mirror of
https://github.com/infiniflow/ragflow.git
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534fa60b2a
### What problem does this PR solve? Fix: Agent.reset() argument wrong #10463 & Unable to converse with agent through Python API. #10415 ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)
513 lines
20 KiB
Python
513 lines
20 KiB
Python
#
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# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import base64
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import json
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import logging
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import re
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import time
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from concurrent.futures import ThreadPoolExecutor
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from copy import deepcopy
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from functools import partial
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from typing import Any, Union, Tuple
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from agent.component import component_class
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from agent.component.base import ComponentBase
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from api.db.services.file_service import FileService
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from api.utils import get_uuid, hash_str2int
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from rag.prompts.generator import chunks_format
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from rag.utils.redis_conn import REDIS_CONN
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class Graph:
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"""
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dsl = {
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"components": {
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"begin": {
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"obj":{
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"component_name": "Begin",
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"params": {},
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},
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"downstream": ["answer_0"],
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"upstream": [],
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},
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"retrieval_0": {
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"obj": {
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"component_name": "Retrieval",
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"params": {}
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},
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"downstream": ["generate_0"],
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"upstream": ["answer_0"],
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},
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"generate_0": {
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"obj": {
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"component_name": "Generate",
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"params": {}
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},
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"downstream": ["answer_0"],
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"upstream": ["retrieval_0"],
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}
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},
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"history": [],
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"path": ["begin"],
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"retrieval": {"chunks": [], "doc_aggs": []},
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"globals": {
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"sys.query": "",
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"sys.user_id": tenant_id,
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"sys.conversation_turns": 0,
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"sys.files": []
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}
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}
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"""
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def __init__(self, dsl: str, tenant_id=None, task_id=None):
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self.path = []
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self.components = {}
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self.error = ""
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self.dsl = json.loads(dsl)
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self._tenant_id = tenant_id
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self.task_id = task_id if task_id else get_uuid()
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self.load()
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def load(self):
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self.components = self.dsl["components"]
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cpn_nms = set([])
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for k, cpn in self.components.items():
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cpn_nms.add(cpn["obj"]["component_name"])
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for k, cpn in self.components.items():
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cpn_nms.add(cpn["obj"]["component_name"])
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param = component_class(cpn["obj"]["component_name"] + "Param")()
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param.update(cpn["obj"]["params"])
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try:
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param.check()
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except Exception as e:
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raise ValueError(self.get_component_name(k) + f": {e}")
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cpn["obj"] = component_class(cpn["obj"]["component_name"])(self, k, param)
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self.path = self.dsl["path"]
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def __str__(self):
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self.dsl["path"] = self.path
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self.dsl["task_id"] = self.task_id
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dsl = {
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"components": {}
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}
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for k in self.dsl.keys():
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if k in ["components"]:
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continue
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dsl[k] = deepcopy(self.dsl[k])
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for k, cpn in self.components.items():
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if k not in dsl["components"]:
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dsl["components"][k] = {}
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for c in cpn.keys():
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if c == "obj":
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dsl["components"][k][c] = json.loads(str(cpn["obj"]))
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continue
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dsl["components"][k][c] = deepcopy(cpn[c])
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return json.dumps(dsl, ensure_ascii=False)
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def reset(self):
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self.path = []
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for k, cpn in self.components.items():
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self.components[k]["obj"].reset()
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try:
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REDIS_CONN.delete(f"{self.task_id}-logs")
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except Exception as e:
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logging.exception(e)
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def get_component_name(self, cid):
