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ragflow/api/db/services/canvas_service.py

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#
# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import json
import logging
import time
feat: add tag management for Agents with filtering and sorting (#14774) (#14799) ## Summary Closes #14774. Adds free-form tags on agents (UserCanvas) with full UI + API: - Stored as comma-separated `tags` column on `UserCanvas` with online migration. - New endpoints: `GET /v1/agents/tags` (aggregate counts) and `PUT /v1/agent/<id>/tags` (write). `GET /v1/agents` accepts a `tags=` query. - "Edit tags" item in agent dropdown opens a chip-style editor dialog; tags render as badges on each agent card. - New "Tags" facet in the agents filter bar, with counts. ## Implementation notes - **Tag matching is exact-token**: the SQL filter wraps stored tags as `,…,` and matches `,ml,` so `ml` doesn't match `ml-ops`. - **Server-side normalization** in `UserCanvasService.update_tags`: dedup (case-insensitive), per-tag cap of 64 chars, total length capped at 512 chars to fit the column, commas inside tag values are replaced with spaces. - **Tenant authorization**: `PUT /v1/agent/<id>/tags` gates on `UserCanvasService.accessible(canvas_id, tenant_id)`. - **Tag listing scope**: `UserCanvasService.list_tags` follows the same own + team-shared rule as `get_by_tenant_ids`. - **i18n**: keys added to `en.ts` and `zh.ts` only (per project convention; other locales fall back). - **`HomeCard`** gets a non-breaking `extra?: ReactNode` slot for the chip row; no `src/components/ui/` files modified. ## Test plan - [ ] Backend boot runs `migrate_db` → confirm `user_canvas.tags` column exists (`DESCRIBE user_canvas`). - [ ] Agents page renders cards normally (no console error from missing field). - [ ] `⋯ → Edit tags` opens a dialog that stays open (regression: dialog was unmounting with the dropdown). - [ ] Typing a tag without pressing Enter and clicking Save persists it (regression: last typed tag was being dropped). - [ ] Chip input supports Enter/comma to commit, Backspace on empty to remove, `×` to remove individual chip. - [ ] Tag containing a comma sent via API is stored with the comma replaced by a space. - [ ] 20 long tags sent via API does not error (length cap silently truncates). - [ ] "Tags" filter in the filter bar shows counts and narrows the list. - [ ] Filtering by `ml` does **not** return agents tagged `ml-ops`. - [ ] UI in Chinese shows 编辑标签 / 添加标签以整理和筛选你的智能体 etc. - [ ] `PUT /v1/agent/<other-tenant-id>/tags` returns `Agent not found or no permission.`
2026-05-13 06:41:32 -07:00
from functools import reduce
from operator import or_
from uuid import uuid4
from agent.canvas import Canvas
from api.db import CanvasCategory, TenantPermission
from api.db.db_models import DB, CanvasTemplate, User, UserCanvas, API4Conversation, UserCanvasVersion
from api.db.services.api_service import API4ConversationService
from api.db.services.common_service import CommonService
from api.db.services.user_canvas_version import UserCanvasVersionService
fix: offload blocking DB/Redis calls to thread pool for high-concurrency support (#13825) (#13941) ### What problem does this PR solve? Addresses event-loop blocking under high concurrency reported in #13825. When multiple requests hit the API simultaneously, synchronous DB/Redis calls block the async event loop, preventing Quart from handling other requests and causing cascading 502/504 timeouts. This PR wraps all remaining blocking DB/Redis calls in `canvas_app.py`, `chat_api.py`, `session.py`, and `canvas_service.py` with `await thread_pool_exec()` - Offload all synchronous `Service.*`, `REDIS_CONN.*`, and `APIToken.query` calls to the thread pool - Convert sync endpoint handlers (`list_chats`, `get_chat`, `templates`, `sessions`, etc.) to `async def` - Convert sync helper functions (`_ensure_owned_chat`, `_validate_llm_id`, `_validate_dataset_ids`, etc.) to async - no duplicate sync/async pairs - Wrap `CanvasReplicaService` Redis IO calls (`bootstrap`, `replace_for_set`, `commit_after_run`) - Use `asyncio.gather()` for concurrent file uploads and chat response building **Note:** This fixes the code-level event-loop blocking, which is a prerequisite for handling concurrent requests. For the full "30 concurrent requests without 502/504" goal described in the issue, users should also tune deployment config: - `WS=4` or higher (HTTP worker processes, default 1) - `MAX_CONCURRENT_CHATS=50` (default 10) - `SANDBOX_EXECUTOR_MANAGER_POOL_SIZE` for workflow-heavy workloads ### Performance verification Reviewer asked for a before-vs-after comparison ([comment](https://github.com/infiniflow/ragflow/pull/13941#issuecomment-4393667231)). I built a self-contained microbenchmark that reproduces the exact failure mode this PR targets: an async handler that performs blocking DB/Redis-style calls (50 ms each, 3 per request, 30 concurrent requests) is run twice — once with the pre-PR pattern (sync call directly inside the async handler) and once with the post-PR pattern (`await thread_pool_exec(...)`). The benchmark imports nothing from RAGFlow except `thread_pool_exec` itself, so it is hermetic and reproducible (`THREAD_POOL_MAX_WORKERS=128`, Python 3.13.12). **Throughput — wall-clock for 30 concurrent requests (lower is better)** | flavour | wall(s) | p50(s) | p95(s) | max(s) | |---|---:|---:|---:|---:| | before | 4.986 | 0.158 | 0.207 | 0.269 | | after | 0.248 | 0.181 | 0.230 | 0.231 | The pre-PR handler serializes the entire load on the event-loop thread, so 30 × 3 × 50 ms ≈ 4.5 s shows up as the wall time. The post-PR handler parallelizes the blocking work across the thread pool and finishes the same load in 248 ms — a **~20× speedup** on this workload. **Event-loop responsiveness — latency of an unrelated probe coroutine while the 30 slow requests are running (lower is better)** | flavour | samples | probe p50 (ms) | probe p95 (ms) | probe max (ms) | |---|---:|---:|---:|---:| | before | 1 | 5442.26 | 5442.26 | 5442.26 | | after | 28 | 0.88 | 11.53 | 98.02 | This is the metric that maps directly to "the API still answers other requests while one is busy". A 5 ms-interval probe was scheduled while the 30 slow handlers ran. With the pre-PR code the event loop was frozen for the entire duration of the blocking work, so only one probe sample was ever picked up and it waited **5,442 ms**. After the PR, 28 probe samples landed with **p50 0.88 ms / p95 11.53 ms**, meaning unrelated requests are no longer starved by the slow ones. That is the regression mode behind the cascading 502/504s reported in #13825. <details> <summary>Raw benchmark output</summary> ``` config: 30 concurrent requests, 3 blocking calls of 50ms each per request, THREAD_POOL_MAX_WORKERS=128 === Throughput (lower wall is better) === flavour wall(s) p50(s) p95(s) max(s) before 4.986 0.158 0.207 0.269 after 0.248 0.181 0.230 0.231 === Event-loop responsiveness (lower probe latency is better) === flavour samples probe p50(ms) probe p95(ms) probe max(ms) before 1 5442.26 5442.26 5442.26 after 28 0.88 11.53 98.02 ``` </details> The benchmark script is included as a comment on the PR for reproducibility. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] Performance Improvement Closes [#13825](https://github.com/infiniflow/ragflow/issues/13825) --------- Co-authored-by: tmimmanuel <tmimmanuel@users.noreply.github.com> Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
2026-05-10 21:08:55 -10:00
from common.misc_utils import get_uuid, thread_pool_exec
from api.utils.api_utils import get_data_openai
import tiktoken
from peewee import fn
class CanvasTemplateService(CommonService):
model = CanvasTemplate
class DataFlowTemplateService(CommonService):
"""
Alias of CanvasTemplateService
"""
model = CanvasTemplate
class UserCanvasService(CommonService):
model = UserCanvas
@classmethod
@DB.connection_context()
def get_list(cls, tenant_id,
page_number, items_per_page, orderby, desc, id, title, canvas_category=CanvasCategory.Agent):
agents = cls.model.select()
if id:
agents = agents.where(cls.model.id == id)
if title:
agents = agents.where(cls.model.title == title)
agents = agents.where(cls.model.user_id == tenant_id)
agents = agents.where(cls.model.canvas_category == canvas_category)
if desc:
agents = agents.order_by(cls.model.getter_by(orderby).desc())
else:
agents = agents.order_by(cls.model.getter_by(orderby).asc())
agents = agents.paginate(page_number, items_per_page)
