!2 Merge pull request #93 from gc-fu/patch-1

Merge pull request !2 from zhch158/master

NOTICE

@@ -0,0 +1,1109 @@
+==================================================================
+=============== Copyright Notice and License Texts ===============
+==================================================================
+
+
+------------- LICENSE FOR gradio CODE --------------
+ 
+Copyright notice:No copyright info provided
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+
+------------- LICENSE FOR gradio_image_annotation CODE --------------
+ 
+Copyright notice：Copyright (c) 2024 Edgar Gracia
+License :MIT
+MIT License
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+Copyright (c) 2024 Edgar Gracia
+
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+
+
+
+------------- LICENSE FOR PyMuPDF CODE  --------------
+ 
+Copyright notice：Copyright (C) 2007 Free Software Foundation, Inc.
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+  If you convey a covered work, knowingly relying on a patent license, and the Corresponding Source of the work is not available for anyone to copy, free of charge and under the terms of this License, through a publicly available network server or other readily accessible means, then you must either (1) cause the Corresponding Source to be so available, or (2) arrange to deprive yourself of the benefit of the patent license for this particular work, or (3) arrange, in a manner consistent with the requirements of this License, to extend the patent license to downstream recipients.  "Knowingly relying" means you have actual knowledge that, but for the patent license, your conveying the covered work in a country, or your recipient's use of the covered work in a country, would infringe one or more identifiable patents in that country that you have reason to believe are valid.
+
+  If, pursuant to or in connection with a single transaction or arrangement, you convey, or propagate by procuring conveyance of, a covered work, and grant a patent license to some of the parties receiving the covered work authorizing them to use, propagate, modify or convey a specific copy of the covered work, then the patent license you grant is automatically extended to all recipients of the covered work and works based on it.
+
+  A patent license is "discriminatory" if it does not include within the scope of its coverage, prohibits the exercise of, or is conditioned on the non-exercise of one or more of the rights that are specifically granted under this License. You may not convey a covered work if you are a party to an arrangement with a third party that is in the business of distributing software, under which you make payment to the third party based on the extent of your activity of conveying the work, and under which the third party grants, to any of the parties who would receive the covered work from you, a discriminatory patent license (a) in connection with copies of the covered work conveyed by you (or copies made from those copies), or (b) primarily for and in connection with specific products or compilations that contain the covered work, unless you entered into that arrangement, or that patent license was granted, prior to 28 March 2007.
+
+  Nothing in this License shall be construed as excluding or limiting any implied license or other defenses to infringement that may otherwise be available to you under applicable patent law.
+
+  12. No Surrender of Others' Freedom.
+
+  If conditions are imposed on you (whether by court order, agreement or otherwise) that contradict the conditions of this License, they do not excuse you from the conditions of this License. If you cannot convey a covered work so as to satisfy simultaneously your obligations under this License and any other pertinent obligations, then as a consequence you may not convey it at all. For example, if you agree to terms that obligate you to collect a royalty for further conveying from those to whom you convey the Program, the only way you could satisfy both those terms and this License would be to refrain entirely from conveying the Program.
+
+  13. Remote Network Interaction; Use with the GNU General Public License.
+
+  Notwithstanding any other provision of this License, if you modify the Program, your modified version must prominently offer all users interacting with it remotely through a computer network (if your version supports such interaction) an opportunity to receive the Corresponding Source of your version by providing access to theCorresponding Source from a network server at no charge, through some standard or customary means of facilitating copying of software. This Corresponding Source shall include the Corresponding Source for any work covered by version 3 of the GNU General Public License that is incorporated pursuant to the following paragraph.
+
+  Notwithstanding any other provision of this License, you have permission to link or combine any covered work with a work licensed under version 3 of the GNU General Public License into a single combined work, and to convey the resulting work. The terms of this License will continue to apply to the part which is the covered work, but the work with which it is combined will remain governed by version3 of the GNU General Public License.
+
+  14. Revised Versions of this License.
+
+  The Free Software Foundation may publish revised and/or new versions of the GNU Affero General Public License from time to time. Such new versions will be similar in spirit to the present version, but may differ in detail to address new problems or concerns.
+
+  Each version is given a distinguishing version number. If the Program specifies that a certain numbered version of the GNU Affero General Public License "or any later version" applies to it, you have the option of following the terms and conditions either of that numbered version or of any later version published by the Free Software Foundation. If the Program does not specify a version number of the
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+
+  If the Program specifies that a proxy can decide which future versions of the GNU Affero General Public License can be used, that proxy's public statement of acceptance of a version permanently authorizes you to choose that version for the Program.
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+  15. Disclaimer of Warranty.
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+
+  16. Limitation of Liability.
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+
+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided above cannot be given local legal effect according to their terms, reviewing courts shall apply local law that most closely approximates an absolute waiver of all civil liability in connection with the Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program. It is safest to attach them to the start of each source file to most effectively state the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found.
+
+  <one line to give the program's name and a brief idea of what it does.> Copyright (C) <year>  <name of author>
+
+  This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
+
+  This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.
+
+  You should have received a copy of the GNU Affero General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+  If your software can interact with users remotely through a computer network, you should also make sure that it provides a way for users to get its source. For example, if your program is a web application, its interface could display a "Source" link that leads users to an archive of the code. There are many ways you could offer source, and different solutions will be better for different programs; see section 13 for the specific requirements.
+
+  You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary. For more information on this, and how to apply and follow the GNU AGPL, see <http://www.gnu.org/licenses/>.
+
+
+
+------------- LICENSE FOR openai CODE --------------
+
+Copyright notice:Copyright 2025 OpenAI
+
+License:apache2.0
+
+Please see above.
+
+
+
+------------- LICENSE FOR qwen_vl_utils CODE --------------
+
+Copyright notice:No copyright info provided
+
+License:apache2.0
+
+Please see above.
+
+
+
+------------- LICENSE FOR transformers CODE --------------
+
+Copyright notice:Copyright 2018- The Hugging Face team. All rights reserved.
+
+License:apache2.0
+
+Please see above.
+
+
+
+------------- LICENSE FOR huggingface_hub CODE --------------
+
+Copyright notice:No copyright info provided
+
+License:apache2.0
+
+Please see above.
+
+
+
+------------- LICENSE FOR flash-attn CODE --------------
+
+Copyright notice:Copyright (c) 2022, the respective contributors, as shown by the AUTHORS file. All rights reserved.
+
+License:BSD-3-Clause license
+
+BSD 3-Clause License
+
+Copyright (c) 2022, the respective contributors, as shown by the AUTHORS file. All rights reserved.
+
+Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
+
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+
+* Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
+
+* Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISEDOF THE POSSIBILITY OF SUCH DAMAGE.
+
+
+
+------------- LICENSE FOR accelerate CODE --------------
+
+Copyright notice:No copyright info provided
+
+License:apache2.0
+
+Please see above.