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for n in self.dsl.get("graph", {}).get("nodes", []):
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if cid == n["id"]:
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return n["data"]["name"]
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return ""
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def run(self, **kwargs):
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raise NotImplementedError()
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def get_component(self, cpn_id) -> Union[None, dict[str, Any]]:
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return self.components.get(cpn_id)
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def get_component_obj(self, cpn_id) -> ComponentBase:
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return self.components.get(cpn_id)["obj"]
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def get_component_type(self, cpn_id) -> str:
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return self.components.get(cpn_id)["obj"].component_name
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def get_component_input_form(self, cpn_id) -> dict:
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return self.components.get(cpn_id)["obj"].get_input_form()
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def get_tenant_id(self):
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return self._tenant_id
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def get_variable_value(self, exp: str) -> Any:
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exp = exp.strip("{").strip("}").strip(" ").strip("{").strip("}")
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if exp.find("@") < 0:
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return self.globals[exp]
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cpn_id, var_nm = exp.split("@")
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cpn = self.get_component(cpn_id)
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if not cpn:
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raise Exception(f"Can't find variable: '{cpn_id}@{var_nm}'")
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return cpn["obj"].output(var_nm)
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class Canvas(Graph):
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def __init__(self, dsl: str, tenant_id=None, task_id=None):
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self.globals = {
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"sys.query": "",
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"sys.user_id": tenant_id,
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"sys.conversation_turns": 0,
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"sys.files": []
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}
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super().__init__(dsl, tenant_id, task_id)
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def load(self):
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super().load()
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self.history = self.dsl["history"]
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if "globals" in self.dsl:
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self.globals = self.dsl["globals"]
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else:
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self.globals = {
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"sys.query": "",
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"sys.user_id": "",
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"sys.conversation_turns": 0,
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"sys.files": []
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}
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self.retrieval = self.dsl["retrieval"]
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self.memory = self.dsl.get("memory", [])
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def __str__(self):
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self.dsl["history"] = self.history
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self.dsl["retrieval"] = self.retrieval
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self.dsl["memory"] = self.memory
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return super().__str__()
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def reset(self, mem=False):
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super().reset()
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if not mem:
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self.history = []
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self.retrieval = []
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self.memory = []
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for k in self.globals.keys():
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if isinstance(self.globals[k], str):
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self.globals[k] = ""
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elif isinstance(self.globals[k], int):
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self.globals[k] = 0
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elif isinstance(self.globals[k], float):
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self.globals[k] = 0
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elif isinstance(self.globals[k], list):
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self.globals[k] = []
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elif isinstance(self.globals[k], dict):
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self.globals[k] = {}
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else:
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self.globals[k] = None
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def run(self, **kwargs):
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st = time.perf_counter()
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self.message_id = get_uuid()
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created_at = int(time.time())
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self.add_user_input(kwargs.get("query"))
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for k, cpn in self.components.items():
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self.components[k]["obj"].reset(True)
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for k in kwargs.keys():
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if k in ["query", "user_id", "files"] and kwargs[k]:
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if k == "files":
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self.globals[f"sys.{k}"] = self.get_files(kwargs[k])
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else:
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self.globals[f"sys.{k}"] = kwargs[k]
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if not self.globals["sys.conversation_turns"] :
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self.globals["sys.conversation_turns"] = 0
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self.globals["sys.conversation_turns"] += 1
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def decorate(event, dt):
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nonlocal created_at
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return {
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"event": event,
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#"conversation_id": "f3cc152b-24b0-4258-a1a1-7d5e9fc8a115",
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"message_id": self.message_id,
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"created_at": created_at,
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"task_id": self.task_id,
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"data": dt
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}
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if not self.path or self.path[-1].lower().find("userfillup") < 0:
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self.path.append("begin")
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self.retrieval.append({"chunks": [], "doc_aggs": []})
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yield decorate("workflow_started", {"inputs": kwargs.get("inputs")})
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self.retrieval.append({"chunks": {}, "doc_aggs": {}})
