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ragflow/agent/canvas.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 asyncio
import base64
import datetime
import inspect
import json
import logging
import re
import time
from concurrent.futures import ThreadPoolExecutor
from copy import deepcopy
from functools import partial
from typing import Any, Union, Tuple
from agent.component import component_class
from agent.component.base import ComponentBase
from agent.dsl_migration import normalize_chunker_dsl
from api.db.services.file_service import FileService
from api.db.services.llm_service import LLMBundle
from api.db.services.task_service import has_canceled
from api.db.joint_services.tenant_model_service import get_tenant_default_model_by_type
from common.constants import LLMType
from common.misc_utils import get_uuid, hash_str2int
from common.exceptions import TaskCanceledException
from rag.prompts.generator import chunks_format
from rag.utils.redis_conn import REDIS_CONN
feat(tts): cache synthesized speech in Redis to avoid redundant calls (#14851) ## What problem does this PR solve? Closes #12017. TTS output is deterministic for a given `(model, text)` pair, so re-running the same text through the same TTS model produces the same bytes — yet `Canvas.tts` and `dialog_service.tts` re-synthesized on every request. That's slow and wastes provider quota whenever the same assistant response is replayed, shared across users, or repeated within a session. ### Change New helper `rag/utils/tts_cache.py` with `synthesize_with_cache(tts_mdl, cleaned_text)`: - **Key:** `tts:cache:{model_id}:{sha256(text)}` — separate namespace per model, identical cleaned text reuses a single entry across both call sites. - **Value:** the hex-encoded audio blob both call sites already returned. No format change for downstream consumers. - **TTL:** 7 days by default, configurable via `RAGFLOW_TTS_CACHE_TTL_SECONDS`. - **Failure modes:** a Redis hiccup falls back to direct synthesis; a failed synthesis still returns `None` (existing contract preserved). [`Canvas.tts`](https://github.com/infiniflow/ragflow/blob/main/agent/canvas.py#L683-L724) and [`dialog_service.tts`](https://github.com/infiniflow/ragflow/blob/main/api/db/services/dialog_service.py#L1367-L1380) now route through the helper; the per-file bytes-accumulation/hex-encode loop has been removed in favor of one shared implementation. ## Type of change - [x] New Feature (non-breaking change which adds functionality) ## Test plan - [ ] **Cache hit, chat path:** Configure a dialog with TTS enabled, ask the same question twice with `stream=false`. Verify the second response returns the same `audio_binary` and that the second invocation doesn't hit the TTS provider (e.g., observe provider-side logs / usage counters; check no `LLMBundle.tts can't update token usage` log line on the second run). - [ ] **Cache hit, agent path:** Same exercise via a Conversational Agent that includes a Message component playing back the answer. - [ ] **Cache isolation per model:** Switch tenant's `tts_id` between two models, run the same text against each — confirm the second model's first synthesis still happens (no cross-model hits). - [ ] **TTL override:** Set `RAGFLOW_TTS_CACHE_TTL_SECONDS=120`, confirm the entry expires after 2 minutes. - [ ] **Redis unavailable:** Stop Redis (or break the connection). Verify the TTS endpoint still works — synthesis falls back to direct calls, with a `TTS cache lookup failed` / `TTS cache store failed` warning logged. - [ ] **Failure path:** Configure a TTS model with an invalid API key, ensure the response still returns successfully with `audio_binary=None` (no regression vs. current behavior).
2026-05-18 23:20:40 -07:00
from rag.utils.tts_cache import synthesize_with_cache
class Graph:
"""
dsl = {
"components": {
"begin": {
"obj":{
"component_name": "Begin",
"params": {},
},
"downstream": ["answer_0"],
"upstream": [],
},
"retrieval_0": {
"obj": {
"component_name": "Retrieval",
"params": {}
},
"downstream": ["generate_0"],
"upstream": ["answer_0"],
},
"generate_0": {
"obj": {
"component_name": "Generate",
"params": {}
},
"downstream": ["answer_0"],
"upstream": ["retrieval_0"],
}
},
"history": [],
"path": ["begin"],
"retrieval": {"chunks": [], "doc_aggs": []},
"globals": {
"sys.query": "",
"sys.user_id": tenant_id,
"sys.conversation_turns": 0,
"sys.files": []
}
}
"""
def __init__(self, dsl: str, tenant_id=None, task_id=None, custom_header=None):
self.path = []
self.components = {}
self.error = ""