return list(agents.dicts())
@classmethod
@DB.connection_context()
def get_all_agents_by_tenant_ids(cls, tenant_ids, user_id):
# will get all permitted agents, be cautious
fields = [
cls.model.id,
cls.model.avatar,
cls.model.title,
cls.model.permission,
cls.model.canvas_type,
cls.model.canvas_category
]
# find team agents and owned agents
agents = cls.model.select(*fields).where(
(cls.model.user_id.in_(tenant_ids) & (cls.model.permission == TenantPermission.TEAM.value)) | (
cls.model.user_id == user_id
)
)
# sort by create_time, asc
agents.order_by(cls.model.create_time.asc())
# maybe cause slow query by deep paginate, optimize later
offset, limit = 0, 50
res = []
while True:
ag_batch = agents.offset(offset).limit(limit)
_temp = list(ag_batch.dicts())
if not _temp:
break
res.extend(_temp)
offset += limit
return res
@classmethod
@DB.connection_context()
def get_by_canvas_id(cls, pid):
try:
fields = [
cls.model.id,
cls.model.avatar,
cls.model.title,
cls.model.dsl,
cls.model.description,
cls.model.permission,
cls.model.update_time,
cls.model.user_id,
cls.model.create_time,
cls.model.create_date,
cls.model.update_date,
cls.model.canvas_category,
User.nickname,
User.avatar.alias('tenant_avatar'),
]
agents = cls.model.select(*fields) \
.join(User, on=(cls.model.user_id == User.id)) \
.where(cls.model.id == pid)
# obj = cls.model.query(id=pid)[0]
return True, agents.dicts()[0]
except Exception as e:
logging.exception(e)
return False, None
@classmethod
@DB.connection_context()
def get_basic_info_by_canvas_ids(cls, canvas_id):
fields = [
cls.model.id,
cls.model.avatar,
cls.model.user_id,
cls.model.title,
cls.model.permission,
cls.model.canvas_category
]
return cls.model.select(*fields).where(cls.model.id.in_(canvas_id)).dicts()
@classmethod
@DB.connection_context()
Feat: Agent api (#14157) ### What problem does this PR solve? 1. **List agents** **Prev API**: - `/v1/canvas/list GET` - `/api/v1/agents GET` **Current API**: `/api/v2/agents GET` 2. **Get canvas template** **Prev API**: `/v1/canvas/templates GET` **Current API**: `/api/v2/agents/templates GET` 3. **Delete an agent** **Prev API**: - `/v1/canvas/rm POST` - `/api/v1/agents/<agent_id> DELETE` **Current API**: `/api/v2/agents/<agent_id> DELETE` 4. **Update an agent** **Prev API**: - `/api/v1/agents/<agent_id> PUT` - `/v1/canvas/setting POST ` **Current API**: `/api/v2/agents/<agent_id> PATCH` 5. **Create an agent** **Prev API**: - `/v1/canvas/set POST` - `/api/v1/agents POST` **Current API**: `/api/v2/agents POST` 6. **Get an agent** **Prev API**: - `/v1/canvas/get/<canvas_id> GET ` **Current API**: `/api/v2/agents/<agent_id> GET` 7. **Reset an agent** **Prev API**: - `/v1/canvas/reset POST` **Current API**: `/api/v2/agents/<agent_id>/reset POST` 8. **Upload a file to an agent** **Prev API**: - `/v1/canvas/upload/<canvas_id> POST` **Current API**: `/api/v2/agents/<agent_id>/upload POST` 9. **Input form** **Prev API**: - `/v1/canvas/input_form GET` **Current API**: `/api/v2/agents/<agent_id>/components/<component_id>/input-form GET` 10. **Debug an agent** **Prev API**: - `/v1/canvas/debug POST` **Current API**: `/api/v2/agents/<agent_id>/components/<component_id>/debug POST` 11. **Trace an agent** **Prev API**: - `/v1/canvas/trace GET` **Current API**: `/api/v2/agents/<agent_id>/logs/<message_id> GET` 12. **Get an agent version list** **Prev API**: - `/v1/canvas/getlistversion/<canvas_id>` **Current API**: `/api/v2/agents/<agent_id>/versions GET` 13. **Get a version of agent** **Prev API**: - `/v1/canvas/getversion/<version_id>` **Current API**: `/api/v2/agents/<agent_id>/versions/<version_id> GET` 14. **Test db connection** **Prev API**: - `/v1/canvas/test_db_connect POST` **Current API**: `/api/v2/agents/test_db_connection` 15. **Rerun the agent** **Prev API**: - `/v1/canvas/rerun POST` **Current API**: `/api/v2/agents/rerun POST` 16. **Get prompts** **Prev API**: - `/v1/canvas/prompts GET` **Current API**: `/api/v2/agents/prompts GET` ### Type of change - [x] New Feature (non-breaking change which adds functionality) --------- Co-authored-by: chanx <1243304602@qq.com>
2026-04-24 10:02:22 +08:00
def get_by_tenant_ids(
cls,
joined_tenant_ids,
user_id,
page_number,
items_per_page,
orderby,
desc,
keywords,
canvas_category=None,
feat: add tag management for Agents with filtering and sorting (#14774) (#14799) ## Summary Closes #14774. Adds free-form tags on agents (UserCanvas) with full UI + API: - Stored as comma-separated `tags` column on `UserCanvas` with online migration. - New endpoints: `GET /v1/agents/tags` (aggregate counts) and `PUT /v1/agent/<id>/tags` (write). `GET /v1/agents` accepts a `tags=` query. - "Edit tags" item in agent dropdown opens a chip-style editor dialog; tags render as badges on each agent card. - New "Tags" facet in the agents filter bar, with counts. ## Implementation notes - **Tag matching is exact-token**: the SQL filter wraps stored tags as `,…,` and matches `,ml,` so `ml` doesn't match `ml-ops`. - **Server-side normalization** in `UserCanvasService.update_tags`: dedup (case-insensitive), per-tag cap of 64 chars, total length capped at 512 chars to fit the column, commas inside tag values are replaced with spaces. - **Tenant authorization**: `PUT /v1/agent/<id>/tags` gates on `UserCanvasService.accessible(canvas_id, tenant_id)`. - **Tag listing scope**: `UserCanvasService.list_tags` follows the same own + team-shared rule as `get_by_tenant_ids`. - **i18n**: keys added to `en.ts` and `zh.ts` only (per project convention; other locales fall back). - **`HomeCard`** gets a non-breaking `extra?: ReactNode` slot for the chip row; no `src/components/ui/` files modified. ## Test plan - [ ] Backend boot runs `migrate_db` → confirm `user_canvas.tags` column exists (`DESCRIBE user_canvas`). - [ ] Agents page renders cards normally (no console error from missing field). - [ ] `⋯ → Edit tags` opens a dialog that stays open (regression: dialog was unmounting with the dropdown). - [ ] Typing a tag without pressing Enter and clicking Save persists it (regression: last typed tag was being dropped). - [ ] Chip input supports Enter/comma to commit, Backspace on empty to remove, `×` to remove individual chip. - [ ] Tag containing a comma sent via API is stored with the comma replaced by a space. - [ ] 20 long tags sent via API does not error (length cap silently truncates). - [ ] "Tags" filter in the filter bar shows counts and narrows the list. - [ ] Filtering by `ml` does **not** return agents tagged `ml-ops`. - [ ] UI in Chinese shows 编辑标签 / 添加标签以整理和筛选你的智能体 etc. - [ ] `PUT /v1/agent/<other-tenant-id>/tags` returns `Agent not found or no permission.`
2026-05-13 06:41:32 -07:00
tags=None,
Feat: Agent api (#14157) ### What problem does this PR solve? 1. **List agents** **Prev API**: - `/v1/canvas/list GET` - `/api/v1/agents GET` **Current API**: `/api/v2/agents GET` 2. **Get canvas template** **Prev API**: `/v1/canvas/templates GET` **Current API**: `/api/v2/agents/templates GET` 3. **Delete an agent** **Prev API**: - `/v1/canvas/rm POST` - `/api/v1/agents/<agent_id> DELETE` **Current API**: `/api/v2/agents/<agent_id> DELETE` 4. **Update an agent** **Prev API**: - `/api/v1/agents/<agent_id> PUT` - `/v1/canvas/setting POST ` **Current API**: `/api/v2/agents/<agent_id> PATCH` 5. **Create an agent** **Prev API**: - `/v1/canvas/set POST` - `/api/v1/agents POST` **Current API**: `/api/v2/agents POST` 6. **Get an agent** **Prev API**: - `/v1/canvas/get/<canvas_id> GET ` **Current API**: `/api/v2/agents/<agent_id> GET` 7. **Reset an agent** **Prev API**: - `/v1/canvas/reset POST` **Current API**: `/api/v2/agents/<agent_id>/reset POST` 8. **Upload a file to an agent** **Prev API**: - `/v1/canvas/upload/<canvas_id> POST` **Current API**: `/api/v2/agents/<agent_id>/upload POST` 9. **Input form** **Prev API**: - `/v1/canvas/input_form GET` **Current API**: `/api/v2/agents/<agent_id>/components/<component_id>/input-form GET` 10. **Debug an agent** **Prev API**: - `/v1/canvas/debug POST` **Current API**: `/api/v2/agents/<agent_id>/components/<component_id>/debug POST` 11. **Trace an agent** **Prev API**: - `/v1/canvas/trace GET` **Current API**: `/api/v2/agents/<agent_id>/logs/<message_id> GET` 12. **Get an agent version list** **Prev API**: - `/v1/canvas/getlistversion/<canvas_id>` **Current API**: `/api/v2/agents/<agent_id>/versions GET` 13. **Get a version of agent** **Prev API**: - `/v1/canvas/getversion/<version_id>` **Current API**: `/api/v2/agents/<agent_id>/versions/<version_id> GET` 14. **Test db connection** **Prev API**: - `/v1/canvas/test_db_connect POST` **Current API**: `/api/v2/agents/test_db_connection` 15. **Rerun the agent** **Prev API**: - `/v1/canvas/rerun POST` **Current API**: `/api/v2/agents/rerun POST` 16. **Get prompts** **Prev API**: - `/v1/canvas/prompts GET` **Current API**: `/api/v2/agents/prompts GET` ### Type of change - [x] New Feature (non-breaking change which adds functionality) --------- Co-authored-by: chanx <1243304602@qq.com>
