Yuge Zhang
663 lines
22 KiB
Python
663 lines
22 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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"""
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Script to inject mock data directly into an InMemoryLightningStore.
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This script creates sample rollouts, attempts, spans, and resources that match
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the TypeScript mock data (from dashboard/src/components/RolloutTable.story.tsx)
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and injects them directly into the store's private variables for testing.
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Usage:
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from dashboard.test_utils.inject_mock_data import inject_mock_data
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store = InMemoryLightningStore()
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inject_mock_data(store)
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"""
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# pyright: reportPrivateUsage=false
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import argparse
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import asyncio
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import time
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from typing import List
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from agentlightning.store.client_server import LightningStoreServer
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from agentlightning.store.memory import InMemoryLightningStore
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from agentlightning.types import (
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LLM,
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Attempt,
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OtelResource,
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PromptTemplate,
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ResourcesUpdate,
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Rollout,
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RolloutConfig,
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Span,
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TraceStatus,
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)
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def inject_mock_data(store: InMemoryLightningStore, now: float | None = None) -> None:
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"""
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Inject mock data directly into the InMemoryLightningStore.
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Args:
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store: The InMemoryLightningStore instance to inject data into
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now: The current timestamp (defaults to current time)
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"""
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if now is None:
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now = time.time()
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# Create rollouts matching the TypeScript mock data
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# Based on sampleRollouts from dashboard/src/components/RolloutTable.story.tsx
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# Rollout 1: Running
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rollout1 = Rollout(
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rollout_id="ro-story-001",
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input=dict(task="Generate onboarding summary"),
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start_time=now - 3200,
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end_time=None,
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mode="train",
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resources_id="rs-story-001",
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status="running",
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config=RolloutConfig(max_attempts=1),
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metadata={"owner": "alice"},
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)
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attempt1 = Attempt(
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rollout_id="ro-story-001",
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attempt_id="at-story-010",
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sequence_id=1,
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start_time=now - 3200,
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end_time=None,
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status="running",
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worker_id="worker-east",
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last_heartbeat_time=now - 45,
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metadata={"info": "Worker is processing"},
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)
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# Rollout 2: Succeeded
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rollout2 = Rollout(
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rollout_id="ro-story-002",
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# NOTE: input is a string here, not a dict
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input="Classify feedback tickets",
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start_time=now - 7200,
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end_time=now - 5400,
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mode="val",
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resources_id="rs-story-002",
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status="succeeded",
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config=RolloutConfig(max_attempts=2, timeout_seconds=86400, unresponsive_seconds=86400 * 2),
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metadata={"owner": "bob"},
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)
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attempt2_1 = Attempt(
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rollout_id="ro-story-002",
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attempt_id="at-story-021",
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sequence_id=1,
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start_time=now - 7200,
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end_time=now - 5400,
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status="timeout",
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last_heartbeat_time=None,
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worker_id=None,
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metadata=None,
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)
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attempt2_2 = Attempt(
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rollout_id="ro-story-002",
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attempt_id="at-story-022",
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sequence_id=2,
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start_time=now - 6200,
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end_time=now - 5400,
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status="succeeded",
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worker_id="worker-north",
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last_heartbeat_time=now - 5400,
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metadata={"previousAttempt": "at-story-010"},
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)
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# Rollout 3: Failed
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rollout3 = Rollout(
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rollout_id="ro-story-003",
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input=dict(task="Analyze experiment results"),
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start_time=now - 10800,
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end_time=now - 9600,
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mode="test",
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resources_id="rs-story-003",
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status="failed",
