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chore: apply ruff E501 line-too-long linter rule (#8275)
Co-authored-by: -LAN- <laipz8200@outlook.com>
This commit is contained in:
Bowen Liang
GitHub
parent
56c90e212a
commit
c69f5b07ba
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@ -411,7 +411,8 @@ def migrate_knowledge_vector_database():
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try:
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click.echo(
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click.style(
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f"Start to created vector index with {len(documents)} documents of {segments_count} segments for dataset {dataset.id}.",
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f"Start to created vector index with {len(documents)} documents of {segments_count}"
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f" segments for dataset {dataset.id}.",
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fg="green",
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)
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)
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@ -29,10 +29,13 @@ class DailyMessageStatistic(Resource):
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parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
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args = parser.parse_args()
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sql_query = """
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SELECT date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date, count(*) AS message_count
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FROM messages where app_id = :app_id
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"""
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sql_query = """SELECT
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DATE(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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COUNT(*) AS message_count
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FROM
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messages
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WHERE
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app_id = :app_id"""
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arg_dict = {"tz": account.timezone, "app_id": app_model.id}
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timezone = pytz.timezone(account.timezone)
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@ -45,7 +48,7 @@ class DailyMessageStatistic(Resource):
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start_datetime_timezone = timezone.localize(start_datetime)
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start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at >= :start"
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sql_query += " AND created_at >= :start"
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arg_dict["start"] = start_datetime_utc
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if args["end"]:
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@ -55,10 +58,10 @@ class DailyMessageStatistic(Resource):
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end_datetime_timezone = timezone.localize(end_datetime)
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end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at < :end"
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sql_query += " AND created_at < :end"
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arg_dict["end"] = end_datetime_utc
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sql_query += " GROUP BY date order by date"
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sql_query += " GROUP BY date ORDER BY date"
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response_data = []
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@ -83,10 +86,13 @@ class DailyConversationStatistic(Resource):
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parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
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args = parser.parse_args()
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sql_query = """
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SELECT date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date, count(distinct messages.conversation_id) AS conversation_count
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FROM messages where app_id = :app_id
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"""
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sql_query = """SELECT
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DATE(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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COUNT(DISTINCT messages.conversation_id) AS conversation_count
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FROM
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messages
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WHERE
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app_id = :app_id"""
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arg_dict = {"tz": account.timezone, "app_id": app_model.id}
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timezone = pytz.timezone(account.timezone)
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@ -99,7 +105,7 @@ class DailyConversationStatistic(Resource):
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start_datetime_timezone = timezone.localize(start_datetime)
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start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at >= :start"
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sql_query += " AND created_at >= :start"
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arg_dict["start"] = start_datetime_utc
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if args["end"]:
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@ -109,10 +115,10 @@ class DailyConversationStatistic(Resource):
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end_datetime_timezone = timezone.localize(end_datetime)
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end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at < :end"
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sql_query += " AND created_at < :end"
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arg_dict["end"] = end_datetime_utc
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sql_query += " GROUP BY date order by date"
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sql_query += " GROUP BY date ORDER BY date"
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response_data = []
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@ -137,10 +143,13 @@ class DailyTerminalsStatistic(Resource):
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parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
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args = parser.parse_args()
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sql_query = """
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SELECT date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date, count(distinct messages.from_end_user_id) AS terminal_count
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FROM messages where app_id = :app_id
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"""
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sql_query = """SELECT
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DATE(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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COUNT(DISTINCT messages.from_end_user_id) AS terminal_count
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FROM
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messages
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WHERE
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app_id = :app_id"""
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arg_dict = {"tz": account.timezone, "app_id": app_model.id}
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timezone = pytz.timezone(account.timezone)
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@ -153,7 +162,7 @@ class DailyTerminalsStatistic(Resource):
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start_datetime_timezone = timezone.localize(start_datetime)
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start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at >= :start"
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sql_query += " AND created_at >= :start"
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arg_dict["start"] = start_datetime_utc
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if args["end"]:
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@ -163,10 +172,10 @@ class DailyTerminalsStatistic(Resource):
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end_datetime_timezone = timezone.localize(end_datetime)
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end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at < :end"
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sql_query += " AND created_at < :end"
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arg_dict["end"] = end_datetime_utc
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sql_query += " GROUP BY date order by date"
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sql_query += " GROUP BY date ORDER BY date"
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response_data = []
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@ -191,12 +200,14 @@ class DailyTokenCostStatistic(Resource):
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parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
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args = parser.parse_args()
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sql_query = """
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SELECT date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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(sum(messages.message_tokens) + sum(messages.answer_tokens)) as token_count,
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sum(total_price) as total_price
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FROM messages where app_id = :app_id
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"""
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sql_query = """SELECT
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DATE(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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(SUM(messages.message_tokens) + SUM(messages.answer_tokens)) AS token_count,
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SUM(total_price) AS total_price
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FROM
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messages
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WHERE
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app_id = :app_id"""
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arg_dict = {"tz": account.timezone, "app_id": app_model.id}
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timezone = pytz.timezone(account.timezone)
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@ -209,7 +220,7 @@ class DailyTokenCostStatistic(Resource):
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start_datetime_timezone = timezone.localize(start_datetime)
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start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at >= :start"
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sql_query += " AND created_at >= :start"
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arg_dict["start"] = start_datetime_utc
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if args["end"]:
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@ -219,10 +230,10 @@ class DailyTokenCostStatistic(Resource):
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end_datetime_timezone = timezone.localize(end_datetime)
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end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at < :end"
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sql_query += " AND created_at < :end"
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arg_dict["end"] = end_datetime_utc
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sql_query += " GROUP BY date order by date"
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sql_query += " GROUP BY date ORDER BY date"
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response_data = []
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@ -249,12 +260,22 @@ class AverageSessionInteractionStatistic(Resource):
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parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
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args = parser.parse_args()
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sql_query = """SELECT date(DATE_TRUNC('day', c.created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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AVG(subquery.message_count) AS interactions
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FROM (SELECT m.conversation_id, COUNT(m.id) AS message_count
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FROM conversations c
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JOIN messages m ON c.id = m.conversation_id
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WHERE c.override_model_configs IS NULL AND c.app_id = :app_id"""
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sql_query = """SELECT
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DATE(DATE_TRUNC('day', c.created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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AVG(subquery.message_count) AS interactions
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FROM
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(
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SELECT
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m.conversation_id,
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COUNT(m.id) AS message_count
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FROM
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conversations c
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JOIN
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messages m
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ON c.id = m.conversation_id
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WHERE
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c.override_model_configs IS NULL
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AND c.app_id = :app_id"""
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arg_dict = {"tz": account.timezone, "app_id": app_model.id}
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timezone = pytz.timezone(account.timezone)
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@ -267,7 +288,7 @@ FROM (SELECT m.conversation_id, COUNT(m.id) AS message_count
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start_datetime_timezone = timezone.localize(start_datetime)
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start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and c.created_at >= :start"
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sql_query += " AND c.created_at >= :start"
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arg_dict["start"] = start_datetime_utc
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if args["end"]:
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@ -277,14 +298,19 @@ FROM (SELECT m.conversation_id, COUNT(m.id) AS message_count
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end_datetime_timezone = timezone.localize(end_datetime)
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end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and c.created_at < :end"
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sql_query += " AND c.created_at < :end"
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arg_dict["end"] = end_datetime_utc
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sql_query += """
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GROUP BY m.conversation_id) subquery
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LEFT JOIN conversations c on c.id=subquery.conversation_id
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GROUP BY date
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ORDER BY date"""
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GROUP BY m.conversation_id
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) subquery
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LEFT JOIN
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conversations c
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ON c.id = subquery.conversation_id
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GROUP BY
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date
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ORDER BY
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date"""
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response_data = []
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@ -311,13 +337,17 @@ class UserSatisfactionRateStatistic(Resource):
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parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
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args = parser.parse_args()
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sql_query = """
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SELECT date(DATE_TRUNC('day', m.created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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COUNT(m.id) as message_count, COUNT(mf.id) as feedback_count
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FROM messages m
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LEFT JOIN message_feedbacks mf on mf.message_id=m.id and mf.rating='like'
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WHERE m.app_id = :app_id
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"""
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sql_query = """SELECT
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DATE(DATE_TRUNC('day', m.created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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COUNT(m.id) AS message_count,
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COUNT(mf.id) AS feedback_count
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FROM
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messages m
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LEFT JOIN
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message_feedbacks mf
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ON mf.message_id=m.id AND mf.rating='like'
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WHERE
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m.app_id = :app_id"""
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arg_dict = {"tz": account.timezone, "app_id": app_model.id}
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timezone = pytz.timezone(account.timezone)
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@ -330,7 +360,7 @@ class UserSatisfactionRateStatistic(Resource):
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start_datetime_timezone = timezone.localize(start_datetime)
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start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and m.created_at >= :start"
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sql_query += " AND m.created_at >= :start"
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arg_dict["start"] = start_datetime_utc
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if args["end"]:
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@ -340,10 +370,10 @@ class UserSatisfactionRateStatistic(Resource):
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end_datetime_timezone = timezone.localize(end_datetime)
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end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and m.created_at < :end"
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sql_query += " AND m.created_at < :end"
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arg_dict["end"] = end_datetime_utc
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sql_query += " GROUP BY date order by date"
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sql_query += " GROUP BY date ORDER BY date"
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response_data = []
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@ -373,12 +403,13 @@ class AverageResponseTimeStatistic(Resource):
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parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
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args = parser.parse_args()
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sql_query = """
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SELECT date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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AVG(provider_response_latency) as latency
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FROM messages
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WHERE app_id = :app_id
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"""
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sql_query = """SELECT
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DATE(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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AVG(provider_response_latency) AS latency
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FROM
