33db5aeb10
- Replay models: StepType enum, ReplayStep, ReplayPage frozen dataclasses
- Checkpoint transformer: PostgresSaver JSONB -> structured timeline steps
- Replay API: GET /api/conversations (paginated), GET /api/replay/{thread_id}
- Analytics models: AgentUsage, InterruptStats, AnalyticsResult
- Analytics event recorder: Protocol + PostgresAnalyticsRecorder + NoOp
- Analytics queries: resolution_rate, agent_usage, escalation_rate, cost, interrupts
- Analytics API: GET /api/analytics?range=Xd with envelope response
- DB migration: analytics_events table + conversations column additions
- 74 new tests, 399 total passing, 92.87% coverage
117 lines
3.5 KiB
Python
117 lines
3.5 KiB
Python
"""Transforms PostgresSaver checkpoint rows into ReplayStep list."""
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from __future__ import annotations
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import logging
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from app.replay.models import ReplayStep, StepType
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logger = logging.getLogger(__name__)
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_EMPTY_TIMESTAMP = "1970-01-01T00:00:00Z"
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def _extract_messages(row: dict) -> list[dict]:
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"""Safely extract messages list from a checkpoint row."""
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checkpoint = row.get("checkpoint")
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if not checkpoint or not isinstance(checkpoint, dict):
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return []
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channel_values = checkpoint.get("channel_values")
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if not channel_values or not isinstance(channel_values, dict):
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return []
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messages = channel_values.get("messages")
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if not messages or not isinstance(messages, list):
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return []
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return messages
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def _step_from_message(msg: dict, step_number: int) -> ReplayStep | None:
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"""Convert a single message dict to a ReplayStep. Returns None for unknown types."""
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msg_type = msg.get("type", "")
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timestamp = msg.get("created_at") or _EMPTY_TIMESTAMP
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content = msg.get("content") or ""
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if isinstance(content, list):
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# LangChain may encode content as a list of parts
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content = " ".join(
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part.get("text", "") if isinstance(part, dict) else str(part)
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for part in content
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)
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if msg_type == "human":
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return ReplayStep(
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step=step_number,
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type=StepType.user_message,
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timestamp=timestamp,
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content=content,
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)
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if msg_type == "ai":
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tool_calls = msg.get("tool_calls") or []
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if tool_calls:
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first = tool_calls[0]
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return ReplayStep(
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step=step_number,
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type=StepType.tool_call,
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timestamp=timestamp,
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content=content,
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tool=first.get("name"),
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params=dict(first.get("args") or {}),
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)
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return ReplayStep(
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step=step_number,
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type=StepType.agent_response,
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timestamp=timestamp,
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content=content,
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agent=msg.get("name"),
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)
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if msg_type == "tool":
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raw = content
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result: dict | None = None
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try:
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import json
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result = json.loads(raw)
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except (ValueError, TypeError):
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result = {"raw": raw}
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return ReplayStep(
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step=step_number,
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type=StepType.tool_result,
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timestamp=timestamp,
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tool=msg.get("name"),
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result=result,
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)
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logger.debug("Skipping unknown message type: %s", msg_type)
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return None
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def transform_checkpoints(rows: list[dict]) -> list[ReplayStep]:
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"""Transform a list of checkpoint rows into an ordered list of ReplaySteps.
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Steps are numbered sequentially starting from 1 across all rows.
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Unknown or malformed messages are silently skipped.
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"""
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steps: list[ReplayStep] = []
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step_number = 1
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for row in rows:
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try:
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messages = _extract_messages(row)
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except Exception: # noqa: BLE001
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logger.exception("Error extracting messages from checkpoint row")
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continue
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for msg in messages:
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try:
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step = _step_from_message(msg, step_number)
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except Exception: # noqa: BLE001
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logger.exception("Error converting message to ReplayStep")
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step = None
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if step is not None:
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steps.append(step)
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step_number += 1
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return steps
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