mirror of
https://github.com/danswer-ai/danswer.git
synced 2025-09-19 20:24:32 +02:00
Paginate Query History table (#3592)
* Add pagination for query history table * Fix method name * Fix mypy
This commit is contained in:
skylares
GitHub
@@ -1,27 +1,135 @@
|
||||
import datetime
|
||||
from typing import Literal
|
||||
from collections.abc import Sequence
|
||||
from datetime import datetime
|
||||
|
||||
from sqlalchemy import asc
|
||||
from sqlalchemy import BinaryExpression
|
||||
from sqlalchemy import ColumnElement
|
||||
from sqlalchemy import desc
|
||||
from sqlalchemy import distinct
|
||||
from sqlalchemy.orm import contains_eager
|
||||
from sqlalchemy.orm import joinedload
|
||||
from sqlalchemy.orm import Session
|
||||
from sqlalchemy.sql import case
|
||||
from sqlalchemy.sql import func
|
||||
from sqlalchemy.sql import select
|
||||
from sqlalchemy.sql.expression import literal
|
||||
from sqlalchemy.sql.expression import UnaryExpression
|
||||
|
||||
from onyx.configs.constants import QAFeedbackType
|
||||
from onyx.db.models import ChatMessage
|
||||
from onyx.db.models import ChatMessageFeedback
|
||||
from onyx.db.models import ChatSession
|
||||
|
||||
SortByOptions = Literal["time_sent"]
|
||||
|
||||
def _build_filter_conditions(
|
||||
start_time: datetime | None,
|
||||
end_time: datetime | None,
|
||||
feedback_filter: QAFeedbackType | None,
|
||||
) -> list[ColumnElement]:
|
||||
"""
|
||||
Helper function to build all filter conditions for chat sessions.
|
||||
Filters by start and end time, feedback type, and any sessions without messages.
|
||||
start_time: Date from which to filter
|
||||
end_time: Date to which to filter
|
||||
feedback_filter: Feedback type to filter by
|
||||
Returns: List of filter conditions
|
||||
"""
|
||||
conditions = []
|
||||
|
||||
if start_time is not None:
|
||||
conditions.append(ChatSession.time_created >= start_time)
|
||||
if end_time is not None:
|
||||
conditions.append(ChatSession.time_created <= end_time)
|
||||
|
||||
if feedback_filter is not None:
|
||||
feedback_subq = (
|
||||
select(ChatMessage.chat_session_id)
|
||||
.join(ChatMessageFeedback)
|
||||
.group_by(ChatMessage.chat_session_id)
|
||||
.having(
|
||||
case(
|
||||
(
|
||||
case(
|
||||
{literal(feedback_filter == QAFeedbackType.LIKE): True},
|
||||
else_=False,
|
||||
),
|
||||
func.bool_and(ChatMessageFeedback.is_positive),
|
||||
),
|
||||
(
|
||||
case(
|
||||
{literal(feedback_filter == QAFeedbackType.DISLIKE): True},
|
||||
else_=False,
|
||||
),
|
||||
func.bool_and(func.not_(ChatMessageFeedback.is_positive)),
|
||||
),
|
||||
else_=func.bool_or(ChatMessageFeedback.is_positive)
|
||||
& func.bool_or(func.not_(ChatMessageFeedback.is_positive)),
|
||||
)
|
||||
)
|
||||
)
|
||||
conditions.append(ChatSession.id.in_(feedback_subq))
|
||||
|
||||
return conditions
|
||||
|
||||
|
||||
def get_total_filtered_chat_sessions_count(
|
||||
db_session: Session,
|
||||
start_time: datetime | None,
|
||||
end_time: datetime | None,
|
||||
feedback_filter: QAFeedbackType | None,