2026-04-24 10:02:22 +08:00
):
fields = [
cls.model.id,
cls.model.avatar,
cls.model.title,
cls.model.description,
cls.model.permission,
Feat: Use data pipeline to visualize the parsing configuration of the knowledge base (#10423) ### What problem does this PR solve? #9869 ### Type of change - [x] New Feature (non-breaking change which adds functionality) --------- Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: jinhai <haijin.chn@gmail.com> Signed-off-by: Jin Hai <haijin.chn@gmail.com> Co-authored-by: chanx <1243304602@qq.com> Co-authored-by: balibabu <cike8899@users.noreply.github.com> Co-authored-by: Lynn <lynn_inf@hotmail.com> Co-authored-by: 纷繁下的无奈 <zhileihuang@126.com> Co-authored-by: huangzl <huangzl@shinemo.com> Co-authored-by: writinwaters <93570324+writinwaters@users.noreply.github.com> Co-authored-by: Wilmer <33392318@qq.com> Co-authored-by: Adrian Weidig <adrianweidig@gmx.net> Co-authored-by: Zhichang Yu <yuzhichang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Yongteng Lei <yongtengrey@outlook.com> Co-authored-by: Liu An <asiro@qq.com> Co-authored-by: buua436 <66937541+buua436@users.noreply.github.com> Co-authored-by: BadwomanCraZY <511528396@qq.com> Co-authored-by: cucusenok <31804608+cucusenok@users.noreply.github.com> Co-authored-by: Russell Valentine <russ@coldstonelabs.org> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Billy Bao <newyorkupperbay@gmail.com> Co-authored-by: Zhedong Cen <cenzhedong2@126.com> Co-authored-by: TensorNull <129579691+TensorNull@users.noreply.github.com> Co-authored-by: TensorNull <tensor.null@gmail.com> Co-authored-by: TeslaZY <TeslaZY@outlook.com> Co-authored-by: Ajay <160579663+aybanda@users.noreply.github.com> Co-authored-by: AB <aj@Ajays-MacBook-Air.local> Co-authored-by: 天海蒼灆 <huangaoqin@tecpie.com> Co-authored-by: He Wang <wanghechn@qq.com> Co-authored-by: Atsushi Hatakeyama <atu729@icloud.com> Co-authored-by: Jin Hai <haijin.chn@gmail.com> Co-authored-by: Mohamed Mathari <155896313+melmathari@users.noreply.github.com> Co-authored-by: Mohamed Mathari <nocodeventure@Mac-mini-van-Mohamed.fritz.box> Co-authored-by: Stephen Hu <stephenhu@seismic.com> Co-authored-by: Shaun Zhang <zhangwfjh@users.noreply.github.com> Co-authored-by: zhimeng123 <60221886+zhimeng123@users.noreply.github.com> Co-authored-by: mxc <mxc@example.com> Co-authored-by: Dominik Novotný <50611433+SgtMarmite@users.noreply.github.com> Co-authored-by: EVGENY M <168018528+rjohny55@users.noreply.github.com> Co-authored-by: mcoder6425 <mcoder64@gmail.com> Co-authored-by: lemsn <lemsn@msn.com> Co-authored-by: lemsn <lemsn@126.com> Co-authored-by: Adrian Gora <47756404+adagora@users.noreply.github.com> Co-authored-by: Womsxd <45663319+Womsxd@users.noreply.github.com> Co-authored-by: FatMii <39074672+FatMii@users.noreply.github.com>
2025-10-09 12:36:19 +08:00
cls.model.user_id.alias("tenant_id"),
User.nickname,
User.avatar.alias('tenant_avatar'),
cls.model.update_time,
cls.model.canvas_category,
feat: add tag management for Agents with filtering and sorting (#14774) (#14799) ## Summary Closes #14774. Adds free-form tags on agents (UserCanvas) with full UI + API: - Stored as comma-separated `tags` column on `UserCanvas` with online migration. - New endpoints: `GET /v1/agents/tags` (aggregate counts) and `PUT /v1/agent/<id>/tags` (write). `GET /v1/agents` accepts a `tags=` query. - "Edit tags" item in agent dropdown opens a chip-style editor dialog; tags render as badges on each agent card. - New "Tags" facet in the agents filter bar, with counts. ## Implementation notes - **Tag matching is exact-token**: the SQL filter wraps stored tags as `,…,` and matches `,ml,` so `ml` doesn't match `ml-ops`. - **Server-side normalization** in `UserCanvasService.update_tags`: dedup (case-insensitive), per-tag cap of 64 chars, total length capped at 512 chars to fit the column, commas inside tag values are replaced with spaces. - **Tenant authorization**: `PUT /v1/agent/<id>/tags` gates on `UserCanvasService.accessible(canvas_id, tenant_id)`. - **Tag listing scope**: `UserCanvasService.list_tags` follows the same own + team-shared rule as `get_by_tenant_ids`. - **i18n**: keys added to `en.ts` and `zh.ts` only (per project convention; other locales fall back). - **`HomeCard`** gets a non-breaking `extra?: ReactNode` slot for the chip row; no `src/components/ui/` files modified. ## Test plan - [ ] Backend boot runs `migrate_db` → confirm `user_canvas.tags` column exists (`DESCRIBE user_canvas`). - [ ] Agents page renders cards normally (no console error from missing field). - [ ] `⋯ → Edit tags` opens a dialog that stays open (regression: dialog was unmounting with the dropdown). - [ ] Typing a tag without pressing Enter and clicking Save persists it (regression: last typed tag was being dropped). - [ ] Chip input supports Enter/comma to commit, Backspace on empty to remove, `×` to remove individual chip. - [ ] Tag containing a comma sent via API is stored with the comma replaced by a space. - [ ] 20 long tags sent via API does not error (length cap silently truncates). - [ ] "Tags" filter in the filter bar shows counts and narrows the list. - [ ] Filtering by `ml` does **not** return agents tagged `ml-ops`. - [ ] UI in Chinese shows 编辑标签 / 添加标签以整理和筛选你的智能体 etc. - [ ] `PUT /v1/agent/<other-tenant-id>/tags` returns `Agent not found or no permission.`
2026-05-13 06:41:32 -07:00
cls.model.tags,
]
if keywords:
agents = cls.model.select(*fields).join(User, on=(cls.model.user_id == User.id)).where(
(((cls.model.user_id.in_(joined_tenant_ids)) & (cls.model.permission == TenantPermission.TEAM.value)) | (cls.model.user_id == user_id)),
(fn.LOWER(cls.model.title).contains(keywords.lower()))
)
else:
agents = cls.model.select(*fields).join(User, on=(cls.model.user_id == User.id)).where(
(((cls.model.user_id.in_(joined_tenant_ids)) & (cls.model.permission == TenantPermission.TEAM.value)) | (cls.model.user_id == user_id))
)
Feat: Use data pipeline to visualize the parsing configuration of the knowledge base (#10423) ### What problem does this PR solve? #9869 ### Type of change - [x] New Feature (non-breaking change which adds functionality) --------- Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: jinhai <haijin.chn@gmail.com> Signed-off-by: Jin Hai <haijin.chn@gmail.com> Co-authored-by: chanx <1243304602@qq.com> Co-authored-by: balibabu <cike8899@users.noreply.github.com> Co-authored-by: Lynn <lynn_inf@hotmail.com> Co-authored-by: 纷繁下的无奈 <zhileihuang@126.com> Co-authored-by: huangzl <huangzl@shinemo.com> Co-authored-by: writinwaters <93570324+writinwaters@users.noreply.github.com> Co-authored-by: Wilmer <33392318@qq.com> Co-authored-by: Adrian Weidig <adrianweidig@gmx.net> Co-authored-by: Zhichang Yu <yuzhichang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Yongteng Lei <yongtengrey@outlook.com> Co-authored-by: Liu An <asiro@qq.com> Co-authored-by: buua436 <66937541+buua436@users.noreply.github.com> Co-authored-by: BadwomanCraZY <511528396@qq.com> Co-authored-by: cucusenok <31804608+cucusenok@users.noreply.github.com> Co-authored-by: Russell Valentine <russ@coldstonelabs.org> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Billy Bao <newyorkupperbay@gmail.com> Co-authored-by: Zhedong Cen <cenzhedong2@126.com> Co-authored-by: TensorNull <129579691+TensorNull@users.noreply.github.com> Co-authored-by: TensorNull <tensor.null@gmail.com> Co-authored-by: TeslaZY <TeslaZY@outlook.com> Co-authored-by: Ajay <160579663+aybanda@users.noreply.github.com> Co-authored-by: AB <aj@Ajays-MacBook-Air.local> Co-authored-by: 天海蒼灆 <huangaoqin@tecpie.com> Co-authored-by: He Wang <wanghechn@qq.com> Co-authored-by: Atsushi Hatakeyama <atu729@icloud.com> Co-authored-by: Jin Hai <haijin.chn@gmail.com> Co-authored-by: Mohamed Mathari <155896313+melmathari@users.noreply.github.com> Co-authored-by: Mohamed Mathari <nocodeventure@Mac-mini-van-Mohamed.fritz.box> Co-authored-by: Stephen Hu <stephenhu@seismic.com> Co-authored-by: Shaun Zhang <zhangwfjh@users.noreply.github.com> Co-authored-by: zhimeng123 <60221886+zhimeng123@users.noreply.github.com> Co-authored-by: mxc <mxc@example.com> Co-authored-by: Dominik Novotný <50611433+SgtMarmite@users.noreply.github.com> Co-authored-by: EVGENY M <168018528+rjohny55@users.noreply.github.com> Co-authored-by: mcoder6425 <mcoder64@gmail.com> Co-authored-by: lemsn <lemsn@msn.com> Co-authored-by: lemsn <lemsn@126.com> Co-authored-by: Adrian Gora <47756404+adagora@users.noreply.github.com> Co-authored-by: Womsxd <45663319+Womsxd@users.noreply.github.com> Co-authored-by: FatMii <39074672+FatMii@users.noreply.github.com>