+
+
+
+------------- LICENSE FOR MonkeyOCR CODE --------------
+
+Copyright notice:No copyright info provided
+
+License:apache2.0
+
+Please see above.
+
+
+
+------------- LICENSE FOR OmniDocbench CODE --------------
+
+Copyright notice:No copyright info provided
+
+License:apache2.0
+
+Please see above.
+
+
+
+------------- LICENSE FOR Qwen2.5-VL CODE --------------
+
+Copyright notice:No copyright info provided
+
+License:apache2.0
+
+Please see above.
+
+
+
+------------- LICENSE FOR aimv2 CODE --------------
+
+Copyright notice: Copyright (C) 2024 Apple Inc. All Rights Reserved.
+
+License：
+
+IMPORTANT:  This Apple software is supplied to you by Apple Inc. ("Apple") in consideration of your agreement to the following terms, and your use, installation, modification or redistribution of this Apple software constitutes acceptance of these terms.  If you do not agree with these terms, please do not use, install, modify or
+redistribute this Apple software.
+
+In consideration of your agreement to abide by the following terms, and subject to these terms, Apple grants you a personal, non-exclusive license, under Apple's copyrights in this original Apple software (the "Apple Software"), to use, reproduce, modify and redistribute the Apple Software, with or without modifications, in source and/or binary forms; provided that if you redistribute the Apple Software in its entirety and without modifications, you must retain this notice and the following text and disclaimers in all such redistributions of the Apple Software. Neither the name, trademarks, service marks or logos of Apple Inc. May be used to endorse or promote products derived from the Apple Software without specific prior written permission from Apple.  Except as expressly stated in this notice, no other rights or licenses, express or implied, are granted by Apple herein, including but not limited to any patent rights that may be infringed by your derivative works or by other works in which the Apple Software may be incorporated.
+
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+FOR A PARTICULAR PURPOSE, REGARDING THE APPLE SOFTWARE OR ITS USE AND OPERATION ALONE OR IN COMBINATION WITH YOUR PRODUCTS. IN NO EVENT SHALL APPLE BE LIABLE FOR ANY SPECIAL, INDIRECT, INCIDENTAL
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+SOFTWARE DISTRIBUTED WITH AUTOREGRESSIVE IMAGE MODELS:
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+The Autoregressive Image Models software includes a number of subcomponents with
+separate  copyright notices and license terms - please see the file ACKNOWLEDGEMENTS.
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+Acknowledgements：
+
+Portions of the Autoregressive Image Models project may utilize the following copyrighted material, the use of which is hereby acknowledged.
+
+_____________________
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+Meta Platforms, Inc. and affiliates (Data-Efficient architectures and training for Image classification)
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+Copyright notice：Copyright 2020 - present, Facebook, Inc
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+License：apache2.0
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+     
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+_____________________
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+Meta Platforms, Inc. and affiliates (ImageBind: One Embedding Space To Bind Them All)
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+License：Attribution-NonCommercial-ShareAlike 4.0 International
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+  Creative Commons Corporation ("Creative Commons") is not a law firm and does not provide legal services or legal advice. Distribution of Creative Commons public licenses does not create a lawyer-client or other relationship. Creative Commons makes its licenses and related information available on an "as-is" basis. Creative Commons gives no warranties regarding its licenses, any material licensed under their terms and conditions, or any related information. Creative Commons disclaims all liability for damages resulting from their use to the fullest extent possible.
+
+   Using Creative Commons Public Licenses
+
+   Creative Commons public licenses provide a standard set of terms and conditions that creators and other rights holders may use to share original works of authorship and other material subject to copyright and certain other rights specified in the public license below. The following considerations are for informational purposes only, are not exhaustive, and do not form part of our licenses.
+
+    Considerations for licensors: Our public licenses are intended for use by those authorized to give the public permission to use material in ways otherwise restricted by copyright and certain other rights. Our licenses are irrevocable. Licensors should read and understand the terms and conditions of the license they choose before applying it. Licensors should also secure all rights necessary before applying our licenses so that the public can reuse the material as expected. Licensors should clearly mark any material not subject to the license. This includes other CC- licensed material, or material used under an exception or limitation to copyright. More considerations for licensors: wiki.creativecommons.org/Considerations_for_licensors
+
+    Considerations for the public: By using one of our public licenses, a licensor grants the public permission to use the licensed material under specified terms and conditions. If the licensor's permission is not necessary for any reason--for example, because of any applicable exception or limitation to copyright--then that use is not regulated by the license. Our licenses grant only permissions under copyright and certain other rights that a licensor has authority to grant. Use of the licensed material may still be restricted for other reasons, including because others have copyright or other rights in the material. A licensor may make special requests, such as asking that all changes be marked or described. Although not required by our licenses, you are encouraged to respect those requests where reasonable. More considerations for the public： wiki.creativecommons.org/Considerations_for_licensees
+
+
+
+Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License
+
+    By exercising the Licensed Rights (defined below), You accept and agree to be bound by the terms and conditions of this Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License  ("Public License"). To the extent this Public License may be interpreted as a contract, You are granted the Licensed Rights in consideration of Your acceptance of these terms and conditions, and the Licensor grants You such rights in consideration of benefits the Licensor receives from making the Licensed Material available under these terms and conditions.
+
+
+   Section 1 -- Definitions.
+
+   a. Adapted Material means material subject to Copyright and Similar Rights that is derived from or based upon the Licensed Material and in which the Licensed Material is translated, altered, arranged, transformed, or otherwise modified in a manner requiring permission under the Copyright and Similar Rights held by the Licensor. For purposes of this Public License, where the Licensed Material is a musical work, performance, or sound recording,  Adapted Material is always produced where the Licensed Material is synched in timed relation with a moving image.
+
+   b. Adapter's License means the license You apply to Your Copyright and Similar Rights in Your contributions to Adapted Material in accordance with the terms and conditions of this Public License.
+
+   c. BY-NC-SA Compatible License means a license listed at creative commons.org/compatiblelicenses, approved by CreativeCommons as essentially the equivalent of this Public License.
+
+   d. Copyright and Similar Rights means copyright and/or similar rights closely related to copyright including, without limitation, performance, broadcast, sound recording, and Sui Generis Database Rights, without regard to how the rights are labeled or categorized. For purposes of this Public License, the rights specified in Section 2(b)(1)-(2) are not Copyright and Similar Rights.
+
+   e. Effective Technological Measures means those measures that, in the absence of proper authority, may not be circumvented under laws fulfilling obligations under Article 11 of the WIPO Copyright Treaty adopted on December 20, 1996, and/or similar international agreements.
+
+   f. Exceptions and Limitations means fair use, fair dealing, and/or any other exception or limitation to Copyright and Similar Rights that applies to Your use of the Licensed Material.
+
+    g. License Elements means the license attributes listed in the name of a Creative Commons Public License. The License Elements of this Public License are Attribution, NonCommercial, and ShareAlike.