|
||||
) -> int:
|
||||
conditions = _build_filter_conditions(start_time, end_time, feedback_filter)
|
||||
stmt = (
|
||||
select(func.count(distinct(ChatSession.id)))
|
||||
.select_from(ChatSession)
|
||||
.filter(*conditions)
|
||||
)
|
||||
return db_session.scalar(stmt) or 0
|
||||
|
||||
|
||||
def get_page_of_chat_sessions(
|
||||
start_time: datetime | None,
|
||||
end_time: datetime | None,
|
||||
db_session: Session,
|
||||
page_num: int,
|
||||
page_size: int,
|
||||
feedback_filter: QAFeedbackType | None = None,
|
||||
) -> Sequence[ChatSession]:
|
||||
conditions = _build_filter_conditions(start_time, end_time, feedback_filter)
|
||||
|
||||
subquery = (
|
||||
select(ChatSession.id, ChatSession.time_created)
|
||||
.filter(*conditions)
|
||||
.order_by(ChatSession.id, desc(ChatSession.time_created))
|
||||
.distinct(ChatSession.id)
|
||||
.limit(page_size)
|
||||
.offset(page_num * page_size)
|
||||
.subquery()
|
||||
)
|
||||
|
||||
stmt = (
|
||||
select(ChatSession)
|
||||
.join(subquery, ChatSession.id == subquery.c.id)
|
||||
.outerjoin(ChatMessage, ChatSession.id == ChatMessage.chat_session_id)
|
||||
.options(
|
||||
joinedload(ChatSession.user),
|
||||
joinedload(ChatSession.persona),
|
||||
contains_eager(ChatSession.messages).joinedload(
|
||||
ChatMessage.chat_message_feedbacks
|
||||
),
|
||||
)
|
||||
.order_by(desc(ChatSession.time_created), asc(ChatMessage.id))
|
||||
)
|
||||
|
||||
return db_session.scalars(stmt).unique().all()
|
||||
|
||||
|
||||
def fetch_chat_sessions_eagerly_by_time(
|
||||
start: datetime.datetime,
|
||||
end: datetime.datetime,
|
||||
start: datetime,
|
||||
end: datetime,
|
||||
db_session: Session,
|
||||
limit: int | None = 500,
|
||||
initial_time: datetime.datetime | None = None,
|
||||
initial_time: datetime | None = None,
|
||||
) -> list[ChatSession]:
|
||||
time_order: UnaryExpression = desc(ChatSession.time_created)
|
||||
message_order: UnaryExpression = asc(ChatMessage.id)
|
||||
|
||||
@@ -1,19 +1,23 @@
|
||||
import csv
|
||||
import io
|
||||
from datetime import datetime
|
||||
from datetime import timedelta
|
||||
from datetime import timezone
|
||||
from typing import Literal
|
||||
from uuid import UUID
|
||||
|
||||
from fastapi import APIRouter
|
||||
from fastapi import Depends
|
||||
from fastapi import HTTPException
|
||||
from fastapi import Query
|
||||
from fastapi.responses import StreamingResponse
|
||||
from pydantic import BaseModel
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from ee.onyx.db.query_history import fetch_chat_sessions_eagerly_by_time
|
||||
from ee.onyx.db.query_history import get_page_of_chat_sessions
|
||||
from ee.onyx.db.query_history import get_total_filtered_chat_sessions_count
|
||||
from ee.onyx.server.query_history.models import ChatSessionMinimal
|
||||
from ee.onyx.server.query_history.models import ChatSessionSnapshot
|
||||
from ee.onyx.server.query_history.models import MessageSnapshot
|
||||
from ee.onyx.server.query_history.models import QuestionAnswerPairSnapshot