# Accept legacy DSL on read, but keep the in-memory canvas in the latest schema.
self.dsl = normalize_chunker_dsl(json.loads(dsl))
self._tenant_id = tenant_id
self.task_id = task_id if task_id else get_uuid()
self.custom_header = custom_header
self._thread_pool = ThreadPoolExecutor(max_workers=5)
self.load()
def load(self):
self.components = self.dsl["components"]
cpn_nms = set([])
for k, cpn in self.components.items():
cpn_nms.add(cpn["obj"]["component_name"])
param = component_class(cpn["obj"]["component_name"] + "Param")()
cpn["obj"]["params"]["custom_header"] = self.custom_header
param.update(cpn["obj"]["params"])
try:
param.check()
except Exception as e:
raise ValueError(self.get_component_name(k) + f": {e}")
cpn["obj"] = component_class(cpn["obj"]["component_name"])(self, k, param)
self.path = self.dsl["path"]
def __str__(self):
self.dsl["path"] = self.path
self.dsl["task_id"] = self.task_id
dsl = {
"components": {}
}
for k in self.dsl.keys():
if k in ["components"]:
continue
dsl[k] = deepcopy(self.dsl[k])
for k, cpn in self.components.items():
if k not in dsl["components"]:
dsl["components"][k] = {}
for c in cpn.keys():
if c == "obj":
dsl["components"][k][c] = json.loads(str(cpn["obj"]))
continue
dsl["components"][k][c] = deepcopy(cpn[c])
return json.dumps(dsl, ensure_ascii=False)
def reset(self):
self.path = []
for k, cpn in self.components.items():
self.components[k]["obj"].reset()
try:
REDIS_CONN.delete(f"{self.task_id}-logs")
REDIS_CONN.delete(f"{self.task_id}-cancel")
except Exception as e:
logging.exception(e)
def get_component_name(self, cid):
for n in self.dsl.get("graph", {}).get("nodes", []):
if cid == n["id"]:
return n["data"]["name"]
return ""
def run(self, **kwargs):
raise NotImplementedError()
def get_component(self, cpn_id) -> Union[None, dict[str, Any]]:
return self.components.get(cpn_id)
def get_component_obj(self, cpn_id) -> ComponentBase:
return self.components.get(cpn_id)["obj"]
def get_component_type(self, cpn_id) -> str:
return self.components.get(cpn_id)["obj"].component_name
def get_component_input_form(self, cpn_id) -> dict:
return self.components.get(cpn_id)["obj"].get_input_form()
def get_tenant_id(self):
return self._tenant_id
def get_value_with_variable(self,value: str) -> Any:
pat = re.compile(r"\{* *\{([a-zA-Z:0-9]+@[A-Za-z0-9_.-]+|sys\.[A-Za-z0-9_.]+|env\.[A-Za-z0-9_.]+)\} *\}*")
out_parts = []
last = 0
for m in pat.finditer(value):
out_parts.append(value[last:m.start()])
key = m.group(1)
v = self.get_variable_value(key)
if v is None:
rep = ""
elif isinstance(v, partial):
buf = []
for chunk in v():
buf.append(chunk)
rep = "".join(buf)
elif isinstance(v, str):
rep = v
else:
rep = json.dumps(v, ensure_ascii=False)
out_parts.append(rep)
last = m.end()
out_parts.append(value[last:])
return("".join(out_parts))
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
def get_variable_value(self, exp: str) -> Any:
exp = exp.strip("{").strip("}").strip(" ").strip("{").strip("}")
if exp.find("@") < 0:
return self.globals[exp]
cpn_id, var_nm = exp.split("@")
cpn = self.get_component(cpn_id)
if not cpn:
raise Exception(f"Can't find variable: '{cpn_id}@{var_nm}'")
parts = var_nm.split(".", 1)
root_key = parts[0]
rest = parts[1] if len(parts) > 1 else ""
root_val = cpn["obj"].output(root_key)
if not rest:
return root_val
return self.get_variable_param_value(root_val,rest)
def get_variable_param_value(self, obj: Any, path: str) -> Any:
cur = obj
if not path:
return cur
for key in path.split('.'):
if cur is None:
return None
if isinstance(cur, str):
try:
cur = json.loads(cur)
except Exception:
return None
if isinstance(cur, dict):
cur = cur.get(key)
continue
if isinstance(cur, (list, tuple)):
try:
idx = int(key)
cur = cur[idx]
except Exception:
return None
continue
cur = getattr(cur, key, None)
return cur
def set_variable_value(self, exp: str,value):
exp = exp.strip("{").strip("}").strip(" ").strip("{").strip("}")
if exp.find("@") < 0:
self.globals[exp] = value
return
cpn_id, var_nm = exp.split("@")
cpn = self.get_component(cpn_id)
if not cpn:
raise Exception(f"Can't find variable: '{cpn_id}@{var_nm}'")
parts = var_nm.split(".", 1)
root_key = parts[0]
rest = parts[1] if len(parts) > 1 else ""
if not rest:
cpn["obj"].set_output(root_key, value)
return
root_val = cpn["obj"].output(root_key)
if not root_val:
root_val = {}
cpn["obj"].set_output(root_key, self.set_variable_param_value(root_val,rest,value))
def set_variable_param_value(self, obj: Any, path: str, value) -> Any:
cur = obj
keys = path.split('.')