2025-10-09 12:36:19 +08:00
if canvas_category:
agents = agents.where(cls.model.canvas_category == canvas_category)
feat: add tag management for Agents with filtering and sorting (#14774) (#14799) ## Summary Closes #14774. Adds free-form tags on agents (UserCanvas) with full UI + API: - Stored as comma-separated `tags` column on `UserCanvas` with online migration. - New endpoints: `GET /v1/agents/tags` (aggregate counts) and `PUT /v1/agent/<id>/tags` (write). `GET /v1/agents` accepts a `tags=` query. - "Edit tags" item in agent dropdown opens a chip-style editor dialog; tags render as badges on each agent card. - New "Tags" facet in the agents filter bar, with counts. ## Implementation notes - **Tag matching is exact-token**: the SQL filter wraps stored tags as `,…,` and matches `,ml,` so `ml` doesn't match `ml-ops`. - **Server-side normalization** in `UserCanvasService.update_tags`: dedup (case-insensitive), per-tag cap of 64 chars, total length capped at 512 chars to fit the column, commas inside tag values are replaced with spaces. - **Tenant authorization**: `PUT /v1/agent/<id>/tags` gates on `UserCanvasService.accessible(canvas_id, tenant_id)`. - **Tag listing scope**: `UserCanvasService.list_tags` follows the same own + team-shared rule as `get_by_tenant_ids`. - **i18n**: keys added to `en.ts` and `zh.ts` only (per project convention; other locales fall back). - **`HomeCard`** gets a non-breaking `extra?: ReactNode` slot for the chip row; no `src/components/ui/` files modified. ## Test plan - [ ] Backend boot runs `migrate_db` → confirm `user_canvas.tags` column exists (`DESCRIBE user_canvas`). - [ ] Agents page renders cards normally (no console error from missing field). - [ ] `⋯ → Edit tags` opens a dialog that stays open (regression: dialog was unmounting with the dropdown). - [ ] Typing a tag without pressing Enter and clicking Save persists it (regression: last typed tag was being dropped). - [ ] Chip input supports Enter/comma to commit, Backspace on empty to remove, `×` to remove individual chip. - [ ] Tag containing a comma sent via API is stored with the comma replaced by a space. - [ ] 20 long tags sent via API does not error (length cap silently truncates). - [ ] "Tags" filter in the filter bar shows counts and narrows the list. - [ ] Filtering by `ml` does **not** return agents tagged `ml-ops`. - [ ] UI in Chinese shows 编辑标签 / 添加标签以整理和筛选你的智能体 etc. - [ ] `PUT /v1/agent/<other-tenant-id>/tags` returns `Agent not found or no permission.`
2026-05-13 06:41:32 -07:00
if tags:
tag_list = [t.strip() for t in tags if t and t.strip()] if isinstance(tags, (list, tuple)) else [t.strip() for t in str(tags).split(",") if t.strip()]
if tag_list:
# Wrap value with commas so 'ml' doesn't match 'ml-ops'.
wrapped = fn.CONCAT(",", cls.model.tags, ",")
clauses = [wrapped.contains(f",{t},") for t in tag_list]
agents = agents.where(reduce(or_, clauses))
if desc:
agents = agents.order_by(cls.model.getter_by(orderby).desc())
else:
agents = agents.order_by(cls.model.getter_by(orderby).asc())
Feat: Use data pipeline to visualize the parsing configuration of the knowledge base (#10423) ### What problem does this PR solve? #9869 ### Type of change - [x] New Feature (non-breaking change which adds functionality) --------- Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: jinhai <haijin.chn@gmail.com> Signed-off-by: Jin Hai <haijin.chn@gmail.com> Co-authored-by: chanx <1243304602@qq.com> Co-authored-by: balibabu <cike8899@users.noreply.github.com> Co-authored-by: Lynn <lynn_inf@hotmail.com> Co-authored-by: 纷繁下的无奈 <zhileihuang@126.com> Co-authored-by: huangzl <huangzl@shinemo.com> Co-authored-by: writinwaters <93570324+writinwaters@users.noreply.github.com> Co-authored-by: Wilmer <33392318@qq.com> Co-authored-by: Adrian Weidig <adrianweidig@gmx.net> Co-authored-by: Zhichang Yu <yuzhichang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Yongteng Lei <yongtengrey@outlook.com> Co-authored-by: Liu An <asiro@qq.com> Co-authored-by: buua436 <66937541+buua436@users.noreply.github.com> Co-authored-by: BadwomanCraZY <511528396@qq.com> Co-authored-by: cucusenok <31804608+cucusenok@users.noreply.github.com> Co-authored-by: Russell Valentine <russ@coldstonelabs.org> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Billy Bao <newyorkupperbay@gmail.com> Co-authored-by: Zhedong Cen <cenzhedong2@126.com> Co-authored-by: TensorNull <129579691+TensorNull@users.noreply.github.com> Co-authored-by: TensorNull <tensor.null@gmail.com> Co-authored-by: TeslaZY <TeslaZY@outlook.com> Co-authored-by: Ajay <160579663+aybanda@users.noreply.github.com> Co-authored-by: AB <aj@Ajays-MacBook-Air.local> Co-authored-by: 天海蒼灆 <huangaoqin@tecpie.com> Co-authored-by: He Wang <wanghechn@qq.com> Co-authored-by: Atsushi Hatakeyama <atu729@icloud.com> Co-authored-by: Jin Hai <haijin.chn@gmail.com> Co-authored-by: Mohamed Mathari <155896313+melmathari@users.noreply.github.com> Co-authored-by: Mohamed Mathari <nocodeventure@Mac-mini-van-Mohamed.fritz.box> Co-authored-by: Stephen Hu <stephenhu@seismic.com> Co-authored-by: Shaun Zhang <zhangwfjh@users.noreply.github.com> Co-authored-by: zhimeng123 <60221886+zhimeng123@users.noreply.github.com> Co-authored-by: mxc <mxc@example.com> Co-authored-by: Dominik Novotný <50611433+SgtMarmite@users.noreply.github.com> Co-authored-by: EVGENY M <168018528+rjohny55@users.noreply.github.com> Co-authored-by: mcoder6425 <mcoder64@gmail.com> Co-authored-by: lemsn <lemsn@msn.com> Co-authored-by: lemsn <lemsn@126.com> Co-authored-by: Adrian Gora <47756404+adagora@users.noreply.github.com> Co-authored-by: Womsxd <45663319+Womsxd@users.noreply.github.com> Co-authored-by: FatMii <39074672+FatMii@users.noreply.github.com>
2025-10-09 12:36:19 +08:00
count = agents.count()
Feat: Use data pipeline to visualize the parsing configuration of the knowledge base (#10423) ### What problem does this PR solve? #9869 ### Type of change - [x] New Feature (non-breaking change which adds functionality) --------- Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: jinhai <haijin.chn@gmail.com> Signed-off-by: Jin Hai <haijin.chn@gmail.com> Co-authored-by: chanx <1243304602@qq.com> Co-authored-by: balibabu <cike8899@users.noreply.github.com> Co-authored-by: Lynn <lynn_inf@hotmail.com> Co-authored-by: 纷繁下的无奈 <zhileihuang@126.com> Co-authored-by: huangzl <huangzl@shinemo.com> Co-authored-by: writinwaters <93570324+writinwaters@users.noreply.github.com> Co-authored-by: Wilmer <33392318@qq.com> Co-authored-by: Adrian Weidig <adrianweidig@gmx.net> Co-authored-by: Zhichang Yu <yuzhichang@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Yongteng Lei <yongtengrey@outlook.com> Co-authored-by: Liu An <asiro@qq.com> Co-authored-by: buua436 <66937541+buua436@users.noreply.github.com> Co-authored-by: BadwomanCraZY <511528396@qq.com> Co-authored-by: cucusenok <31804608+cucusenok@users.noreply.github.com> Co-authored-by: Russell Valentine <russ@coldstonelabs.org> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Billy Bao <newyorkupperbay@gmail.com> Co-authored-by: Zhedong Cen <cenzhedong2@126.com> Co-authored-by: TensorNull <129579691+TensorNull@users.noreply.github.com> Co-authored-by: TensorNull <tensor.null@gmail.com> Co-authored-by: TeslaZY <TeslaZY@outlook.com> Co-authored-by: Ajay <160579663+aybanda@users.noreply.github.com> Co-authored-by: AB <aj@Ajays-MacBook-Air.local> Co-authored-by: 天海蒼灆 <huangaoqin@tecpie.com> Co-authored-by: He Wang <wanghechn@qq.com> Co-authored-by: Atsushi Hatakeyama <atu729@icloud.com> Co-authored-by: Jin Hai <haijin.chn@gmail.com> Co-authored-by: Mohamed Mathari <155896313+melmathari@users.noreply.github.com> Co-authored-by: Mohamed Mathari <nocodeventure@Mac-mini-van-Mohamed.fritz.box> Co-authored-by: Stephen Hu <stephenhu@seismic.com> Co-authored-by: Shaun Zhang <zhangwfjh@users.noreply.github.com> Co-authored-by: zhimeng123 <60221886+zhimeng123@users.noreply.github.com> Co-authored-by: mxc <mxc@example.com> Co-authored-by: Dominik Novotný <50611433+SgtMarmite@users.noreply.github.com> Co-authored-by: EVGENY M <168018528+rjohny55@users.noreply.github.com> Co-authored-by: mcoder6425 <mcoder64@gmail.com> Co-authored-by: lemsn <lemsn@msn.com> Co-authored-by: lemsn <lemsn@126.com> Co-authored-by: Adrian Gora <47756404+adagora@users.noreply.github.com> Co-authored-by: Womsxd <45663319+Womsxd@users.noreply.github.com> Co-authored-by: FatMii <39074672+FatMii@users.noreply.github.com>