+
+    h. Licensed Material means the artistic or literary work, database, or other material to which the Licensor applied this Public License.
+
+    i. Licensed Rights means the rights granted to You subject to the terms and conditions of this Public License, which are limited to all Copyright and Similar Rights that apply to Your use of the Licensed Material and that the Licensor has authority to license.
+
+    j. Licensor means the individual(s) or entity(ies) granting rights under this Public License.
+
+    k. NonCommercial means not primarily intended for or directed towards commercial advantage or monetary compensation. For purposes of this Public License, the exchange of the Licensed Material for other material subject to Copyright and Similar Rights by digital file-sharing or similar means is NonCommercial provided there is no payment of monetary compensation in connection with the exchange.
+
+    l. Share means to provide material to the public by any means or process that requires permission under the Licensed Rights, such as reproduction, public display, public performance, distribution, dissemination, communication, or importation, and to make material available to the public including in ways that members of the public may access the material from a place and at a time individually chosen by them.
+
+    m. Sui Generis Database Rights means rights other than copyright resulting from Directive 96/9/EC of the European Parliament and of the Council of 11 March 1996 on the legal protection of databases, as amended and/or succeeded, as well as other essentially equivalent rights anywhere in the world.
+
+    n. You means the individual or entity exercising the Licensed Rights under this Public License. Your has a corresponding meaning.
+
+
+    Section 2 -- Scope.
+
+    a. License grant.
+
+    1. Subject to the terms and conditions of this Public License, the Licensor hereby grants You a worldwide, royalty-free, non-sublicensable, non-exclusive, irrevocable license to exercise the Licensed Rights in the Licensed Material to:
+
+    a. reproduce and Share the Licensed Material, in whole or in part, for NonCommercial purposes only; and
+
+    b. produce, reproduce, and Share Adapted Material for NonCommercial purposes only.
+
+    2. Exceptions and Limitations. For the avoidance of doubt, where Exceptions and Limitations apply to Your use, this Public License does not apply, and You do not need to comply with its terms and conditions.
+
+    3. Term. The term of this Public License is specified in Section  6(a).
+
+    4. Media and formats; technical modifications allowed. The Licensor authorizes You to exercise the Licensed Rights in all media and formats whether now known or hereafter created, and to make technical modifications necessary to do so. The Licensor waives and/or agrees not to assert any right orauthority to forbid You from making technical modifications necessary to exercise the Licensed Rights, including technical modifications necessary to circumvent Effective Technological Measures. For purposes of this Public License, simply making modifications authorized by this Section 2(a)(4) never produces Adapted Material.
+
+    5. Downstream recipients.
+
+    a. Offer from the Licensor -- Licensed Material. Every recipient of the Licensed Material automatically receives an offer from the Licensor to exercise the Licensed Rights under the terms and conditions of this Public License.
+
+    b. Additional offer from the Licensor -- Adapted Material. Every recipient of Adapted Material from You automatically receives an offer from the Licensor to exercise the Licensed Rights in the Adapted Material under the conditions of the Adapter's License You apply.
+
+   c. No downstream restrictions. You may not offer or impose any additional or different terms or conditions on, or apply any Effective Technological Measures to, the Licensed Material if doing so restricts exercise of the Licensed Rights by any recipient of the Licensed Material.
+
+   6. No endorsement. Nothing in this Public License constitutes or may be construed as permission to assert or imply that You are, or that Your use of the Licensed Material is, connected with, or sponsored, endorsed, or granted official status by, the Licensor or others designated to receive attribution as provided in Section 3(a)(1)(A)(i).
+
+   b. Other rights.
+
+   1. Moral rights, such as the right of integrity, are not licensed under this Public License, nor are publicity, privacy, and/or other similar personality rights; however, to the extent possible, the Licensor waives and/or agrees not to assert any such rights held by the Licensor to the limited extent necessary to allow You to exercise the Licensed Rights, but not otherwise.
+
+   2. Patent and trademark rights are not licensed under this Public License.
+
+   3. To the extent possible, the Licensor waives any right to collect royalties from You for the exercise of the Licensed Rights, whether directly or through a collecting society under any voluntary or waivable statutory or compulsory licensing scheme. In all other cases the Licensor expressly reserves any right to collect such royalties, including when the Licensed Material is used other than for NonCommercial purposes.
+
+
+   Section 3 -- License Conditions.
+
+   Your exercise of the Licensed Rights is expressly made subject to the following conditions.
+
+   a. Attribution.
+
+   1. If You Share the Licensed Material (including in modified form), You must: a. retain the following if it is supplied by the Licensor with the Licensed Material:
+ i. identification of the creator(s) of the Licensed Material and any others designated to receive attribution, in any reasonable manner requested by the Licensor (including by pseudonym if designated); ii. a copyright notice; iii. a notice that refers to this Public License; iv. a notice that refers to the disclaimer of warranties; v. a URI or hyperlink to the Licensed Material to the extent reasonably practicable;
+
+    b. indicate if You modified the Licensed Material and retain an indication of any previous modifications; and
+
+   c. indicate the Licensed Material is licensed under this Public License, and include the text of, or the URI or hyperlink to, this Public License.
+
+      2. You may satisfy the conditions in Section 3(a)(1) in any reasonable manner based on the medium, means, and context in which You Share the Licensed Material. For example, it may be reasonable to satisfy the conditions by providing a URI or hyperlink to a resource that includes the required information.
+           
+3. If requested by the Licensor, You must remove any of the information required by Section 3(a)(1)(A) to the extent reasonably practicable.
+
+      b. ShareAlike. In addition to the conditions in Section 3(a), if You Share Adapted Material You produce, the following conditions also apply.
+
+ 1. The Adapter's License You apply must be a Creative Commons license with the same License Elements, this version or later, or a BY-NC-SA Compatible License.
+
+     2. You must include the text of, or the URI or hyperlink to, the Adapter's License You apply. You may satisfy this condition in any reasonable manner based on the medium, means, and context in which You Share Adapted Material.
+
+     3. You may not offer or impose any additional or different terms or conditions on, or apply any Effective Technological Measures to, Adapted Material that restrict exercise of the rights granted under the Adapter's License You apply.
+
+
+    Section 4 -- Sui Generis Database Rights.
+
+    Where the Licensed Rights include Sui Generis Database Rights that apply to Your use of the Licensed Material:
+
+     a. for the avoidance of doubt, Section 2(a)(1) grants You the right to extract, reuse, reproduce, and Share all or a substantial portion of the contents of the database for NonCommercial purposes only;
+
+      b. if You include all or a substantial portion of the database contents in a database in which You have Sui Generis Database Rights, then the database in which You have Sui Generis Database Rights (but not its individual contents) is Adapted Material, including for purposes of Section 3(b); and
+
+     c. You must comply with the conditions in Section 3(a) if You Share all or a substantial portion of the contents of the database.