|
||||
from onyx.auth.users import current_admin_user
|
||||
from onyx.auth.users import get_display_email
|
||||
from onyx.chat.chat_utils import create_chat_chain
|
||||
@@ -23,257 +27,15 @@ from onyx.configs.constants import SessionType
|
||||
from onyx.db.chat import get_chat_session_by_id
|
||||
from onyx.db.chat import get_chat_sessions_by_user
|
||||
from onyx.db.engine import get_session
|
||||
from onyx.db.models import ChatMessage
|
||||
from onyx.db.models import ChatSession
|
||||
from onyx.db.models import User
|
||||
from onyx.server.documents.models import PaginatedReturn
|
||||
from onyx.server.query_and_chat.models import ChatSessionDetails
|
||||
from onyx.server.query_and_chat.models import ChatSessionsResponse
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
class AbridgedSearchDoc(BaseModel):
|
||||
"""A subset of the info present in `SearchDoc`"""
|
||||
|
||||
document_id: str
|
||||
semantic_identifier: str
|
||||
link: str | None
|
||||
|
||||
|
||||
class MessageSnapshot(BaseModel):
|
||||
message: str
|
||||
message_type: MessageType
|
||||
documents: list[AbridgedSearchDoc]
|
||||
feedback_type: QAFeedbackType | None
|
||||
feedback_text: str | None
|
||||
time_created: datetime
|
||||
|
||||
@classmethod
|
||||
def build(cls, message: ChatMessage) -> "MessageSnapshot":
|
||||
latest_messages_feedback_obj = (
|
||||
message.chat_message_feedbacks[-1]
|
||||
if len(message.chat_message_feedbacks) > 0
|
||||
else None
|
||||
)
|
||||
feedback_type = (
|
||||
(
|
||||
QAFeedbackType.LIKE
|
||||
if latest_messages_feedback_obj.is_positive
|
||||
else QAFeedbackType.DISLIKE
|
||||
)
|
||||
if latest_messages_feedback_obj
|
||||
else None
|
||||
)
|
||||
feedback_text = (
|
||||
latest_messages_feedback_obj.feedback_text
|
||||
if latest_messages_feedback_obj
|
||||
else None
|
||||
)
|
||||
return cls(
|
||||
message=message.message,
|
||||
message_type=message.message_type,
|
||||
documents=[
|
||||
AbridgedSearchDoc(
|
||||
document_id=document.document_id,
|
||||
semantic_identifier=document.semantic_id,
|
||||
link=document.link,
|
||||
)
|
||||
for document in message.search_docs
|
||||
],
|
||||
feedback_type=feedback_type,
|
||||
feedback_text=feedback_text,
|
||||
time_created=message.time_sent,
|
||||
)
|
||||
|
||||
|
||||
class ChatSessionMinimal(BaseModel):
|
||||
id: UUID
|
||||
user_email: str
|
||||
name: str | None
|
||||
first_user_message: str
|
||||
first_ai_message: str
|
||||
assistant_id: int | None
|
||||
assistant_name: str | None
|
||||
time_created: datetime
|
||||
feedback_type: QAFeedbackType | Literal["mixed"] | None
|
||||
flow_type: SessionType
|
||||
conversation_length: int
|
||||
|
||||
|
||||
class ChatSessionSnapshot(BaseModel):
|
||||
id: UUID
|
||||
user_email: str
|
||||
name: str | None
|
||||
messages: list[MessageSnapshot]
|
||||
assistant_id: int | None
|
||||
assistant_name: str | None
|
||||
time_created: datetime
|
||||
flow_type: SessionType
|
||||
|
||||
|
||||
class QuestionAnswerPairSnapshot(BaseModel):