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config=RolloutConfig(max_attempts=3),
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metadata={"owner": "carol"},
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)
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attempt3_1 = Attempt(
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rollout_id="ro-story-003",
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attempt_id="at-story-031",
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sequence_id=3,
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start_time=now - 10200,
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end_time=now - 9600,
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status="failed",
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worker_id="worker-west",
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last_heartbeat_time=now - 9600,
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metadata={"reason": "Timeout"},
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)
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attempt3_2 = Attempt(
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rollout_id="ro-story-003",
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attempt_id="at-story-032",
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sequence_id=2,
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start_time=now - 9600,
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end_time=None,
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status="unresponsive",
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worker_id="worker-west",
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last_heartbeat_time=now - 3600,
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metadata={"reason": "Unresponsive"},
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)
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attempt3_3 = Attempt(
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rollout_id="ro-story-003",
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attempt_id="at-story-033",
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sequence_id=3,
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start_time=now - 9000,
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end_time=now - 3600,
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status="failed",
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worker_id="worker-west",
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)
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# Rollout 4: Queuing (no attempt yet)
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rollout4 = Rollout(
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rollout_id="ro-story-004",
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input=dict(task="Evaluate prompt variants"),
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start_time=now - 3600,
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end_time=None,
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mode="train",
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resources_id=None,
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status="requeuing",
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config=RolloutConfig(max_attempts=5, retry_condition=["timeout"]),
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metadata={"owner": "dave"},
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)
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# Rollout 5: Running
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rollout5 = Rollout(
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rollout_id="ro-story-005",
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input=dict(task="Generate quick answers"),
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start_time=now - 1800,
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end_time=None,
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mode="val",
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resources_id="rs-story-004",
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status="running",
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config=RolloutConfig(max_attempts=1),
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metadata={"owner": "eva"},
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)
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attempt5 = Attempt(
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rollout_id="ro-story-005",
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attempt_id="at-story-013",
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sequence_id=1,
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start_time=now - 1800,
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end_time=None,
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status="running",
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worker_id=None,
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last_heartbeat_time=now - 75,
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metadata=None,
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)
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# Rollout 6: Cancelled
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rollout6 = Rollout(
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rollout_id="ro-story-006",
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input=dict(task="Compile release notes"),
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start_time=now - 9600,
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end_time=now - 9000,
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mode=None,
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resources_id="rs-story-005",
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status="cancelled",
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config=RolloutConfig(max_attempts=3),
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metadata=None,
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)
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attempt6 = Attempt(
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rollout_id="ro-story-006",
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attempt_id="at-story-014",
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sequence_id=1,
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start_time=now - 9600,
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end_time=now - 9000,
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status="timeout",
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worker_id="worker-south",
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last_heartbeat_time=now - 9000,
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metadata={"info": "Cancelled by operator"},
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)
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# Inject rollouts directly into store
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store._rollouts["ro-story-001"] = rollout1
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store._rollouts["ro-story-002"] = rollout2
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store._rollouts["ro-story-003"] = rollout3
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store._rollouts["ro-story-004"] = rollout4
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store._rollouts["ro-story-005"] = rollout5
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store._rollouts["ro-story-006"] = rollout6
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# Inject attempts directly into store
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store._attempts["ro-story-001"] = [attempt1]
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store._attempts["ro-story-002"] = [attempt2_1, attempt2_2]
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store._attempts["ro-story-003"] = [attempt3_1, attempt3_2, attempt3_3]
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store._attempts["ro-story-004"] = [] # No attempt for preparing rollout
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store._attempts["ro-story-005"] = [attempt5]
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store._attempts["ro-story-006"] = [attempt6]
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# Create and inject spans with diverse data
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# Spans for ro-story-001 (Running) - Multiple nested spans with ongoing execution
