mirror of
https://github.com/infiniflow/ragflow.git
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f24d464a53
### What problem does this PR solve? ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)
110 lines
3.5 KiB
Python
110 lines
3.5 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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#
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import io
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import re
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import numpy as np
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from PIL import Image
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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 deepdoc.vision import OCR
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from rag.nlp import rag_tokenizer, tokenize
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from rag.utils import clean_markdown_block
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ocr = OCR()
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# Gemini supported MIME types
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VIDEO_EXTS = [".mp4", ".mov", ".avi", ".flv", ".mpeg", ".mpg", ".webm", ".wmv", ".3gp", ".3gpp", ".mkv"]
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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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eng = lang.lower() == "english"
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if any(filename.lower().endswith(ext) for ext in VIDEO_EXTS):
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try:
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doc.update({"doc_type_kwd": "video"})
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cv_mdl = LLMBundle(tenant_id, llm_type=LLMType.IMAGE2TEXT, lang=lang)
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ans = cv_mdl.chat(system="", history=[], gen_conf={}, video_bytes=binary, filename=filename)
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callback(0.8, "CV LLM respond: %s ..." % ans[:32])
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ans += "\n" + ans
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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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else:
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img = Image.open(io.BytesIO(binary)).convert("RGB")
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doc.update(
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{
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"image": img,
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"doc_type_kwd": "image",
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}
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)
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bxs = ocr(np.array(img))
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txt = "\n".join([t[0] for _, t in bxs if t[0]])
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callback(0.4, "Finish OCR: (%s ...)" % txt[:12])
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if (eng and len(txt.split()) > 32) or len(txt) > 32:
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tokenize(doc, txt, eng)
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callback(0.8, "OCR results is too long to use CV LLM.")
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return [doc]
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try:
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callback(0.4, "Use CV LLM to describe the picture.")
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cv_mdl = LLMBundle(tenant_id, LLMType.IMAGE2TEXT, lang=lang)
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img_binary = io.BytesIO()
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img.save(img_binary, format="JPEG")
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img_binary.seek(0)
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ans = cv_mdl.describe(img_binary.read())
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callback(0.8, "CV LLM respond: %s ..." % ans[:32])
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txt += "\n" + ans
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tokenize(doc, txt, 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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def vision_llm_chunk(binary, vision_model, prompt=None, callback=None):
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"""
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A simple wrapper to process image to markdown texts via VLM.
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Returns:
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Simple markdown texts generated by VLM.
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"""
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callback = callback or (lambda prog, msg: None)
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img = binary
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txt = ""
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try:
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with io.BytesIO() as img_binary:
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img.save(img_binary, format="JPEG")
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img_binary.seek(0)
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ans = clean_markdown_block(vision_model.describe_with_prompt(img_binary.read(), prompt))
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txt += "\n" + ans
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return txt
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except Exception as e:
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callback(-1, str(e))
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return ""
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