mirror of
https://github.com/infiniflow/ragflow.git
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41 lines
1.4 KiB
Python
41 lines
1.4 KiB
Python
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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 re
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from api.db import LLMType
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from rag.nlp import rag_tokenizer
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from api.db.services.llm_service import LLMBundle
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from rag.nlp import tokenize
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def chunk(filename, binary, tenant_id, lang, callback=None, **kwargs):
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doc = {
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"docnm_kwd": filename,
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"title_tks": rag_tokenizer.tokenize(re.sub(r"\.[a-zA-Z]+$", "", filename))
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}
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doc["title_sm_tks"] = rag_tokenizer.fine_grained_tokenize(doc["title_tks"])
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# is it English
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eng = lang.lower() == "english" # is_english(sections)
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try:
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callback(0.1, "USE Sequence2Txt LLM to transcription the audio")
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seq2txt_mdl = LLMBundle(tenant_id, LLMType.SPEECH2TEXT, lang=lang)
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ans = seq2txt_mdl.transcription(binary)
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callback(0.8, "Sequence2Txt LLM respond: %s ..." % ans[:32])
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tokenize(doc, ans, eng)
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return [doc]
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except Exception as e:
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callback(prog=-1, msg=str(e))
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return []
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