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messages
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WHERE
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app_id = :app_id"""
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arg_dict = {"tz": account.timezone, "app_id": app_model.id}
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timezone = pytz.timezone(account.timezone)
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@ -391,7 +422,7 @@ class AverageResponseTimeStatistic(Resource):
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start_datetime_timezone = timezone.localize(start_datetime)
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start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at >= :start"
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sql_query += " AND created_at >= :start"
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arg_dict["start"] = start_datetime_utc
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if args["end"]:
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@ -401,10 +432,10 @@ class AverageResponseTimeStatistic(Resource):
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end_datetime_timezone = timezone.localize(end_datetime)
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end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at < :end"
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sql_query += " AND created_at < :end"
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arg_dict["end"] = end_datetime_utc
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sql_query += " GROUP BY date order by date"
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sql_query += " GROUP BY date ORDER BY date"
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response_data = []
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@ -429,13 +460,16 @@ class TokensPerSecondStatistic(Resource):
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parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
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args = parser.parse_args()
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sql_query = """SELECT date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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CASE
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sql_query = """SELECT
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DATE(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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CASE
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WHEN SUM(provider_response_latency) = 0 THEN 0
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ELSE (SUM(answer_tokens) / SUM(provider_response_latency))
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END as tokens_per_second
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FROM messages
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WHERE app_id = :app_id"""
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FROM
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messages
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WHERE
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app_id = :app_id"""
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arg_dict = {"tz": account.timezone, "app_id": app_model.id}
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timezone = pytz.timezone(account.timezone)
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@ -448,7 +482,7 @@ WHERE app_id = :app_id"""
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start_datetime_timezone = timezone.localize(start_datetime)
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start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at >= :start"
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sql_query += " AND created_at >= :start"
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arg_dict["start"] = start_datetime_utc
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if args["end"]:
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@ -458,10 +492,10 @@ WHERE app_id = :app_id"""
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end_datetime_timezone = timezone.localize(end_datetime)
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end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at < :end"
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sql_query += " AND created_at < :end"
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arg_dict["end"] = end_datetime_utc
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sql_query += " GROUP BY date order by date"
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sql_query += " GROUP BY date ORDER BY date"
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response_data = []
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@ -30,12 +30,14 @@ class WorkflowDailyRunsStatistic(Resource):
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parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
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args = parser.parse_args()
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sql_query = """
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SELECT date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date, count(id) AS runs
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FROM workflow_runs
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WHERE app_id = :app_id
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AND triggered_from = :triggered_from
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"""
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sql_query = """SELECT
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DATE(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
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COUNT(id) AS runs
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FROM
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workflow_runs
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WHERE
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app_id = :app_id
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AND triggered_from = :triggered_from"""
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arg_dict = {
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"tz": account.timezone,
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"app_id": app_model.id,
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@ -52,7 +54,7 @@ class WorkflowDailyRunsStatistic(Resource):
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start_datetime_timezone = timezone.localize(start_datetime)
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start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
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sql_query += " and created_at >= :start"
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sql_query += " AND created_at >= :start"
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arg_dict["start"] = start_datetime_utc
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if args["end"]:
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@ -62,10 +64,10 @@ class WorkflowDailyRunsStatistic(Resource):
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end_datetime_timezone = timezone.localize(end_datetime)
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end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
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|
||||
sql_query += " and created_at < :end"
|
||||
sql_query += " AND created_at < :end"
|
||||
arg_dict["end"] = end_datetime_utc
|
||||
|
||||
sql_query += " GROUP BY date order by date"
|
||||
sql_query += " GROUP BY date ORDER BY date"
|
||||
|
||||
response_data = []
|
||||
|
||||
|
|
@ -90,12 +92,14 @@ class WorkflowDailyTerminalsStatistic(Resource):
|
|||
parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
|
||||
args = parser.parse_args()
|
||||
|
||||
sql_query = """
|
||||
SELECT date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date, count(distinct workflow_runs.created_by) AS terminal_count
|
||||
FROM workflow_runs
|
||||
WHERE app_id = :app_id
|
||||
AND triggered_from = :triggered_from
|
||||
"""
|
||||
sql_query = """SELECT
|
||||
DATE(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
|
||||
COUNT(DISTINCT workflow_runs.created_by) AS terminal_count
|
||||
FROM
|
||||
workflow_runs
|
||||
WHERE
|
||||
app_id = :app_id
|
||||
AND triggered_from = :triggered_from"""
|
||||
arg_dict = {
|
||||
"tz": account.timezone,
|
||||
"app_id": app_model.id,
|
||||
|
|
@ -112,7 +116,7 @@ class WorkflowDailyTerminalsStatistic(Resource):
|
|||
start_datetime_timezone = timezone.localize(start_datetime)
|
||||
start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
|
||||
|
||||
sql_query += " and created_at >= :start"
|
||||
sql_query += " AND created_at >= :start"
|
||||
arg_dict["start"] = start_datetime_utc
|
||||
|
||||
if args["end"]:
|
||||
|
|
@ -122,10 +126,10 @@ class WorkflowDailyTerminalsStatistic(Resource):
|
|||
end_datetime_timezone = timezone.localize(end_datetime)
|
||||
end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
|
||||
|
||||
sql_query += " and created_at < :end"
|
||||
sql_query += " AND created_at < :end"
|
||||
arg_dict["end"] = end_datetime_utc
|
||||
|
||||
sql_query += " GROUP BY date order by date"
|
||||
sql_query += " GROUP BY date ORDER BY date"
|
||||
|
||||
response_data = []
|
||||
|
||||
|
|
@ -150,14 +154,14 @@ class WorkflowDailyTokenCostStatistic(Resource):
|
|||
parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
|
||||
args = parser.parse_args()
|
||||
|
||||
sql_query = """
|
||||
SELECT
|
||||
date(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
|
||||
SUM(workflow_runs.total_tokens) as token_count
|
||||
FROM workflow_runs
|
||||
WHERE app_id = :app_id
|
||||
AND triggered_from = :triggered_from
|
||||
"""
|
||||
sql_query = """SELECT
|
||||
DATE(DATE_TRUNC('day', created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
|
||||
SUM(workflow_runs.total_tokens) AS token_count
|
||||
FROM
|
||||
workflow_runs
|
||||
WHERE
|
||||
app_id = :app_id
|
||||
AND triggered_from = :triggered_from"""
|
||||
arg_dict = {
|
||||
"tz": account.timezone,
|
||||
"app_id": app_model.id,
|
||||
|
|
@ -174,7 +178,7 @@ class WorkflowDailyTokenCostStatistic(Resource):
|
|||
start_datetime_timezone = timezone.localize(start_datetime)
|
||||
start_datetime_utc = start_datetime_timezone.astimezone(utc_timezone)
|
||||
|
||||
sql_query += " and created_at >= :start"
|
||||
sql_query += " AND created_at >= :start"
|
||||
arg_dict["start"] = start_datetime_utc
|
||||
|
||||
if args["end"]:
|
||||
|
|
@ -184,10 +188,10 @@ class WorkflowDailyTokenCostStatistic(Resource):
|
|||
end_datetime_timezone = timezone.localize(end_datetime)
|
||||
end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
|
||||
|
||||
sql_query += " and created_at < :end"
|
||||
sql_query += " AND created_at < :end"
|
||||
arg_dict["end"] = end_datetime_utc
|
||||
|
||||
sql_query += " GROUP BY date order by date"
|
||||
sql_query += " GROUP BY date ORDER BY date"
|
||||
|
||||
response_data = []
|
||||
|
||||
|
|
@ -217,23 +221,27 @@ class WorkflowAverageAppInteractionStatistic(Resource):
|
|||
parser.add_argument("end", type=DatetimeString("%Y-%m-%d %H:%M"), location="args")
|
||||
args = parser.parse_args()
|
||||
|
||||
sql_query = """
|
||||
SELECT
|
||||
AVG(sub.interactions) as interactions,
|
||||
sub.date
|
||||
FROM
|
||||
(SELECT
|
||||
date(DATE_TRUNC('day', c.created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
|
||||
c.created_by,
|
||||
COUNT(c.id) AS interactions
|
||||
FROM workflow_runs c
|
||||
WHERE c.app_id = :app_id
|
||||
AND c.triggered_from = :triggered_from
|
||||
{{start}}
|
||||
{{end}}
|
||||
GROUP BY date, c.created_by) sub
|
||||
GROUP BY sub.date
|
||||
"""
|
||||
sql_query = """SELECT
|
||||
AVG(sub.interactions) AS interactions,
|
||||
sub.date
|
||||
FROM
|
||||
(
|
||||
SELECT
|
||||
DATE(DATE_TRUNC('day', c.created_at AT TIME ZONE 'UTC' AT TIME ZONE :tz )) AS date,
|
||||
c.created_by,
|
||||
COUNT(c.id) AS interactions
|
||||
FROM
|
||||
workflow_runs c
|
||||
WHERE
|
||||
c.app_id = :app_id
|
||||
AND c.triggered_from = :triggered_from
|
||||
{{start}}
|
||||
{{end}}
|
||||
GROUP BY
|
||||
date, c.created_by
|
||||
) sub
|
||||
GROUP BY
|
||||
sub.date"""
|
||||
arg_dict = {
|
||||
"tz": account.timezone,
|
||||
"app_id": app_model.id,
|
||||
|
|
@ -262,7 +270,7 @@ class WorkflowAverageAppInteractionStatistic(Resource):
|
|||
end_datetime_timezone = timezone.localize(end_datetime)
|
||||
end_datetime_utc = end_datetime_timezone.astimezone(utc_timezone)
|
||||
|
||||
sql_query = sql_query.replace("{{end}}", " and c.created_at < :end")
|
||||
sql_query = sql_query.replace("{{end}}", " AND c.created_at < :end")
|
||||
arg_dict["end"] = end_datetime_utc
|
||||
else:
|
||||
sql_query = sql_query.replace("{{end}}", "")
|
||||
|
|
|
|||
|
|
@ -64,7 +64,8 @@ def cloud_edition_billing_resource_check(resource: str):
|
|||
elif resource == "vector_space" and 0 < vector_space.limit <= vector_space.size:
|
||||
abort(403, "The capacity of the vector space has reached the limit of your subscription.")
|
||||
elif resource == "documents" and 0 < documents_upload_quota.limit <= documents_upload_quota.size:
|
||||
# The api of file upload is used in the multiple places, so we need to check the source of the request from datasets
|
||||
# The api of file upload is used in the multiple places,
|
||||
# so we need to check the source of the request from datasets
|
||||
source = request.args.get("source")
|
||||
if source == "datasets":
|
||||
abort(403, "The number of documents has reached the limit of your subscription.")
|
||||
|
|
|
|||
|
|
@ -80,7 +80,8 @@ def _validate_web_sso_token(decoded, system_features, app_code):
|
|||
if not source or source != "sso":
|
||||
raise WebSSOAuthRequiredError()
|
||||
|
||||
# Check if SSO is not enforced for web, and if the token source is SSO, raise an error and redirect to normal passport login
|
||||
# Check if SSO is not enforced for web, and if the token source is SSO,
|
||||
# raise an error and redirect to normal passport login
|
||||
if not system_features.sso_enforced_for_web or not app_web_sso_enabled:
|
||||
source = decoded.get("token_source")
|
||||
if source and source == "sso":
|
||||
|
|
|
|||
|
|
@ -41,7 +41,8 @@ Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use
|
|||
{{historic_messages}}
|
||||
Question: {{query}}
|
||||
{{agent_scratchpad}}
|
||||
Thought:"""
|
||||
Thought:""" # noqa: E501
|
||||
|
||||
|
||||
ENGLISH_REACT_COMPLETION_AGENT_SCRATCHPAD_TEMPLATES = """Observation: {{observation}}
|
||||
Thought:"""
|
||||
|
|
@ -86,7 +87,8 @@ Action:
|
|||
```
|
||||
|
||||
Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use tools if necessary. Respond directly if appropriate. Format is Action:```$JSON_BLOB```then Observation:.
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
|
||||
ENGLISH_REACT_CHAT_AGENT_SCRATCHPAD_TEMPLATES = ""
|
||||
|
||||
|
|
|
|||
|
|
@ -84,10 +84,12 @@ class WorkflowLoggingCallback(WorkflowCallback):
|
|||
if route_node_state.node_run_result:
|
||||
node_run_result = route_node_state.node_run_result
|
||||
self.print_text(
|
||||
f"Inputs: {jsonable_encoder(node_run_result.inputs) if node_run_result.inputs else ''}", color="green"
|
||||
f"Inputs: " f"{jsonable_encoder(node_run_result.inputs) if node_run_result.inputs else ''}",
|
||||
color="green",
|
||||
)
|
||||
self.print_text(
|
||||
f"Process Data: {jsonable_encoder(node_run_result.process_data) if node_run_result.process_data else ''}",
|
||||
f"Process Data: "
|
||||
f"{jsonable_encoder(node_run_result.process_data) if node_run_result.process_data else ''}",
|
||||
color="green",
|
||||
)
|
||||
self.print_text(
|
||||
|
|
@ -114,14 +116,17 @@ class WorkflowLoggingCallback(WorkflowCallback):
|
|||
node_run_result = route_node_state.node_run_result
|
||||
self.print_text(f"Error: {node_run_result.error}", color="red")
|
||||
self.print_text(
|
||||
f"Inputs: {jsonable_encoder(node_run_result.inputs) if node_run_result.inputs else ''}", color="red"
|
||||
)
|
||||
self.print_text(
|
||||
f"Process Data: {jsonable_encoder(node_run_result.process_data) if node_run_result.process_data else ''}",
|
||||
f"Inputs: " f"" f"{jsonable_encoder(node_run_result.inputs) if node_run_result.inputs else ''}",
|
||||
color="red",
|
||||
)
|
||||
self.print_text(
|
||||
f"Outputs: {jsonable_encoder(node_run_result.outputs) if node_run_result.outputs else ''}", color="red"
|
||||
f"Process Data: "
|
||||
f"{jsonable_encoder(node_run_result.process_data) if node_run_result.process_data else ''}",
|
||||
color="red",
|
||||
)
|
||||
self.print_text(
|
||||
f"Outputs: " f"{jsonable_encoder(node_run_result.outputs) if node_run_result.outputs else ''}",
|
||||
color="red",
|
||||
)
|
||||
|
||||
def on_node_text_chunk(self, event: NodeRunStreamChunkEvent) -> None:
|
||||
|
|
|
|||
|
|
@ -188,7 +188,8 @@ class MessageFileParser:
|
|||
def _check_image_remote_url(self, url):
|
||||
try:
|
||||
headers = {
|
||||
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
|
||||
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)"
|
||||
" Chrome/91.0.4472.124 Safari/537.36"
|
||||
}
|
||||
|
||||
def is_s3_presigned_url(url):
|
||||
|
|
|
|||
|
|
@ -89,7 +89,8 @@ class CodeExecutor:
|
|||
raise CodeExecutionError("Code execution service is unavailable")
|
||||
elif response.status_code != 200:
|
||||
raise Exception(
|
||||
f"Failed to execute code, got status code {response.status_code}, please check if the sandbox service is running"
|
||||
f"Failed to execute code, got status code {response.status_code},"
|
||||
f" please check if the sandbox service is running"
|
||||
)
|
||||
except CodeExecutionError as e:
|
||||
raise e
|
||||
|
|
|
|||
|
|
@ -14,7 +14,10 @@ class ToolParameterCache:
|
|||
def __init__(
|
||||
self, tenant_id: str, provider: str, tool_name: str, cache_type: ToolParameterCacheType, identity_id: str
|
||||
):
|
||||
self.cache_key = f"{cache_type.value}_secret:tenant_id:{tenant_id}:provider:{provider}:tool_name:{tool_name}:identity_id:{identity_id}"
|
||||
self.cache_key = (
|
||||
f"{cache_type.value}_secret:tenant_id:{tenant_id}:provider:{provider}:tool_name:{tool_name}"
|
||||
f":identity_id:{identity_id}"
|
||||
)
|
||||
|
||||
def get(self) -> Optional[dict]:
|
||||
"""
|
||||
|
|
|
|||
|
|
@ -59,24 +59,27 @@ User Input: yo, 你今天咋样？
|
|||
}
|
||||
|
||||
User Input:
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (
|
||||
"Please help me predict the three most likely questions that human would ask, "
|
||||
"and keeping each question under 20 characters.\n"
|
||||
"MAKE SURE your output is the SAME language as the Assistant's latest response(if the main response is written in Chinese, then the language of your output must be using Chinese.)!\n"
|
||||
"MAKE SURE your output is the SAME language as the Assistant's latest response"
|
||||
"(if the main response is written in Chinese, then the language of your output must be using Chinese.)!\n"
|
||||
"The output must be an array in JSON format following the specified schema:\n"
|
||||
'["question1","question2","question3"]\n'
|
||||
)
|
||||
|
||||
GENERATOR_QA_PROMPT = (
|
||||
"<Task> The user will send a long text. Generate a Question and Answer pairs only using the knowledge in the long text. Please think step by step."
|
||||
"<Task> The user will send a long text. Generate a Question and Answer pairs only using the knowledge"
|
||||
" in the long text. Please think step by step."
|
||||
"Step 1: Understand and summarize the main content of this text.\n"
|
||||
"Step 2: What key information or concepts are mentioned in this text?\n"
|
||||
"Step 3: Decompose or combine multiple pieces of information and concepts.\n"
|
||||
"Step 4: Generate questions and answers based on these key information and concepts.\n"
|
||||
"<Constraints> The questions should be clear and detailed, and the answers should be detailed and complete. "
|
||||
"You must answer in {language}, in a style that is clear and detailed in {language}. No language other than {language} should be used. \n"
|
||||
"You must answer in {language}, in a style that is clear and detailed in {language}."
|
||||
" No language other than {language} should be used. \n"
|
||||
"<Format> Use the following format: Q1:\nA1:\nQ2:\nA2:...\n"
|
||||
"<QA Pairs>"
|
||||
)
|
||||
|
|
@ -94,7 +97,7 @@ Based on task description, please create a well-structured prompt template that
|
|||
- Use the same language as task description.
|
||||
- Output in ``` xml ``` and start with <instruction>
|
||||
Please generate the full prompt template with at least 300 words and output only the prompt template.
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
RULE_CONFIG_PROMPT_GENERATE_TEMPLATE = """
|
||||
Here is a task description for which I would like you to create a high-quality prompt template for:
|
||||
|
|
@ -109,7 +112,7 @@ Based on task description, please create a well-structured prompt template that
|
|||
- Use the same language as task description.
|
||||
- Output in ``` xml ``` and start with <instruction>
|
||||
Please generate the full prompt template and output only the prompt template.
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
RULE_CONFIG_PARAMETER_GENERATE_TEMPLATE = """
|
||||
I need to extract the following information from the input text. The <information to be extracted> tag specifies the 'type', 'description' and 'required' of the information to be extracted.
|
||||
|
|
@ -134,7 +137,7 @@ Inside <text></text> XML tags, there is a text that I should extract parameters
|
|||
|
||||
### Answer
|
||||
I should always output a valid list. Output nothing other than the list of variable_name. Output an empty list if there is no variable name in input text.