+
+    For the avoidance of doubt, this Section 4 supplements and does not replace Your obligations under this Public License where the Licensed Rights include other Copyright and Similar Rights.
+    Section 5 -- Disclaimer of Warranties and Limitation of Liability.
+
+      a. UNLESS OTHERWISE SEPARATELY UNDERTAKEN BY THE LICENSOR, TO THE EXTENT POSSIBLE, THE LICENSOR OFFERS THE LICENSED MATERIAL AS-IS AND AS-AVAILABLE, AND MAKES NO REPRESENTATIONS OR WARRANTIES OF  ANY KIND CONCERNING THE LICENSED MATERIAL, WHETHER EXPRESS, IMPLIED, STATUTORY, OR OTHER. THIS INCLUDES, WITHOUT LIMITATION, WARRANTIES OF TITLE, MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, NON-INFRINGEMENT, ABSENCE OF LATENT OR OTHER DEFECTS, ACCURACY, OR THE PRESENCE OR ABSENCE OF ERRORS, WHETHER OR NOT KNOWN OR DISCOVERABLE. WHERE DISCLAIMERS OF WARRANTIES ARE NOT  ALLOWED IN FULL OR IN PART, THIS DISCLAIMER MAY NOT APPLY TO YOU.
+
+      b. TO THE EXTENT POSSIBLE, IN NO EVENT WILL THE LICENSOR BE LIABLE TO YOU ON ANY LEGAL THEORY (INCLUDING, WITHOUT LIMITATION, NEGLIGENCE) OR OTHERWISE FOR ANY DIRECT, SPECIAL, INDIRECT, INCIDENTAL, CONSEQUENTIAL, PUNITIVE, EXEMPLARY, OR OTHER LOSSES, COSTS, EXPENSES, OR DAMAGES ARISING OUT OF THIS PUBLIC LICENSE OR USE OF THE LICENSED MATERIAL, EVEN IF THE LICENSOR HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH LOSSES, COSTS, EXPENSES, OR  DAMAGES. WHERE A LIMITATION OF LIABILITY IS NOT ALLOWED IN FULL OR IN PART, THIS LIMITATION MAY NOT APPLY TO YOU.
+
+      c. The disclaimer of warranties and limitation of liability provided above shall be interpreted in a manner that, to the extent possible, most closely approximates an absolute disclaimer and waiver of all liability.
+
+    Section 6 -- Term and Termination.
+
+      a. This Public License applies for the term of the Copyright and  Similar Rights licensed here. However, if You fail to comply with this Public License, then Your rights under this Public License  terminate automatically.
+
+      b. Where Your right to use the Licensed Material has terminated under Section 6(a), it reinstates:
+
+     1. automatically as of the date the violation is cured, provided it is cured within 30 days of Your discovery of the violation; or
+
+     2. upon express reinstatement by the Licensor.
+
+     For the avoidance of doubt, this Section 6(b) does not affect anyright the Licensor may have to seek remedies for Your violations of this Public License.
+
+     c. For the avoidance of doubt, the Licensor may also offer the  Licensed Material under separate terms or conditions or stop distributing the Licensed Material at any time; however, doing so will not terminate this Public License.
+
+    d. Sections 1, 5, 6, 7, and 8 survive termination of this Public License.
+
+
+    Section 7 -- Other Terms and Conditions.
+
+    a. The Licensor shall not be bound by any additional or different terms or conditions communicated by You unless expressly agreed.
+
+    b. Any arrangements, understandings, or agreements regarding the Licensed Material not stated herein are separate from and independent of the terms and conditions of this Public License.
+
+
+    Section 8 -- Interpretation.
+
+    a. For the avoidance of doubt, this Public License does not, and shall not be interpreted to, reduce, limit, restrict, or impose conditions on any use of the Licensed Material that could lawfully be made without permission under this Public License.
+
+    b. To the extent possible, if any provision of this Public License is deemed unenforceable, it shall be automatically reformed to the minimum extent necessary to make it enforceable. If the provision cannot be reformed, it shall be severed from this Public License without affecting the enforceability of the remaining terms and conditions.
+
+    c. No term or condition of this Public License will be waived and no failure to comply consented to unless expressly agreed to by the Licensor.
+
+    d. Nothing in this Public License constitutes or may be interpreted as a limitation upon, or waiver of, any privileges and immunities that apply to the Licensor or You, including from the legal processes of any jurisdiction or authority.
+
+    
+    Creative Commons is not a party to its public licenses. Notwithstanding, Creative Commons may elect to apply one of its public licenses to material it publishes and in those instances will be considered the “Licensor.” The text of the Creative Commons public licenses is dedicated to the public domain under the CC0 Public Domain Dedication. Except for the limited purpose of indicating that material is shared under a Creative Commons public license or as otherwise permitted by the Creative Commons policies published at creativecommons.org/policies, Creative Commons does not authorize the use of the trademark "Creative Commons" or any other trademark or logo of Creative Commons without its prior written consent including, without limitation, in connection with any unauthorized modifications to any of its public licenses or any other arrangements, understandings, or agreements concerning use of licensed material. For the avoidance of doubt, this paragraph does not form part of the public licenses.
+
+    Creative Commons may be contacted at creativecommons.org.
+
+
+
+------------- LICENSE FOR Hugging Face CODE --------------
+
+Copyright notice：Copyright 2019 Ross Wightman
+
+License:apache2.0
+
+Please see above.
+
+
+
+------------- LICENSE FOR vLLM CODE --------------
+
+Copyright notice:No copyright info provided
+
+License:apache2.0
+
+Please see above.
+
+
+
+------------- LICENSE FOR Doclaynet --------------
+
+Copyright notice:No copyright info provided
+
+License:Community Data License Agreement
+
+Community Data License Agreement – Permissive – Version 1.0
+
+This is the Community Data License Agreement – Permissive, Version 1.0 (“Agreement”). Data is provided to You under this Agreement by each of the Data Providers. Your exercise of any of the rights and permissions granted below constitutes your acceptance and agreement to be bound by the terms and conditions of this Agreement.
+
+The benefits that each Data Provider receives from making Data available and that You receive from Data or otherwise under these terms and conditions shall be deemed sufficient consideration for the formation of this Agreement. Accordingly, Data Provider(s) and You (the "Parties") agree as follows:
+
+Section 1.  Definitions
+
+1.1 "Add" means to supplement Data with Your own or someone else's Data, resulting in Your “Additions.” Additions do not include Results.
+
+1.2 "Computational Use" means Your analysis (through the use of computational devices or otherwise) or other interpretation of Data. By way of example and not limitation, "Computational Use" includes the application of any computational analytical technique, the purpose of which is the analysis of any Data in digital form to generate information about Data such as patterns, trends, correlations, inferences, insights and attributes.
