "message": f"Unknown action: {action}"
                }))
        except json.JSONDecodeError:
            await self.send(json.dumps({
                "type": "error",
                "message": "Invalid JSON"
            }))
        except Exception as e:
            await self.send(json.dumps({
                "type": "error",
                "message": str(e)
            }))

    async def handle_fine_tune(self, data):
        agent = await self.get_agent(self.agent_id)
        if not agent:
            await self.send(json.dumps({
                "type": "error",
                "message": "Agent not found"
            }))
            return

        input_data = data.get("input_data") or {}
        execution = await self.create_run(agent, self.user, input_data)

        await self.send(json.dumps({
            "type": "execution_started",
            "execution_id": str(execution.uuid),
            "agent_id": str(agent.uuid),
            "message": f"Fine-tune run {execution.uuid} queued"
        }))

        start_fine_tune_run_task.delay(str(execution.uuid))

    async def handle_infer(self, data):
        agent = await self.get_agent(self.agent_id)
        if not agent:
            await self.send(json.dumps({
                "type": "error",
                "message": "Agent not found"
            }))
            return

        input_data = data.get("input_data") or {}
        execution = await self.create_run(agent, self.user, input_data)

        await self.send(json.dumps({
            "type": "execution_started",
            "execution_id": str(execution.uuid),
            "agent_id": str(agent.uuid),
            "message": f"Inference run {execution.uuid} queued"
        }))

        infer_run_task.delay(str(execution.uuid))

    async def handle_stop(self, data):
        execution_id = data.get("execution_id")
        if not execution_id:
            await self.send(json.dumps({
                "type": "error",
                "message": "execution_id required to stop"
            }))
            return

        execution = await self.get_execution(execution_id)
        if not execution:
            await self.send(json.dumps({
                "type": "error",
                "message": "Execution not found"
            }))
            return

        await self.update_execution_status(execution, "failed")
        await self.send(json.dumps({
            "type": "execution_error",
            "execution_id": str(execution.uuid),
            "error_message": "Execution stopped by user"
        }))

    async def mlstore_event(self, event):
        await self.send(json.dumps({
            "type": "mlstore_event",
            "event_type": event["event_type"],
            "content": event["content"],
            "timestamp": event["timestamp"]
        }))

    async def mlstore_completed(self, event):
        await self.send(json.dumps({
            "type": "execution_completed",
            "execution_id": event["execution_id"],
            "output_data": event["output_data"],
            "message": "Execution completed"
        }))

    async def mlstore_error(self, event):
        await self.send(json.dumps({
            "type": "execution_error",
            "execution_id": event["execution_id"],
            "error_message": event["error_message"]
        }))

    @database_sync_to_async
    def get_agent(self, agent_id):
        try:
            return Agent.objects.get(uuid=agent_id)
        except Agent.DoesNotExist:
            return None

    @database_sync_to_async
    def create_run(self, agent, user, input_data):
        return AgentRun.objects.create(
            agent=agent,
            user=user,
            input_data=input_data,
        )

    @database_sync_to_async
    def get_execution(self, execution_id):
        try:
            return AgentRun.objects.get(uuid=execution_id)
        except AgentRun.DoesNotExist:
            return None

    @database_sync_to_async
    def update_execution_status(self, execution, status):
        execution.status = status
        execution.completed_at = timezone.now()
        execution.save()
        try:
            agent = execution.agent
            agent.status = status
            agent.completed_at = timezone.now()
            agent.save()
        except Exception:
            pass
        return execution

    @database_sync_to_async
    def create_event(self, execution, event_type, content):
        return AgentEvent.objects.create(
            execution=execution,
            event_type=event_type,
            content=content,
        )