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spans_ro1: List[Span] = [
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Span(
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rollout_id="ro-story-001",
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attempt_id="at-story-010",
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sequence_id=1,
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trace_id="trace-001-main",
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span_id="span-001-root",
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parent_id=None,
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name="agent_execution",
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status=TraceStatus(status_code="OK", description=None),
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attributes={"component": "agent", "framework": "autogen", "version": "0.2.0"},
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events=[],
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links=[],
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start_time=now - 3200,
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end_time=now - 3100,
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context=None,
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parent=None,
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resource=OtelResource(attributes={"service.name": "agent-service"}, schema_url=""),
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),
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Span(
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rollout_id="ro-story-001",
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attempt_id="at-story-010",
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sequence_id=2,
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trace_id="trace-001-main",
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span_id="span-002-llm",
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parent_id="span-001-root",
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name="llm_call",
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status=TraceStatus(status_code="OK", description=None),
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attributes={"model": "gpt-4", "temperature": 0.7, "tokens": 150},
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events=[],
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links=[],
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start_time=now - 3180,
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end_time=now - 3120,
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context=None,
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parent=None,
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resource=OtelResource(attributes={"service.name": "llm-service"}, schema_url=""),
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),
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Span(
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rollout_id="ro-story-001",
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attempt_id="at-story-010",
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sequence_id=3,
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trace_id="trace-001-main",
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span_id="span-003-tool",
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parent_id="span-001-root",
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name="tool_execution",
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status=TraceStatus(status_code="OK", description=None),
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attributes={"tool": "web_search", "query": "onboarding summary"},
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events=[],
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links=[],
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start_time=now - 3140,
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end_time=now - 3100,
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context=None,
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parent=None,
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resource=OtelResource(attributes={"service.name": "tool-service"}, schema_url=""),
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),
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]
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# Spans for ro-story-002 attempt 1 (timeout) - Failed workflow
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spans_ro2_a1: List[Span] = [
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Span(
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rollout_id="ro-story-002",
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attempt_id="at-story-021",
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sequence_id=1,
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trace_id="trace-002-attempt1",
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span_id="span-004-root",
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parent_id=None,
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name="classification_pipeline",
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status=TraceStatus(status_code="ERROR", description="Request timeout"),
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attributes={"type": "classification", "model": "bert-classifier", "timeout": True},
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events=[],
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links=[],
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start_time=now - 7200,
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end_time=now - 6800,
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context=None,
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parent=None,
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resource=OtelResource(attributes={"service.name": "classifier"}, schema_url=""),
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),
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]
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# Spans for ro-story-002 attempt 2 (succeeded) - Successful workflow
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spans_ro2_a2: List[Span] = [
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Span(
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rollout_id="ro-story-002",
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attempt_id="at-story-022",
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sequence_id=1,
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trace_id="trace-002-attempt2",
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span_id="span-005-root",
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parent_id=None,
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name="classification_pipeline",
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status=TraceStatus(status_code="OK", description=None),
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attributes={"type": "classification", "model": "bert-classifier", "retry": True},
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events=[],
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links=[],
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start_time=now - 6200,
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end_time=now - 5400,
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context=None,
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parent=None,
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resource=OtelResource(attributes={"service.name": "classifier"}, schema_url=""),
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),
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Span(
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rollout_id="ro-story-002",
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attempt_id="at-story-022",
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sequence_id=2,
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trace_id="trace-002-attempt2",
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span_id="span-006-preprocess",
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parent_id="span-005-root",
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name="preprocess_tickets",
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status=TraceStatus(status_code="OK", description=None),
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attributes={"tickets_count": 50, "duration_ms": 120},