|
||||
chat_session_id: UUID
|
||||
# 1-indexed message number in the chat_session
|
||||
# e.g. the first message pair in the chat_session is 1, the second is 2, etc.
|
||||
message_pair_num: int
|
||||
user_message: str
|
||||
ai_response: str
|
||||
retrieved_documents: list[AbridgedSearchDoc]
|
||||
feedback_type: QAFeedbackType | None
|
||||
feedback_text: str | None
|
||||
persona_name: str | None
|
||||
user_email: str
|
||||
time_created: datetime
|
||||
flow_type: SessionType
|
||||
|
||||
@classmethod
|
||||
def from_chat_session_snapshot(
|
||||
cls,
|
||||
chat_session_snapshot: ChatSessionSnapshot,
|
||||
) -> list["QuestionAnswerPairSnapshot"]:
|
||||
message_pairs: list[tuple[MessageSnapshot, MessageSnapshot]] = []
|
||||
for ind in range(1, len(chat_session_snapshot.messages), 2):
|
||||
message_pairs.append(
|
||||
(
|
||||
chat_session_snapshot.messages[ind - 1],
|
||||
chat_session_snapshot.messages[ind],
|
||||
)
|
||||
)
|
||||
|
||||
return [
|
||||
cls(
|
||||
chat_session_id=chat_session_snapshot.id,
|
||||
message_pair_num=ind + 1,
|
||||
user_message=user_message.message,
|
||||
ai_response=ai_message.message,
|
||||
retrieved_documents=ai_message.documents,
|
||||
feedback_type=ai_message.feedback_type,
|
||||
feedback_text=ai_message.feedback_text,
|
||||
persona_name=chat_session_snapshot.assistant_name,
|
||||
user_email=get_display_email(chat_session_snapshot.user_email),
|
||||
time_created=user_message.time_created,
|
||||
flow_type=chat_session_snapshot.flow_type,
|
||||
)
|
||||
for ind, (user_message, ai_message) in enumerate(message_pairs)
|
||||
]
|
||||
|
||||
def to_json(self) -> dict[str, str | None]:
|
||||
return {
|
||||
"chat_session_id": str(self.chat_session_id),
|
||||
"message_pair_num": str(self.message_pair_num),
|
||||
"user_message": self.user_message,
|
||||
"ai_response": self.ai_response,
|
||||
"retrieved_documents": "|".join(
|
||||
[
|
||||
doc.link or doc.semantic_identifier
|
||||
for doc in self.retrieved_documents
|
||||
]
|
||||
),
|
||||
"feedback_type": self.feedback_type.value if self.feedback_type else "",
|
||||
"feedback_text": self.feedback_text or "",
|
||||
"persona_name": self.persona_name,
|
||||
"user_email": self.user_email,
|
||||
"time_created": str(self.time_created),
|
||||
"flow_type": self.flow_type,
|
||||
}
|
||||
|
||||
|
||||
def determine_flow_type(chat_session: ChatSession) -> SessionType:
|
||||
return SessionType.SLACK if chat_session.onyxbot_flow else SessionType.CHAT
|
||||
|
||||
|
||||
def fetch_and_process_chat_session_history_minimal(
|
||||
db_session: Session,
|
||||
start: datetime,
|
||||
end: datetime,
|
||||
feedback_filter: QAFeedbackType | None = None,
|
||||
limit: int | None = 500,
|
||||
) -> list[ChatSessionMinimal]:
|
||||
chat_sessions = fetch_chat_sessions_eagerly_by_time(
|
||||
start=start, end=end, db_session=db_session, limit=limit
|
||||
)
|
||||
|
||||
minimal_sessions = []
|
||||
for chat_session in chat_sessions:
|
||||
if not chat_session.messages:
|
||||
continue
|
||||
|
||||
first_user_message = next(
|
||||
(
|
||||
message.message
|
||||
for message in chat_session.messages
|
||||
if message.message_type == MessageType.USER
|
||||
),
|
||||
"",
|
||||
)
|
||||
first_ai_message = next(
|
||||
(
|
||||
message.message
|
||||
for message in chat_session.messages
|
||||
if message.message_type == MessageType.ASSISTANT
|
||||
),
|
||||
"",
|
||||
)
|
||||
|
||||
has_positive_feedback = any(
|
||||
feedback.is_positive
|
||||
for message in chat_session.messages
|
||||
for feedback in message.chat_message_feedbacks
