Files
ragflow/agent/canvas.py
Willsgao 78db4e949b feat(agent): add module-level debug logging for canvas execution flow (#16200)
Summary

Add module-level debug logging to track Agent canvas execution flow
(Closes #9306), enabling developers to diagnose component invocation,
input/output states, and variable resolution without modifying
production code.

Also fix related bugs in message.py: re.sub backreference issue and
unawaited _save_to_memory coroutine causing silent memory save failures.

Changes

agent/canvas.py: log workflow start, component invocation, and component
completion
agent/component/agent_with_tools.py: log Agent parameter resolution and
LLM invocation path; standardize json.dumps usage
agent/component/base.py: log get_input() variable resolution branches
agent/component/message.py: fix re.sub backreference issue; properly
await _save_to_memory coroutine

Design

Uses module-level loggers (logging.getLogger(__name__)) to support
selective debugging: LOG_LEVELS=agent=DEBUG
Zero performance impact in production (INFO level by default)
Works with existing PUT /system/config/log API for runtime level changes

Closes #9306

Note: While adding debug logging, I discovered and fixed two related
bugs in message.py:
- re.sub replacement value was interpreted as regex backreference
instead of literal string
- _save_to_memory coroutine was not properly awaited, causing silent
failures

---------

Co-authored-by: wills <willsgao@163.com>
2026-06-29 09:45:17 +08:00

899 lines
35 KiB
Python

#
# 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
from rag.utils.tts_cache import synthesize_with_cache
_logger = logging.getLogger(__name__)
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))
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
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
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 clear_history(self):
self.history = []
if isinstance(self.globals.get("sys.history"), list):
self.globals["sys.history"] = []
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"))
path_set = set(self.path)
for k, cpn in self.components.items():
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)
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":
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
is_resume = bool(self.path) and self.path[0].lower().find("userfillup") >= 0
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 is_resume:
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)
if not is_resume:
yield decorate("workflow_started", {"inputs": kwargs.get("inputs")})
_logger.debug(
"[Canvas] Workflow started. Path: %s, Inputs: %s",
[self.get_component_name(c) for c in self.path],
json.dumps(kwargs.get("inputs", {}), ensure_ascii=False, default=str)[:500],
)
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
_logger.debug(
"[Canvas] Invoking component '%s' (%s) with inputs: %s",
self.get_component_name(self.path[i - 1]),
cpn.component_name,
json.dumps(call_kwargs, ensure_ascii=False, default=str)[:500],
)
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):
outputs = cpn_obj.output()
_logger.debug(
"[Canvas] Component '%s' (%s) finished. Outputs: %s, Error: %s",
self.get_component_name(cpn_obj._id),
self.get_component_type(cpn_obj._id),
json.dumps(outputs, ensure_ascii=False, default=str)[:500],
cpn_obj.error(),
)
return decorate("node_finished",{
"inputs": cpn_obj.get_input_values(),
"outputs": outputs,
"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 = 0 if is_resume else 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")})
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.components.get(c) is not None and 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.components.get(c) is not None and self.get_component(c)["obj"].component_name.lower() == "userfillup"]
path.extend([c for c in self.path[idx:] if self.components.get(c) is not None and 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({
k: v for k, v in o.get_input_elements().items()
if not self._is_input_field_satisfied(v)
})
if o.get_param("enable_tips"):
tips = o.output("tips")
if not another_inputs:
continue
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
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))
rendered = json.dumps(question, ensure_ascii=False) if isinstance(question, dict) else question
self.globals["sys.history"].append(f"{self.history[-1][0]}: {rendered}")
@staticmethod
def _is_input_field_satisfied(field: Any) -> bool:
if not isinstance(field, dict):
return field is not None
value = field.get("value")
field_type = str(field.get("type", "")).lower()
if field_type.find("file") >= 0:
if field.get("optional") and value is None:
return True
return value not in (None, [], "")
if value is None:
return False
return True
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()
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"])
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)
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():
return asyncio.run_coroutine_threadsafe(self.get_files_async(files, layout_recognize), loop).result()
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]
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()