if not path:
return value
fix: correct nested path traversal in set_variable_param_value (#13986) ## Summary `Graph.set_variable_param_value()` in `agent/canvas.py` has a bug in its nested path traversal logic. The `for` loop iterates through **all** keys in the path (including the last one), descending into every level. After the loop, it then tries to set `cur[keys[-1]] = value`, but `cur` has already descended one level too deep. **Example:** For `path = "a.b"`, `value = "hello"`: - **Before (bug):** `obj["a"]["b"]` becomes `{"b": "hello"}` instead of `"hello"` - **After (fix):** `obj["a"]["b"]` becomes `"hello"` as expected The fix changes `for key in keys:` to `for key in keys[:-1]:`, so the loop only navigates to the parent dict, and the final key is set directly. This is consistent with how the read-side counterpart `get_variable_param_value()` works. This method is called by `set_variable_value()` when assigning to nested variable paths (e.g., `component@root.nested.key`), which is used by the `VariableAssigner` component. ## Test plan - [ ] Create a canvas with a VariableAssigner that writes to a nested path (e.g., `component@obj.nested.key`) - [ ] Verify the value is set correctly at the expected path, not wrapped in an extra dict layer - [ ] Verify single-key paths (e.g., `component@key`) still work correctly <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **Bug Fixes** * Fixed a bug in variable parameter assignment where nested structures were being incorrectly modified, ensuring values are now properly set at their intended locations without unintended overwrites. <!-- end of auto-generated comment: release notes by coderabbit.ai --> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-05-14 13:27:04 +08:00
for key in keys[:-1]:
if key not in cur or not isinstance(cur[key], dict):
cur[key] = {}
cur = cur[key]
cur[keys[-1]] = value
return obj
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
def is_canceled(self) -> bool:
return has_canceled(self.task_id)
def cancel_task(self) -> bool:
try:
REDIS_CONN.set(f"{self.task_id}-cancel", "x")
except Exception as e:
logging.exception(e)
return False
return True
class Canvas(Graph):
def __init__(self, dsl: str, tenant_id=None, task_id=None, canvas_id=None, custom_header=None):
self.globals = {
"sys.query": "",
"sys.user_id": tenant_id,
"sys.conversation_turns": 0,
"sys.files": [],
"sys.history": [],
"sys.date": datetime.datetime.now(datetime.timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
}
self.variables = {}
super().__init__(dsl, tenant_id, task_id, custom_header=custom_header)
self._id = canvas_id
def load(self):
super().load()
self.history = self.dsl["history"]
if "globals" in self.dsl:
self.globals = self.dsl["globals"]
if "sys.history" not in self.globals:
self.globals["sys.history"] = []
if "sys.date" not in self.globals:
self.globals["sys.date"] = datetime.datetime.now(datetime.timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
else:
self.globals = {
"sys.query": "",
"sys.user_id": "",
"sys.conversation_turns": 0,
"sys.files": [],
"sys.history": [],
"sys.date": datetime.datetime.now(datetime.timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
}
if "variables" in self.dsl:
self.variables = self.dsl["variables"]
else:
self.variables = {}
self.retrieval = self.dsl["retrieval"]
self.memory = self.dsl.get("memory", [])
def __str__(self):
self.dsl["history"] = self.history
self.dsl["retrieval"] = self.retrieval
self.dsl["memory"] = self.memory
return super().__str__()
def reset(self, mem=False):
super().reset()
if not mem:
self.history = []
self.retrieval = []
self.memory = []
print(self.variables)
for k in self.globals.keys():
if k.startswith("sys."):
if isinstance(self.globals[k], str):
self.globals[k] = ""
elif isinstance(self.globals[k], int):
self.globals[k] = 0
elif isinstance(self.globals[k], float):
self.globals[k] = 0
elif isinstance(self.globals[k], list):
self.globals[k] = []
elif isinstance(self.globals[k], dict):
self.globals[k] = {}
else:
self.globals[k] = None
if k.startswith("env."):
key = k[4:]
if key in self.variables:
variable = self.variables[key]
value = variable.get("value")
if value is not None:
self.globals[k] = value
else:
var_type = variable.get("type", "")
if var_type == "number":
self.globals[k] = 0
elif var_type == "boolean":
self.globals[k] = False
elif var_type == "object":
self.globals[k] = {}
elif var_type.startswith("array"):
self.globals[k] = []
else: # "string" or unknown
self.globals[k] = ""
else:
self.globals[k] = ""
async def run(self, **kwargs):
self.globals["sys.date"] = datetime.datetime.now(datetime.timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
st = time.perf_counter()
self._loop = asyncio.get_running_loop()
self.message_id = get_uuid()
created_at = int(time.time())
self.add_user_input(kwargs.get("query"))