|
||||
)
|
||||
|
||||
has_negative_feedback = any(
|
||||
not feedback.is_positive
|
||||
for message in chat_session.messages
|
||||
for feedback in message.chat_message_feedbacks
|
||||
)
|
||||
|
||||
feedback_type: QAFeedbackType | Literal["mixed"] | None = (
|
||||
"mixed"
|
||||
if has_positive_feedback and has_negative_feedback
|
||||
else QAFeedbackType.LIKE
|
||||
if has_positive_feedback
|
||||
else QAFeedbackType.DISLIKE
|
||||
if has_negative_feedback
|
||||
else None
|
||||
)
|
||||
|
||||
if feedback_filter:
|
||||
if feedback_filter == QAFeedbackType.LIKE and not has_positive_feedback:
|
||||
continue
|
||||
if feedback_filter == QAFeedbackType.DISLIKE and not has_negative_feedback:
|
||||
continue
|
||||
|
||||
flow_type = determine_flow_type(chat_session)
|
||||
|
||||
minimal_sessions.append(
|
||||
ChatSessionMinimal(
|
||||
id=chat_session.id,
|
||||
user_email=get_display_email(
|
||||
chat_session.user.email if chat_session.user else None
|
||||
),
|
||||
name=chat_session.description,
|
||||
first_user_message=first_user_message,
|
||||
first_ai_message=first_ai_message,
|
||||
assistant_id=chat_session.persona_id,
|
||||
assistant_name=(
|
||||
chat_session.persona.name if chat_session.persona else None
|
||||
),
|
||||
time_created=chat_session.time_created,
|
||||
feedback_type=feedback_type,
|
||||
flow_type=flow_type,
|
||||
conversation_length=len(
|
||||
[
|
||||
m
|
||||
for m in chat_session.messages
|
||||
if m.message_type != MessageType.SYSTEM
|
||||
]
|
||||
),
|
||||
)
|
||||
)
|
||||
|
||||
return minimal_sessions
|
||||
|
||||
|
||||
def fetch_and_process_chat_session_history(
|
||||
db_session: Session,
|
||||
start: datetime,
|
||||
@@ -319,7 +81,7 @@ def snapshot_from_chat_session(
|
||||
except RuntimeError:
|
||||
return None
|
||||
|
||||
flow_type = determine_flow_type(chat_session)
|
||||
flow_type = SessionType.SLACK if chat_session.onyxbot_flow else SessionType.CHAT
|
||||
|
||||
return ChatSessionSnapshot(
|
||||
id=chat_session.id,
|
||||
@@ -371,22 +133,38 @@ def get_user_chat_sessions(
|
||||
|
||||
@router.get("/admin/chat-session-history")
|
||||
def get_chat_session_history(
|
||||
page_num: int = Query(0, ge=0),
|
||||
page_size: int = Query(10, ge=10),
|
||||
feedback_type: QAFeedbackType | None = None,
|
||||
start: datetime | None = None,
|
||||
end: datetime | None = None,
|
||||
start_time: datetime | None = None,
|
||||
end_time: datetime | None = None,
|
||||
_: User | None = Depends(current_admin_user),
|
||||
db_session: Session = Depends(get_session),
|
||||
) -> list[ChatSessionMinimal]:
|
||||
return fetch_and_process_chat_session_history_minimal(
|
||||
) -> PaginatedReturn[ChatSessionMinimal]:
|
||||
page_of_chat_sessions = get_page_of_chat_sessions(
|
||||
page_num=page_num,
|
||||
page_size=page_size,
|
||||
db_session=db_session,
|
||||
start=start
|
||||
or (
|
||||
datetime.now(tz=timezone.utc) - timedelta(days=30)
|
||||
), # default is 30d lookback
|
||||
end=end or datetime.now(tz=timezone.utc),
|
||||
start_time=start_time,
|
||||
end_time=end_time,
|
||||
feedback_filter=feedback_type,
|
||||
)
|
||||
|
||||
total_filtered_chat_sessions_count = get_total_filtered_chat_sessions_count(
|
||||
db_session=db_session,
|
||||
start_time=start_time,
|
||||
end_time=end_time,
|
||||
feedback_filter=feedback_type,
|
||||
)
|
||||
|
||||
return PaginatedReturn(
|
||||
items=[
|
||||
ChatSessionMinimal.from_chat_session(chat_session)
|
||||
for chat_session in page_of_chat_sessions
|
||||
],
|
||||
total_items=total_filtered_chat_sessions_count,
|
||||