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def _run_batch(f, t):
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with ThreadPoolExecutor(max_workers=5) as executor:
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thr = []
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for i in range(f, t):
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cpn = self.get_component_obj(self.path[i])
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if cpn.component_name.lower() in ["begin", "userfillup"]:
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thr.append(executor.submit(cpn.invoke, inputs=kwargs.get("inputs", {})))
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else:
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thr.append(executor.submit(cpn.invoke, **cpn.get_input()))
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for t in thr:
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t.result()
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def _node_finished(cpn_obj):
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return decorate("node_finished",{
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"inputs": cpn_obj.get_input_values(),
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"outputs": cpn_obj.output(),
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"component_id": cpn_obj._id,
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"component_name": self.get_component_name(cpn_obj._id),
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"component_type": self.get_component_type(cpn_obj._id),
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"error": cpn_obj.error(),
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"elapsed_time": time.perf_counter() - cpn_obj.output("_created_time"),
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"created_at": cpn_obj.output("_created_time"),
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})
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self.error = ""
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idx = len(self.path) - 1
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partials = []
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while idx < len(self.path):
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to = len(self.path)
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for i in range(idx, to):
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yield decorate("node_started", {
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"inputs": None, "created_at": int(time.time()),
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"component_id": self.path[i],
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"component_name": self.get_component_name(self.path[i]),
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"component_type": self.get_component_type(self.path[i]),
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"thoughts": self.get_component_thoughts(self.path[i])
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})
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_run_batch(idx, to)
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# post processing of components invocation
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for i in range(idx, to):
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cpn = self.get_component(self.path[i])
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cpn_obj = self.get_component_obj(self.path[i])
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if cpn_obj.component_name.lower() == "message":
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if isinstance(cpn_obj.output("content"), partial):
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_m = ""
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for m in cpn_obj.output("content")():
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if not m:
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continue
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if m == "<think>":
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yield decorate("message", {"content": "", "start_to_think": True})
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elif m == "</think>":
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yield decorate("message", {"content": "", "end_to_think": True})
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else:
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yield decorate("message", {"content": m})
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_m += m
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cpn_obj.set_output("content", _m)
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cite = re.search(r"\[ID:[ 0-9]+\]", _m)
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else:
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yield decorate("message", {"content": cpn_obj.output("content")})
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cite = re.search(r"\[ID:[ 0-9]+\]", cpn_obj.output("content"))
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yield decorate("message_end", {"reference": self.get_reference() if cite else None})
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while partials:
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_cpn_obj = self.get_component_obj(partials[0])
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if isinstance(_cpn_obj.output("content"), partial):
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break
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yield _node_finished(_cpn_obj)
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partials.pop(0)
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other_branch = False
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if cpn_obj.error():
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ex = cpn_obj.exception_handler()
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if ex and ex["goto"]:
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self.path.extend(ex["goto"])
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other_branch = True
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elif ex and ex["default_value"]:
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yield decorate("message", {"content": ex["default_value"]})
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yield decorate("message_end", {})
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else:
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self.error = cpn_obj.error()
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if cpn_obj.component_name.lower() != "iteration":
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if isinstance(cpn_obj.output("content"), partial):
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if self.error:
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cpn_obj.set_output("content", None)
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yield _node_finished(cpn_obj)
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else:
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partials.append(self.path[i])
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else:
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yield _node_finished(cpn_obj)
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def _append_path(cpn_id):
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nonlocal other_branch
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if other_branch:
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return
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if self.path[-1] == cpn_id:
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return
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self.path.append(cpn_id)
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def _extend_path(cpn_ids):
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nonlocal other_branch
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if other_branch:
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return
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for cpn_id in cpn_ids:
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_append_path(cpn_id)
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if cpn_obj.component_name.lower() == "iterationitem" and cpn_obj.end():
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iter = cpn_obj.get_parent()
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yield _node_finished(iter)
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_extend_path(self.get_component(cpn["parent_id"])["downstream"])