Fix: path-aware reset in canvas.run() to preserve cross-run outputs (#14600) ## Summary - When an agent workflow has multiple `UserFillUp` pause points, `canvas.run()` calls `reset(True)` on **all** components at the start of each run. This clears outputs from components that completed in prior runs, so downstream references like `{Agent:XXX@content}` resolve to `None`. - This fix only resets components on the **current execution path** (`self.path`), preserving outputs from previously completed components. ## Problem In a multi-step agent (e.g. draft email → user confirms → send email): 1. First `run()`: Agent drafts content, UserFillUp pauses for user input → Agent output is saved 2. Second `run()`: User submits input, but `reset(True)` clears **all** components including the Agent that already completed 3. Email component references `{Agent:XXX@content}` → gets `None` instead of the draft This affects **all** agents that reference upstream component outputs after a UserFillUp pause point. ## Fix ```python # Before: reset ALL components for k, cpn in self.components.items(): self.components[k]["obj"].reset(True) # After: only reset components on current execution path path_set = set(self.path) for k, cpn in self.components.items(): if k in path_set: self.components[k]["obj"].reset(True) ``` `self.path` already tracks the current execution path. For agents without UserFillUp (single run), `path` contains all components, so behavior is unchanged. ## Test plan - [x] Agent with single UserFillUp: outputs from prior components are preserved after resume - [x] Agent with multiple UserFillUp: each resume preserves all previously completed outputs - [x] Agent without UserFillUp: behavior unchanged (all components in path, all reset) - [x] Webhook-triggered agents: unaffected (path includes all components on first run) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: wanghualoong <wanghualoong@gmail.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-05-08 15:10:15 +08:00
path_set = set(self.path)
for k, cpn in self.components.items():
Fix: path-aware reset in canvas.run() to preserve cross-run outputs (#14600) ## Summary - When an agent workflow has multiple `UserFillUp` pause points, `canvas.run()` calls `reset(True)` on **all** components at the start of each run. This clears outputs from components that completed in prior runs, so downstream references like `{Agent:XXX@content}` resolve to `None`. - This fix only resets components on the **current execution path** (`self.path`), preserving outputs from previously completed components. ## Problem In a multi-step agent (e.g. draft email → user confirms → send email): 1. First `run()`: Agent drafts content, UserFillUp pauses for user input → Agent output is saved 2. Second `run()`: User submits input, but `reset(True)` clears **all** components including the Agent that already completed 3. Email component references `{Agent:XXX@content}` → gets `None` instead of the draft This affects **all** agents that reference upstream component outputs after a UserFillUp pause point. ## Fix ```python # Before: reset ALL components for k, cpn in self.components.items(): self.components[k]["obj"].reset(True) # After: only reset components on current execution path path_set = set(self.path) for k, cpn in self.components.items(): if k in path_set: self.components[k]["obj"].reset(True) ``` `self.path` already tracks the current execution path. For agents without UserFillUp (single run), `path` contains all components, so behavior is unchanged. ## Test plan - [x] Agent with single UserFillUp: outputs from prior components are preserved after resume - [x] Agent with multiple UserFillUp: each resume preserves all previously completed outputs - [x] Agent without UserFillUp: behavior unchanged (all components in path, all reset) - [x] Webhook-triggered agents: unaffected (path includes all components on first run) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-authored-by: wanghualoong <wanghualoong@gmail.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-05-08 15:10:15 +08:00
if k in path_set:
self.components[k]["obj"].reset(True)
if kwargs.get("webhook_payload"):
for k, cpn in self.components.items():
if self.components[k]["obj"].component_name.lower() == "begin" and self.components[k]["obj"]._param.mode == "Webhook":
payload = kwargs.get("webhook_payload", {})
if "input" in payload:
self.components[k]["obj"].set_input_value("request", payload["input"])
for kk, vv in payload.items():
if kk == "input":
continue
self.components[k]["obj"].set_output(kk, vv)
2026-03-04 05:09:33 +02:00
layout_recognize = None
for cpn in self.components.values():
if cpn["obj"].component_name.lower() == "begin":
layout_recognize = getattr(cpn["obj"]._param, "layout_recognize", None)
break
for k in kwargs.keys():
if k in ["query", "user_id", "files", "chat_template_kwargs"] and kwargs[k]:
if k == "files":
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self.globals[f"sys.{k}"] = await self.get_files_async(kwargs[k], layout_recognize)
else:
self.globals[f"sys.{k}"] = kwargs[k]
if not self.globals["sys.conversation_turns"] :
self.globals["sys.conversation_turns"] = 0
self.globals["sys.conversation_turns"] += 1
def decorate(event, dt):
nonlocal created_at
return {
"event": event,
#"conversation_id": "f3cc152b-24b0-4258-a1a1-7d5e9fc8a115",
"message_id": self.message_id,
"created_at": created_at,
"task_id": self.task_id,
"data": dt
}
if not self.path or self.path[-1].lower().find("userfillup") < 0:
self.path.append("begin")
self.retrieval.append({"chunks": [], "doc_aggs": []})
if self.is_canceled():
msg = f"Task {self.task_id} has been canceled before starting."
logging.info(msg)
raise TaskCanceledException(msg)
yield decorate("workflow_started", {"inputs": kwargs.get("inputs")})
self.retrieval.append({"chunks": {}, "doc_aggs": {}})
async def _run_batch(f, t):
if self.is_canceled():
msg = f"Task {self.task_id} has been canceled during batch execution."