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events=[],
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links=[],
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start_time=now - 6200,
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end_time=now - 6100,
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context=None,
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parent=None,
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resource=OtelResource(attributes={}, schema_url=""),
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),
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Span(
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rollout_id="ro-story-002",
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attempt_id="at-story-022",
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sequence_id=3,
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trace_id="trace-002-attempt2",
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span_id="span-007-classify",
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parent_id="span-005-root",
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name="run_classifier",
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status=TraceStatus(status_code="OK", description=None),
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attributes={"batch_size": 10, "accuracy": 0.95},
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events=[],
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links=[],
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start_time=now - 6000,
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end_time=now - 5400,
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context=None,
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parent=None,
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resource=OtelResource(attributes={}, schema_url=""),
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),
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]
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# Spans for ro-story-003 attempt 3 (failed) - Error scenario with nested failures
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spans_ro3_a3: List[Span] = [
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Span(
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rollout_id="ro-story-003",
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attempt_id="at-story-033",
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sequence_id=1,
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trace_id="trace-003-experiment",
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span_id="span-008-root",
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parent_id=None,
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name="experiment_analysis",
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status=TraceStatus(status_code="ERROR", description="Analysis failed"),
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attributes={"experiment_id": "exp-123", "timeout_seconds": 300},
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events=[],
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links=[],
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start_time=now - 9000,
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end_time=now - 3600,
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context=None,
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parent=None,
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resource=OtelResource(attributes={"service.name": "experiment-runner"}, schema_url=""),
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),
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Span(
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rollout_id="ro-story-003",
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attempt_id="at-story-033",
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sequence_id=2,
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trace_id="trace-003-experiment",
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span_id="span-009-fetch",
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parent_id="span-008-root",
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name="fetch_experiment_data",
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status=TraceStatus(status_code="ERROR", description="Connection timeout"),
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attributes={"data_source": "database", "retry_count": 3},
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events=[],
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links=[],
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start_time=now - 9000,
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end_time=now - 7000,
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context=None,
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parent=None,
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resource=OtelResource(attributes={}, schema_url=""),
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),
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Span(
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rollout_id="ro-story-003",
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attempt_id="at-story-033",
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sequence_id=3,
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trace_id="trace-003-experiment",
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span_id="span-010-process",
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parent_id="span-008-root",
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name="process_results",
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status=TraceStatus(status_code="UNSET", description=None),
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attributes={"stage": "aggregation", "partial_results": True},
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events=[],
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links=[],
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start_time=now - 6000,
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end_time=now - 3600,
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context=None,
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parent=None,
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resource=OtelResource(attributes={}, schema_url=""),
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),
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]
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# Spans for ro-story-005 (Running) - In-progress with mixed statuses
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spans_ro5: List[Span] = [
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Span(
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rollout_id="ro-story-005",
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attempt_id="at-story-013",
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sequence_id=1,
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trace_id="trace-005-answers",
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span_id="span-011-root",
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parent_id=None,
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name="quick_answer_generation",
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status=TraceStatus(status_code="OK", description=None),
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attributes={"batch_size": 10, "model": "llama-3"},
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events=[],
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links=[],
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start_time=now - 1800,
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end_time=now - 1500,
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context=None,
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parent=None,
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resource=OtelResource(attributes={"service.name": "qa-service"}, schema_url=""),
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),
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Span(
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rollout_id="ro-story-005",
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attempt_id="at-story-013",
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sequence_id=2,
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trace_id="trace-005-answers",