)
|
||||
|
||||
|
||||
@router.get("/admin/chat-session-history/{chat_session_id}")
|
||||
def get_chat_session_admin(
|
||||
|
||||
218
backend/ee/onyx/server/query_history/models.py
Normal file
218
backend/ee/onyx/server/query_history/models.py
Normal file
@@ -0,0 +1,218 @@
|
||||
from datetime import datetime
|
||||
from uuid import UUID
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from onyx.auth.users import get_display_email
|
||||
from onyx.configs.constants import MessageType
|
||||
from onyx.configs.constants import QAFeedbackType
|
||||
from onyx.configs.constants import SessionType
|
||||
from onyx.db.models import ChatMessage
|
||||
from onyx.db.models import ChatSession
|
||||
|
||||
|
||||
class AbridgedSearchDoc(BaseModel):
|
||||
"""A subset of the info present in `SearchDoc`"""
|
||||
|
||||
document_id: str
|
||||
semantic_identifier: str
|
||||
link: str | None
|
||||
|
||||
|
||||
class MessageSnapshot(BaseModel):
|
||||
id: int
|
||||
message: str
|
||||
message_type: MessageType
|
||||
documents: list[AbridgedSearchDoc]
|
||||
feedback_type: QAFeedbackType | None
|
||||
feedback_text: str | None
|
||||
time_created: datetime
|
||||
|
||||
@classmethod
|
||||
def build(cls, message: ChatMessage) -> "MessageSnapshot":
|
||||
latest_messages_feedback_obj = (
|
||||
message.chat_message_feedbacks[-1]
|
||||
if len(message.chat_message_feedbacks) > 0
|
||||
else None
|
||||
)
|
||||
feedback_type = (
|
||||
(
|
||||
QAFeedbackType.LIKE
|
||||
if latest_messages_feedback_obj.is_positive
|
||||
else QAFeedbackType.DISLIKE
|
||||
)
|
||||
if latest_messages_feedback_obj
|
||||
else None
|
||||
)
|
||||
feedback_text = (
|
||||
latest_messages_feedback_obj.feedback_text
|
||||
if latest_messages_feedback_obj
|
||||
else None
|
||||
)
|
||||
return cls(
|
||||
id=message.id,
|
||||
message=message.message,
|
||||
message_type=message.message_type,
|
||||
documents=[
|
||||
AbridgedSearchDoc(
|
||||
document_id=document.document_id,
|
||||
semantic_identifier=document.semantic_id,
|
||||
link=document.link,
|
||||
)
|
||||
for document in message.search_docs
|
||||
],
|
||||
feedback_type=feedback_type,
|
||||
feedback_text=feedback_text,
|
||||
time_created=message.time_sent,
|
||||
)
|
||||
|
||||
|
||||
class ChatSessionMinimal(BaseModel):
|
||||
id: UUID
|
||||
user_email: str
|
||||
name: str | None
|
||||
first_user_message: str
|
||||
first_ai_message: str
|
||||
assistant_id: int | None
|
||||
assistant_name: str | None
|
||||
time_created: datetime
|
||||
feedback_type: QAFeedbackType | None
|
||||
flow_type: SessionType
|
||||
conversation_length: int
|
||||
|
||||
@classmethod
|
||||
def from_chat_session(cls, chat_session: ChatSession) -> "ChatSessionMinimal":
|
||||
first_user_message = next(
|
||||
(
|
||||
message.message
|
||||
for message in chat_session.messages
|
||||
if message.message_type == MessageType.USER
|
||||
),
|
||||
"",
|
||||
)
|
||||
first_ai_message = next(
|
||||
(
|
||||
message.message
|
||||
for message in chat_session.messages
|
||||
if message.message_type == MessageType.ASSISTANT
|
||||
),
|
||||
"",
|
||||
)
|
||||
|
||||
list_of_message_feedbacks = [
|
||||
feedback.is_positive
|
||||
for message in chat_session.messages
|
||||
for feedback in message.chat_message_feedbacks
|
||||
]
|
||||
session_feedback_type = None
|
||||
if list_of_message_feedbacks:
|
||||
if all(list_of_message_feedbacks):
|
||||
session_feedback_type = QAFeedbackType.LIKE
|
||||
elif not any(list_of_message_feedbacks):
|
||||
session_feedback_type = QAFeedbackType.DISLIKE
|
||||
else:
|
||||