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
RULE_CONFIG_STATEMENT_GENERATE_TEMPLATE = """
|
||||
<instruction>
|
||||
|
|
@ -150,4 +153,4 @@ Welcome! I'm here to assist you with any questions or issues you might have with
|
|||
Here is the task description: {{INPUT_TEXT}}
|
||||
|
||||
You just need to generate the output
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
|
|
|||
|
|
@ -8,8 +8,11 @@ PARAMETER_RULE_TEMPLATE: dict[DefaultParameterName, dict] = {
|
|||
},
|
||||
"type": "float",
|
||||
"help": {
|
||||
"en_US": "Controls randomness. Lower temperature results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive. Higher temperature results in more random completions.",
|
||||
"zh_Hans": "温度控制随机性。较低的温度会导致较少的随机完成。随着温度接近零，模型将变得确定性和重复性。较高的温度会导致更多的随机完成。",
|
||||
"en_US": "Controls randomness. Lower temperature results in less random completions."
|
||||
" As the temperature approaches zero, the model will become deterministic and repetitive."
|
||||
" Higher temperature results in more random completions.",
|
||||
"zh_Hans": "温度控制随机性。较低的温度会导致较少的随机完成。随着温度接近零，模型将变得确定性和重复性。"
|
||||
"较高的温度会导致更多的随机完成。",
|
||||
},
|
||||
"required": False,
|
||||
"default": 0.0,
|
||||
|
|
@ -24,7 +27,8 @@ PARAMETER_RULE_TEMPLATE: dict[DefaultParameterName, dict] = {
|
|||
},
|
||||
"type": "float",
|
||||
"help": {
|
||||
"en_US": "Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered.",
|
||||
"en_US": "Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options"
|
||||
" are considered.",
|
||||
"zh_Hans": "通过核心采样控制多样性：0.5表示考虑了一半的所有可能性加权选项。",
|
||||
},
|
||||
"required": False,
|
||||
|
|
@ -88,7 +92,8 @@ PARAMETER_RULE_TEMPLATE: dict[DefaultParameterName, dict] = {
|
|||
},
|
||||
"type": "int",
|
||||
"help": {
|
||||
"en_US": "Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.",
|
||||
"en_US": "Specifies the upper limit on the length of generated results."
|
||||
" If the generated results are truncated, you can increase this parameter.",
|
||||
"zh_Hans": "指定生成结果长度的上限。如果生成结果截断，可以调大该参数。",
|
||||
},
|
||||
"required": False,
|
||||
|
|
@ -104,7 +109,8 @@ PARAMETER_RULE_TEMPLATE: dict[DefaultParameterName, dict] = {
|
|||
},
|
||||
"type": "string",
|
||||
"help": {
|
||||
"en_US": "Set a response format, ensure the output from llm is a valid code block as possible, such as JSON, XML, etc.",
|
||||
"en_US": "Set a response format, ensure the output from llm is a valid code block as possible,"
|
||||
" such as JSON, XML, etc.",
|
||||
"zh_Hans": "设置一个返回格式，确保llm的输出尽可能是有效的代码块，如JSON、XML等",
|
||||
},
|
||||
"required": False,
|
||||
|
|
|
|||
|
|
@ -72,7 +72,9 @@ class AIModel(ABC):
|
|||
if isinstance(error, tuple(model_errors)):
|
||||
if invoke_error == InvokeAuthorizationError:
|
||||
return invoke_error(
|
||||
description=f"[{provider_name}] Incorrect model credentials provided, please check and try again. "
|
||||
description=(
|
||||
f"[{provider_name}] Incorrect model credentials provided, please check and try again."
|
||||
)
|
||||
)
|
||||
|
||||
return invoke_error(description=f"[{provider_name}] {invoke_error.description}, {str(error)}")
|
||||
|
|
|
|||
|
|
@ -187,7 +187,7 @@ if you are not sure about the structure.
|
|||
<instructions>
|
||||
{{instructions}}
|
||||
</instructions>
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
code_block = model_parameters.get("response_format", "")
|
||||
if not code_block:
|
||||
|
|
@ -830,7 +830,8 @@ if you are not sure about the structure.
|
|||
else:
|
||||
if parameter_value != round(parameter_value, parameter_rule.precision):
|
||||
raise ValueError(
|
||||
f"Model Parameter {parameter_name} should be round to {parameter_rule.precision} decimal places."
|
||||
f"Model Parameter {parameter_name} should be round to {parameter_rule.precision}"
|
||||
f" decimal places."
|
||||
)
|
||||
|
||||
# validate parameter value range
|
||||
|
|
|
|||
|
|
@ -51,7 +51,7 @@ if you are not sure about the structure.
|
|||
<instructions>
|
||||
{{instructions}}
|
||||
</instructions>
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
|
||||
class AnthropicLargeLanguageModel(LargeLanguageModel):
|
||||
|
|
|
|||
|
|
@ -16,6 +16,15 @@ from core.model_runtime.entities.model_entities import (
|
|||
|
||||
AZURE_OPENAI_API_VERSION = "2024-02-15-preview"
|
||||
|
||||
AZURE_DEFAULT_PARAM_SEED_HELP = I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，"
|
||||
"您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically,"
|
||||
" such that repeated requests with the same seed and parameters should return the same result."
|
||||
" Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter"
|
||||
" to monitor changes in the backend.",
|
||||
)
|
||||
|
||||
|
||||
def _get_max_tokens(default: int, min_val: int, max_val: int) -> ParameterRule:
|
||||
rule = ParameterRule(
|
||||
|
|
@ -229,10 +238,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
@ -297,10 +303,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
@ -365,10 +368,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
@ -433,10 +433,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
@ -502,10 +499,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
@ -571,10 +565,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
@ -650,10 +641,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
@ -719,10 +707,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
@ -788,10 +773,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
@ -867,10 +849,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
@ -936,10 +915,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
@ -1000,10 +976,7 @@ LLM_BASE_MODELS = [
|
|||
name="seed",
|
||||
label=I18nObject(zh_Hans="种子", en_US="Seed"),
|
||||
type="int",
|
||||
help=I18nObject(
|
||||
zh_Hans="如果指定，模型将尽最大努力进行确定性采样，使得重复的具有相同种子和参数的请求应该返回相同的结果。不能保证确定性，您应该参考 system_fingerprint 响应参数来监视变化。",
|
||||
en_US="If specified, model will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.",
|
||||
),
|
||||
help=AZURE_DEFAULT_PARAM_SEED_HELP,
|
||||
required=False,
|
||||
precision=2,
|
||||
min=0,
|
||||
|
|
|
|||
|
|
@ -15,6 +15,7 @@ class BaichuanTokenizer:
|
|||
|
||||
@classmethod
|
||||
def _get_num_tokens(cls, text: str) -> int:
|
||||
# tokens = number of Chinese characters + number of English words * 1.3 (for estimation only, subject to actual return)
|
||||
# tokens = number of Chinese characters + number of English words * 1.3
|
||||
# (for estimation only, subject to actual return)
|
||||
# https://platform.baichuan-ai.com/docs/text-Embedding
|
||||
return int(cls.count_chinese_characters(text) + cls.count_english_vocabularies(text) * 1.3)
|
||||
|
|
|
|||
|
|
@ -52,7 +52,7 @@ if you are not sure about the structure.
|
|||
<instructions>
|
||||
{{instructions}}
|
||||
</instructions>
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
|
||||
class BedrockLargeLanguageModel(LargeLanguageModel):
|
||||
|
|
@ -541,7 +541,9 @@ class BedrockLargeLanguageModel(LargeLanguageModel):
|
|||
"max_tokens": 32,
|
||||
}
|
||||
elif "ai21" in model:
|
||||
# ValidationException: Malformed input request: #/temperature: expected type: Number, found: Null#/maxTokens: expected type: Integer, found: Null#/topP: expected type: Number, found: Null, please reformat your input and try again.
|
||||
# ValidationException: Malformed input request: #/temperature: expected type: Number,
|
||||
# found: Null#/maxTokens: expected type: Integer, found: Null#/topP: expected type: Number, found: Null,
|
||||
# please reformat your input and try again.
|
||||
required_params = {
|
||||
"temperature": 0.7,
|
||||
"topP": 0.9,
|
||||
|
|
|
|||
|
|
@ -45,7 +45,7 @@ if you are not sure about the structure.
|
|||
<instructions>
|
||||
{{instructions}}
|
||||
</instructions>
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
|
||||
class GoogleLargeLanguageModel(LargeLanguageModel):
|
||||
|
|
|
|||
|
|
@ -54,7 +54,8 @@ class TeiHelper:
|
|||
|
||||
url = str(URL(server_url) / "info")
|
||||
|
||||
# this method is surrounded by a lock, and default requests may hang forever, so we just set a Adapter with max_retries=3
|
||||
# this method is surrounded by a lock, and default requests may hang forever,
|
||||
# so we just set a Adapter with max_retries=3
|
||||
session = Session()
|
||||
session.mount("http://", HTTPAdapter(max_retries=3))
|
||||
session.mount("https://", HTTPAdapter(max_retries=3))
|
||||
|
|
|
|||
|
|
@ -131,7 +131,8 @@ class HunyuanLargeLanguageModel(LargeLanguageModel):
|
|||
{
|
||||
"Role": message.role.value,
|
||||
# fix set content = "" while tool_call request
|
||||
# fix [hunyuan] None, [TencentCloudSDKException] code:InvalidParameter message:Messages Content and Contents not allowed empty at the same time.
|
||||
# fix [hunyuan] None, [TencentCloudSDKException] code:InvalidParameter
|
||||
# message:Messages Content and Contents not allowed empty at the same time.
|
||||
"Content": " ", # message.content if (message.content is not None) else "",
|
||||
"ToolCalls": dict_tool_calls,
|
||||
}
|
||||
|
|
|
|||
|
|
@ -93,7 +93,8 @@ class NVIDIALargeLanguageModel(OAIAPICompatLargeLanguageModel):
|
|||
|
||||
def _validate_credentials(self, model: str, credentials: dict) -> None:
|
||||
"""
|
||||
Validate model credentials using requests to ensure compatibility with all providers following OpenAI's API standard.
|
||||
Validate model credentials using requests to ensure compatibility with all providers following
|
||||
OpenAI's API standard.
|
||||
|
||||
:param model: model name
|
||||
:param credentials: model credentials
|
||||
|
|
|
|||
|
|
@ -239,7 +239,8 @@ class OCILargeLanguageModel(LargeLanguageModel):
|
|||
config_items = oci_config_content.split("/")
|
||||
if len(config_items) != 5:
|
||||
raise CredentialsValidateFailedError(
|
||||
"oci_config_content should be base64.b64encode('user_ocid/fingerprint/tenancy_ocid/region/compartment_ocid'.encode('utf-8'))"
|
||||
"oci_config_content should be base64.b64encode("
|
||||
"'user_ocid/fingerprint/tenancy_ocid/region/compartment_ocid'.encode('utf-8'))"
|
||||
)
|
||||
oci_config["user"] = config_items[0]
|
||||
oci_config["fingerprint"] = config_items[1]
|
||||
|
|
|
|||
|
|
@ -146,7 +146,8 @@ class OCITextEmbeddingModel(TextEmbeddingModel):
|
|||
config_items = oci_config_content.split("/")
|
||||
if len(config_items) != 5:
|
||||
raise CredentialsValidateFailedError(
|
||||
"oci_config_content should be base64.b64encode('user_ocid/fingerprint/tenancy_ocid/region/compartment_ocid'.encode('utf-8'))"
|
||||
"oci_config_content should be base64.b64encode("
|
||||
"'user_ocid/fingerprint/tenancy_ocid/region/compartment_ocid'.encode('utf-8'))"
|
||||
)
|
||||
oci_config["user"] = config_items[0]
|
||||
oci_config["fingerprint"] = config_items[1]
|
||||
|
|
|
|||
|
|
@ -639,9 +639,10 @@ class OllamaLargeLanguageModel(LargeLanguageModel):
|
|||
type=ParameterType.STRING,
|
||||
help=I18nObject(
|
||||
en_US="Sets how long the model is kept in memory after generating a response. "
|
||||
"This must be a duration string with a unit (e.g., '10m' for 10 minutes or '24h' for 24 hours). "
|
||||
"A negative number keeps the model loaded indefinitely, and '0' unloads the model immediately after generating a response. "
|
||||
"Valid time units are 's','m','h'. (Default: 5m)"
|
||||
"This must be a duration string with a unit (e.g., '10m' for 10 minutes or '24h' for 24 hours)."
|
||||
" A negative number keeps the model loaded indefinitely, and '0' unloads the model"
|
||||
" immediately after generating a response."
|
||||
" Valid time units are 's','m','h'. (Default: 5m)"
|
||||
),
|
||||
),
|
||||
ParameterRule(
|
||||
|
|
|
|||
|
|
@ -37,7 +37,7 @@ if you are not sure about the structure.
|
|||
<instructions>
|
||||
{{instructions}}
|
||||
</instructions>
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
|
||||
class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel):
|
||||
|
|
|
|||
|
|
@ -103,7 +103,8 @@ class OAIAPICompatLargeLanguageModel(_CommonOaiApiCompat, LargeLanguageModel):
|
|||
|
||||
def validate_credentials(self, model: str, credentials: dict) -> None:
|
||||
"""
|
||||
Validate model credentials using requests to ensure compatibility with all providers following OpenAI's API standard.
|
||||
Validate model credentials using requests to ensure compatibility with all providers following
|
||||
OpenAI's API standard.
|
||||
|
||||
:param model: model name
|
||||
:param credentials: model credentials
|
||||
|
|
@ -262,7 +263,8 @@ class OAIAPICompatLargeLanguageModel(_CommonOaiApiCompat, LargeLanguageModel):
|
|||
|
||||
return entity
|
||||
|
||||
# validate_credentials method has been rewritten to use the requests library for compatibility with all providers following OpenAI's API standard.
|
||||
# validate_credentials method has been rewritten to use the requests library for compatibility with all providers
|
||||
# following OpenAI's API standard.
|
||||
def _generate(
|
||||
self,
|
||||
model: str,
|
||||
|
|
|
|||
|
|
@ -61,7 +61,10 @@ class SparkLLMClient:
|
|||
|
||||
signature_sha_base64 = base64.b64encode(signature_sha).decode(encoding="utf-8")
|
||||
|
||||
authorization_origin = f'api_key="{api_key}", algorithm="hmac-sha256", headers="host date request-line", signature="{signature_sha_base64}"'
|
||||
authorization_origin = (
|
||||
f'api_key="{api_key}", algorithm="hmac-sha256", headers="host date request-line",'
|
||||
f' signature="{signature_sha_base64}"'
|
||||
)
|
||||
|
||||
authorization = base64.b64encode(authorization_origin.encode("utf-8")).decode(encoding="utf-8")
|
||||
|
||||
|
|
|
|||
|
|
@ -34,7 +34,7 @@ if you are not sure about the structure.
|
|||
<instructions>
|
||||
{{instructions}}
|
||||
</instructions>
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
|
||||
class UpstageLargeLanguageModel(_CommonUpstage, LargeLanguageModel):
|
||||
|
|
|
|||
|
|
@ -114,7 +114,8 @@ class VertexAiLargeLanguageModel(LargeLanguageModel):
|
|||
credentials.refresh(request)
|
||||
token = credentials.token
|
||||
|
||||
# Vertex AI Anthropic Claude3 Opus model available in us-east5 region, Sonnet and Haiku available in us-central1 region
|
||||
# Vertex AI Anthropic Claude3 Opus model available in us-east5 region, Sonnet and Haiku available
|
||||
# in us-central1 region
|
||||
if "opus" in model or "claude-3-5-sonnet" in model:
|
||||
location = "us-east5"
|
||||
else:
|
||||
|
|
@ -123,7 +124,8 @@ class VertexAiLargeLanguageModel(LargeLanguageModel):
|
|||
# use access token to authenticate
|
||||
if token:
|
||||
client = AnthropicVertex(region=location, project_id=project_id, access_token=token)
|
||||
# When access token is empty, try to use the Google Cloud VM's built-in service account or the GOOGLE_APPLICATION_CREDENTIALS environment variable
|
||||
# When access token is empty, try to use the Google Cloud VM's built-in service account
|
||||
# or the GOOGLE_APPLICATION_CREDENTIALS environment variable
|
||||
else:
|
||||
client = AnthropicVertex(
|
||||
region=location,
|
||||
|
|
|
|||
|
|
@ -28,7 +28,7 @@ if you are not sure about the structure.
|
|||
</instructions>
|
||||
|
||||
You should also complete the text started with ``` but not tell ``` directly.
