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2c62652ea8
### What problem does this PR solve? Some models force thinking, resulting in the absence of the think tag in the returned content ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)
67 lines
2.1 KiB
Python
67 lines
2.1 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 logging
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import re
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from abc import ABC
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from api.db import LLMType
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from api.db.services.llm_service import LLMBundle
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from agent.component import GenerateParam, Generate
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class KeywordExtractParam(GenerateParam):
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"""
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Define the KeywordExtract component parameters.
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"""
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def __init__(self):
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super().__init__()
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self.top_n = 1
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def check(self):
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super().check()
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self.check_positive_integer(self.top_n, "Top N")
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def get_prompt(self):
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self.prompt = """
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- Role: You're a question analyzer.
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- Requirements:
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- Summarize user's question, and give top %s important keyword/phrase.
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- Use comma as a delimiter to separate keywords/phrases.
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- Answer format: (in language of user's question)
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- keyword:
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""" % self.top_n
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return self.prompt
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class KeywordExtract(Generate, ABC):
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component_name = "KeywordExtract"
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def _run(self, history, **kwargs):
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query = self.get_input()
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query = str(query["content"][0]) if "content" in query else ""
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chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id)
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ans = chat_mdl.chat(self._param.get_prompt(), [{"role": "user", "content": query}],
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self._param.gen_conf())
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ans = re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)
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ans = re.sub(r".*keyword:", "", ans).strip()
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logging.debug(f"ans: {ans}")
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return KeywordExtract.be_output(ans)
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def debug(self, **kwargs):
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return self._run([], **kwargs)
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