2025-10-09 12:36:19 +08:00
if page_number and items_per_page:
agents = agents.paginate(page_number, items_per_page)
agents_list = list(agents.dicts())
# Get latest release time for each canvas
if agents_list:
canvas_ids = [a['id'] for a in agents_list]
release_times = (
UserCanvasVersion.select(UserCanvasVersion.user_canvas_id, fn.MAX(UserCanvasVersion.create_time).alias("release_time"))
.where((UserCanvasVersion.user_canvas_id.in_(canvas_ids)) & (UserCanvasVersion.release))
.group_by(UserCanvasVersion.user_canvas_id)
)
release_time_map = {r.user_canvas_id: r.release_time for r in release_times}
for agent in agents_list:
agent['release_time'] = release_time_map.get(agent['id'])
return agents_list, count
feat: add tag management for Agents with filtering and sorting (#14774) (#14799) ## Summary Closes #14774. Adds free-form tags on agents (UserCanvas) with full UI + API: - Stored as comma-separated `tags` column on `UserCanvas` with online migration. - New endpoints: `GET /v1/agents/tags` (aggregate counts) and `PUT /v1/agent/<id>/tags` (write). `GET /v1/agents` accepts a `tags=` query. - "Edit tags" item in agent dropdown opens a chip-style editor dialog; tags render as badges on each agent card. - New "Tags" facet in the agents filter bar, with counts. ## Implementation notes - **Tag matching is exact-token**: the SQL filter wraps stored tags as `,…,` and matches `,ml,` so `ml` doesn't match `ml-ops`. - **Server-side normalization** in `UserCanvasService.update_tags`: dedup (case-insensitive), per-tag cap of 64 chars, total length capped at 512 chars to fit the column, commas inside tag values are replaced with spaces. - **Tenant authorization**: `PUT /v1/agent/<id>/tags` gates on `UserCanvasService.accessible(canvas_id, tenant_id)`. - **Tag listing scope**: `UserCanvasService.list_tags` follows the same own + team-shared rule as `get_by_tenant_ids`. - **i18n**: keys added to `en.ts` and `zh.ts` only (per project convention; other locales fall back). - **`HomeCard`** gets a non-breaking `extra?: ReactNode` slot for the chip row; no `src/components/ui/` files modified. ## Test plan - [ ] Backend boot runs `migrate_db` → confirm `user_canvas.tags` column exists (`DESCRIBE user_canvas`). - [ ] Agents page renders cards normally (no console error from missing field). - [ ] `⋯ → Edit tags` opens a dialog that stays open (regression: dialog was unmounting with the dropdown). - [ ] Typing a tag without pressing Enter and clicking Save persists it (regression: last typed tag was being dropped). - [ ] Chip input supports Enter/comma to commit, Backspace on empty to remove, `×` to remove individual chip. - [ ] Tag containing a comma sent via API is stored with the comma replaced by a space. - [ ] 20 long tags sent via API does not error (length cap silently truncates). - [ ] "Tags" filter in the filter bar shows counts and narrows the list. - [ ] Filtering by `ml` does **not** return agents tagged `ml-ops`. - [ ] UI in Chinese shows 编辑标签 / 添加标签以整理和筛选你的智能体 etc. - [ ] `PUT /v1/agent/<other-tenant-id>/tags` returns `Agent not found or no permission.`
2026-05-13 06:41:32 -07:00
@classmethod
@DB.connection_context()
def list_tags(cls, joined_tenant_ids, user_id, canvas_category=None):
"""Return {tag: agent_count} aggregated across agents visible to the user."""
query = cls.model.select(cls.model.tags).where(
((cls.model.user_id.in_(joined_tenant_ids)) & (cls.model.permission == TenantPermission.TEAM.value)) | (cls.model.user_id == user_id)
)
if canvas_category:
query = query.where(cls.model.canvas_category == canvas_category)
counts: dict[str, int] = {}
for row in query.dicts():
for t in (row.get("tags") or "").split(","):
t = t.strip()
if t:
counts[t] = counts.get(t, 0) + 1
logging.info(
"UserCanvasService.list_tags user=%s canvas_category=%s tags_count=%d",
user_id,
canvas_category,
len(counts),
)
return counts
# Tag storage is a single comma-separated CharField(max_length=512);
# commas inside a tag would corrupt the encoding, so strip them on write.
TAGS_FIELD_MAX = 512
TAG_MAX_LEN = 64
@classmethod
@DB.connection_context()
def update_tags(cls, canvas_id, tags):
"""Persist a normalized comma-separated tag string for the given canvas."""
if isinstance(tags, (list, tuple)):
cleaned = [str(t).replace(",", " ").strip() for t in tags if t and str(t).strip()]
else:
cleaned = [t.strip() for t in str(tags or "").split(",") if t.strip()]
# Dedupe (case-insensitive, preserve order), cap individual tag length,
# then truncate the joined value so it always fits the column.
seen = set()
normalized = []
used = 0
for t in cleaned:
t = t[: cls.TAG_MAX_LEN]
key = t.lower()
if key in seen:
continue
extra = len(t) + (1 if normalized else 0)
if used + extra > cls.TAGS_FIELD_MAX:
break
seen.add(key)
normalized.append(t)
used += extra
value = ",".join(normalized)
rows_affected = cls.model.update(tags=value).where(cls.model.id == canvas_id).execute()
logging.info(
"UserCanvasService.update_tags canvas_id=%s tags_count=%d rows=%d",
canvas_id,
len(normalized),
rows_affected,
)
return rows_affected
@classmethod
@DB.connection_context()
def accessible(cls, canvas_id, tenant_id):
from api.db.services.user_service import UserTenantService
e, c = UserCanvasService.get_by_canvas_id(canvas_id)
if not e:
return False
tids = [t.tenant_id for t in UserTenantService.query(user_id=tenant_id)]
Feat: Agent api (#14157) ### What problem does this PR solve? 1. **List agents** **Prev API**: - `/v1/canvas/list GET` - `/api/v1/agents GET` **Current API**: `/api/v2/agents GET` 2. **Get canvas template** **Prev API**: `/v1/canvas/templates GET` **Current API**: `/api/v2/agents/templates GET` 3. **Delete an agent** **Prev API**: - `/v1/canvas/rm POST` - `/api/v1/agents/<agent_id> DELETE` **Current API**: `/api/v2/agents/<agent_id> DELETE` 4. **Update an agent** **Prev API**: - `/api/v1/agents/<agent_id> PUT` - `/v1/canvas/setting POST ` **Current API**: `/api/v2/agents/<agent_id> PATCH` 5. **Create an agent** **Prev API**: - `/v1/canvas/set POST` - `/api/v1/agents POST` **Current API**: `/api/v2/agents POST` 6. **Get an agent** **Prev API**: - `/v1/canvas/get/<canvas_id> GET ` **Current API**: `/api/v2/agents/<agent_id> GET` 7. **Reset an agent** **Prev API**: - `/v1/canvas/reset POST` **Current API**: `/api/v2/agents/<agent_id>/reset POST` 8. **Upload a file to an agent** **Prev API**: - `/v1/canvas/upload/<canvas_id> POST` **Current API**: `/api/v2/agents/<agent_id>/upload POST` 9. **Input form** **Prev API**: - `/v1/canvas/input_form GET` **Current API**: `/api/v2/agents/<agent_id>/components/<component_id>/input-form GET` 10. **Debug an agent** **Prev API**: - `/v1/canvas/debug POST` **Current API**: `/api/v2/agents/<agent_id>/components/<component_id>/debug POST` 11. **Trace an agent** **Prev API**: - `/v1/canvas/trace GET` **Current API**: `/api/v2/agents/<agent_id>/logs/<message_id> GET` 12. **Get an agent version list** **Prev API**: - `/v1/canvas/getlistversion/<canvas_id>` **Current API**: `/api/v2/agents/<agent_id>/versions GET` 13. **Get a version of agent** **Prev API**: - `/v1/canvas/getversion/<version_id>` **Current API**: `/api/v2/agents/<agent_id>/versions/<version_id> GET` 14. **Test db connection** **Prev API**: - `/v1/canvas/test_db_connect POST` **Current API**: `/api/v2/agents/test_db_connection` 15. **Rerun the agent** **Prev API**: - `/v1/canvas/rerun POST` **Current API**: `/api/v2/agents/rerun POST` 16. **Get prompts** **Prev API**: - `/v1/canvas/prompts GET` **Current API**: `/api/v2/agents/prompts GET` ### Type of change - [x] New Feature (non-breaking change which adds functionality) --------- Co-authored-by: chanx <1243304602@qq.com>
2026-04-24 10:02:22 +08:00
if c["user_id"] == tenant_id:
return True
if c["user_id"] not in tids:
return False
if c["permission"] != TenantPermission.TEAM.value:
return False
return True
@classmethod
def get_agent_dsl_with_release(cls, agent_id, release_mode=False, tenant_id=None):
e, cvs = cls.get_by_id(agent_id)
if not e:
raise LookupError("Agent not found.")