logging.info(msg)
raise TaskCanceledException(msg)
loop = asyncio.get_running_loop()
tasks = []
max_concurrency = getattr(self._thread_pool, "_max_workers", 5)
sem = asyncio.Semaphore(max_concurrency)
async def _invoke_one(cpn_obj, sync_fn, call_kwargs, use_async: bool):
async with sem:
if use_async:
await cpn_obj.invoke_async(**(call_kwargs or {}))
return
await loop.run_in_executor(self._thread_pool, partial(sync_fn, **(call_kwargs or {})))
i = f
while i < t:
cpn = self.get_component_obj(self.path[i])
task_fn = None
call_kwargs = None
if cpn.component_name.lower() in ["begin", "userfillup"]:
call_kwargs = {"inputs": kwargs.get("inputs", {})}
task_fn = cpn.invoke
i += 1
else:
for _, ele in cpn.get_input_elements().items():
if isinstance(ele, dict) and ele.get("_cpn_id") and ele.get("_cpn_id") not in self.path[:i] and self.path[0].lower().find("userfillup") < 0:
self.path.pop(i)
t -= 1
break
else:
call_kwargs = cpn.get_input()
task_fn = cpn.invoke
i += 1
if task_fn is None:
continue
fn_invoke_async = getattr(cpn, "_invoke_async", None)
use_async = (fn_invoke_async and asyncio.iscoroutinefunction(fn_invoke_async)) or asyncio.iscoroutinefunction(getattr(cpn, "_invoke", None))
tasks.append(asyncio.create_task(_invoke_one(cpn, task_fn, call_kwargs, use_async)))
if tasks:
await asyncio.gather(*tasks)
def _node_finished(cpn_obj):
return decorate("node_finished",{
"inputs": cpn_obj.get_input_values(),
"outputs": cpn_obj.output(),
"component_id": cpn_obj._id,
"component_name": self.get_component_name(cpn_obj._id),
"component_type": self.get_component_type(cpn_obj._id),
"error": cpn_obj.error(),
"elapsed_time": time.perf_counter() - cpn_obj.output("_created_time"),
"created_at": cpn_obj.output("_created_time"),
})
self.error = ""
idx = len(self.path) - 1
partials = []
tts_mdl = None
while idx < len(self.path):
to = len(self.path)
for i in range(idx, to):
yield decorate("node_started", {
"inputs": None, "created_at": int(time.time()),
"component_id": self.path[i],
"component_name": self.get_component_name(self.path[i]),
"component_type": self.get_component_type(self.path[i]),
"thoughts": self.get_component_thoughts(self.path[i])
})
await _run_batch(idx, to)
to = len(self.path)
# post-processing of components invocation
for i in range(idx, to):
cpn = self.get_component(self.path[i])
cpn_obj = self.get_component_obj(self.path[i])
if cpn_obj.component_name.lower() == "message":
if cpn_obj.get_param("auto_play"):
tts_model_config = get_tenant_default_model_by_type(self._tenant_id, LLMType.TTS)
tts_mdl = LLMBundle(self._tenant_id, tts_model_config)
if isinstance(cpn_obj.output("content"), partial):
_m = ""
buff_m = ""
stream = cpn_obj.output("content")()
async def _process_stream(m):
nonlocal buff_m, _m, tts_mdl
if not m:
return
if m == "<think>":
return decorate("message", {"content": "", "start_to_think": True})
elif m == "</think>":
return decorate("message", {"content": "", "end_to_think": True})
buff_m += m
_m += m
if len(buff_m) > 16:
ev = decorate(
"message",
{
"content": m,
"audio_binary": self.tts(tts_mdl, buff_m)
}
)
buff_m = ""
return ev
return decorate("message", {"content": m})
if inspect.isasyncgen(stream):
async for m in stream:
ev= await _process_stream(m)
if ev:
yield ev
else:
for m in stream:
ev= await _process_stream(m)
if ev:
yield ev
if buff_m:
yield decorate("message", {"content": "", "audio_binary": self.tts(tts_mdl, buff_m)})
buff_m = ""
cpn_obj.set_output("content", _m)
else:
yield decorate("message", {"content": cpn_obj.output("content")})
Feature rtl support (#13118) ### What problem does this PR solve? This PR adds comprehensive **Right-to-Left (RTL) language support**, primarily targeting Arabic and other RTL scripts (Hebrew, Persian, Urdu, etc.). Previously, RTL content had multiple rendering issues: - Incorrect sentence splitting for Arabic punctuation in citation logic - Misaligned text in chat messages and markdown components - Improper positioning of blockquotes and “think” sections - Incorrect table alignment - Citation placement ambiguity in RTL prompts - UI layout inconsistencies when mixing LTR and RTL text This PR introduces backend and frontend improvements to properly detect, render, and style RTL content while preserving existing LTR behavior. #### Backend - Updated sentence boundary regex in `rag/nlp/search.py` to include Arabic punctuation: - `،` (comma) - `؛` (semicolon) - `؟` (question mark) - `۔