+
+1.3 "Data" means the information (including copyrightable information, such as images or text), collectively or individually, whether created or gathered by a Data Provider or an Entity acting on its behalf, to which rights are granted under this Agreement.
+
+1.4 "Data Provider" means any Entity (including any employee or contractor of such Entity authorized to Publish Data on behalf of such Entity) that Publishes Data under this Agreement prior to Your Receiving it.
+
+1.5 "Enhanced Data" means the subset of Data that You Publish and that is composed of (a) Your Additions and/or (b) Modifications to Data You have received under this Agreement.
+
+1.6 "Entity" means any natural person or organization that exists under the laws of the jurisdiction in which it is organized, together with all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (a) the power, directly or indirectly, to cause the direction or management of such entity, whether by contract or otherwise, (b) the ownership of more than fifty percent (50%) of the outstanding shares or securities, (c) the beneficial ownership of such entity or, (d) the ability to appoint, whether by agreement or right, the majority of directors of an Entity.
+
+1.7 "Modify" means to delete, erase, correct or re-arrange Data, resulting in “Modifications.” Modifications do not include Results.
+
+1.8 "Publish" means to make all or a subset of Data (including Your Enhanced Data) available in any manner which enables its use, including by providing a copy on physical media or remote access. For any form of Entity, that is to make the Data available to any individual who is not employed by that Entity or engaged as a contractor or agent to perform work on that Entity's behalf. A "Publication" occurs each time you Publish Data.
+
+1.9 "Receive" or "Receives" means to have been given access to Data, locally or remotely.
+
+1.10 "Results" means the outcomes or outputs that You obtain from Your Computational Use of Data. Results shall not include more than a de minimis portion of the Data on which the Computational Use is based.
+
+1.11 "Sui Generis Database Rights" means rights, other than copyright, resulting from Directive 96/9/EC of the European Parliament and of the Council of 11 March 1996 on the legal protection of databases, as amended and/or succeeded, as well as other equivalent rights anywhere in the world.
+
+1.12 "Use" means using Data (including accessing, copying, studying, reviewing, adapting, analyzing, evaluating, or making Computational Use of it), either by machines or humans, or a combination of both.
+
+1.13 "You" or "Your" means any Entity that Receives Data under this Agreement.
+
+Section 2. Right and License to Use and to Publish
+
+2.1 Subject to the conditions set forth in Section 3 of this Agreement, Data Provider(s) hereby grant(s) to You a worldwide, non-exclusive, irrevocable (except as provided in Section 5) right to: (a) Use Data; and (b) Publish Data.
+
+2.2 To the extent that the Data or the coordination, selection or arrangement of Data is protected or protectable under copyright, Sui Generis Database Rights, or other law, Data Provider(s) further agree(s) that such Data or coordination, selection or arrangement is hereby licensed to You and to anyone else who Receives Data under this Agreement for Use and Publication, subject to the conditions set forth in Section 3 of this Agreement.
+
+2.3 Except for these rights and licenses expressly granted, no other intellectual property rights are granted or should be implied.
+
+Section 3. Conditions on Rights Granted
+
+3.1 If You Publish Data You Receive or Enhanced Data:
+
+(a) You may do so under a license of your choice provided that you give anyone who receives the data from you the text of this Agreement, the name of this Agreement and/or a hyperlink or other method reasonably likely to provide a copy of the text of this Agreement; and
+
+(b) You must cause any Data files containing Enhanced Data to carry prominent notices that you have changed those files; and
+
+(c) If You Publish Data You Receive, You must preserve all credit or attribution to the Data Provider(s). Such retained credit or attribution includes any of the following to the extent they exist in the Data as You have Received it: legal notices or metadata; identification of the Data Provider(s); or hyperlinks to Data to the extent it is practical to do so.
+
+3.2 You may provide additional or different license terms and conditions for use, reproduction, or distribution of that Enhanced Data, or for any combination of Data and Enhanced Data as a whole, provided that Your Use and Publication of that combined Data otherwise complies with the conditions stated in this License.
+
+3.3 You and each Data Provider agree that Enhanced Data shall not be considered a work of joint authorship by virtue of its relationship to Data licensed under this Agreement and shall not require either any obligation of accounting to or the consent of any Data Provider.
+
+3.4 This Agreement imposes no obligations or restrictions on Your Use or Publication of Results.
+
+Section 4. Data Provider(s)' Representations
+
+4.1 Each Data Provider represents that the Data Provider has exercised reasonable care, to assure that: (a) the Data it Publishes was created or generated by it or was obtained from others with the right to Publish the Data under this Agreement; and (b) Publication of such Data does not violate any privacy or confidentiality obligation undertaken by the Data Provider.
+
+Section 5.  Termination
+
+5.1 All of Your rights under this Agreement will terminate, and Your right to Receive, Use or Publish the Data will be revoked or modified if You materially fail to comply with the terms and conditions of this Agreement and You do not cure such failure in a reasonable period of time after becoming aware of such noncompliance. If your rights under this Agreement terminate, you agree to cease Receipt, Use and Publication of Data. However, your obligations and any rights and permissions granted by you under this Agreement relating to Data that you published prior to such termination will continue and survive.
+
+5.2 If you institute litigation against a Data Provider or anyone else who Receives the Data (including a cross-claim in a lawsuit) based on the Data, other than a claim asserting breach of this Agreement, then any rights previously granted to You to Receive, Use and Publish Data under this Agreement will terminate as of the date such litigation is filed.
+
+Section 6. Disclaimer of Warranties and Limitation of Liability
+
+6.1 EXCEPT AS EXPRESSLY SET FORTH IN THIS AGREEMENT, THE DATA (INCLUDING ENHANCED DATA) IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, EITHER EXPRESS OR IMPLIED INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OR CONDITIONS OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.
+
+6.2 NEITHER YOU NOR ANY DATA PROVIDERS SHALL HAVE ANY LIABILITY FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING WITHOUT LIMITATION LOST PROFITS), HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OR DISTRIBUTION OF THE DATA OR THE EXERCISE OF ANY RIGHTS GRANTED HEREUNDER, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
+
+Section 7.  Miscellaneous
+
+7.1 You agree that it is solely your responsibility to comply with all applicable laws with regard to Your Use or Publication of Data, including any applicable privacy, data protection, security and export laws. You agree to take reasonable steps to assist a Data Provider fulfilling responsibilities to comply with applicable laws with regard to Use or Publication of Data Received hereunder.
+
+7.2 You and Data Provider(s), collectively and individually, waive and/or agree not to assert, to the extent permitted by law, any moral rights you or they hold in Data.
+
+7.3 This Agreement confers no rights or remedies upon any person or entity other than the Parties and their respective heirs, executors, successors and assigns.
+
+7.4 The Data Provider(s) reserve no right or expectation of privacy, data protection or confidentiality in any Data that they Publish under this Agreement. If you choose to Publish Data under this Agreement, you similarly do so with no reservation or expectation of any rights of privacy or confidentiality in that Data.