if release_mode:
released_version = UserCanvasVersionService.get_latest_released(agent_id)
if not released_version:
raise PermissionError("No available published version")
dsl = released_version.dsl
else:
dsl = cvs.dsl
if not isinstance(dsl, str):
dsl = json.dumps(dsl, ensure_ascii=False)
return cvs, dsl
async def completion(tenant_id, agent_id, session_id=None, **kwargs):
query = kwargs.get("query", "") or kwargs.get("question", "")
files = kwargs.get("files", [])
inputs = kwargs.get("inputs", {})
user_id = kwargs.get("user_id", "")
chat_template_kwargs = kwargs.get("chat_template_kwargs")
custom_header = kwargs.get("custom_header", "")
release_mode = str(kwargs.get("release", "")).strip().lower()
if session_id:
fix: offload blocking DB/Redis calls to thread pool for high-concurrency support (#13825) (#13941) ### What problem does this PR solve? Addresses event-loop blocking under high concurrency reported in #13825. When multiple requests hit the API simultaneously, synchronous DB/Redis calls block the async event loop, preventing Quart from handling other requests and causing cascading 502/504 timeouts. This PR wraps all remaining blocking DB/Redis calls in `canvas_app.py`, `chat_api.py`, `session.py`, and `canvas_service.py` with `await thread_pool_exec()` - Offload all synchronous `Service.*`, `REDIS_CONN.*`, and `APIToken.query` calls to the thread pool - Convert sync endpoint handlers (`list_chats`, `get_chat`, `templates`, `sessions`, etc.) to `async def` - Convert sync helper functions (`_ensure_owned_chat`, `_validate_llm_id`, `_validate_dataset_ids`, etc.) to async - no duplicate sync/async pairs - Wrap `CanvasReplicaService` Redis IO calls (`bootstrap`, `replace_for_set`, `commit_after_run`) - Use `asyncio.gather()` for concurrent file uploads and chat response building **Note:** This fixes the code-level event-loop blocking, which is a prerequisite for handling concurrent requests. For the full "30 concurrent requests without 502/504" goal described in the issue, users should also tune deployment config: - `WS=4` or higher (HTTP worker processes, default 1) - `MAX_CONCURRENT_CHATS=50` (default 10) - `SANDBOX_EXECUTOR_MANAGER_POOL_SIZE` for workflow-heavy workloads ### Performance verification Reviewer asked for a before-vs-after comparison ([comment](https://github.com/infiniflow/ragflow/pull/13941#issuecomment-4393667231)). I built a self-contained microbenchmark that reproduces the exact failure mode this PR targets: an async handler that performs blocking DB/Redis-style calls (50 ms each, 3 per request, 30 concurrent requests) is run twice — once with the pre-PR pattern (sync call directly inside the async handler) and once with the post-PR pattern (`await thread_pool_exec(...)`). The benchmark imports nothing from RAGFlow except `thread_pool_exec` itself, so it is hermetic and reproducible (`THREAD_POOL_MAX_WORKERS=128`, Python 3.13.12). **Throughput — wall-clock for 30 concurrent requests (lower is better)** | flavour | wall(s) | p50(s) | p95(s) | max(s) | |---|---:|---:|---:|---:| | before | 4.986 | 0.158 | 0.207 | 0.269 | | after | 0.248 | 0.181 | 0.230 | 0.231 | The pre-PR handler serializes the entire load on the event-loop thread, so 30 × 3 × 50 ms ≈ 4.5 s shows up as the wall time. The post-PR handler parallelizes the blocking work across the thread pool and finishes the same load in 248 ms — a **~20× speedup** on this workload. **Event-loop responsiveness — latency of an unrelated probe coroutine while the 30 slow requests are running (lower is better)** | flavour | samples | probe p50 (ms) | probe p95 (ms) | probe max (ms) | |---|---:|---:|---:|---:| | before | 1 | 5442.26 | 5442.26 | 5442.26 | | after | 28 | 0.88 | 11.53 | 98.02 | This is the metric that maps directly to "the API still answers other requests while one is busy". A 5 ms-interval probe was scheduled while the 30 slow handlers ran. With the pre-PR code the event loop was frozen for the entire duration of the blocking work, so only one probe sample was ever picked up and it waited **5,442 ms**. After the PR, 28 probe samples landed with **p50 0.88 ms / p95 11.53 ms**, meaning unrelated requests are no longer starved by the slow ones. That is the regression mode behind the cascading 502/504s reported in #13825. <details> <summary>Raw benchmark output</summary> ``` config: 30 concurrent requests, 3 blocking calls of 50ms each per request, THREAD_POOL_MAX_WORKERS=128 === Throughput (lower wall is better) === flavour wall(s) p50(s) p95(s) max(s) before 4.986 0.158 0.207 0.269 after 0.248 0.181 0.230 0.231 === Event-loop responsiveness (lower probe latency is better) === flavour samples probe p50(ms) probe p95(ms) probe max(ms) before 1 5442.26 5442.26 5442.26 after 28 0.88 11.53 98.02 ``` </details> The benchmark script is included as a comment on the PR for reproducibility. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] Performance Improvement Closes [#13825](https://github.com/infiniflow/ragflow/issues/13825) --------- Co-authored-by: tmimmanuel <tmimmanuel@users.noreply.github.com> Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
2026-05-10 21:08:55 -10:00
e, conv = await thread_pool_exec(API4ConversationService.get_by_id, session_id)
if not e:
raise LookupError("Session not found!")
if not conv.message:
conv.message = []
if not isinstance(conv.dsl, str):
conv.dsl = json.dumps(conv.dsl, ensure_ascii=False)
canvas = Canvas(conv.dsl, tenant_id, agent_id, canvas_id=agent_id, custom_header=custom_header)
else:
fix: offload blocking DB/Redis calls to thread pool for high-concurrency support (#13825) (#13941) ### What problem does this PR solve? Addresses event-loop blocking under high concurrency reported in #13825. When multiple requests hit the API simultaneously, synchronous DB/Redis calls block the async event loop, preventing Quart from handling other requests and causing cascading 502/504 timeouts. This PR wraps all remaining blocking DB/Redis calls in `canvas_app.py`, `chat_api.py`, `session.py`, and `canvas_service.py` with `await thread_pool_exec()` - Offload all synchronous `Service.*`, `REDIS_CONN.*`, and `APIToken.query` calls to the thread pool - Convert sync endpoint handlers (`list_chats`, `get_chat`, `templates`, `sessions`, etc.) to `async def` - Convert sync helper functions (`_ensure_owned_chat`, `_validate_llm_id`, `_validate_dataset_ids`, etc.) to async - no duplicate sync/async pairs - Wrap `CanvasReplicaService` Redis IO calls (`bootstrap`, `replace_for_set`, `commit_after_run`) - Use `asyncio.gather()` for concurrent file uploads and chat response building **Note:** This fixes the code-level event-loop blocking, which is a prerequisite for handling concurrent requests. For the full "30 concurrent requests without 502/504" goal described in the issue, users should also tune deployment config: - `WS=4` or higher (HTTP worker processes, default 1) - `MAX_CONCURRENT_CHATS=50` (default 10) - `SANDBOX_EXECUTOR_MANAGER_POOL_SIZE` for workflow-heavy workloads ### Performance verification Reviewer asked for a before-vs-after comparison ([comment](https://github.com/infiniflow/ragflow/pull/13941#issuecomment-4393667231)). I built a self-contained microbenchmark that reproduces the exact failure mode this PR targets: an async handler that performs blocking DB/Redis-style calls (50 ms each, 3 per request, 30 concurrent requests) is run twice — once with the pre-PR pattern (sync call directly inside the async handler) and once with the post-PR pattern (`await thread_pool_exec(...)`). The benchmark imports nothing from RAGFlow except `thread_pool_exec` itself, so it is hermetic and reproducible (`THREAD_POOL_MAX_WORKERS=128`, Python 3.13.12). **Throughput — wall-clock for 30 concurrent requests (lower is better)** | flavour | wall(s) | p50(s) | p95(s) | max(s) | |---|---:|---:|---:|---:| | before | 4.986 | 0.158 | 0.207 | 0.269 | | after | 0.248 | 0.181 | 0.230 | 0.231 | The pre-PR handler serializes the entire load on the event-loop thread, so 30 × 3 × 50 ms ≈ 4.5 s shows up as the wall time. The post-PR handler parallelizes the blocking work across the thread pool and finishes the same load in 248 ms — a **~20× speedup** on this workload. **Event-loop responsiveness — latency of an unrelated probe coroutine while the 30 slow requests are running (lower is better)** | flavour | samples | probe p50 (ms) | probe p95 (ms) | probe max (ms) | |---|---:|---:|---:|---:| | before | 1 | 5442.26 | 5442.26 | 5442.26 | | after | 28 | 0.88 | 11.53 | 98.02 | This is the metric that maps directly to "the API still answers other requests while one is busy". A 5 ms-interval probe was scheduled while the 30 slow handlers ran. With the pre-PR code the event loop was frozen for the entire duration of the blocking work, so only one probe sample was ever picked up and it waited **5,442 ms**. After the PR, 28 probe samples landed with **p50 0.88 ms / p95 11.53 ms**, meaning unrelated requests are no longer starved by the slow ones. That is the regression mode behind the cascading 502/504s reported in #13825. <details> <summary>Raw benchmark output</summary> ``` config: 30 concurrent requests, 3 blocking calls of 50ms each per request, THREAD_POOL_MAX_WORKERS=128 === Throughput (lower wall is better) === flavour wall(s) p50(s) p95(s) max(s) before 4.986 0.158 0.207 0.269 after 0.248 0.181 0.230 0.231 === Event-loop responsiveness (lower probe latency is better) === flavour samples probe p50(ms) probe p95(ms) probe max(ms) before 1 5442.26 5442.26 5442.26 after 28 0.88 11.53 98.02 ``` </details> The benchmark script is included as a comment on the PR for reproducibility. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] Performance Improvement Closes [#13825](https://github.com/infiniflow/ragflow/issues/13825) --------- Co-authored-by: tmimmanuel <tmimmanuel@users.noreply.github.com> Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