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
|
||||
class ErnieBotLargeLanguageModel(LargeLanguageModel):
|
||||
|
|
|
|||
|
|
@ -130,7 +130,8 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
|
|||
credentials["completion_type"] = "completion"
|
||||
else:
|
||||
raise ValueError(
|
||||
f"xinference model ability {extra_param.model_ability} is not supported, check if you have the right model type"
|
||||
f"xinference model ability {extra_param.model_ability} is not supported,"
|
||||
f" check if you have the right model type"
|
||||
)
|
||||
|
||||
if extra_param.support_function_call:
|
||||
|
|
@ -358,7 +359,8 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
|
|||
help=I18nObject(
|
||||
en_US="Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they "
|
||||
"appear in the text so far, increasing the model's likelihood to talk about new topics.",
|
||||
zh_Hans="介于 -2.0 和 2.0 之间的数字。正值会根据新词是否已出现在文本中对其进行惩罚，从而增加模型谈论新话题的可能性。",
|
||||
zh_Hans="介于 -2.0 和 2.0 之间的数字。正值会根据新词是否已出现在文本中对其进行惩罚，"
|
||||
"从而增加模型谈论新话题的可能性。",
|
||||
),
|
||||
default=0.0,
|
||||
min=-2.0,
|
||||
|
|
@ -378,7 +380,8 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
|
|||
en_US="Number between -2.0 and 2.0. Positive values penalize new tokens based on their "
|
||||
"existing frequency in the text so far, decreasing the model's likelihood to repeat the "
|
||||
"same line verbatim.",
|
||||
zh_Hans="介于 -2.0 和 2.0 之间的数字。正值会根据新词在文本中的现有频率对其进行惩罚，从而降低模型逐字重复相同内容的可能性。",
|
||||
zh_Hans="介于 -2.0 和 2.0 之间的数字。正值会根据新词在文本中的现有频率对其进行惩罚，"
|
||||
"从而降低模型逐字重复相同内容的可能性。",
|
||||
),
|
||||
default=0.0,
|
||||
min=-2.0,
|
||||
|
|
|
|||
|
|
@ -101,12 +101,16 @@ class XinferenceSpeech2TextModel(Speech2TextModel):
|
|||
|
||||
:param model: model name
|
||||
:param credentials: model credentials
|
||||
:param file: The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpe g,mpga, m4a, ogg, wav, or webm.
|
||||
:param file: The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg,
|
||||
mpga, m4a, ogg, wav, or webm.
|
||||
:param language: The language of the input audio. Supplying the input language in ISO-639-1
|
||||
:param prompt: An optional text to guide the model's style or continue a previous audio segment.
|
||||
The prompt should match the audio language.
|
||||
:param response_format: The format of the transcript output, in one of these options: json, text, srt, verbose _json, or vtt.
|
||||
:param temperature: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output mor e random,while lower values like 0.2 will make it more focused and deterministic.If set to 0, the model wi ll use log probability to automatically increase the temperature until certain thresholds are hit.
|
||||
:param response_format: The format of the transcript output, in one of these options: json, text, srt,
|
||||
verbose_json, or vtt.
|
||||
:param temperature: The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more
|
||||
random,while lower values like 0.2 will make it more focused and deterministic.If set to 0, the model will use
|
||||
log probability to automatically increase the temperature until certain thresholds are hit.
|
||||
:return: text for given audio file
|
||||
"""
|
||||
server_url = credentials["server_url"]
|
||||
|
|
|
|||
|
|
@ -76,7 +76,8 @@ class XinferenceHelper:
|
|||
|
||||
url = str(URL(server_url) / "v1" / "models" / model_uid)
|
||||
|
||||
# this method is surrounded by a lock, and default requests may hang forever, so we just set a Adapter with max_retries=3
|
||||
# this method is surrounded by a lock, and default requests may hang forever,
|
||||
# so we just set a Adapter with max_retries=3
|
||||
session = Session()
|
||||
session.mount("http://", HTTPAdapter(max_retries=3))
|
||||
session.mount("https://", HTTPAdapter(max_retries=3))
|
||||
|
|
@ -88,7 +89,8 @@ class XinferenceHelper:
|
|||
raise RuntimeError(f"get xinference model extra parameter failed, url: {url}, error: {e}")
|
||||
if response.status_code != 200:
|
||||
raise RuntimeError(
|
||||
f"get xinference model extra parameter failed, status code: {response.status_code}, response: {response.text}"
|
||||
f"get xinference model extra parameter failed, status code: {response.status_code},"
|
||||
f" response: {response.text}"
|
||||
)
|
||||
|
||||
response_json = response.json()
|
||||
|
|
|
|||
|
|
@ -31,7 +31,7 @@ And you should always end the block with a "```" to indicate the end of the JSON
|
|||
{{instructions}}
|
||||
</instructions>
|
||||
|
||||
```JSON"""
|
||||
```JSON""" # noqa: E501
|
||||
|
||||
|
||||
class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
|
||||
|
|
|
|||
|
|
@ -75,7 +75,8 @@ Headers = Mapping[str, Union[str, Omit]]
|
|||
|
||||
ResponseT = TypeVar(
|
||||
"ResponseT",
|
||||
bound="Union[str, None, BaseModel, list[Any], Dict[str, Any], Response, UnknownResponse, ModelBuilderProtocol, BinaryResponseContent]",
|
||||
bound="Union[str, None, BaseModel, list[Any], Dict[str, Any], Response, UnknownResponse, ModelBuilderProtocol,"
|
||||
" BinaryResponseContent]",
|
||||
)
|
||||
|
||||
# for user input files
|
||||
|
|
|
|||
|
|
@ -67,7 +67,8 @@ class CommonValidator:
|
|||
if credential_form_schema.max_length:
|
||||
if len(value) > credential_form_schema.max_length:
|
||||
raise ValueError(
|
||||
f"Variable {credential_form_schema.variable} length should not greater than {credential_form_schema.max_length}"
|
||||
f"Variable {credential_form_schema.variable} length should not"
|
||||
f" greater than {credential_form_schema.max_length}"
|
||||
)
|
||||
|
||||
# check the type of value
|
||||
|
|
|
|||
|
|
@ -1,11 +1,11 @@
|
|||
CONTEXT = "Use the following context as your learned knowledge, inside <context></context> XML tags.\n\n<context>\n{{#context#}}\n</context>\n\nWhen answer to user:\n- If you don't know, just say that you don't know.\n- If you don't know when you are not sure, ask for clarification.\nAvoid mentioning that you obtained the information from the context.\nAnd answer according to the language of the user's question.\n"
|
||||
CONTEXT = "Use the following context as your learned knowledge, inside <context></context> XML tags.\n\n<context>\n{{#context#}}\n</context>\n\nWhen answer to user:\n- If you don't know, just say that you don't know.\n- If you don't know when you are not sure, ask for clarification.\nAvoid mentioning that you obtained the information from the context.\nAnd answer according to the language of the user's question.\n" # noqa: E501
|
||||
|
||||
BAICHUAN_CONTEXT = "用户在与一个客观的助手对话。助手会尊重找到的材料，给出全面专业的解释，但不会过度演绎。同时回答中不会暴露引用的材料：\n\n```\n{{#context#}}\n```\n\n"
|
||||
BAICHUAN_CONTEXT = "用户在与一个客观的助手对话。助手会尊重找到的材料，给出全面专业的解释，但不会过度演绎。同时回答中不会暴露引用的材料：\n\n```\n{{#context#}}\n```\n\n" # noqa: E501
|
||||
|
||||
CHAT_APP_COMPLETION_PROMPT_CONFIG = {
|
||||
"completion_prompt_config": {
|
||||
"prompt": {
|
||||
"text": "{{#pre_prompt#}}\nHere is the chat histories between human and assistant, inside <histories></histories> XML tags.\n\n<histories>\n{{#histories#}}\n</histories>\n\n\nHuman: {{#query#}}\n\nAssistant: "
|
||||
"text": "{{#pre_prompt#}}\nHere is the chat histories between human and assistant, inside <histories></histories> XML tags.\n\n<histories>\n{{#histories#}}\n</histories>\n\n\nHuman: {{#query#}}\n\nAssistant: " # noqa: E501
|
||||
},
|
||||
"conversation_histories_role": {"user_prefix": "Human", "assistant_prefix": "Assistant"},
|
||||
},
|
||||
|
|
@ -24,7 +24,7 @@ COMPLETION_APP_COMPLETION_PROMPT_CONFIG = {
|
|||
BAICHUAN_CHAT_APP_COMPLETION_PROMPT_CONFIG = {
|
||||
"completion_prompt_config": {
|
||||
"prompt": {
|
||||
"text": "{{#pre_prompt#}}\n\n用户和助手的历史对话内容如下：\n```\n{{#histories#}}\n```\n\n\n\n用户：{{#query#}}"
|
||||
"text": "{{#pre_prompt#}}\n\n用户和助手的历史对话内容如下：\n```\n{{#histories#}}\n```\n\n\n\n用户：{{#query#}}" # noqa: E501
|
||||
},
|
||||
"conversation_histories_role": {"user_prefix": "用户", "assistant_prefix": "助手"},
|
||||
},
|
||||
|
|
|
|||
|
|
@ -195,7 +195,8 @@ class OracleVector(BaseVector):
|
|||
top_k = kwargs.get("top_k", 5)
|
||||
with self._get_cursor() as cur:
|
||||
cur.execute(
|
||||
f"SELECT meta, text, vector_distance(embedding,:1) AS distance FROM {self.table_name} ORDER BY distance fetch first {top_k} rows only",
|
||||
f"SELECT meta, text, vector_distance(embedding,:1) AS distance FROM {self.table_name}"
|
||||
f" ORDER BY distance fetch first {top_k} rows only",
|
||||
[numpy.array(query_vector)],
|
||||
)
|
||||
docs = []
|
||||
|
|
@ -254,7 +255,8 @@ class OracleVector(BaseVector):
|
|||
entities.append(token)
|
||||
with self._get_cursor() as cur:
|
||||
cur.execute(
|
||||
f"select meta, text, embedding FROM {self.table_name} WHERE CONTAINS(text, :1, 1) > 0 order by score(1) desc fetch first {top_k} rows only",
|
||||
f"select meta, text, embedding FROM {self.table_name}"
|
||||
f" WHERE CONTAINS(text, :1, 1) > 0 order by score(1) desc fetch first {top_k} rows only",
|
||||
[" ACCUM ".join(entities)],
|
||||
)
|
||||
docs = []
|
||||
|
|
|
|||
|
|
@ -139,7 +139,8 @@ class PGVector(BaseVector):
|
|||
|
||||
with self._get_cursor() as cur:
|
||||
cur.execute(
|
||||
f"SELECT meta, text, embedding <=> %s AS distance FROM {self.table_name} ORDER BY distance LIMIT {top_k}",
|
||||
f"SELECT meta, text, embedding <=> %s AS distance FROM {self.table_name}"
|
||||
f" ORDER BY distance LIMIT {top_k}",
|
||||
(json.dumps(query_vector),),
|
||||
)
|
||||
docs = []
|
||||
|
|
|
|||
|
|
@ -30,7 +30,10 @@ from extensions.ext_storage import storage
|
|||
from models.model import UploadFile
|
||||
|
||||
SUPPORT_URL_CONTENT_TYPES = ["application/pdf", "text/plain", "application/json"]
|
||||
USER_AGENT = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
|
||||
USER_AGENT = (
|
||||
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124"
|
||||
" Safari/537.36"
|
||||
)
|
||||
|
||||
|
||||
class ExtractProcessor:
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ from core.workflow.nodes.llm.llm_node import LLMNode
|
|||
PREFIX = """Respond to the human as helpfully and accurately as possible. You have access to the following tools:"""
|
||||
|
||||
SUFFIX = """Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use tools if necessary. Respond directly if appropriate. Format is Action:```$JSON_BLOB```then Observation:.
|
||||
Thought:"""
|
||||
Thought:""" # noqa: E501
|
||||
|
||||
FORMAT_INSTRUCTIONS = """Use a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).
|
||||
The nouns in the format of "Thought", "Action", "Action Input", "Final Answer" must be expressed in English.
|
||||
|
|
@ -46,7 +46,7 @@ Action:
|
|||
"action": "Final Answer",
|
||||
"action_input": "Final response to human"
|
||||
}}
|
||||
```"""
|
||||
```""" # noqa: E501
|
||||
|
||||
|
||||
class ReactMultiDatasetRouter:
|
||||
|
|
@ -204,7 +204,8 @@ class ReactMultiDatasetRouter:
|
|||
tool_strings = []
|
||||
for tool in tools:
|
||||
tool_strings.append(
|
||||
f"{tool.name}: {tool.description}, args: {{'query': {{'title': 'Query', 'description': 'Query for the dataset to be used to retrieve the dataset.', 'type': 'string'}}}}"
|
||||
f"{tool.name}: {tool.description}, args: {{'query': {{'title': 'Query',"
|
||||
f" 'description': 'Query for the dataset to be used to retrieve the dataset.', 'type': 'string'}}}}"
|
||||
)
|
||||
formatted_tools = "\n".join(tool_strings)
|
||||
unique_tool_names = {tool.name for tool in tools}
|
||||
|
|
@ -236,7 +237,7 @@ class ReactMultiDatasetRouter:
|
|||
suffix = """Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use tools if necessary. Respond directly if appropriate. Format is Action:```$JSON_BLOB```then Observation:.
|
||||
Question: {input}
|
||||
Thought: {agent_scratchpad}
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
tool_strings = "\n".join([f"{tool.name}: {tool.description}" for tool in tools])
|
||||
tool_names = ", ".join([tool.name for tool in tools])
|
||||
|
|
|
|||
|
|
@ -7,7 +7,8 @@ from core.tools.entities.tool_entities import ToolParameter
|
|||
|
||||
class ApiToolBundle(BaseModel):
|
||||
"""
|
||||
This class is used to store the schema information of an api based tool. such as the url, the method, the parameters, etc.