+
+7.5 The Community Data License Agreement workgroup under The Linux Foundation is the steward of this Agreement (“Steward”). No one other than the Steward has the right to modify or publish new versions of this Agreement. Each version will be given a distinguishing version number. You may Use and Publish Data Received hereunder under the terms of the version of the Agreement under which You originally Received the Data, or under the terms of any subsequent version published by the Steward.
+
+
+
+------------- LICENSE FOR M6Doc --------------
+
+Copyright notice:No copyright info provided
+
+License:Attribution-NonCommercial-NoDerivatives 4.0
+
+=======Attribution-NonCommercial-NoDerivatives 4.0 International==========
+
+Creative Commons Corporation ("Creative Commons") is not a law firm and does not provide legal services or legal advice. Distribution of Creative Commons public licenses does not create a lawyer-client or other relationship. Creative Commons makes its licenses and related information available on an "as-is" basis. Creative Commons gives no warranties regarding its licenses, any material licensed under their terms and conditions, or any related information. Creative Commons disclaims all liability for damages resulting from their use to the fullest extent possible.
+
+Using Creative Commons Public Licenses
+
+Creative Commons public licenses provide a standard set of terms and conditions that creators and other rights holders may use to share original works of authorship and other material subject to copyright and certain other rights specified in the public license below. The following considerations are for informational purposes only, are not exhaustive, and do not form part of our licenses.
+
+Considerations for licensors: Our public licenses are intended for use by those authorized to give the public permission to use material in ways otherwise restricted by copyright and certain other rights. Our licenses are irrevocable. Licensors should read and understand the terms and conditions of the license they choose before applying it. Licensors should also secure all rights necessary before applying our licenses so that the public can reuse the material as expected. Licensors should clearly mark any material not subject to the license. This includes other CC- licensed material, or material used under an exception or limitation to copyright. More considerations for licensors: wiki.creativecommons.org/Considerations_for_licensors
+
+Considerations for the public: By using one of our public licenses, a licensor grants the public permission to use the licensed material under specified terms and conditions. If the licensor's permission is not necessary for any reason--for example, because of any applicable exception or limitation to copyright--then that use is not regulated by the license. Our licenses grant only permissions under copyright and certain other rights that a licensor has authority to grant. Use of the licensed material may still be restricted for other reasons, including because others have copyright or other rights in the material. A licensor may make special requests, such as asking that all changes be marked or described. Although not required by our licenses, you are encouraged to respect those requests where reasonable. More considerations for the public: wiki.creativecommons.org/Considerations_for_licensees
+
+Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License
+
+By exercising the Licensed Rights (defined below), You accept and agree to be bound by the terms and conditions of this Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License ("Public License"). To the extent this Public License may be interpreted as a contract, You are granted the Licensed Rights in consideration of Your acceptance of these terms and conditions, and the Licensor grants You such rights in consideration of benefits the Licensor receives from making the Licensed Material available under these terms and conditions.
+
+
+Section 1 -- Definitions.
+
+  a. Adapted Material means material subject to Copyright and Similar Rights that is derived from or based upon the Licensed Material and in which the Licensed Material is translated, altered, arranged, transformed, or otherwise modified in a manner requiring permission under the Copyright and Similar Rights held by the Licensor. For purposes of this Public License, where the Licensed Material is a musical work, performance, or sound recording, Adapted Material is always produced where the Licensed Material is synched in timed relation with a moving image.
+
+  b. Copyright and Similar Rights means copyright and/or similar rights closely related to copyright including, without limitation, performance, broadcast, sound recording, and Sui Generis Database Rights, without regard to how the rights are labeled or categorized. For purposes of this Public License, the rights specified in Section 2(b)(1)-(2) are not Copyright and Similar Rights.
+
+  c. Effective Technological Measures means those measures that, in the absence of proper authority, may not be circumvented under laws fulfilling obligations under Article 11 of the WIPO Copyright Treaty adopted on December 20, 1996, and/or similar international agreements.
+
+  d. Exceptions and Limitations means fair use, fair dealing, and/or any other exception or limitation to Copyright and Similar Rights that applies to Your use of the Licensed Material.
+
+  e. Licensed Material means the artistic or literary work, database, or other material to which the Licensor applied this Public License.
+
+  f. Licensed Rights means the rights granted to You subject to the terms and conditions of this Public License, which are limited to all Copyright and Similar Rights that apply to Your use of the Licensed Material and that the Licensor has authority to license.
+
+  g. Licensor means the individual(s) or entity(ies) granting rights under this Public License.
+
+  h. NonCommercial means not primarily intended for or directed towards commercial advantage or monetary compensation. For purposes of this Public License, the exchange of the Licensed Material for other material subject to Copyright and Similar Rights by digital file-sharing or similar means is NonCommercial provided there is no payment of monetary compensation in connection with the exchange.
+
+  i. Share means to provide material to the public by any means or process that requires permission under the Licensed Rights, such as reproduction, public display, public performance, distribution, dissemination, communication, or importation, and to make material available to the public including in ways that members of the public may access the material from a place and at a time individually chosen by them.
+
+  j. Sui Generis Database Rights means rights other than copyright resulting from Directive 96/9/EC of the European Parliament and of the Council of 11 March 1996 on the legal protection of databases, as amended and/or succeeded, as well as other essentially equivalent rights anywhere in the world.
+
+  k. You means the individual or entity exercising the Licensed Rights under this Public License. Your has a corresponding meaning.
+
+
+Section 2 -- Scope.
+
+  a. License granted.
+
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+------------- LICENSE FOR CDLA --------------
+
+Copyright notice:No copyright info provided
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+License:No License info provided
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+------------- LICENSE FOR D4LA --------------
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+Copyright notice:No copyright info provided
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+License:No License info provided

README.md

@@ -1131,6 +1131,10 @@ print(output_text)
 
 </details>
 
+### Hugginface inference with CPU
+Please refer to [CPU inference](https://github.com/rednote-hilab/dots.ocr/issues/1#issuecomment-3148962536)
+
+
 ## 3. Document Parse
 **Based on vLLM server**, you can parse an image or a pdf file using the following commands:
 ```bash
@@ -1151,6 +1155,9 @@ python3 dots_ocr/parser.py demo/demo_image1.jpg --prompt prompt_ocr
 python3 dots_ocr/parser.py demo/demo_image1.jpg --prompt prompt_grounding_ocr --bbox 163 241 1536 705
 
 ```
+**Based on Transformers**, you can parse an image or a pdf file using the same commands above, just add `--use_hf true`. 
