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https://github.com/langbot-app/LangBot.git
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feat(agent-runner): add event-first context facts and pull APIs
Add EventLog and Transcript persistence entities for storing auditable event facts and conversation history projection. Implement event-first AgentRunContext builder that produces Protocol v1 compliant context payloads with required fields: event, delivery, context (ContextAccess). Key changes: - EventLog ORM: auditable event records with indexes - Transcript ORM: conversation history projection with composite indexes - AgentRunContextBuilder: Protocol v1 payload with delivery, context, bootstrap - EventLogStore/TranscriptStore: async stores for fact sources - Host action handlers: HISTORY_PAGE, HISTORY_SEARCH, EVENT_GET, EVENT_PAGE - Context validation: build_context output validates via SDK AgentRunContext - Alembic migration for event_log and transcript tables - Alembic env.py imports all ORM models for autogenerate discovery Legacy compatibility: max-round messages go into bootstrap.messages and compatibility.legacy_messages, not top-level messages field.
This commit is contained in:
huanghuoguoguo
288
src/langbot/pkg/agent/runner/transcript_store.py
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288
src/langbot/pkg/agent/runner/transcript_store.py
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"""Transcript store for writing and querying conversation history."""
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from __future__ import annotations
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import json
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import datetime
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import typing
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import uuid
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import sqlalchemy
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from sqlalchemy.ext.asyncio import AsyncEngine
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from ...entity.persistence.transcript import Transcript
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class TranscriptStore:
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"""Store for Transcript records.
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Handles writing transcript items and querying them for history API.
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All methods are async and use the provided database engine.
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"""
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engine: AsyncEngine
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# Hard limits
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MAX_CONTENT_LENGTH = 4000
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HARD_LIMIT = 100
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def __init__(self, engine: AsyncEngine):
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self.engine = engine
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async def append_transcript(
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self,
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transcript_id: str | None,
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event_id: str,
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conversation_id: str,
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role: str,
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content: str | None = None,
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content_json: dict[str, typing.Any] | None = None,
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artifact_refs: list[dict[str, typing.Any]] | None = None,
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thread_id: str | None = None,
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item_type: str = "message",
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run_id: str | None = None,
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runner_id: str | None = None,
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metadata: dict[str, typing.Any] | None = None,
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) -> str:
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"""Append a transcript item.
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Args:
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transcript_id: Unique transcript ID (generated if None)
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event_id: Source event ID
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conversation_id: Conversation ID
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role: Message role (user, assistant, system, tool)
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content: Text content
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content_json: Full structured content
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artifact_refs: Artifact references
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thread_id: Thread ID
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item_type: Item type
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run_id: Run ID that generated this
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runner_id: Runner ID that generated this
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metadata: Additional metadata
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Returns:
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The transcript_id
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"""
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if transcript_id is None:
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transcript_id = str(uuid.uuid4())
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# Truncate content if too long
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if content and len(content) > self.MAX_CONTENT_LENGTH:
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content = content[:self.MAX_CONTENT_LENGTH - 3] + "..."
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# Get next sequence number for this conversation
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seq = await self._get_next_seq(conversation_id)
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async with self.engine.connect() as conn:
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await conn.execute(
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sqlalchemy.insert(Transcript).values(
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transcript_id=transcript_id,
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event_id=event_id,
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conversation_id=conversation_id,
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thread_id=thread_id,
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role=role,
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item_type=item_type,
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content=content,
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content_json=json.dumps(content_json) if content_json else None,
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artifact_refs_json=json.dumps(artifact_refs) if artifact_refs else None,
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seq=seq,
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run_id=run_id,
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runner_id=runner_id,
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created_at=datetime.datetime.utcnow(),
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metadata_json=json.dumps(metadata) if metadata else None,
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)
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)
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await conn.commit()
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return transcript_id
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async def page_transcript(
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self,
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conversation_id: str,
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before_seq: int | None = None,
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after_seq: int | None = None,
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limit: int = 50,
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direction: str = "backward",
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include_artifacts: bool = False,
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) -> tuple[list[dict[str, typing.Any]], int | None, int | None, bool]:
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"""Page through transcript items.