|
||||
This class is used to store the schema information of an api based tool.
|
||||
such as the url, the method, the parameters, etc.
|
||||
"""
|
||||
|
||||
# server_url
|
||||
|
|
|
|||
|
|
@ -4,52 +4,52 @@ from core.tools.entities.tool_entities import ToolLabel, ToolLabelEnum
|
|||
ICONS = {
|
||||
ToolLabelEnum.SEARCH: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M7.33398 1.3335C10.646 1.3335 13.334 4.0215 13.334 7.3335C13.334 10.6455 10.646 13.3335 7.33398 13.3335C4.02198 13.3335 1.33398 10.6455 1.33398 7.3335C1.33398 4.0215 4.02198 1.3335 7.33398 1.3335ZM7.33398 12.0002C9.91232 12.0002 12.0007 9.91183 12.0007 7.3335C12.0007 4.75516 9.91232 2.66683 7.33398 2.66683C4.75565 2.66683 2.66732 4.75516 2.66732 7.3335C2.66732 9.91183 4.75565 12.0002 7.33398 12.0002ZM12.9909 12.0476L14.8764 13.9332L13.9337 14.876L12.0481 12.9904L12.9909 12.0476Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.IMAGE: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M13.0514 9.71752L10.4718 7.13792C10.2115 6.87752 9.78932 6.87752 9.52898 7.13792L4.57721 12.0897C3.4097 11.1113 2.66732 9.64232 2.66732 7.99992C2.66732 5.0544 5.05513 2.66659 8.00065 2.66659C10.9462 2.66659 13.334 5.0544 13.334 7.99992C13.334 8.60085 13.2346 9.17852 13.0514 9.71752ZM5.72683 12.8257L10.0004 8.55212L12.4259 10.9777C11.4668 12.4001 9.84152 13.3331 8.00038 13.3331C7.18632 13.3331 6.41628 13.1511 5.72683 12.8257ZM8.00065 14.6666C11.6825 14.6666 14.6673 11.6818 14.6673 7.99992C14.6673 4.31802 11.6825 1.33325 8.00065 1.33325C4.31875 1.33325 1.33398 4.31802 1.33398 7.99992C1.33398 11.6818 4.31875 14.6666 8.00065 14.6666ZM7.33398 6.66658C7.33398 7.40299 6.73705 7.99992 6.00065 7.99992C5.26427 7.99992 4.66732 7.40299 4.66732 6.66658C4.66732 5.9302 5.26427 5.33325 6.00065 5.33325C6.73705 5.33325 7.33398 5.9302 7.33398 6.66658Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.VIDEOS: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M8.00065 13.3333H13.334V14.6666H8.00065C4.31875 14.6666 1.33398 11.6818 1.33398 7.99992C1.33398 4.31802 4.31875 1.33325 8.00065 1.33325C11.6825 1.33325 14.6673 4.31802 14.6673 7.99992C14.6673 9.50072 14.1714 10.8857 13.3345 11.9999H11.5284C12.6356 11.0227 13.334 9.59285 13.334 7.99992C13.334 5.0544 10.9462 2.66659 8.00065 2.66659C5.05513 2.66659 2.66732 5.0544 2.66732 7.99992C2.66732 10.9455 5.05513 13.3333 8.00065 13.3333ZM8.00065 6.66658C7.26425 6.66658 6.66732 6.06963 6.66732 5.33325C6.66732 4.59687 7.26425 3.99992 8.00065 3.99992C8.73705 3.99992 9.33398 4.59687 9.33398 5.33325C9.33398 6.06963 8.73705 6.66658 8.00065 6.66658ZM5.33398 9.33325C4.5976 9.33325 4.00065 8.73632 4.00065 7.99992C4.00065 7.26352 4.5976 6.66658 5.33398 6.66658C6.07036 6.66658 6.66732 7.26352 6.66732 7.99992C6.66732 8.73632 6.07036 9.33325 5.33398 9.33325ZM10.6673 9.33325C9.93092 9.33325 9.33398 8.73632 9.33398 7.99992C9.33398 7.26352 9.93092 6.66658 10.6673 6.66658C11.4037 6.66658 12.0007 7.26352 12.0007 7.99992C12.0007 8.73632 11.4037 9.33325 10.6673 9.33325ZM8.00065 11.9999C7.26425 11.9999 6.66732 11.403 6.66732 10.6666C6.66732 9.93018 7.26425 9.33325 8.00065 9.33325C8.73705 9.33325 9.33398 9.93018 9.33398 10.6666C9.33398 11.403 8.73705 11.9999 8.00065 11.9999Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.WEATHER: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M6.6553 3.37344C7.42088 2.1484 8.78162 1.3335 10.3327 1.3335C12.7259 1.3335 14.666 3.2736 14.666 5.66683C14.666 6.38704 14.4903 7.06623 14.1794 7.66383C14.8894 8.3325 15.3327 9.28123 15.3327 10.3335C15.3327 12.3586 13.6911 14.0002 11.666 14.0002H5.99935C3.05383 14.0002 0.666016 11.6124 0.666016 8.66683C0.666016 5.72131 3.05383 3.3335 5.99935 3.3335C6.22143 3.3335 6.44034 3.34707 6.6553 3.37344ZM8.03628 3.73629C9.37768 4.29108 10.4435 5.37735 10.9711 6.73256C11.1961 6.68943 11.4284 6.66683 11.666 6.66683C12.1561 6.66683 12.6237 6.76296 13.0511 6.93743C13.2317 6.55162 13.3327 6.12102 13.3327 5.66683C13.3327 4.00998 11.9895 2.66683 10.3327 2.66683C9.41115 2.66683 8.58662 3.08236 8.03628 3.73629ZM11.666 12.6668C12.9547 12.6668 13.9993 11.6222 13.9993 10.3335C13.9993 9.04483 12.9547 8.00016 11.666 8.00016C11.013 8.00016 10.4227 8.26836 9.99922 8.70063C9.99928 8.68936 9.99935 8.6781 9.99935 8.66683C9.99935 6.45769 8.20848 4.66683 5.99935 4.66683C3.79021 4.66683 1.99935 6.45769 1.99935 8.66683C1.99935 10.876 3.79021 12.6668 5.99935 12.6668H11.666Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.FINANCE: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M8.00262 14.6685C4.32071 14.6685 1.33594 11.6838 1.33594 8.00184C1.33594 4.31997 4.32071 1.33521 8.00262 1.33521C11.6845 1.33521 14.6693 4.31997 14.6693 8.00184C14.6693 11.6838 11.6845 14.6685 8.00262 14.6685ZM8.00262 13.3352C10.9482 13.3352 13.336 10.9474 13.336 8.00184C13.336 5.05635 10.9482 2.66854 8.00262 2.66854C5.05708 2.66854 2.66927 5.05635 2.66927 8.00184C2.66927 10.9474 5.05708 13.3352 8.00262 13.3352ZM5.66927 9.33517H9.33595C9.52002 9.33517 9.66928 9.18597 9.66928 9.00184C9.66928 8.81777 9.52002 8.66851 9.33595 8.66851H6.66928C5.7488 8.66851 5.0026 7.92237 5.0026 7.00184C5.0026 6.08139 5.7488 5.33521 6.66928 5.33521H7.33595V4.00187H8.66928V5.33521H10.336V6.66851H6.66928C6.48518 6.66851 6.33594 6.81777 6.33594 7.00184C6.33594 7.18597 6.48518 7.33517 6.66928 7.33517H9.33595C10.2564 7.33517 11.0026 8.08137 11.0026 9.00184C11.0026 9.92237 10.2564 10.6685 9.33595 10.6685H8.66928V12.0018H7.33595V10.6685H5.66927V9.33517Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.DESIGN: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M4.70152 9.41416L3.2873 10.8284L5.17292 12.714L12.7154 5.17154L10.8298 3.28592L9.41557 4.70013L10.3584 5.64295L9.41557 6.58575L8.47277 5.64295L7.52997 6.58575L8.47277 7.52856L7.52997 8.47136L6.58713 7.52856L5.64433 8.47136L6.58713 9.41416L5.64433 10.357L4.70152 9.41416ZM11.3012 1.87171L14.1296 4.70013C14.39 4.96049 14.39 5.38259 14.1296 5.64295L5.64433 14.1282C5.38397 14.3886 4.96187 14.3886 4.70152 14.1282L1.87309 11.2998C1.61274 11.0394 1.61274 10.6174 1.87309 10.357L10.3584 1.87171C10.6187 1.61136 11.0408 1.61136 11.3012 1.87171ZM9.41557 12.2423L10.3584 11.2995L11.8534 12.7945H12.7962V11.8517L11.3012 10.3567L12.244 9.41383L14.0011 11.171V13.9999H11.1732L9.41557 12.2423ZM3.75861 6.58533L1.87299 4.69971C1.61265 4.43937 1.61265 4.01725 1.87299 3.75691L3.75861 1.87129C4.01896 1.61094 4.44107 1.61094 4.70142 1.87129L6.58704 3.75691L5.64423 4.69971L4.23002 3.2855L3.28721 4.22831L4.70142 5.64253L3.75861 6.58533Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.TRAVEL: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M9.44839 2C9.80198 2 10.1411 2.14047 10.3912 2.39053L13.6101 5.60947C13.8602 5.85953 14.0007 6.19866 14.0007 6.55229V11.3333H15.334V12.6667L9.91652 12.6672C9.62032 13.8171 8.57638 14.6667 7.33398 14.6667C6.0916 14.6667 5.04766 13.8171 4.75146 12.6672L2.00065 12.6667C1.63246 12.6667 1.33398 12.3682 1.33398 12V3.33333C1.33398 2.59695 1.93094 2 2.66732 2H9.44839ZM7.33398 10.6667C6.5976 10.6667 6.00065 11.2636 6.00065 12C6.00065 12.7364 6.5976 13.3333 7.33398 13.3333C8.07038 13.3333 8.66732 12.7364 8.66732 12C8.66732 11.2636 8.07038 10.6667 7.33398 10.6667ZM9.44839 3.33333H2.66732V11.3333L4.75128 11.3335C5.04726 10.1833 6.09136 9.33333 7.33398 9.33333C8.57658 9.33333 9.62072 10.1833 9.91665 11.3335L12.6673 11.3333V6.55229L9.44839 3.33333ZM9.33398 4.66667V8.66667H4.00065V4.66667H9.33398ZM8.00065 6H5.33398V7.33333H8.00065V6Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.SOCIAL: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M13.334 7.99992C13.334 5.0544 10.9462 2.66659 8.00065 2.66659C5.05513 2.66659 2.66732 5.0544 2.66732 7.99992C2.66732 10.9455 5.05513 13.3333 8.00065 13.3333C9.09518 13.3333 10.1127 13.0035 10.9594 12.438L11.699 13.5475C10.6408 14.2545 9.36885 14.6666 8.00065 14.6666C4.31875 14.6666 1.33398 11.6818 1.33398 7.99992C1.33398 4.31802 4.31875 1.33325 8.00065 1.33325C11.6825 1.33325 14.6673 4.31802 14.6673 7.99992V8.99992C14.6673 10.2886 13.6227 11.3333 12.334 11.3333C11.5312 11.3333 10.8231 10.9278 10.4032 10.3105C9.79678 10.9409 8.94452 11.3333 8.00065 11.3333C6.1597 11.3333 4.66732 9.84085 4.66732 7.99992C4.66732 6.15897 6.1597 4.66658 8.00065 4.66658C8.75118 4.66658 9.44378 4.91464 10.001 5.33325H11.334V8.99992C11.334 9.55219 11.7817 9.99992 12.334 9.99992C12.8863 9.99992 13.334 9.55219 13.334 8.99992V7.99992ZM8.00065 5.99992C6.89605 5.99992 6.00065 6.89532 6.00065 7.99992C6.00065 9.10452 6.89605 9.99992 8.00065 9.99992C9.10525 9.99992 10.0007 9.10452 10.0007 7.99992C10.0007 6.89532 9.10525 5.99992 8.00065 5.99992Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.NEWS: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M10.6673 13.3335V2.66683H2.66732V12.6668C2.66732 13.035 2.9658 13.3335 3.33398 13.3335H10.6673ZM12.6673 14.6668H3.33398C2.22942 14.6668 1.33398 13.7714 1.33398 12.6668V2.00016C1.33398 1.63198 1.63246 1.3335 2.00065 1.3335H11.334C11.7022 1.3335 12.0007 1.63198 12.0007 2.00016V6.66683H14.6673V12.6668C14.6673 13.7714 13.7719 14.6668 12.6673 14.6668ZM12.0007 8.00016V12.6668C12.0007 13.035 12.2991 13.3335 12.6673 13.3335C13.0355 13.3335 13.334 13.035 13.334 12.6668V8.00016H12.0007ZM4.00065 4.00016H8.00065V8.00016H4.00065V4.00016ZM5.33398 5.3335V6.66683H6.66732V5.3335H5.33398ZM4.00065 8.66683H9.33398V10.0002H4.00065V8.66683ZM4.00065 10.6668H9.33398V12.0002H4.00065V10.6668Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.MEDICAL: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M8.79747 1.51186L10.9641 5.26464C11.1482 5.5835 11.0389 5.99122 10.7201 6.17532L9.85373 6.67474L10.5207 7.83001L9.366 8.49668L8.699 7.34141L7.83333 7.84201C7.51447 8.02608 7.10673 7.91681 6.92267 7.59794L5.69747 5.47632C4.32922 5.89145 3.33333 7.16268 3.33333 8.66654C3.33333 9.08348 3.40987 9.48248 3.54965 9.85034C4.06613 9.52254 4.67762 9.33321 5.33333 9.33321C6.45605 9.33321 7.44913 9.88828 8.05313 10.7389L13.1787 7.78014L13.8454 8.93488L8.5932 11.9672C8.64133 12.1927 8.66667 12.4267 8.66667 12.6665C8.66667 12.895 8.64367 13.1181 8.59993 13.3337L14 13.3332V14.6665L2.66703 14.6673C2.2482 14.1101 2 13.4173 2 12.6665C2 11.9951 2.19855 11.3699 2.54014 10.8467C2.19517 10.1964 2 9.45428 2 8.66654C2 6.66968 3.25421 4.96575 5.01785 4.29953L4.75598 3.84519C4.38779 3.20747 4.60629 2.39202 5.24402 2.02382L6.97607 1.02382C7.6138 0.655637 8.42927 0.874138 8.79747 1.51186ZM5.33333 10.6665C4.22877 10.6665 3.33333 11.562 3.33333 12.6665C3.33333 12.9003 3.37343 13.1247 3.44711 13.3331H7.21953C7.29327 13.1247 7.33333 12.9003 7.33333 12.6665C7.33333 11.562 6.4379 10.6665 5.33333 10.6665ZM7.64273 2.17852L5.91068 3.17852L7.744 6.35395L9.47607 5.35395L7.64273 2.17852Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.PRODUCTIVITY: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M6.64807 11.9999H9.35062C9.43862 11.1989 9.84742 10.5376 10.5111 9.81499C10.5858 9.73365 11.0652 9.23752 11.1221 9.16665C11.6872 8.46199 11.9993 7.58992 11.9993 6.66659C11.9993 4.45745 10.2085 2.66659 7.99935 2.66659C5.79021 2.66659 3.99935 4.45745 3.99935 6.66659C3.99935 7.58945 4.31118 8.46105 4.87576 9.16552C4.93271 9.23659 5.41322 9.73405 5.48704 9.81445C6.15112 10.5375 6.56004 11.1989 6.64807 11.9999ZM9.33268 13.3333H6.66602V13.9999H9.33268V13.3333ZM3.83532 9.99939C3.10365 9.08639 2.66602 7.92759 2.66602 6.66659C2.66602 3.72107 5.05383 1.33325 7.99935 1.33325C10.9449 1.33325 13.3327 3.72107 13.3327 6.66659C13.3327 7.92825 12.8945 9.08759 12.1622 10.0009C11.7487 10.5165 10.666 11.3333 10.666 12.3333V13.9999C10.666 14.7363 10.0691 15.3333 9.33268 15.3333H6.66602C5.92964 15.3333 5.33268 14.7363 5.33268 13.9999V12.3333C5.33268 11.3333 4.24907 10.5157 3.83532 9.99939ZM8.66602 6.66979H10.3327L7.33268 10.6698V8.00312H5.66602L8.66602 3.99992V6.66979Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.EDUCATION: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M14 2.66683H4.66667C3.93029 2.66683 3.33333 3.26378 3.33333 4.00016C3.33333 4.73654 3.93029 5.3335 4.66667 5.3335H14V14.0002C14 14.3684 13.7015 14.6668 13.3333 14.6668H4.66667C3.19391 14.6668 2 13.4729 2 12.0002V4.00016C2 2.5274 3.19391 1.3335 4.66667 1.3335H13.3333C13.7015 1.3335 14 1.63198 14 2.00016V2.66683ZM3.33333 12.0002C3.33333 12.7366 3.93029 13.3335 4.66667 13.3335H12.6667V6.66683H4.66667C4.18095 6.66683 3.72557 6.53697 3.33333 6.31008V12.0002ZM13.3333 4.66683H4.66667C4.29848 4.66683 4 4.36835 4 4.00016C4 3.63198 4.29848 3.3335 4.66667 3.3335H13.3333V4.66683Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.BUSINESS: """<svg xmlns="http://www.w3.org/2000/svg" width="14" height="14" viewBox="0 0 14 14" fill="none">