+
+> Notice: transformers is slower than vllm, if you want to use demo/* with transformers，just add `use_hf=True` in `DotsOCRParser(..,use_hf=True)`
 
 <details>
 <summary><b>Output Results</b></summary>

demo/demo_colab_remote_server.ipynb

@@ -0,0 +1,1166 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "machine_shape": "hm",
+      "gpuType": "L4",
+      "authorship_tag": "ABX9TyOkGQh7maXiQhQ6pYoY2NaU",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "accelerator": "GPU"
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/louisoutin/dots.ocr/blob/master/dots_ocr.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# DotsOCR vLLM Openai API Compatible server"
+      ],
+      "metadata": {
+        "id": "PshK9ZarVTfM"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install pyngrok\n",
+        "!ngrok authtoken  # Get this from https://dashboard.ngrok.com/"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "oyY3E3mlOXNX",
+        "outputId": "8d7ba92f-7170-4b2e-e8a0-c7f94096f7e0"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Requirement already satisfied: pyngrok in /usr/local/lib/python3.11/dist-packages (7.3.0)\n",
+            "Requirement already satisfied: PyYAML>=5.1 in /usr/local/lib/python3.11/dist-packages (from pyngrok) (6.0.2)\n",
+            "Authtoken saved to configuration file: /root/.config/ngrok/ngrok.yml\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!conda create -n dots_ocr python=3.12\n",
+        "!conda activate dots_ocr\n",
+        "\n",
+        "!git clone https://github.com/rednote-hilab/dots.ocr.git"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "BcV7hkvuRnwS",
+        "outputId": "7cb9c743-6f41-4c90-a05b-90bce2c29ced"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "/bin/bash: line 1: conda: command not found\n",
+            "/bin/bash: line 1: conda: command not found\n",
+            "Cloning into 'dots.ocr'...\n",
+            "remote: Enumerating objects: 163, done.\u001b[K\n",
+            "remote: Counting objects: 100% (51/51), done.\u001b[K\n",
+            "remote: Compressing objects: 100% (31/31), done.\u001b[K\n",
+            "remote: Total 163 (delta 30), reused 30 (delta 20), pack-reused 112 (from 1)\u001b[K\n",
+            "Receiving objects: 100% (163/163), 35.82 MiB | 13.64 MiB/s, done.\n",
+            "Resolving deltas: 100% (56/56), done.\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cd /content/dots.ocr"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Rsc_MkGfRpit",
+        "outputId": "5265315f-c27c-4346-cda7-aba7d4c226d6"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "/content/dots.ocr\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Install pytorch, see https://pytorch.org/get-started/previous-versions/ for your cuda version\n",
+        "!pip install torch==2.7.0 torchvision==0.22.0 torchaudio==2.7.0 --index-url https://download.pytorch.org/whl/cu128\n",
+        "!pip install -e ."
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "OxLaSyTJPFwk",
+        "outputId": "a073dcdd-5e5d-4f62-d3b9-be9e9cf98d2f"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Looking in indexes: https://download.pytorch.org/whl/cu128\n",
+            "Requirement already satisfied: torch==2.7.0 in /usr/local/lib/python3.11/dist-packages (2.7.0+cu128)\n",
+            "Requirement already satisfied: torchvision==0.22.0 in /usr/local/lib/python3.11/dist-packages (0.22.0+cu128)\n",
+            "Requirement already satisfied: torchaudio==2.7.0 in /usr/local/lib/python3.11/dist-packages (2.7.0+cu128)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (3.18.0)\n",
+            "Requirement already satisfied: typing-extensions>=4.10.0 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (4.14.1)\n",
+            "Requirement already satisfied: sympy>=1.13.3 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (1.13.3)\n",
+            "Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (3.5)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (3.1.6)\n",
+            "Requirement already satisfied: fsspec in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (2025.3.0)\n",
+            "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.8.61 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (12.8.61)\n",
+            "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.8.57 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (12.8.57)\n",
+            "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.8.57 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (12.8.57)\n",
+            "Requirement already satisfied: nvidia-cudnn-cu12==9.7.1.26 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (9.7.1.26)\n",
+            "Requirement already satisfied: nvidia-cublas-cu12==12.8.3.14 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (12.8.3.14)\n",
+            "Requirement already satisfied: nvidia-cufft-cu12==11.3.3.41 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (11.3.3.41)\n",
+            "Requirement already satisfied: nvidia-curand-cu12==10.3.9.55 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (10.3.9.55)\n",
+            "Requirement already satisfied: nvidia-cusolver-cu12==11.7.2.55 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (11.7.2.55)\n",
+            "Requirement already satisfied: nvidia-cusparse-cu12==12.5.7.53 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (12.5.7.53)\n",
+            "Requirement already satisfied: nvidia-cusparselt-cu12==0.6.3 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (0.6.3)\n",
+            "Requirement already satisfied: nvidia-nccl-cu12==2.26.2 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (2.26.2)\n",
+            "Requirement already satisfied: nvidia-nvtx-cu12==12.8.55 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (12.8.55)\n",
+            "Requirement already satisfied: nvidia-nvjitlink-cu12==12.8.61 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (12.8.61)\n",
+            "Requirement already satisfied: nvidia-cufile-cu12==1.13.0.11 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (1.13.0.11)\n",
+            "Requirement already satisfied: triton==3.3.0 in /usr/local/lib/python3.11/dist-packages (from torch==2.7.0) (3.3.0)\n",
+            "Requirement already satisfied: numpy in /usr/local/lib/python3.11/dist-packages (from torchvision==0.22.0) (2.0.2)\n",
+            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.11/dist-packages (from torchvision==0.22.0) (11.3.0)\n",
+            "Requirement already satisfied: setuptools>=40.8.0 in /usr/local/lib/python3.11/dist-packages (from triton==3.3.0->torch==2.7.0) (75.2.0)\n",
+            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy>=1.13.3->torch==2.7.0) (1.3.0)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch==2.7.0) (3.0.2)\n",
+            "Obtaining file:///content/dots.ocr\n",
+            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "Requirement already satisfied: gradio in /usr/local/lib/python3.11/dist-packages (from dots_ocr==1.0) (5.39.0)\n",
+            "Collecting gradio_image_annotation (from dots_ocr==1.0)\n",
+            "  Downloading gradio_image_annotation-0.4.0-py3-none-any.whl.metadata (17 kB)\n",
+            "Collecting PyMuPDF (from dots_ocr==1.0)\n",
+            "  Downloading pymupdf-1.26.3-cp39-abi3-manylinux_2_28_x86_64.whl.metadata (3.4 kB)\n",
+            "Requirement already satisfied: openai in /usr/local/lib/python3.11/dist-packages (from dots_ocr==1.0) (1.98.0)\n",