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Args:
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conversation_id: Conversation ID
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before_seq: Get items before this sequence (backward)
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after_seq: Get items after this sequence (forward)
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limit: Maximum items to return (capped at 100)
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direction: 'backward' (older) or 'forward' (newer)
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include_artifacts: Include artifact refs
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Returns:
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Tuple of (items, next_seq, prev_seq, has_more)
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"""
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limit = min(limit, self.HARD_LIMIT)
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async with self.engine.connect() as conn:
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query = sqlalchemy.select(Transcript).where(
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Transcript.conversation_id == conversation_id
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)
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if direction == "backward" and before_seq is not None:
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query = query.where(Transcript.seq < before_seq)
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query = query.order_by(Transcript.seq.desc())
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elif direction == "forward" and after_seq is not None:
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query = query.where(Transcript.seq > after_seq)
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query = query.order_by(Transcript.seq.asc())
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else:
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# Default: most recent items first (backward from latest)
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query = query.order_by(Transcript.seq.desc())
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query = query.limit(limit + 1)
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result = await conn.execute(query)
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rows = result.fetchall()
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items = [self._row_to_dict(row[0], include_artifacts) for row in rows[:limit]]
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has_more = len(rows) > limit
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# Calculate cursors
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next_seq = None
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prev_seq = None
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if direction == "backward":
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# Items are in descending order
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if items:
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next_seq = items[-1].get('seq') if has_more else None
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prev_seq = items[0].get('seq')
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else:
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# Items are in ascending order
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if items:
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next_seq = items[-1].get('seq') if has_more else None
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prev_seq = items[0].get('seq')
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return items, next_seq, prev_seq, has_more
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async def search_transcript(
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self,
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conversation_id: str,
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query_text: str,
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filters: dict[str, typing.Any] | None = None,
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top_k: int = 10,
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) -> list[dict[str, typing.Any]]:
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"""Search transcript items.
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Basic implementation using LIKE filtering.
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Args:
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conversation_id: Conversation ID
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query_text: Search query
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filters: Optional filters
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top_k: Maximum results
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Returns:
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List of matching items
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"""
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async with self.engine.connect() as conn:
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query = sqlalchemy.select(Transcript).where(
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Transcript.conversation_id == conversation_id,
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Transcript.content.ilike(f"%{query_text}%"),
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)
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# Apply additional filters
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if filters:
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if 'roles' in filters:
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query = query.where(Transcript.role.in_(filters['roles']))
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if 'item_types' in filters:
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query = query.where(Transcript.item_type.in_(filters['item_types']))
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query = query.order_by(Transcript.seq.desc()).limit(top_k)
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result = await conn.execute(query)
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rows = result.fetchall()
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return [self._row_to_dict(row[0], include_artifacts=True) for row in rows]
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async def get_latest_cursor(
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self,
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conversation_id: str,
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) -> str | None:
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"""Get the latest cursor for a conversation.
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Args:
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conversation_id: Conversation ID
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Returns:
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Cursor string (seq number), or None if no items
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"""
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async with self.engine.connect() as conn:
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result = await conn.execute(
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sqlalchemy.select(Transcript.seq)
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.where(Transcript.conversation_id == conversation_id)
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.order_by(Transcript.seq.desc())
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.limit(1)
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)
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row = result.fetchone()
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if row is None:
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return None
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return str(row[0])
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async def has_history_before(
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self,
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conversation_id: str,
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seq: int,
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) -> bool:
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"""Check if there is history before a sequence number.
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Args:
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conversation_id: Conversation ID
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seq: Sequence number
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Returns:
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True if there are items before
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"""
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async with self.engine.connect() as conn:
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result = await conn.execute(
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sqlalchemy.select(sqlalchemy.func.count())
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.select_from(Transcript)
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.where(
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Transcript.conversation_id == conversation_id,
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Transcript.seq < seq,
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)
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)
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count = result.scalar()
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return count > 0
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async def _get_next_seq(self, conversation_id: str) -> int:
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"""Get the next sequence number for a conversation."""
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async with self.engine.connect() as conn:
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result = await conn.execute(
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sqlalchemy.select(sqlalchemy.func.max(Transcript.seq))
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.where(Transcript.conversation_id == conversation_id)
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)
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max_seq = result.scalar()
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return (max_seq or 0) + 1
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def _row_to_dict(
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self,
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row: Transcript,
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include_artifacts: bool = False,
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) -> dict[str, typing.Any]:
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"""Convert a Transcript row to dict."""
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result = {
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'transcript_id': row.transcript_id,
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'event_id': row.event_id,
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'conversation_id': row.conversation_id,
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'thread_id': row.thread_id,
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'role': row.role,
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'item_type': row.item_type,
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'content': row.content,
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'content_json': json.loads(row.content_json) if row.content_json else None,
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'seq': row.seq,
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'cursor': str(row.seq),
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'created_at': int(row.created_at.timestamp()) if row.created_at else None,
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'metadata': json.loads(row.metadata_json) if row.metadata_json else {},
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}
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if include_artifacts and row.artifact_refs_json:
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result['artifact_refs'] = json.loads(row.artifact_refs_json)
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else:
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result['artifact_refs'] = []
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return result
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