2026-05-10 21:08:55 -10:00
cvs, dsl = await thread_pool_exec(UserCanvasService.get_agent_dsl_with_release, agent_id, release_mode=release_mode == "true", tenant_id=tenant_id)
session_id = get_uuid()
canvas = Canvas(dsl, tenant_id, agent_id, canvas_id=cvs.id, custom_header=custom_header)
canvas.reset()
# Get the version title based on release_mode
fix: offload blocking DB/Redis calls to thread pool for high-concurrency support (#13825) (#13941) ### What problem does this PR solve? Addresses event-loop blocking under high concurrency reported in #13825. When multiple requests hit the API simultaneously, synchronous DB/Redis calls block the async event loop, preventing Quart from handling other requests and causing cascading 502/504 timeouts. This PR wraps all remaining blocking DB/Redis calls in `canvas_app.py`, `chat_api.py`, `session.py`, and `canvas_service.py` with `await thread_pool_exec()` - Offload all synchronous `Service.*`, `REDIS_CONN.*`, and `APIToken.query` calls to the thread pool - Convert sync endpoint handlers (`list_chats`, `get_chat`, `templates`, `sessions`, etc.) to `async def` - Convert sync helper functions (`_ensure_owned_chat`, `_validate_llm_id`, `_validate_dataset_ids`, etc.) to async - no duplicate sync/async pairs - Wrap `CanvasReplicaService` Redis IO calls (`bootstrap`, `replace_for_set`, `commit_after_run`) - Use `asyncio.gather()` for concurrent file uploads and chat response building **Note:** This fixes the code-level event-loop blocking, which is a prerequisite for handling concurrent requests. For the full "30 concurrent requests without 502/504" goal described in the issue, users should also tune deployment config: - `WS=4` or higher (HTTP worker processes, default 1) - `MAX_CONCURRENT_CHATS=50` (default 10) - `SANDBOX_EXECUTOR_MANAGER_POOL_SIZE` for workflow-heavy workloads ### Performance verification Reviewer asked for a before-vs-after comparison ([comment](https://github.com/infiniflow/ragflow/pull/13941#issuecomment-4393667231)). I built a self-contained microbenchmark that reproduces the exact failure mode this PR targets: an async handler that performs blocking DB/Redis-style calls (50 ms each, 3 per request, 30 concurrent requests) is run twice — once with the pre-PR pattern (sync call directly inside the async handler) and once with the post-PR pattern (`await thread_pool_exec(...)`). The benchmark imports nothing from RAGFlow except `thread_pool_exec` itself, so it is hermetic and reproducible (`THREAD_POOL_MAX_WORKERS=128`, Python 3.13.12). **Throughput — wall-clock for 30 concurrent requests (lower is better)** | flavour | wall(s) | p50(s) | p95(s) | max(s) | |---|---:|---:|---:|---:| | before | 4.986 | 0.158 | 0.207 | 0.269 | | after | 0.248 | 0.181 | 0.230 | 0.231 | The pre-PR handler serializes the entire load on the event-loop thread, so 30 × 3 × 50 ms ≈ 4.5 s shows up as the wall time. The post-PR handler parallelizes the blocking work across the thread pool and finishes the same load in 248 ms — a **~20× speedup** on this workload. **Event-loop responsiveness — latency of an unrelated probe coroutine while the 30 slow requests are running (lower is better)** | flavour | samples | probe p50 (ms) | probe p95 (ms) | probe max (ms) | |---|---:|---:|---:|---:| | before | 1 | 5442.26 | 5442.26 | 5442.26 | | after | 28 | 0.88 | 11.53 | 98.02 | This is the metric that maps directly to "the API still answers other requests while one is busy". A 5 ms-interval probe was scheduled while the 30 slow handlers ran. With the pre-PR code the event loop was frozen for the entire duration of the blocking work, so only one probe sample was ever picked up and it waited **5,442 ms**. After the PR, 28 probe samples landed with **p50 0.88 ms / p95 11.53 ms**, meaning unrelated requests are no longer starved by the slow ones. That is the regression mode behind the cascading 502/504s reported in #13825. <details> <summary>Raw benchmark output</summary> ``` config: 30 concurrent requests, 3 blocking calls of 50ms each per request, THREAD_POOL_MAX_WORKERS=128 === Throughput (lower wall is better) === flavour wall(s) p50(s) p95(s) max(s) before 4.986 0.158 0.207 0.269 after 0.248 0.181 0.230 0.231 === Event-loop responsiveness (lower probe latency is better) === flavour samples probe p50(ms) probe p95(ms) probe max(ms) before 1 5442.26 5442.26 5442.26 after 28 0.88 11.53 98.02 ``` </details> The benchmark script is included as a comment on the PR for reproducibility. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] Performance Improvement Closes [#13825](https://github.com/infiniflow/ragflow/issues/13825) --------- Co-authored-by: tmimmanuel <tmimmanuel@users.noreply.github.com> Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
2026-05-10 21:08:55 -10:00
version_title = await thread_pool_exec(UserCanvasVersionService.get_latest_version_title, cvs.id, release_mode=release_mode == "true")
conv = {"id": session_id, "dialog_id": cvs.id, "user_id": user_id, "message": [], "source": "agent", "dsl": dsl, "reference": [], "version_title": version_title}
fix: offload blocking DB/Redis calls to thread pool for high-concurrency support (#13825) (#13941) ### What problem does this PR solve? Addresses event-loop blocking under high concurrency reported in #13825. When multiple requests hit the API simultaneously, synchronous DB/Redis calls block the async event loop, preventing Quart from handling other requests and causing cascading 502/504 timeouts. This PR wraps all remaining blocking DB/Redis calls in `canvas_app.py`, `chat_api.py`, `session.py`, and `canvas_service.py` with `await thread_pool_exec()` - Offload all synchronous `Service.*`, `REDIS_CONN.*`, and `APIToken.query` calls to the thread pool - Convert sync endpoint handlers (`list_chats`, `get_chat`, `templates`, `sessions`, etc.) to `async def` - Convert sync helper functions (`_ensure_owned_chat`, `_validate_llm_id`, `_validate_dataset_ids`, etc.) to async - no duplicate sync/async pairs - Wrap `CanvasReplicaService` Redis IO calls (`bootstrap`, `replace_for_set`, `commit_after_run`) - Use `asyncio.gather()` for concurrent file uploads and chat response building **Note:** This fixes the code-level event-loop blocking, which is a prerequisite for handling concurrent requests. For the full "30 concurrent requests without 502/504" goal described in the issue, users should also tune deployment config: - `WS=4` or higher (HTTP worker processes, default 1) - `MAX_CONCURRENT_CHATS=50` (default 10) - `SANDBOX_EXECUTOR_MANAGER_POOL_SIZE` for workflow-heavy workloads ### Performance verification Reviewer asked for a before-vs-after comparison ([comment](https://github.com/infiniflow/ragflow/pull/13941#issuecomment-4393667231)). I built a self-contained microbenchmark that reproduces the exact failure mode this PR targets: an async handler that performs blocking DB/Redis-style calls (50 ms each, 3 per request, 30 concurrent requests) is run twice — once with the pre-PR pattern (sync call directly inside the async handler) and once with the post-PR pattern (`await thread_pool_exec(...)`). The benchmark imports nothing from RAGFlow except `thread_pool_exec` itself, so it is hermetic and reproducible (`THREAD_POOL_MAX_WORKERS=128`, Python 3.13.12). **Throughput — wall-clock for 30 concurrent requests (lower is better)** | flavour | wall(s) | p50(s) | p95(s) | max(s) | |---|---:|---:|---:|---:| | before | 4.986 | 0.158 | 0.207 | 0.269 | | after | 0.248 | 0.181 | 0.230 | 0.231 | The pre-PR handler serializes the entire load on the event-loop thread, so 30 × 3 × 50 ms ≈ 4.5 s shows up as the wall time. The post-PR handler parallelizes the blocking work across the thread pool and finishes the same load in 248 ms — a **~20× speedup** on this workload. **Event-loop responsiveness — latency of an unrelated probe coroutine while the 30 slow requests are running (lower is better)** | flavour | samples | probe p50 (ms) | probe p95 (ms) | probe max (ms) | |---|---:|---:|---:|---:| | before | 1 | 5442.26 | 5442.26 | 5442.26 | | after | 28 | 0.88 | 11.53 | 98.02 | This is the metric that maps directly to "the API still answers other requests while one is busy". A 5 ms-interval probe was scheduled while the 30 slow handlers ran. With the pre-PR code the event loop was frozen for the entire duration of the blocking work, so only one probe sample was ever picked up and it waited **5,442 ms**. After the PR, 28 probe samples landed with **p50 0.88 ms / p95 11.53 ms**, meaning unrelated requests are no longer starved by the slow ones. That is the regression mode behind the cascading 502/504s reported in #13825. <details> <summary>Raw benchmark output</summary> ``` config: 30 concurrent requests, 3 blocking calls of 50ms each per request, THREAD_POOL_MAX_WORKERS=128 === Throughput (lower wall is better) === flavour wall(s) p50(s) p95(s) max(s) before 4.986 0.158 0.207 0.269 after 0.248 0.181 0.230 0.231 === Event-loop responsiveness (lower probe latency is better) === flavour samples probe p50(ms) probe p95(ms) probe max(ms) before 1 5442.26 5442.26 5442.26 after 28 0.88 11.53 98.02 ``` </details> The benchmark script is included as a comment on the PR for reproducibility. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] Performance Improvement Closes [#13825](https://github.com/infiniflow/ragflow/issues/13825) --------- Co-authored-by: tmimmanuel <tmimmanuel@users.noreply.github.com> Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