|
||||
<path d="M3.66732 3.33341V1.33341C3.66732 0.965228 3.9658 0.666748 4.33398 0.666748H9.66732C10.0355 0.666748 10.334 0.965228 10.334 1.33341V3.33341H13.0007C13.3689 3.33341 13.6673 3.63189 13.6673 4.00008V13.3334C13.6673 13.7016 13.3689 14.0001 13.0007 14.0001H1.00065C0.632464 14.0001 0.333984 13.7016 0.333984 13.3334V4.00008C0.333984 3.63189 0.632464 3.33341 1.00065 3.33341H3.66732ZM12.334 8.66675H1.66732V12.6667H12.334V8.66675ZM12.334 4.66675H1.66732V7.33341H3.66732V6.00008H5.00065V7.33341H9.00065V6.00008H10.334V7.33341H12.334V4.66675ZM5.00065 2.00008V3.33341H9.00065V2.00008H5.00065Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.ENTERTAINMENT: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M11.3327 2.66675C13.5418 2.66675 15.3327 4.45761 15.3327 6.66675V9.33342C15.3327 11.5425 13.5418 13.3334 11.3327 13.3334H4.66602C2.45688 13.3334 0.666016 11.5425 0.666016 9.33342V6.66675C0.666016 4.45761 2.45688 2.66675 4.66602 2.66675H11.3327ZM11.3327 4.00008H4.66602C3.23788 4.00008 2.07196 5.12273 2.00262 6.53365L1.99935 6.66675V9.33342C1.99935 10.7615 3.122 11.9275 4.53292 11.9968L4.66602 12.0001H11.3327C12.7608 12.0001 13.9267 10.8774 13.9961 9.46648L13.9993 9.33342V6.66675C13.9993 5.23861 12.8767 4.07269 11.4657 4.00335L11.3327 4.00008ZM6.66602 6.00008V7.33342H7.99935V8.66675H6.66535L6.66602 10.0001H5.33268L5.33202 8.66675H3.99935V7.33342H5.33268V6.00008H6.66602ZM11.9993 8.66675V10.0001H10.666V8.66675H11.9993ZM10.666 6.00008V7.33342H9.33268V6.00008H10.666Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.UTILITIES: """<svg xmlns="http://www.w3.org/2000/svg" width="13" height="15" viewBox="0 0 13 15" fill="none">
|
||||
<path d="M12.3346 0.333252C12.7028 0.333252 13.0013 0.631732 13.0013 0.999919V4.33325C13.0013 4.70144 12.7028 4.99992 12.3346 4.99992H9.0013V13.6666C9.0013 14.0348 8.70284 14.3333 8.33463 14.3333H5.66797C5.29978 14.3333 5.0013 14.0348 5.0013 13.6666V4.99992H1.33464C0.966449 4.99992 0.667969 4.70144 0.667969 4.33325V2.74527C0.667969 2.49276 0.810635 2.26192 1.0365 2.14899L4.66797 0.333252H12.3346ZM9.0013 1.66659H4.98273L2.0013 3.1573V3.66659H6.33464V12.9999H7.66797V3.66659H9.0013V1.66659ZM11.668 1.66659H10.3346V3.66659H11.668V1.66659Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
ToolLabelEnum.OTHER: """<svg xmlns="http://www.w3.org/2000/svg" width="16" height="16" viewBox="0 0 16 16" fill="none">
|
||||
<path d="M8.00052 0.666748L4.00065 7.33342H12.0007L8.00052 0.666748ZM8.00052 3.25828L9.64572 6.00008H6.35553L8.00052 3.25828ZM4.50065 13.3334C3.48813 13.3334 2.66732 12.5126 2.66732 11.5001C2.66732 10.4875 3.48813 9.66675 4.50065 9.66675C5.51317 9.66675 6.33398 10.4875 6.33398 11.5001C6.33398 12.5126 5.51317 13.3334 4.50065 13.3334ZM4.50065 14.6667C6.24955 14.6667 7.66732 13.249 7.66732 11.5001C7.66732 9.75115 6.24955 8.33342 4.50065 8.33342C2.75175 8.33342 1.33398 9.75115 1.33398 11.5001C1.33398 13.249 2.75175 14.6667 4.50065 14.6667ZM10.0007 10.3334V13.0001H12.6673V10.3334H10.0007ZM8.66732 14.3334V9.00008H14.0007V14.3334H8.66732Z" fill="#344054"/>
|
||||
</svg>""",
|
||||
</svg>""", # noqa: E501
|
||||
}
|
||||
|
||||
default_tool_label_dict = {
|
||||
|
|
|
|||
|
|
@ -46,7 +46,8 @@ class AIPPTGenerateTool(BuiltinTool):
|
|||
tool_parameters (dict[str, Any]): The parameters for the tool
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation, which can be a single message or a list of messages.
|
||||
ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation,
|
||||
which can be a single message or a list of messages.
|
||||
"""
|
||||
title = tool_parameters.get("title", "")
|
||||
if not title:
|
||||
|
|
|
|||
|
|
@ -104,7 +104,8 @@ class ArxivSearchTool(BuiltinTool):
|
|||
tool_parameters (dict[str, Any]): The parameters for the tool, including the 'query' parameter.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation, which can be a single message or a list of messages.
|
||||
ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation,
|
||||
which can be a single message or a list of messages.
|
||||
"""
|
||||
query = tool_parameters.get("query", "")
|
||||
|
||||
|
|
|
|||
|
|
@ -62,7 +62,8 @@ class ApplyGuardrailTool(BuiltinTool):
|
|||
if isinstance(policy_data, dict) and "topics" in policy_data:
|
||||
for topic in policy_data["topics"]:
|
||||
formatted_assessments.append(
|
||||
f"Policy: {policy_type}, Topic: {topic['name']}, Type: {topic['type']}, Action: {topic['action']}"
|
||||
f"Policy: {policy_type}, Topic: {topic['name']}, Type: {topic['type']},"
|
||||
f" Action: {topic['action']}"
|
||||
)
|
||||
else:
|
||||
formatted_assessments.append(f"Policy: {policy_type}, Data: {policy_data}")
|
||||
|
|
|
|||
|
|
@ -24,7 +24,8 @@ class SearchDevDocsTool(BuiltinTool):
|
|||
tool_parameters (dict[str, Any]): The parameters for the tool, including 'doc' and 'topic'.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation, which can be a single message or a list of messages.
|
||||
ToolInvokeMessage | list[ToolInvokeMessage]: The result of the tool invocation,
|
||||
which can be a single message or a list of messages.
|
||||
"""
|
||||
doc = tool_parameters.get("doc", "")
|
||||
topic = tool_parameters.get("topic", "")
|
||||
|
|
|
|||
|
|
@ -70,7 +70,10 @@ class GitlabFilesTool(BuiltinTool):
|
|||
)
|
||||
else: # It's a file
|
||||
if is_repository:
|
||||
file_url = f"{domain}/api/v4/projects/{encoded_identifier}/repository/files/{item_path}/raw?ref={branch}"
|
||||
file_url = (
|
||||
f"{domain}/api/v4/projects/{encoded_identifier}/repository/files"
|
||||
f"/{item_path}/raw?ref={branch}"
|
||||
)
|
||||
else:
|
||||
file_url = (
|
||||
f"{domain}/api/v4/projects/{project_id}/repository/files/{item_path}/raw?ref={branch}"
|
||||
|
|
|
|||
|
|
@ -35,7 +35,8 @@ class GoogleTranslate(BuiltinTool):
|
|||
params = {"client": "gtx", "sl": "auto", "tl": dest, "dt": "t", "q": content}
|
||||
|
||||
headers = {
|
||||
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
|
||||
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)"
|
||||
" Chrome/91.0.4472.124 Safari/537.36"
|
||||
}
|
||||
|
||||
response_json = requests.get(url, params=params, headers=headers).json()
|
||||
|
|
|
|||
|
|
@ -114,7 +114,8 @@ class GetWorksheetFieldsTool(BuiltinTool):
|
|||
}
|
||||
fields.append(field)
|
||||
fields_list.append(
|
||||
f"|{field['id']}|{field['name']}|{field['type']}|{field['typeId']}|{field['description']}|{field['options'] if field['options'] else ''}|"
|
||||
f"|{field['id']}|{field['name']}|{field['type']}|{field['typeId']}|{field['description']}"
|
||||
f"|{field['options'] if field['options'] else ''}|"
|
||||
)
|
||||
|
||||
fields.append(
|
||||
|
|
|
|||
|
|
@ -112,7 +112,10 @@ class ListWorksheetRecordsTool(BuiltinTool):
|
|||
else:
|
||||
result_text = f"Found {result['total']} rows in worksheet \"{worksheet_name}\"."
|
||||
if result["total"] > 0:
|
||||
result_text += f" The following are {result['total'] if result['total'] < limit else limit} pieces of data presented in a table format:\n\n{table_header}"
|
||||
result_text += (
|
||||
f" The following are {result['total'] if result['total'] < limit else limit}"
|
||||
f" pieces of data presented in a table format:\n\n{table_header}"
|
||||
)
|
||||
for row in rows:
|
||||
result_values = []
|
||||
for f in fields:
|
||||
|
|
|
|||
|
|
@ -64,7 +64,10 @@ class SearchAPI:
|
|||
elif type == "link":
|
||||
if "answer_box" in res and "organic_result" in res["answer_box"]:
|
||||
if "title" in res["answer_box"]["organic_result"]:
|
||||
toret = f"[{res['answer_box']['organic_result']['title']}]({res['answer_box']['organic_result']['link']})\n"
|
||||
toret = (
|
||||
f"[{res['answer_box']['organic_result']['title']}]"
|
||||
f"({res['answer_box']['organic_result']['link']})\n"
|
||||
)
|
||||
elif "organic_results" in res and "link" in res["organic_results"][0]:
|
||||
toret = ""
|
||||
for item in res["organic_results"]:
|
||||
|
|
|
|||
|
|
@ -310,7 +310,8 @@ class StableDiffusionTool(BuiltinTool):
|
|||
),
|
||||
type=ToolParameter.ToolParameterType.STRING,
|
||||
form=ToolParameter.ToolParameterForm.LLM,
|
||||
llm_description="Image prompt of Stable Diffusion, you should describe the image you want to generate as a list of words as possible as detailed, the prompt must be written in English.",
|
||||
llm_description="Image prompt of Stable Diffusion, you should describe the image you want to generate"
|
||||
" as a list of words as possible as detailed, the prompt must be written in English.",
|
||||
required=True,
|
||||
),
|
||||
]
|
||||
|
|
@ -320,12 +321,14 @@ class StableDiffusionTool(BuiltinTool):
|
|||
name="image_id",
|
||||
label=I18nObject(en_US="image_id", zh_Hans="image_id"),
|
||||
human_description=I18nObject(
|
||||
en_US="Image id of the image you want to generate based on, if you want to generate image based on the default image, you can leave this field empty.",
|
||||
en_US="Image id of the image you want to generate based on, if you want to generate image based"
|
||||
" on the default image, you can leave this field empty.",
|
||||
zh_Hans="您想要生成的图像的图像 ID，如果您想要基于默认图像生成图像，则可以将此字段留空。",
|
||||
),
|
||||
type=ToolParameter.ToolParameterType.STRING,
|
||||
form=ToolParameter.ToolParameterForm.LLM,
|
||||
llm_description="Image id of the original image, you can leave this field empty if you want to generate a new image.",
|
||||
llm_description="Image id of the original image, you can leave this field empty if you want to"
|
||||
" generate a new image.",
|
||||
required=True,
|
||||
options=[
|
||||
ToolParameterOption(value=i.name, label=I18nObject(en_US=i.name, zh_Hans=i.name))
|
||||
|
|
@ -343,12 +346,14 @@ class StableDiffusionTool(BuiltinTool):
|
|||
name="model",
|
||||
label=I18nObject(en_US="Model", zh_Hans="Model"),
|
||||
human_description=I18nObject(
|
||||
en_US="Model of Stable Diffusion, you can check the official documentation of Stable Diffusion",
|
||||
en_US="Model of Stable Diffusion, you can check the official documentation"
|
||||
" of Stable Diffusion",
|
||||
zh_Hans="Stable Diffusion 的模型，您可以查看 Stable Diffusion 的官方文档",
|
||||
),
|
||||
type=ToolParameter.ToolParameterType.SELECT,
|
||||
form=ToolParameter.ToolParameterForm.FORM,
|
||||
llm_description="Model of Stable Diffusion, you can check the official documentation of Stable Diffusion",
|
||||
llm_description="Model of Stable Diffusion, you can check the official documentation"
|
||||
" of Stable Diffusion",
|
||||
required=True,
|
||||
default=models[0],
|
||||
options=[
|
||||
|
|
@ -367,12 +372,14 @@ class StableDiffusionTool(BuiltinTool):
|
|||
name="sampler_name",
|
||||
label=I18nObject(en_US="Sampling method", zh_Hans="Sampling method"),
|
||||
human_description=I18nObject(
|
||||
en_US="Sampling method of Stable Diffusion, you can check the official documentation of Stable Diffusion",
|
||||
en_US="Sampling method of Stable Diffusion, you can check the official documentation"
|
||||
" of Stable Diffusion",
|
||||
zh_Hans="Stable Diffusion 的Sampling method，您可以查看 Stable Diffusion 的官方文档",
|
||||
),
|
||||
type=ToolParameter.ToolParameterType.SELECT,
|
||||
form=ToolParameter.ToolParameterForm.FORM,
|
||||
llm_description="Sampling method of Stable Diffusion, you can check the official documentation of Stable Diffusion",
|
||||
llm_description="Sampling method of Stable Diffusion, you can check the official documentation"
|
||||
" of Stable Diffusion",
|
||||
required=True,
|
||||
default=sample_methods[0],
|
||||
options=[
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ class CreateListOnBoardTool(BuiltinTool):
|
|||
|
||||
Args:
|
||||
user_id (str): The ID of the user invoking the tool.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, including the board ID and list name.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation,
|
||||
including the board ID and list name.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage: The result of the tool invocation.