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elif cpn_obj.component_name.lower() in ["categorize", "switch"]:
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_extend_path(cpn_obj.output("_next"))
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elif cpn_obj.component_name.lower() == "iteration":
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_append_path(cpn_obj.get_start())
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elif not cpn["downstream"] and cpn_obj.get_parent():
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_append_path(cpn_obj.get_parent().get_start())
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else:
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_extend_path(cpn["downstream"])
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if self.error:
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logging.error(f"Runtime Error: {self.error}")
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break
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idx = to
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if any([self.get_component_obj(c).component_name.lower() == "userfillup" for c in self.path[idx:]]):
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path = [c for c in self.path[idx:] if self.get_component(c)["obj"].component_name.lower() == "userfillup"]
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path.extend([c for c in self.path[idx:] if self.get_component(c)["obj"].component_name.lower() != "userfillup"])
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another_inputs = {}
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tips = ""
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for c in path:
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o = self.get_component_obj(c)
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if o.component_name.lower() == "userfillup":
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another_inputs.update(o.get_input_elements())
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if o.get_param("enable_tips"):
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tips = o.get_param("tips")
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self.path = path
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yield decorate("user_inputs", {"inputs": another_inputs, "tips": tips})
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return
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self.path = self.path[:idx]
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if not self.error:
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yield decorate("workflow_finished",
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{
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"inputs": kwargs.get("inputs"),
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"outputs": self.get_component_obj(self.path[-1]).output(),
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"elapsed_time": time.perf_counter() - st,
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"created_at": st,
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})
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self.history.append(("assistant", self.get_component_obj(self.path[-1]).output()))
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def is_reff(self, exp: str) -> bool:
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exp = exp.strip("{").strip("}")
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if exp.find("@") < 0:
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return exp in self.globals
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arr = exp.split("@")
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if len(arr) != 2:
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return False
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if self.get_component(arr[0]) is None:
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return False
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return True
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def get_history(self, window_size):
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convs = []
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if window_size <= 0:
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return convs
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for role, obj in self.history[window_size * -2:]:
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if isinstance(obj, dict):
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convs.append({"role": role, "content": obj.get("content", "")})
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else:
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convs.append({"role": role, "content": str(obj)})
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return convs
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def add_user_input(self, question):
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self.history.append(("user", question))
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def get_prologue(self):
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return self.components["begin"]["obj"]._param.prologue
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def get_mode(self):
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return self.components["begin"]["obj"]._param.mode
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def set_global_param(self, **kwargs):
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self.globals.update(kwargs)
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def get_preset_param(self):
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return self.components["begin"]["obj"]._param.inputs
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def get_component_input_elements(self, cpnnm):
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return self.components[cpnnm]["obj"].get_input_elements()
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def get_files(self, files: Union[None, list[dict]]) -> list[str]:
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if not files:
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return []
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def image_to_base64(file):
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return "data:{};base64,{}".format(file["mime_type"],
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base64.b64encode(FileService.get_blob(file["created_by"], file["id"])).decode("utf-8"))
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exe = ThreadPoolExecutor(max_workers=5)
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threads = []
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for file in files:
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if file["mime_type"].find("image") >=0:
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threads.append(exe.submit(image_to_base64, file))
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continue
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threads.append(exe.submit(FileService.parse, file["name"], FileService.get_blob(file["created_by"], file["id"]), True, file["created_by"]))
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return [th.result() for th in threads]
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def tool_use_callback(self, agent_id: str, func_name: str, params: dict, result: Any, elapsed_time=None):
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agent_ids = agent_id.split("-->")
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agent_name = self.get_component_name(agent_ids[0])
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path = agent_name if len(agent_ids) < 2 else agent_name+"-->"+"-->".join(agent_ids[1:])
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try:
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bin = REDIS_CONN.get(f"{self.task_id}-{self.message_id}-logs")
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if bin:
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obj = json.loads(bin.encode("utf-8"))
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if obj[-1]["component_id"] == agent_ids[0]:
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obj[-1]["trace"].append({"path": path, "tool_name": func_name, "arguments": params, "result": result, "elapsed_time": elapsed_time})
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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 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()
|
|
|