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1b19d302c5
### What problem does this PR solve? ### Type of change - [x] New Feature (non-breaking change which adds functionality)
60 lines
2.0 KiB
Python
60 lines
2.0 KiB
Python
#
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# Copyright 2025 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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import random
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from agent.component.llm import LLMParam, LLM
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class ExtractorParam(LLMParam):
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def __init__(self):
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super().__init__()
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self.field_name = ""
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def check(self):
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super().check()
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self.check_empty(self.field_name, "Result Destination")
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class Extractor(LLM):
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component_name = "Extractor"
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async def _invoke(self, **kwargs):
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self.callback(random.randint(1, 5) / 100.0, "Start to generate.")
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inputs = self.get_input_elements()
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chunks = []
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chunks_key = ""
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args = {}
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for k, v in inputs.items():
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args[k] = v["value"]
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if isinstance(args[k], list):
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chunks = args[k]
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chunks_key = k
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if chunks:
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prog = 0
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for i, ck in enumerate(chunks):
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args[chunks_key] = ck["text"]
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msg, sys_prompt = self._sys_prompt_and_msg([], args)
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msg.insert(0, {"role": "system", "content": sys_prompt})
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ck[self._param.field_name] = self._generate(msg)
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prog += 1./len(chunks)
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self.callback(prog, f"{i+1} / {len(chunks)}")
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self.set_output("chunks", chunks)
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else:
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msg, sys_prompt = self._sys_prompt_and_msg([], args)
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msg.insert(0, {"role": "system", "content": sys_prompt})
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self.set_output("chunks", [{self._param.field_name: self._generate(msg)}])
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