2026-05-10 21:08:55 -10:00
await thread_pool_exec(API4ConversationService.save, **conv)
conv = API4Conversation(**conv)
message_id = str(uuid4())
conv.message.append({
"role": "user",
"content": query,
"id": message_id,
"files": files
})
txt = ""
run_kwargs = {
"query": query,
"files": files,
"user_id": user_id,
"inputs": inputs,
}
if chat_template_kwargs is not None:
run_kwargs["chat_template_kwargs"] = chat_template_kwargs
async for ans in canvas.run(**run_kwargs):
ans["session_id"] = session_id
if ans["event"] == "message":
txt += ans["data"]["content"]
if ans["data"].get("start_to_think", False):
txt += "<think>"
elif ans["data"].get("end_to_think", False):
txt += "</think>"
yield "data:" + json.dumps(ans, ensure_ascii=False) + "\n\n"
conv.message.append({"role": "assistant", "content": txt, "created_at": time.time(), "id": message_id})
conv.reference = canvas.get_reference()
conv.errors = canvas.error
conv.dsl = str(canvas)
conv = conv.to_dict()
fix: offload blocking DB/Redis calls to thread pool for high-concurrency support (#13825) (#13941) ### What problem does this PR solve? Addresses event-loop blocking under high concurrency reported in #13825. When multiple requests hit the API simultaneously, synchronous DB/Redis calls block the async event loop, preventing Quart from handling other requests and causing cascading 502/504 timeouts. This PR wraps all remaining blocking DB/Redis calls in `canvas_app.py`, `chat_api.py`, `session.py`, and `canvas_service.py` with `await thread_pool_exec()` - Offload all synchronous `Service.*`, `REDIS_CONN.*`, and `APIToken.query` calls to the thread pool - Convert sync endpoint handlers (`list_chats`, `get_chat`, `templates`, `sessions`, etc.) to `async def` - Convert sync helper functions (`_ensure_owned_chat`, `_validate_llm_id`, `_validate_dataset_ids`, etc.) to async - no duplicate sync/async pairs - Wrap `CanvasReplicaService` Redis IO calls (`bootstrap`, `replace_for_set`, `commit_after_run`) - Use `asyncio.gather()` for concurrent file uploads and chat response building **Note:** This fixes the code-level event-loop blocking, which is a prerequisite for handling concurrent requests. For the full "30 concurrent requests without 502/504" goal described in the issue, users should also tune deployment config: - `WS=4` or higher (HTTP worker processes, default 1) - `MAX_CONCURRENT_CHATS=50` (default 10) - `SANDBOX_EXECUTOR_MANAGER_POOL_SIZE` for workflow-heavy workloads ### Performance verification Reviewer asked for a before-vs-after comparison ([comment](https://github.com/infiniflow/ragflow/pull/13941#issuecomment-4393667231)). I built a self-contained microbenchmark that reproduces the exact failure mode this PR targets: an async handler that performs blocking DB/Redis-style calls (50 ms each, 3 per request, 30 concurrent requests) is run twice — once with the pre-PR pattern (sync call directly inside the async handler) and once with the post-PR pattern (`await thread_pool_exec(...)`). The benchmark imports nothing from RAGFlow except `thread_pool_exec` itself, so it is hermetic and reproducible (`THREAD_POOL_MAX_WORKERS=128`, Python 3.13.12). **Throughput — wall-clock for 30 concurrent requests (lower is better)** | flavour | wall(s) | p50(s) | p95(s) | max(s) | |---|---:|---:|---:|---:| | before | 4.986 | 0.158 | 0.207 | 0.269 | | after | 0.248 | 0.181 | 0.230 | 0.231 | The pre-PR handler serializes the entire load on the event-loop thread, so 30 × 3 × 50 ms ≈ 4.5 s shows up as the wall time. The post-PR handler parallelizes the blocking work across the thread pool and finishes the same load in 248 ms — a **~20× speedup** on this workload. **Event-loop responsiveness — latency of an unrelated probe coroutine while the 30 slow requests are running (lower is better)** | flavour | samples | probe p50 (ms) | probe p95 (ms) | probe max (ms) | |---|---:|---:|---:|---:| | before | 1 | 5442.26 | 5442.26 | 5442.26 | | after | 28 | 0.88 | 11.53 | 98.02 | This is the metric that maps directly to "the API still answers other requests while one is busy". A 5 ms-interval probe was scheduled while the 30 slow handlers ran. With the pre-PR code the event loop was frozen for the entire duration of the blocking work, so only one probe sample was ever picked up and it waited **5,442 ms**. After the PR, 28 probe samples landed with **p50 0.88 ms / p95 11.53 ms**, meaning unrelated requests are no longer starved by the slow ones. That is the regression mode behind the cascading 502/504s reported in #13825. <details> <summary>Raw benchmark output</summary> ``` config: 30 concurrent requests, 3 blocking calls of 50ms each per request, THREAD_POOL_MAX_WORKERS=128 === Throughput (lower wall is better) === flavour wall(s) p50(s) p95(s) max(s) before 4.986 0.158 0.207 0.269 after 0.248 0.181 0.230 0.231 === Event-loop responsiveness (lower probe latency is better) === flavour samples probe p50(ms) probe p95(ms) probe max(ms) before 1 5442.26 5442.26 5442.26 after 28 0.88 11.53 98.02 ``` </details> The benchmark script is included as a comment on the PR for reproducibility. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) - [x] Performance Improvement Closes [#13825](https://github.com/infiniflow/ragflow/issues/13825) --------- Co-authored-by: tmimmanuel <tmimmanuel@users.noreply.github.com> Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>
2026-05-10 21:08:55 -10:00
await thread_pool_exec(API4ConversationService.append_message, conv["id"], conv)
async def completion_openai(tenant_id, agent_id, question, session_id=None, stream=True, **kwargs):
tiktoken_encoder = tiktoken.get_encoding("cl100k_base")
prompt_tokens = len(tiktoken_encoder.encode(str(question)))
user_id = kwargs.get("user_id", "")
if stream:
completion_tokens = 0
try:
async for ans in completion(
tenant_id=tenant_id,
agent_id=agent_id,
session_id=session_id,
query=question,
user_id=user_id,
**kwargs
):
if isinstance(ans, str):
try:
ans = json.loads(ans[5:]) # remove "data:"
except Exception as e:
logging.exception(f"Agent OpenAI-Compatible completion_openai parse answer failed: {e}")
continue
if ans.get("event") not in ["message", "message_end"]:
continue
content_piece = ""
if ans["event"] == "message":
content_piece = ans["data"]["content"]
completion_tokens += len(tiktoken_encoder.encode(content_piece))
openai_data = get_data_openai(
id=session_id or str(uuid4()),
model=agent_id,
content=content_piece,
prompt_tokens=prompt_tokens,
completion_tokens=completion_tokens,
stream=True
)
if ans.get("data", {}).get("reference", None):
openai_data["choices"][0]["delta"]["reference"] = ans["data"]["reference"]
yield "data: " + json.dumps(openai_data, ensure_ascii=False) + "\n\n"
yield "data: [DONE]\n\n"
except Exception as e:
logging.exception(e)
yield "data: " + json.dumps(
get_data_openai(
id=session_id or str(uuid4()),
model=agent_id,
content=f"**ERROR**: {str(e)}",
finish_reason="stop",
prompt_tokens=prompt_tokens,
completion_tokens=len(tiktoken_encoder.encode(f"**ERROR**: {str(e)}")),
stream=True
),
ensure_ascii=False
) + "\n\n"
yield "data: [DONE]\n\n"
else:
try:
all_content = ""
reference = {}
async for ans in completion(
tenant_id=tenant_id,
agent_id=agent_id,
session_id=session_id,
query=question,
user_id=user_id,
**kwargs
):
if isinstance(ans, str):
ans = json.loads(ans[5:])
if ans.get("event") not in ["message", "message_end"]:
continue
if ans["event"] == "message":
all_content += ans["data"]["content"]
if ans.get("data", {}).get("reference", None):
reference.update(ans["data"]["reference"])
completion_tokens = len(tiktoken_encoder.encode(all_content))
openai_data = get_data_openai(
id=session_id or str(uuid4()),
model=agent_id,
prompt_tokens=prompt_tokens,
completion_tokens=completion_tokens,
content=all_content,
finish_reason="stop",
param=None
)
if reference:
openai_data["choices"][0]["message"]["reference"] = reference
yield openai_data
except Exception as e:
logging.exception(e)
yield get_data_openai(
id=session_id or str(uuid4()),
model=agent_id,
prompt_tokens=prompt_tokens,
completion_tokens=len(tiktoken_encoder.encode(f"**ERROR**: {str(e)}")),
content=f"**ERROR**: {str(e)}",
finish_reason="stop",
param=None
)