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span_id="span-012-llm",
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parent_id="span-011-root",
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name="llm_inference",
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status=TraceStatus(status_code="UNSET", description=None),
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attributes={"model": "llama-3-70b", "batch_id": "batch-001"},
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events=[],
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links=[],
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start_time=now - 1700,
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end_time=None,
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context=None,
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parent=None,
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resource=OtelResource(attributes={}, schema_url=""),
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),
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Span(
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rollout_id="ro-story-005",
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attempt_id="at-story-013",
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sequence_id=3,
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trace_id="trace-005-answers",
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span_id="span-013-retrieve",
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parent_id="span-011-root",
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name="retrieve_context",
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status=TraceStatus(status_code="OK", description=None),
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attributes={"documents_count": 5, "vector_db": "chroma"},
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events=[],
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links=[],
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start_time=now - 1780,
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end_time=now - 1700,
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context=None,
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parent=None,
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resource=OtelResource(attributes={}, schema_url=""),
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),
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]
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# Spans for ro-story-006 (Cancelled) - Cancelled workflow
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spans_ro6: List[Span] = [
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Span(
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rollout_id="ro-story-006",
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attempt_id="at-story-014",
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sequence_id=1,
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trace_id="trace-006-release",
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span_id="span-014-root",
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parent_id=None,
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name="compile_release_notes",
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status=TraceStatus(status_code="ERROR", description="Operation cancelled by user"),
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attributes={"release_version": "v2.0.0", "cancelled": True},
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events=[],
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links=[],
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start_time=now - 9600,
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end_time=now - 9000,
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context=None,
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parent=None,
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resource=OtelResource(attributes={"service.name": "release-automation"}, schema_url=""),
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),
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Span(
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rollout_id="ro-story-006",
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attempt_id="at-story-014",
|
|
sequence_id=2,
|
|
trace_id="trace-006-release",
|
|
span_id="span-015-git",
|
|
parent_id="span-014-root",
|
|
name="fetch_git_commits",
|
|
status=TraceStatus(status_code="OK", description=None),
|
|
attributes={"repo": "main", "commits_count": 45},
|
|
events=[],
|
|
links=[],
|
|
start_time=now - 9600,
|
|
end_time=now - 9400,
|
|
context=None,
|
|
parent=None,
|
|
resource=OtelResource(attributes={}, schema_url=""),
|
|
),
|
|
Span(
|
|
rollout_id="ro-story-006",
|
|
attempt_id="at-story-014",
|
|
sequence_id=3,
|
|
trace_id="trace-006-release",
|
|
span_id="span-016-format",
|
|
parent_id="span-014-root",
|
|
name="format_changelog",
|
|
status=TraceStatus(status_code="ERROR", description="Cancelled during formatting"),
|
|
attributes={"format": "markdown", "cancelled_at": "50%"},
|
|
events=[],
|
|
links=[],
|
|
start_time=now - 9300,
|
|
end_time=now - 9000,
|
|
context=None,
|
|
parent=None,
|
|
resource=OtelResource(attributes={}, schema_url=""),
|
|
),
|
|
]
|
|
|
|
store._spans["ro-story-001"] = spans_ro1
|
|
store._spans["ro-story-002"] = spans_ro2_a1 + spans_ro2_a2
|
|
store._spans["ro-story-003"] = spans_ro3_a3
|
|
store._spans["ro-story-005"] = spans_ro5
|
|
store._spans["ro-story-006"] = spans_ro6
|
|
|
|
# Create and inject resources with diverse types
|
|
resource1 = ResourcesUpdate(
|
|
resources_id="rs-story-001",
|
|
version=1,
|
|
create_time=now - 86400,
|
|
update_time=now - 86400,
|
|
resources={
|
|
"model": LLM(
|
|
endpoint="https://api.openai.com/v1",
|
|
model="gpt-4",
|
|
sampling_parameters={"temperature": 0.7, "max_tokens": 1000},
|
|
),
|
|
},
|
|
)
|
|
|
|
resource2 = ResourcesUpdate(
|
|
resources_id="rs-story-002",
|
|
version=1,
|
|
create_time=now - 86400,
|
|
update_time=now - 43200,
|
|
resources={
|
|
"prompt_main": PromptTemplate(
|
|
template="Classify the following ticket: {ticket}\nCategory:",
|
|
engine="f-string",
|
|
),
|
|
},
|
|
)
|
|
|
|
resource3 = ResourcesUpdate(
|
|
resources_id="rs-story-003",
|
|
version=2,
|
|
create_time=now - 86400,
|
|
update_time=now - 3600,
|
|
resources={
|
|
"model": LLM(
|
|
endpoint="https://api.anthropic.com/v1",
|
|
model="claude-3-sonnet",
|
|
sampling_parameters={"temperature": 0.8, "max_tokens": 2048},
|
|
),
|
|
"prompt": PromptTemplate(
|
|
template="Analyze experiment results:\n{% for result in results %}\n- {{ result }}\n{% endfor %}",
|
|
engine="jinja",
|
|
),
|
|
},
|
|
)
|
|
|
|
resource4 = ResourcesUpdate(
|
|
resources_id="rs-story-004",
|
|
version=1,
|
|
create_time=now - 7200,
|
|
update_time=now - 7200,
|
|
resources={
|
|
"system_prompt": PromptTemplate(
|
|
template="You are a helpful assistant that generates quick, concise answers.",
|
|
engine="f-string",
|
|
),
|
|
"model": LLM(
|
|
endpoint="http://localhost:8000/v1",
|
|
model="llama-3-70b",
|
|
sampling_parameters={"temperature": 0.6, "top_p": 0.95},
|
|
),
|
|
},
|
|
)
|
|
|
|
resource5 = ResourcesUpdate(
|
|
resources_id="rs-story-005",
|
|
version=1,
|
|
create_time=now - 14400,
|
|
update_time=now - 14400,
|
|
resources={
|
|
"prompt": PromptTemplate(
|
|
template="## Release Notes v{{ version }}\n\n### Changes\n{{ changes }}",
|
|
engine="jinja",
|
|
),
|
|
},
|
|
)
|
|
|
|
store._resources["rs-story-001"] = resource1
|
|
store._resources["rs-story-002"] = resource2
|
|
store._resources["rs-story-003"] = resource3
|
|
store._resources["rs-story-004"] = resource4
|
|
store._resources["rs-story-005"] = resource5
|
|
store._latest_resources_id = "rs-story-005"
|
|
|
|
|
|
async def main():
|
|
parser = argparse.ArgumentParser(description="Run a Python server for the LightningStore")
|
|
parser.add_argument("--now", type=float, default=time.time(), help="The current timestamp")
|
|
args = parser.parse_args()
|
|
|
|
store = InMemoryLightningStore()
|
|
inject_mock_data(store, now=args.now)
|
|
|
|
# Start server
|
|
server = LightningStoreServer(store, "127.0.0.1", 8765, "*")
|
|
await server.start()
|
|
|
|
print(f"Server started at {server.endpoint}")
|
|
print("Press Ctrl+C to stop...")
|
|
|
|
try:
|
|
# Keep server running
|
|
await asyncio.Event().wait()
|
|
except KeyboardInterrupt:
|
|
print("\nStopping server...")
|
|
await server.stop()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
asyncio.run(main())
|