` (Arabic full stop) - Ensures citation insertion works correctly in RTL sentences. - Updated citation prompt instructions to clarify citation placement rules for RTL languages. #### Frontend - Introduced a new utility: `text-direction.ts` - Detects text direction based on Unicode ranges. - Supports Arabic, Hebrew, Syriac, Thaana, and related scripts. - Provides `getDirAttribute()` for automatic `dir` assignment. - Applied dynamic `dir` attributes across: - Markdown rendering - Chat messages - Search results - Tables - Hover cards and reference popovers - Added proper RTL styling in LESS: - Text alignment adjustments - Blockquote border flipping - Section indentation correction - Table direction switching - Use of `<bdi>` for figure labels to prevent bidirectional conflicts #### DevOps / Environment - Added Windows backend launch script with retry handling. - Updated dependency metadata. - Adjusted development-only React debugging behavior. --- ### Type of change - [x] Bug Fix (non-breaking change which fixes RTL rendering and citation issues) - [x] New Feature (non-breaking change which adds RTL detection and dynamic direction handling) --------- Co-authored-by: 6ba3i <isbaaoui09@gmail.com> Co-authored-by: Ahmad Intisar <ahmadintisar@Ahmads-MacBook-M4-Pro.local> Co-authored-by: Ahmad Intisar <168020872+ahmadintisar@users.noreply.github.com> Co-authored-by: Liu An <asiro@qq.com>
2026-03-02 08:03:44 +03:00
message_end = self._build_message_end(cpn_obj)
yield decorate("message_end", message_end)
while partials:
_cpn_obj = self.get_component_obj(partials[0])
if isinstance(_cpn_obj.output("content"), partial):
break
yield _node_finished(_cpn_obj)
partials.pop(0)
other_branch = False
if cpn_obj.error():
ex = cpn_obj.exception_handler()
if ex and ex["goto"]:
self.path.extend(ex["goto"])
other_branch = True
elif ex and ex["default_value"]:
yield decorate("message", {"content": ex["default_value"]})
yield decorate("message_end", {})
else:
self.error = cpn_obj.error()
if cpn_obj.component_name.lower() not in ("iteration","loop"):
if isinstance(cpn_obj.output("content"), partial):
if self.error:
cpn_obj.set_output("content", None)
yield _node_finished(cpn_obj)
else:
partials.append(self.path[i])
else:
yield _node_finished(cpn_obj)
def _append_path(cpn_id):
nonlocal other_branch
if other_branch:
return
if self.path[-1] == cpn_id:
return
self.path.append(cpn_id)
def _extend_path(cpn_ids):
nonlocal other_branch
if other_branch:
return
for cpn_id in cpn_ids:
_append_path(cpn_id)
if cpn_obj.component_name.lower() in ("iterationitem","loopitem") and cpn_obj.end():
iter = cpn_obj.get_parent()
yield _node_finished(iter)
_extend_path(self.get_component(cpn["parent_id"])["downstream"])
elif cpn_obj.component_name.lower() in ["categorize", "switch"]:
_extend_path(cpn_obj.output("_next"))
elif cpn_obj.component_name.lower() in ("iteration", "loop"):
_append_path(cpn_obj.get_start())
elif cpn_obj.component_name.lower() == "exitloop" and cpn_obj.get_parent().component_name.lower() == "loop":
_extend_path(self.get_component(cpn["parent_id"])["downstream"])
elif not cpn["downstream"] and cpn_obj.get_parent():
_append_path(cpn_obj.get_parent().get_start())
else:
_extend_path(cpn["downstream"])
if self.error:
logging.error(f"Runtime Error: {self.error}")
break
idx = to
if any([self.get_component_obj(c).component_name.lower() == "userfillup" for c in self.path[idx:]]):
path = [c for c in self.path[idx:] if self.get_component(c)["obj"].component_name.lower() == "userfillup"]
path.extend([c for c in self.path[idx:] if self.get_component(c)["obj"].component_name.lower() != "userfillup"])
another_inputs = {}
tips = ""
for c in path:
o = self.get_component_obj(c)
if o.component_name.lower() == "userfillup":
o.invoke()
another_inputs.update(o.get_input_elements())
if o.get_param("enable_tips"):
tips = o.output("tips")
self.path = path
yield decorate("user_inputs", {"inputs": another_inputs, "tips": tips})
return
self.path = self.path[:idx]
if not self.error:
yield decorate("workflow_finished",
{
"inputs": kwargs.get("inputs"),
"outputs": self.get_component_obj(self.path[-1]).output(),
"elapsed_time": time.perf_counter() - st,
"created_at": st,
})
self.history.append(("assistant", self.get_component_obj(self.path[-1]).output()))
self.globals["sys.history"].append(f"{self.history[-1][0]}: {self.history[-1][1]}")
elif "Task has been canceled" in self.error:
yield decorate("workflow_finished",
{
"inputs": kwargs.get("inputs"),
"outputs": "Task has been canceled",
"elapsed_time": time.perf_counter() - st,
"created_at": st,
})
def is_reff(self, exp: str) -> bool:
exp = exp.strip("{").strip("}")
if exp.find("@") < 0:
return exp in self.globals
arr = exp.split("@")
if len(arr) != 2:
return False
if self.get_component(arr[0]) is None:
return False
return True
def tts(self,tts_mdl, text):
def clean_tts_text(text: str) -> str:
if not text:
return ""
text = text.encode("utf-8", "ignore").decode("utf-8", "ignore")
text = re.sub(r"[\x00-\x08\x0B-\x0C\x0E-\x1F\x7F]", "", text)
emoji_pattern = re.compile(
"[\U0001F600-\U0001F64F"
"\U0001F300-\U0001F5FF"
"\U0001F680-\U0001F6FF"
"\U0001F1E0-\U0001F1FF"
"\U00002700-\U000027BF"
"\U0001F900-\U0001F9FF"
"\U0001FA70-\U0001FAFF"
"\U0001FAD0-\U0001FAFF]+",
flags=re.UNICODE
)
text = emoji_pattern.sub("", text)
text = re.sub(r"\s+", " ", text).strip()
MAX_LEN = 500
if len(text) > MAX_LEN:
text = text[:MAX_LEN]