session_feedback_type = QAFeedbackType.MIXED
|
||||
|
||||
return cls(
|
||||
id=chat_session.id,
|
||||
user_email=get_display_email(
|
||||
chat_session.user.email if chat_session.user else None
|
||||
),
|
||||
name=chat_session.description,
|
||||
first_user_message=first_user_message,
|
||||
first_ai_message=first_ai_message,
|
||||
assistant_id=chat_session.persona_id,
|
||||
assistant_name=(
|
||||
chat_session.persona.name if chat_session.persona else None
|
||||
),
|
||||
time_created=chat_session.time_created,
|
||||
feedback_type=session_feedback_type,
|
||||
flow_type=SessionType.SLACK
|
||||
if chat_session.onyxbot_flow
|
||||
else SessionType.CHAT,
|
||||
conversation_length=len(
|
||||
[
|
||||
message
|
||||
for message in chat_session.messages
|
||||
if message.message_type != MessageType.SYSTEM
|
||||
]
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
class ChatSessionSnapshot(BaseModel):
|
||||
id: UUID
|
||||
user_email: str
|
||||
name: str | None
|
||||
messages: list[MessageSnapshot]
|
||||
assistant_id: int | None
|
||||
assistant_name: str | None
|
||||
time_created: datetime
|
||||
flow_type: SessionType
|
||||
|
||||
|
||||
class QuestionAnswerPairSnapshot(BaseModel):
|
||||
chat_session_id: UUID
|
||||
# 1-indexed message number in the chat_session
|
||||
# e.g. the first message pair in the chat_session is 1, the second is 2, etc.
|
||||
message_pair_num: int
|
||||
user_message: str
|
||||
ai_response: str
|
||||
retrieved_documents: list[AbridgedSearchDoc]
|
||||
feedback_type: QAFeedbackType | None
|
||||
feedback_text: str | None
|
||||
persona_name: str | None
|
||||
user_email: str
|
||||
time_created: datetime
|
||||
flow_type: SessionType
|
||||
|
||||
@classmethod
|
||||
def from_chat_session_snapshot(
|
||||
cls,
|
||||
chat_session_snapshot: ChatSessionSnapshot,
|
||||
) -> list["QuestionAnswerPairSnapshot"]:
|
||||
message_pairs: list[tuple[MessageSnapshot, MessageSnapshot]] = []
|
||||
for ind in range(1, len(chat_session_snapshot.messages), 2):
|
||||
message_pairs.append(
|
||||
(
|
||||
chat_session_snapshot.messages[ind - 1],
|
||||
chat_session_snapshot.messages[ind],
|
||||
)
|
||||
)
|
||||
|
||||
return [
|
||||
cls(
|
||||
chat_session_id=chat_session_snapshot.id,
|
||||
message_pair_num=ind + 1,
|
||||
user_message=user_message.message,
|
||||
ai_response=ai_message.message,
|
||||
retrieved_documents=ai_message.documents,
|
||||
feedback_type=ai_message.feedback_type,
|
||||
feedback_text=ai_message.feedback_text,
|
||||
persona_name=chat_session_snapshot.assistant_name,
|
||||
user_email=get_display_email(chat_session_snapshot.user_email),
|
||||
time_created=user_message.time_created,
|
||||
flow_type=chat_session_snapshot.flow_type,
|
||||
)
|
||||
for ind, (user_message, ai_message) in enumerate(message_pairs)
|
||||
]
|
||||
|
||||
def to_json(self) -> dict[str, str | None]:
|
||||
return {
|
||||
"chat_session_id": str(self.chat_session_id),
|
||||
"message_pair_num": str(self.message_pair_num),
|
||||
"user_message": self.user_message,
|
||||
"ai_response": self.ai_response,
|
||||
"retrieved_documents": "|".join(
|
||||
[
|
||||
doc.link or doc.semantic_identifier
|
||||
for doc in self.retrieved_documents
|
||||
]
|
||||
),
|
||||
"feedback_type": self.feedback_type.value if self.feedback_type else "",
|
||||
"feedback_text": self.feedback_text or "",
|
||||
"persona_name": self.persona_name,
|
||||
"user_email": self.user_email,
|
||||
"time_created": str(self.time_created),
|
||||
"flow_type": self.flow_type,
|
||||
}
|
||||
Reference in New Issue
Block a user