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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 re
from abc import ABC
from api.db import LLMType
from api.db.services.llm_service import LLMBundle
from agent.component import GenerateParam, Generate
from agent.settings import DEBUG
class KeywordExtractParam(GenerateParam):
"""
Define the KeywordExtract component parameters.
"""
def __init__(self):
super().__init__()
self.top_n = 1
def check(self):
super().check()
self.check_positive_integer(self.top_n, "Top N")
def get_prompt(self):
self.prompt = """
- Role: You're a question analyzer.
- Requirements:
- Summarize user's question, and give top %s important keyword/phrase.
- Use comma as a delimiter to separate keywords/phrases.
- Answer format: (in language of user's question)
- keyword:
""" % self.top_n
return self.prompt
class KeywordExtract(Generate, ABC):
component_name = "KeywordExtract"
def _run(self, history, **kwargs):
q = ""
for r, c in self._canvas.history[::-1]:
if r == "user":
q += c
break
chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id)
ans = chat_mdl.chat(self._param.get_prompt(), [{"role": "user", "content": q}],
self._param.gen_conf())
ans = re.sub(r".*keyword:", "", ans).strip()
if DEBUG: print(ans, ":::::::::::::::::::::::::::::::::")
return KeywordExtract.be_output(ans)
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