return text
if not tts_mdl or not text:
return None
text = clean_tts_text(text)
if not text:
return None
feat(tts): cache synthesized speech in Redis to avoid redundant calls (#14851) ## What problem does this PR solve? Closes #12017. TTS output is deterministic for a given `(model, text)` pair, so re-running the same text through the same TTS model produces the same bytes — yet `Canvas.tts` and `dialog_service.tts` re-synthesized on every request. That's slow and wastes provider quota whenever the same assistant response is replayed, shared across users, or repeated within a session. ### Change New helper `rag/utils/tts_cache.py` with `synthesize_with_cache(tts_mdl, cleaned_text)`: - **Key:** `tts:cache:{model_id}:{sha256(text)}` — separate namespace per model, identical cleaned text reuses a single entry across both call sites. - **Value:** the hex-encoded audio blob both call sites already returned. No format change for downstream consumers. - **TTL:** 7 days by default, configurable via `RAGFLOW_TTS_CACHE_TTL_SECONDS`. - **Failure modes:** a Redis hiccup falls back to direct synthesis; a failed synthesis still returns `None` (existing contract preserved). [`Canvas.tts`](https://github.com/infiniflow/ragflow/blob/main/agent/canvas.py#L683-L724) and [`dialog_service.tts`](https://github.com/infiniflow/ragflow/blob/main/api/db/services/dialog_service.py#L1367-L1380) now route through the helper; the per-file bytes-accumulation/hex-encode loop has been removed in favor of one shared implementation. ## Type of change - [x] New Feature (non-breaking change which adds functionality) ## Test plan - [ ] **Cache hit, chat path:** Configure a dialog with TTS enabled, ask the same question twice with `stream=false`. Verify the second response returns the same `audio_binary` and that the second invocation doesn't hit the TTS provider (e.g., observe provider-side logs / usage counters; check no `LLMBundle.tts can't update token usage` log line on the second run). - [ ] **Cache hit, agent path:** Same exercise via a Conversational Agent that includes a Message component playing back the answer. - [ ] **Cache isolation per model:** Switch tenant's `tts_id` between two models, run the same text against each — confirm the second model's first synthesis still happens (no cross-model hits). - [ ] **TTL override:** Set `RAGFLOW_TTS_CACHE_TTL_SECONDS=120`, confirm the entry expires after 2 minutes. - [ ] **Redis unavailable:** Stop Redis (or break the connection). Verify the TTS endpoint still works — synthesis falls back to direct calls, with a `TTS cache lookup failed` / `TTS cache store failed` warning logged. - [ ] **Failure path:** Configure a TTS model with an invalid API key, ensure the response still returns successfully with `audio_binary=None` (no regression vs. current behavior).
2026-05-18 23:20:40 -07:00
return synthesize_with_cache(tts_mdl, text)
def get_history(self, window_size):
convs = []
if window_size <= 0:
return convs
for role, obj in self.history[window_size * -2:]:
if isinstance(obj, dict):
convs.append({"role": role, "content": obj.get("content", "")})
else:
convs.append({"role": role, "content": str(obj)})
return convs
def add_user_input(self, question):
self.history.append(("user", question))
self.globals["sys.history"].append(f"{self.history[-1][0]}: {self.history[-1][1]}")
def get_prologue(self):
return self.components["begin"]["obj"]._param.prologue
def get_mode(self):
return self.components["begin"]["obj"]._param.mode
def get_sys_query(self):
return self.globals.get("sys.query", "")
def set_global_param(self, **kwargs):
self.globals.update(kwargs)
def get_preset_param(self):
return self.components["begin"]["obj"]._param.inputs
def get_component_input_elements(self, cpnnm):
return self.components[cpnnm]["obj"].get_input_elements()
2026-03-04 05:09:33 +02:00
async def get_files_async(self, files: Union[None, list[dict]], layout_recognize: str = None) -> list[str]:
if not files:
return []
def image_to_base64(file):
return "data:{};base64,{}".format(file["mime_type"],
base64.b64encode(FileService.get_blob(file["created_by"], file["id"])).decode("utf-8"))
def parse_file(file):
blob = FileService.get_blob(file["created_by"], file["id"])
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return FileService.parse(file["name"], blob, True, file["created_by"], layout_recognize)
loop = asyncio.get_running_loop()
tasks = []
for file in files:
if file["mime_type"].find("image") >=0:
tasks.append(loop.run_in_executor(self._thread_pool, image_to_base64, file))
continue
tasks.append(loop.run_in_executor(self._thread_pool, parse_file, file))
return await asyncio.gather(*tasks)
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def get_files(self, files: Union[None, list[dict]], layout_recognize: str = None) -> list[str]:
"""
Synchronous wrapper for get_files_async, used by sync component invoke paths.