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ class CreateNewCardOnBoardTool(BuiltinTool):
|
|||
|
||||
Args:
|
||||
user_id (str): The ID of the user invoking the tool.
|
||||
tool_parameters (dict[str, Union[str, int, bool, None]]): The parameters for the tool invocation, including details for the new card.
|
||||
tool_parameters (dict[str, Union[str, int, bool, None]]): The parameters for the tool invocation,
|
||||
including details for the new card.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage: The result of the tool invocation.
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ class DeleteBoardTool(BuiltinTool):
|
|||
|
||||
Args:
|
||||
user_id (str): The ID of the user invoking the tool.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, including the board ID.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation,
|
||||
including the board ID.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage: The result of the tool invocation.
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ class DeleteCardByIdTool(BuiltinTool):
|
|||
|
||||
Args:
|
||||
user_id (str): The ID of the user invoking the tool.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, including the card ID.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation,
|
||||
including the card ID.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage: The result of the tool invocation.
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ class GetBoardActionsTool(BuiltinTool):
|
|||
|
||||
Args:
|
||||
user_id (str): The ID of the user invoking the tool.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, including the board ID.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation,
|
||||
including the board ID.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage: The result of the tool invocation.
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ class GetBoardByIdTool(BuiltinTool):
|
|||
|
||||
Args:
|
||||
user_id (str): The ID of the user invoking the tool.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, including the board ID.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation,
|
||||
including the board ID.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage: The result of the tool invocation.
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ class GetBoardCardsTool(BuiltinTool):
|
|||
|
||||
Args:
|
||||
user_id (str): The ID of the user invoking the tool.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, including the board ID.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation,
|
||||
including the board ID.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage: The result of the tool invocation.
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ class GetFilteredBoardCardsTool(BuiltinTool):
|
|||
|
||||
Args:
|
||||
user_id (str): The ID of the user invoking the tool.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, including the board ID and filter.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation,
|
||||
including the board ID and filter.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage: The result of the tool invocation.
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ class GetListsFromBoardTool(BuiltinTool):
|
|||
|
||||
Args:
|
||||
user_id (str): The ID of the user invoking the tool.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation, including the board ID.
|
||||
tool_parameters (dict[str, Union[str, int, bool]]): The parameters for the tool invocation,
|
||||
including the board ID.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage: The result of the tool invocation.
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ class UpdateBoardByIdTool(BuiltinTool):
|
|||
|
||||
Args:
|
||||
user_id (str): The ID of the user invoking the tool.
|
||||
tool_parameters (dict[str, Union[str, int, bool, None]]): The parameters for the tool invocation, including board ID and updates.
|
||||
tool_parameters (dict[str, Union[str, int, bool, None]]): The parameters for the tool invocation,
|
||||
including board ID and updates.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage: The result of the tool invocation.
|
||||
|
|
|
|||
|
|
@ -17,7 +17,8 @@ class UpdateCardByIdTool(BuiltinTool):
|
|||
|
||||
Args:
|
||||
user_id (str): The ID of the user invoking the tool.
|
||||
tool_parameters (dict[str, Union[str, int, bool, None]]): The parameters for the tool invocation, including the card ID and updates.
|
||||
tool_parameters (dict[str, Union[str, int, bool, None]]): The parameters for the tool invocation,
|
||||
including the card ID and updates.
|
||||
|
||||
Returns:
|
||||
ToolInvokeMessage: The result of the tool invocation.
|
||||
|
|
|
|||
|
|
@ -72,7 +72,8 @@ class SendMessageTool(BuiltinTool):
|
|||
tool_parameters (Dict[str, Any]): The parameters required for sending the message.
|
||||
|
||||
Returns:
|
||||
Union[ToolInvokeMessage, List[ToolInvokeMessage]]: The result of invoking the tool, which includes the status of the message sending operation.
|
||||
Union[ToolInvokeMessage, List[ToolInvokeMessage]]: The result of invoking the tool,
|
||||
which includes the status of the message sending operation.
|
||||
"""
|
||||
|
||||
def _invoke(
|
||||
|
|
|
|||
|
|
@ -1 +1 @@
|
|||
VECTORIZER_ICON_PNG = "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"
|
||||
VECTORIZER_ICON_PNG = "iVBORw0KGgoAAAANSUhEUgAAAGAAAABgCAYAAADimHc4AAAACXBIWXMAACxLAAAsSwGlPZapAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAboSURBVHgB7Z09bBxFFMffRoAvcQqbguBUxu4wCUikMCZ0TmQK4NLQJCJOlQIkokgEGhQ7NCFIKEhQuIqNnIaGMxRY2GVwmlggDHS+pIHELmIXMTEULPP3eeXz7e7szO7MvE1ufpKV03nuNn7/mfcxH7tEHo/H42lXgqwG1bGw65+/aTQM6K0gpJdCoi7ypCIMui5s9Qv9R1OVTqrVxoL1jPbpvH4hrIp/rnmj5+YOhTQ++1kwmdZgT9ovRi6EF4Xhv/XGL0Sv6OLXYMu0BokjYOSDcBQfJI8xhKFP/HAlqCW8v5vqubBr8yn6maCexxiIDR376LnWmBBzQZtPEvx+L3mMAleOZKb1/XgM2EOnyWMFZJKt78UEQKpJHisk2TYmgM967JFk2z3kYcULwIwXgBkvADNeAGa8AMw8Qcwc6N55/eAh0cYmGaOzQtR/kOhQX+M6+/c23r+3RlT/i2ipTrSyRqw4F+CwMMbgANHQwG7jRywLw/wqDDNzI79xYPjqa2L262jjtYzaT0QT3xEbsck4MXUakgWOvUx08liy0ZPYEKNhel4Y6AZpgR7/8Tvq1wEQ+sMJN6Nh9kqwy+bWYwAM8elZovNv6xmlU7iLs280RNO9ls51os/h/8eBVQEig8Dt5OXUsNrno2tluZw0cI3qUXKONQHy9sYkVHqnjntLA2LnFTAv1gSA+zBhfIDvkfVO/B4xRgWZn4fbe2WAnGJFAAxn03+I7PtUXdzE90Sjl4ne+6L4d5nCigAyYyHPn7tFdPN30uJwX/qI6jtISkQZFVLdhd9SrtNPTrFSB6QZBAaYntsptpAyfvk+KYOCamVR/XrNtLqepduiFnkh3g4iIw6YLAhlOJmKwB9zaarhApr/MPREjAZVisSU1s/KYsGzhmKXClYEWLm/8xpV7btXhcv5I7lt2vtJFA3q/T07r1HopdG5l5xhxQVdn28YFn8kBJCBOZmiPHio1m5QuJzlu9ntXApgZwSsNYJslvGjtjrfm8Sq4neceFUtz3dZCzwW09Gqo2hreuPN7HZRnNqa1BP1x8lhczVNK+zT0TqkjYAF4e7Okxoo2PZX5K4IrhNpb/P8FTK2S1+TcUq1HpBFmquJYo1qEYU6RVarJE0c2ooL7C5IRwBZ5nJ9joyRtk5hA3YBdHqWzG1gBKgE/bzMaK5LqMIugKrbUDHu59/YWVRBsWhrsYZdANV5HBUXYGNlC9dFBW8LdgH6FQVYUnQvkQgm3NH8YuO7bM4LsWZBfT3qRY9OxRyJgJRz+Ij+FDPEQ1C3GVMiWAVQ7f31u/ncytxi4wdZTbRGgdcHnpYLD/FcwSrAoOKizfKfVAiIF4kBMPK+Opfe1iWsMUB1BJh2BRgBabSNAOiFqkXYbcNFUF9P+u82FGdWTcEmgGrvh0FUppB1kC073muXEaDq/21kIjLxV9tFAC7/n5X6tkUM0PH/dcP+P0v41fvkFBYBVHs/MD0CDmVsOzEdb7JgEYDT/8uq4rpj44NSjwDTc/CyzV1gxbH7Ac4F0PH/S4ZHAOaFZLiY+2nFuQA6/t9kQMTCz1CG66tbWvWS4VwAVf9vugAbel6efqrsYbKBcwFeVNz8ajobyTppw2F84FQAnfl/kwER6wJZcWdBc7e2KZwKoOP/TVakWb0f7md+kVhwOwI0BDCFyq42rt4PSiuAiRGAEXdK4ZQlV+8HTgVwefwHvR7nhbOA0FwBGDgTIM/Z3SLXUj2hOW1wR10eSrs7Ou9eTB3jo/dzuh/gTABdn35c8dhpM3BxOmeTuXs/cDoCdDY4qe7l32pbaZxL1jF+GXo/cLotBcWVTiZU3T7RMn8rHiijW9FgauP4Ef1TLdhHWgacCgAj6tYCqGKjU/DNbqxIkMYZNs7MpxmnLuhmwYJna1dbdzHjY42hDL4/wqkA6HWuDkAngRH0iYVjRkVwnoZO/0gsuLwpkw7OBcAtwlwvfESHxctmfMBSiOG0oStj4HCF7T3+RWARwIU7QK/HbWlqls52mYJtezqMj3v34C5VOveFy8Ll4QoTsJ8Txp0RsW8/Os2im2LCtSC1RIqLw3RldTVplOKkPEYDhMAPqttnune2rzTv5Y+WKdEem2ixkWqZYSeDSUp3qwIYNOrR7cBjcbOORxkvADNeAGa8AMx4AZjxAjATf5Ab0Tp5rJBk2/iD3PAwYo8Vkmyb9CjDGfLYIaCp1rdiAnT8S5PeDVkgoDuVCsWeJxwToHZ163m3Z8hjloDGk54vn5gFbT/5eZw8phifvZz8XPlA9qmRj8JRCumi+OkljzbbrvxM0qPMm9rIqY6FXZubVBUinMbzcP3jbuXA6Mh2kMx07KPJJLfj8Xg8Hg/4H+KfFYb2WM4MAAAAAElFTkSuQmCC" # noqa: E501
|
||||
|
|
|
|||
|
|
@ -193,7 +193,10 @@ class ToolEngine:
|
|||
response.type == ToolInvokeMessage.MessageType.IMAGE_LINK
|
||||
or response.type == ToolInvokeMessage.MessageType.IMAGE
|
||||
):
|
||||
result += "image has been created and sent to user already, you do not need to create it, just tell the user to check it now."
|
||||
result += (
|
||||
"image has been created and sent to user already, you do not need to create it,"
|
||||
" just tell the user to check it now."
|
||||
)
|
||||
elif response.type == ToolInvokeMessage.MessageType.JSON:
|
||||
result += f"tool response: {json.dumps(response.message, ensure_ascii=False)}."
|
||||
else:
|
||||
|
|
|
|||
|
|
@ -89,7 +89,7 @@ class FeishuRequest:
|
|||
"content": "云文档\n多人实时协同，插入一切元素。不仅是在线文档，更是强大的创作和互动工具\n云文档：专为协作而生\n"
|
||||
}
|
||||
}
|
||||
"""
|
||||
""" # noqa: E501
|
||||
params = {
|
||||
"document_id": document_id,
|
||||
}
|
||||
|
|
|
|||
|
|
@ -43,7 +43,7 @@ class ToolFileMessageTransformer:
|
|||
result.append(
|
||||
ToolInvokeMessage(
|
||||
type=ToolInvokeMessage.MessageType.TEXT,
|
||||
message=f"Failed to download image: {message.message}, you can try to download it yourself.",
|
||||
message=f"Failed to download image: {message.message}, please try to download it manually.",
|
||||
meta=message.meta.copy() if message.meta is not None else {},
|
||||
save_as=message.save_as,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -315,7 +315,8 @@ class ApiBasedToolSchemaParser:
|
|||
yaml_error = e
|
||||
if loaded_content is None:
|
||||
raise ToolApiSchemaError(
|
||||
f"Invalid api schema, schema is neither json nor yaml. json error: {str(json_error)}, yaml error: {str(yaml_error)}"
|
||||
f"Invalid api schema, schema is neither json nor yaml. json error: {str(json_error)},"
|
||||
f" yaml error: {str(yaml_error)}"
|
||||
)
|
||||
|
||||
swagger_error = None
|
||||
|
|
@ -355,5 +356,6 @@ class ApiBasedToolSchemaParser:
|
|||
openapi_plugin_error = e
|
||||
|
||||
raise ToolApiSchemaError(
|
||||
f"Invalid api schema, openapi error: {str(openapi_error)}, swagger error: {str(swagger_error)}, openapi plugin error: {str(openapi_plugin_error)}"
|
||||
f"Invalid api schema, openapi error: {str(openapi_error)}, swagger error: {str(swagger_error)},"
|
||||
f" openapi plugin error: {str(openapi_plugin_error)}"
|
||||
)
|
||||
|
|
|
|||
|
|
@ -38,7 +38,8 @@ def page_result(text: str, cursor: int, max_length: int) -> str:
|
|||
def get_url(url: str, user_agent: str = None) -> str:
|
||||
"""Fetch URL and return the contents as a string."""
|
||||
headers = {
|
||||
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
|
||||
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)"
|
||||
" Chrome/91.0.4472.124 Safari/537.36"
|
||||
}
|
||||
if user_agent:
|
||||
headers["User-Agent"] = user_agent
|
||||
|
|
|
|||
|
|
@ -179,7 +179,8 @@ class CodeNode(BaseNode):
|
|||
)
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Output {prefix}.{output_name} is not a valid array. make sure all elements are of the same type."
|
||||
f"Output {prefix}.{output_name} is not a valid array."
|
||||
f" make sure all elements are of the same type."
|
||||
)
|
||||
elif isinstance(output_value, type(None)):
|
||||
pass
|
||||
|
|
@ -201,7 +202,8 @@ class CodeNode(BaseNode):
|
|||
transformed_result[output_name] = None
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Output {prefix}{dot}{output_name} is not an object, got {type(result.get(output_name))} instead."
|
||||
f"Output {prefix}{dot}{output_name} is not an object,"
|
||||
f" got {type(result.get(output_name))} instead."
|
||||
)
|
||||
else:
|
||||
transformed_result[output_name] = self._transform_result(
|
||||
|
|
@ -228,7 +230,8 @@ class CodeNode(BaseNode):
|
|||
transformed_result[output_name] = None
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Output {prefix}{dot}{output_name} is not an array, got {type(result.get(output_name))} instead."
|
||||
f"Output {prefix}{dot}{output_name} is not an array,"
|
||||
f" got {type(result.get(output_name))} instead."
|
||||
)
|
||||
else:
|
||||
if len(result[output_name]) > dify_config.CODE_MAX_NUMBER_ARRAY_LENGTH:
|
||||
|
|
@ -248,7 +251,8 @@ class CodeNode(BaseNode):
|
|||
transformed_result[output_name] = None
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Output {prefix}{dot}{output_name} is not an array, got {type(result.get(output_name))} instead."
|
||||
f"Output {prefix}{dot}{output_name} is not an array,"
|
||||
f" got {type(result.get(output_name))} instead."
|
||||
)
|
||||
else:
|
||||
if len(result[output_name]) > dify_config.CODE_MAX_STRING_ARRAY_LENGTH:
|
||||
|
|
@ -268,7 +272,8 @@ class CodeNode(BaseNode):
|
|||
transformed_result[output_name] = None
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Output {prefix}{dot}{output_name} is not an array, got {type(result.get(output_name))} instead."
|
||||
f"Output {prefix}{dot}{output_name} is not an array,"
|
||||
f" got {type(result.get(output_name))} instead."
|
||||
)
|
||||
else:
|
||||
if len(result[output_name]) > dify_config.CODE_MAX_OBJECT_ARRAY_LENGTH:
|
||||
|
|
@ -283,7 +288,8 @@ class CodeNode(BaseNode):
|
|||
pass
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Output {prefix}{dot}{output_name}[{i}] is not an object, got {type(value)} instead at index {i}."
|
||||
f"Output {prefix}{dot}{output_name}[{i}] is not an object,"
|
||||
f" got {type(value)} instead at index {i}."
|
||||
)
|
||||
|
||||
transformed_result[output_name] = [
|
||||
|
|
|
|||
|
|
@ -128,11 +128,12 @@ class KnowledgeRetrievalNode(BaseNode):
|
|||
weights = None
|
||||
elif node_data.multiple_retrieval_config.reranking_mode == "weighted_score":
|
||||
reranking_model = None
|
||||
vector_setting = node_data.multiple_retrieval_config.weights.vector_setting
|
||||
weights = {
|
||||
"vector_setting": {
|
||||
"vector_weight": node_data.multiple_retrieval_config.weights.vector_setting.vector_weight,
|
||||
"embedding_provider_name": node_data.multiple_retrieval_config.weights.vector_setting.embedding_provider_name,
|
||||
"embedding_model_name": node_data.multiple_retrieval_config.weights.vector_setting.embedding_model_name,
|
||||
"vector_weight": vector_setting.vector_weight,
|
||||
"embedding_provider_name": vector_setting.embedding_provider_name,
|
||||
"embedding_model_name": vector_setting.embedding_model_name,
|
||||
},
|
||||
"keyword_setting": {
|
||||
"keyword_weight": node_data.multiple_retrieval_config.weights.keyword_setting.keyword_weight
|
||||
|
|
|
|||
|
|
@ -23,7 +23,7 @@ Steps:
|
|||
To illustrate, if the task involves extracting a user's name and their request, your function call might look like this: Ensure your output follows a similar structure to examples.
|
||||
### Final Output
|
||||
Produce well-formatted function calls in json without XML tags, as shown in the example.
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
FUNCTION_CALLING_EXTRACTOR_USER_TEMPLATE = f"""extract structured information from context inside <context></context> XML tags by calling the function {FUNCTION_CALLING_EXTRACTOR_NAME} with the correct parameters with structure inside <structure></structure> XML tags.
|
||||
<context>
|
||||
|
|
@ -33,7 +33,7 @@ FUNCTION_CALLING_EXTRACTOR_USER_TEMPLATE = f"""extract structured information fr
|
|||
<structure>
|
||||
\x7bstructure\x7d
|
||||
</structure>
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
FUNCTION_CALLING_EXTRACTOR_EXAMPLE = [
|
||||
{
|
||||
|
|
@ -55,7 +55,8 @@ FUNCTION_CALLING_EXTRACTOR_EXAMPLE = [
|
|||
},
|
||||
},
|
||||
"assistant": {
|
||||
"text": "I need always call the function with the correct parameters. in this case, I need to call the function with the location parameter.",
|
||||
"text": "I need always call the function with the correct parameters."
|
||||
" in this case, I need to call the function with the location parameter.",
|
||||
"function_call": {"name": FUNCTION_CALLING_EXTRACTOR_NAME, "parameters": {"location": "San Francisco"}},
|
||||
},
|
||||
},
|
||||
|
|
@ -72,7 +73,8 @@ FUNCTION_CALLING_EXTRACTOR_EXAMPLE = [
|
|||
},
|
||||
},
|
||||
"assistant": {
|
||||
"text": "I need always call the function with the correct parameters. in this case, I need to call the function with the food parameter.",
|
||||
"text": "I need always call the function with the correct parameters."
|
||||
" in this case, I need to call the function with the food parameter.",
|
||||
"function_call": {"name": FUNCTION_CALLING_EXTRACTOR_NAME, "parameters": {"food": "apple pie"}},
|
||||
},
|
||||
},
|
||||
|
|
@ -117,7 +119,7 @@ Inside <text></text> XML tags, there is a text that I should extract parameters
|
|||
### Answer
|
||||
I should always output a valid JSON object. Output nothing other than the JSON object.
|
||||
```JSON
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
CHAT_GENERATE_JSON_PROMPT = """You should always follow the instructions and output a valid JSON object.
|
||||
The structure of the JSON object you can found in the instructions.
|
||||
|
|
|
|||
|
|
@ -12,13 +12,13 @@ QUESTION_CLASSIFIER_SYSTEM_PROMPT = """
|
|||
<histories>
|
||||
{histories}
|
||||
</histories>
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
QUESTION_CLASSIFIER_USER_PROMPT_1 = """
|
||||
{ "input_text": ["I recently had a great experience with your company. The service was prompt and the staff was very friendly."],
|
||||
"categories": [{"category_id":"f5660049-284f-41a7-b301-fd24176a711c","category_name":"Customer Service"},{"category_id":"8d007d06-f2c9-4be5-8ff6-cd4381c13c60","category_name":"Satisfaction"},{"category_id":"5fbbbb18-9843-466d-9b8e-b9bfbb9482c8","category_name":"Sales"},{"category_id":"23623c75-7184-4a2e-8226-466c2e4631e4","category_name":"Product"}],
|
||||
"classification_instructions": ["classify the text based on the feedback provided by customer"]}
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
QUESTION_CLASSIFIER_ASSISTANT_PROMPT_1 = """
|
||||
```json
|
||||
|
|
@ -32,7 +32,7 @@ QUESTION_CLASSIFIER_USER_PROMPT_2 = """
|
|||
{"input_text": ["bad service, slow to bring the food"],
|
||||
"categories": [{"category_id":"80fb86a0-4454-4bf5-924c-f253fdd83c02","category_name":"Food Quality"},{"category_id":"f6ff5bc3-aca0-4e4a-8627-e760d0aca78f","category_name":"Experience"},{"category_id":"cc771f63-74e7-4c61-882e-3eda9d8ba5d7","category_name":"Price"}],
|
||||
"classification_instructions": []}
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
||||
QUESTION_CLASSIFIER_ASSISTANT_PROMPT_2 = """
|
||||
```json
|
||||
|
|
@ -73,4 +73,4 @@ Here is the chat histories between human and assistant, inside <histories></hist
|
|||
### User Input
|
||||
{{"input_text" : ["{input_text}"], "categories" : {categories},"classification_instruction" : ["{classification_instructions}"]}}
|
||||
### Assistant Output
|
||||
"""
|
||||
""" # noqa: E501
|
||||
|
|
|
|||
|
|
@ -204,7 +204,8 @@ class PKCS1OAepCipher:
|
|||
|
||||
|
||||
def new(key, hashAlgo=None, mgfunc=None, label=b"", randfunc=None):
|
||||
"""Return a cipher object :class:`PKCS1OAEP_Cipher` that can be used to perform PKCS#1 OAEP encryption or decryption.
|
||||
"""Return a cipher object :class:`PKCS1OAEP_Cipher`
|
||||
that can be used to perform PKCS#1 OAEP encryption or decryption.
|
||||
|
||||
:param key:
|
||||
The key object to use to encrypt or decrypt the message.
|
||||
|
|
|
|||
|
|
@ -65,7 +65,10 @@ class Provider(db.Model):
|
|||
updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text("CURRENT_TIMESTAMP(0)"))
|
||||
|
||||
def __repr__(self):
|
||||
return f"<Provider(id={self.id}, tenant_id={self.tenant_id}, provider_name='{self.provider_name}', provider_type='{self.provider_type}')>"
|
||||
return (
|
||||
f"<Provider(id={self.id}, tenant_id={self.tenant_id}, provider_name='{self.provider_name}',"
|
||||
f" provider_type='{self.provider_type}')>"
|
||||
)
|
||||
|
||||
@property
|
||||
def token_is_set(self):
|
||||
|
|
|
|||
|
|
@ -62,7 +62,8 @@ class PublishedAppTool(db.Model):
|
|||
description = db.Column(db.Text, nullable=False)
|
||||
# llm_description of the tool, for LLM
|
||||
llm_description = db.Column(db.Text, nullable=False)
|
||||
# query description, query will be seem as a parameter of the tool, to describe this parameter to llm, we need this field
|
||||
# query description, query will be seem as a parameter of the tool,
|
||||
# to describe this parameter to llm, we need this field
|
||||
query_description = db.Column(db.Text, nullable=False)
|
||||
# query name, the name of the query parameter
|
||||
query_name = db.Column(db.String(40), nullable=False)
|
||||
|
|
|
|||
|
|
@ -246,7 +246,8 @@ class Workflow(db.Model):
|
|||
if any(var for var in value if not var.id):
|
||||
raise ValueError("environment variable require a unique id")
|
||||
|
||||
# Compare inputs and origin variables, if the value is HIDDEN_VALUE, use the origin variable value (only update `name`).
|
||||
# Compare inputs and origin variables,
|
||||
# if the value is HIDDEN_VALUE, use the origin variable value (only update `name`).
|
||||
origin_variables_dictionary = {var.id: var for var in self.environment_variables}
|
||||
for i, variable in enumerate(value):
|
||||
if variable.id in origin_variables_dictionary and variable.value == HIDDEN_VALUE:
|
||||
|
|
|
|||
2
api/poetry.lock
generated
2
api/poetry.lock
generated
|
|
@ -10388,4 +10388,4 @@ cffi = ["cffi (>=1.11)"]
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.10,<3.13"
|
||||
content-hash = "2dbff415c3c9ca95c8dcfb59fc088ce2c0d00037c44f386a34c87c98e1d8b942"
|
||||
content-hash = "8179c7e3f91b5a00054e26297040b1969f59b37cb9a707fbaa9c2ea419954718"
|
||||
|
|
|
|||
|
|
@ -27,7 +27,6 @@ select = [
|
|||
"W605", # invalid-escape-sequence
|
||||
]
|
||||
ignore = [
|
||||
"E501", # line-too-long
|
||||
"E402", # module-import-not-at-top-of-file
|
||||
"E711", # none-comparison
|
||||
"E712", # true-false-comparison
|
||||
|
|
@ -68,16 +67,19 @@ ignore = [
|
|||
"F401", # unused-import
|
||||
"F811", # redefined-while-unused
|
||||
]
|
||||
"tests/*" = [
|
||||
"F401", # unused-import
|
||||
"F811", # redefined-while-unused
|
||||
]
|
||||
"configs/*" = [
|
||||
"N802", # invalid-function-name
|
||||
]
|
||||
"libs/gmpy2_pkcs10aep_cipher.py" = [
|
||||
"N803", # invalid-argument-name
|
||||
]
|
||||
"migrations/versions/*" = [
|
||||
"E501", # line-too-long
|
||||
]
|
||||
"tests/*" = [
|
||||
"F401", # unused-import
|
||||
"F811", # redefined-while-unused
|
||||
]
|
||||
|
||||
[tool.ruff.format]
|
||||
exclude = [
|
||||
|
|
@ -270,4 +272,4 @@ optional = true
|
|||
|
||||
[tool.poetry.group.lint.dependencies]
|
||||
dotenv-linter = "~0.5.0"
|
||||
ruff = "~0.6.1"
|
||||
ruff = "~0.6.4"
|
||||
|
|
|
|||
|
|
@ -176,7 +176,8 @@ class ApiToolManageService:
|
|||
get api tool provider remote schema
|
||||
"""
|
||||
headers = {
|
||||
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36 Edg/120.0.0.0",
|
||||
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko)"
|
||||
" Chrome/120.0.0.0 Safari/537.36 Edg/120.0.0.0",
|
||||
"Accept": "*/*",
|
||||
}
|
||||
|
||||
|
|
|
|||
File diff suppressed because one or more lines are too long
|
|
@ -21,9 +21,9 @@ def test_segment_group_to_text():
|
|||
segments_group = parser.convert_template(template=template, variable_pool=variable_pool)
|
||||
|
||||
assert segments_group.text == "Hello, fake-user-id! Your query is fake-user-query. And your key is fake-secret-key."
|
||||
assert (
|
||||
segments_group.log
|
||||
== f"Hello, fake-user-id! Your query is fake-user-query. And your key is {encrypter.obfuscated_token('fake-secret-key')}."
|
||||
assert segments_group.log == (
|
||||
f"Hello, fake-user-id! Your query is fake-user-query."
|
||||
f" And your key is {encrypter.obfuscated_token('fake-secret-key')}."
|
||||
)
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user