"""
loop = getattr(self, "_loop", None)
if loop and loop.is_running():
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return asyncio.run_coroutine_threadsafe(self.get_files_async(files, layout_recognize), loop).result()
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return asyncio.run(self.get_files_async(files, layout_recognize))
def tool_use_callback(self, agent_id: str, func_name: str, params: dict, result: Any, elapsed_time=None):
agent_ids = agent_id.split("-->")
agent_name = self.get_component_name(agent_ids[0])
path = agent_name if len(agent_ids) < 2 else agent_name+"-->"+"-->".join(agent_ids[1:])
try:
bin = REDIS_CONN.get(f"{self.task_id}-{self.message_id}-logs")
if bin:
obj = json.loads(bin.encode("utf-8"))
if obj[-1]["component_id"] == agent_ids[0]:
obj[-1]["trace"].append({"path": path, "tool_name": func_name, "arguments": params, "result": result, "elapsed_time": elapsed_time})
else:
obj.append({
"component_id": agent_ids[0],
"trace": [{"path": path, "tool_name": func_name, "arguments": params, "result": result, "elapsed_time": elapsed_time}]
})
else:
obj = [{
"component_id": agent_ids[0],
"trace": [{"path": path, "tool_name": func_name, "arguments": params, "result": result, "elapsed_time": elapsed_time}]
}]
REDIS_CONN.set_obj(f"{self.task_id}-{self.message_id}-logs", obj, 60*10)
except Exception as e:
logging.exception(e)
def add_reference(self, chunks: list[object], doc_infos: list[object]):
if not self.retrieval:
self.retrieval = [{"chunks": {}, "doc_aggs": {}}]
r = self.retrieval[-1]
for ck in chunks_format({"chunks": chunks}):
cid = hash_str2int(ck["id"], 500)
# cid = uuid.uuid5(uuid.NAMESPACE_DNS, ck["id"])
if cid not in r:
r["chunks"][cid] = ck
for doc in doc_infos:
if doc["doc_name"] not in r:
r["doc_aggs"][doc["doc_name"]] = doc
def get_reference(self):
if not self.retrieval:
return {"chunks": {}, "doc_aggs": {}}
return self.retrieval[-1]
Feature rtl support (#13118) ### What problem does this PR solve? This PR adds comprehensive **Right-to-Left (RTL) language support**, primarily targeting Arabic and other RTL scripts (Hebrew, Persian, Urdu, etc.). Previously, RTL content had multiple rendering issues: - Incorrect sentence splitting for Arabic punctuation in citation logic - Misaligned text in chat messages and markdown components - Improper positioning of blockquotes and “think” sections - Incorrect table alignment - Citation placement ambiguity in RTL prompts - UI layout inconsistencies when mixing LTR and RTL text This PR introduces backend and frontend improvements to properly detect, render, and style RTL content while preserving existing LTR behavior. #### Backend - Updated sentence boundary regex in `rag/nlp/search.py` to include Arabic punctuation: - `،` (comma) - `؛` (semicolon) - `؟` (question mark) - `۔` (Arabic full stop) - Ensures citation insertion works correctly in RTL sentences. - Updated citation prompt instructions to clarify citation placement rules for RTL languages. #### Frontend - Introduced a new utility: `text-direction.ts` - Detects text direction based on Unicode ranges. - Supports Arabic, Hebrew, Syriac, Thaana, and related scripts. - Provides `getDirAttribute()` for automatic `dir` assignment. - Applied dynamic `dir` attributes across: - Markdown rendering - Chat messages - Search results - Tables - Hover cards and reference popovers - Added proper RTL styling in LESS: - Text alignment adjustments - Blockquote border flipping - Section indentation correction - Table direction switching - Use of `<bdi>` for figure labels to prevent bidirectional conflicts #### DevOps / Environment - Added Windows backend launch script with retry handling. - Updated dependency metadata. - Adjusted development-only React debugging behavior. --- ### Type of change - [x] Bug Fix (non-breaking change which fixes RTL rendering and citation issues) - [x] New Feature (non-breaking change which adds RTL detection and dynamic direction handling) --------- Co-authored-by: 6ba3i <isbaaoui09@gmail.com> Co-authored-by: Ahmad Intisar <ahmadintisar@Ahmads-MacBook-M4-Pro.local> Co-authored-by: Ahmad Intisar <168020872+ahmadintisar@users.noreply.github.com> Co-authored-by: Liu An <asiro@qq.com>
2026-03-02 08:03:44 +03:00
def _has_reference(self) -> bool:
ref = self.get_reference()
if not isinstance(ref, dict):
return False
return bool(ref.get("chunks") or ref.get("doc_aggs"))
def _build_message_end(self, cpn_obj) -> dict:
message_end = {}
if cpn_obj.get_param("status"):
message_end["status"] = cpn_obj.get_param("status")
if isinstance(cpn_obj.output("attachment"), dict):
message_end["attachment"] = cpn_obj.output("attachment")
if self._has_reference():
message_end["reference"] = self.get_reference()
return message_end
def add_memory(self, user:str, assist:str, summ: str):
self.memory.append((user, assist, summ))
def get_memory(self) -> list[Tuple]:
return self.memory
def get_component_thoughts(self, cpn_id) -> str:
return self.components.get(cpn_id)["obj"].thoughts()