+            "Collecting qwen_vl_utils (from dots_ocr==1.0)\n",
+            "  Downloading qwen_vl_utils-0.0.11-py3-none-any.whl.metadata (6.3 kB)\n",
+            "Collecting transformers==4.51.3 (from dots_ocr==1.0)\n",
+            "  Downloading transformers-4.51.3-py3-none-any.whl.metadata (38 kB)\n",
+            "Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.11/dist-packages (from dots_ocr==1.0) (0.34.3)\n",
+            "Collecting modelscope (from dots_ocr==1.0)\n",
+            "  Downloading modelscope-1.28.2-py3-none-any.whl.metadata (39 kB)\n",
+            "Collecting flash-attn==2.8.0.post2 (from dots_ocr==1.0)\n",
+            "  Downloading flash_attn-2.8.0.post2.tar.gz (7.9 MB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.9/7.9 MB\u001b[0m \u001b[31m124.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "Requirement already satisfied: accelerate in /usr/local/lib/python3.11/dist-packages (from dots_ocr==1.0) (1.9.0)\n",
+            "Requirement already satisfied: torch in /usr/local/lib/python3.11/dist-packages (from flash-attn==2.8.0.post2->dots_ocr==1.0) (2.7.0+cu128)\n",
+            "Requirement already satisfied: einops in /usr/local/lib/python3.11/dist-packages (from flash-attn==2.8.0.post2->dots_ocr==1.0) (0.8.1)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from transformers==4.51.3->dots_ocr==1.0) (3.18.0)\n",
+            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.11/dist-packages (from transformers==4.51.3->dots_ocr==1.0) (2.0.2)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.11/dist-packages (from transformers==4.51.3->dots_ocr==1.0) (25.0)\n",
+            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from transformers==4.51.3->dots_ocr==1.0) (6.0.2)\n",
+            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.11/dist-packages (from transformers==4.51.3->dots_ocr==1.0) (2024.11.6)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from transformers==4.51.3->dots_ocr==1.0) (2.32.3)\n",
+            "Requirement already satisfied: tokenizers<0.22,>=0.21 in /usr/local/lib/python3.11/dist-packages (from transformers==4.51.3->dots_ocr==1.0) (0.21.4)\n",
+            "Requirement already satisfied: safetensors>=0.4.3 in /usr/local/lib/python3.11/dist-packages (from transformers==4.51.3->dots_ocr==1.0) (0.5.3)\n",
+            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.11/dist-packages (from transformers==4.51.3->dots_ocr==1.0) (4.67.1)\n",
+            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub->dots_ocr==1.0) (2025.3.0)\n",
+            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub->dots_ocr==1.0) (4.14.1)\n",
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+            "Requirement already satisfied: uvicorn>=0.14.0 in /usr/local/lib/python3.11/dist-packages (from gradio->dots_ocr==1.0) (0.35.0)\n",
+            "Requirement already satisfied: websockets<16.0,>=10.0 in /usr/local/lib/python3.11/dist-packages (from gradio-client==1.11.0->gradio->dots_ocr==1.0) (15.0.1)\n",
+            "Requirement already satisfied: setuptools in /usr/local/lib/python3.11/dist-packages (from modelscope->dots_ocr==1.0) (75.2.0)\n",
+            "Requirement already satisfied: urllib3>=1.26 in /usr/local/lib/python3.11/dist-packages (from modelscope->dots_ocr==1.0) (2.5.0)\n",
+            "Requirement already satisfied: distro<2,>=1.7.0 in /usr/local/lib/python3.11/dist-packages (from openai->dots_ocr==1.0) (1.9.0)\n",
+            "Requirement already satisfied: jiter<1,>=0.4.0 in /usr/local/lib/python3.11/dist-packages (from openai->dots_ocr==1.0) (0.10.0)\n",
+            "Requirement already satisfied: sniffio in /usr/local/lib/python3.11/dist-packages (from openai->dots_ocr==1.0) (1.3.1)\n",
+            "Collecting av (from qwen_vl_utils->dots_ocr==1.0)\n",
+            "  Downloading av-15.0.0-cp311-cp311-manylinux_2_28_x86_64.whl.metadata (4.6 kB)\n",
+            "Requirement already satisfied: idna>=2.8 in /usr/local/lib/python3.11/dist-packages (from anyio<5.0,>=3.0->gradio->dots_ocr==1.0) (3.10)\n",
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+            "Requirement already satisfied: httpcore==1.* in /usr/local/lib/python3.11/dist-packages (from httpx<1.0,>=0.24.1->gradio->dots_ocr==1.0) (1.0.9)\n",
+            "Requirement already satisfied: h11>=0.16 in /usr/local/lib/python3.11/dist-packages (from httpcore==1.*->httpx<1.0,>=0.24.1->gradio->dots_ocr==1.0) (0.16.0)\n",
+            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.11/dist-packages (from pandas<3.0,>=1.0->gradio->dots_ocr==1.0) (2.9.0.post0)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas<3.0,>=1.0->gradio->dots_ocr==1.0) (2025.2)\n",
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+            "Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.11/dist-packages (from pydantic<2.12,>=2.0->gradio->dots_ocr==1.0) (0.7.0)\n",
+            "Requirement already satisfied: pydantic-core==2.33.2 in /usr/local/lib/python3.11/dist-packages (from pydantic<2.12,>=2.0->gradio->dots_ocr==1.0) (2.33.2)\n",
+            "Requirement already satisfied: typing-inspection>=0.4.0 in /usr/local/lib/python3.11/dist-packages (from pydantic<2.12,>=2.0->gradio->dots_ocr==1.0) (0.4.1)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests->transformers==4.51.3->dots_ocr==1.0) (3.4.2)\n",
+            "Requirement already satisfied: sympy>=1.13.3 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (1.13.3)\n",
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+            "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.8.61 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (12.8.61)\n",
+            "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.8.57 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (12.8.57)\n",
+            "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.8.57 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (12.8.57)\n",
+            "Requirement already satisfied: nvidia-cudnn-cu12==9.7.1.26 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (9.7.1.26)\n",
+            "Requirement already satisfied: nvidia-cublas-cu12==12.8.3.14 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (12.8.3.14)\n",
+            "Requirement already satisfied: nvidia-cufft-cu12==11.3.3.41 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (11.3.3.41)\n",
+            "Requirement already satisfied: nvidia-curand-cu12==10.3.9.55 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (10.3.9.55)\n",
+            "Requirement already satisfied: nvidia-cusolver-cu12==11.7.2.55 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (11.7.2.55)\n",
+            "Requirement already satisfied: nvidia-cusparse-cu12==12.5.7.53 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (12.5.7.53)\n",
+            "Requirement already satisfied: nvidia-cusparselt-cu12==0.6.3 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (0.6.3)\n",
+            "Requirement already satisfied: nvidia-nccl-cu12==2.26.2 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (2.26.2)\n",
+            "Requirement already satisfied: nvidia-nvtx-cu12==12.8.55 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (12.8.55)\n",
+            "Requirement already satisfied: nvidia-nvjitlink-cu12==12.8.61 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (12.8.61)\n",
+            "Requirement already satisfied: nvidia-cufile-cu12==1.13.0.11 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (1.13.0.11)\n",
+            "Requirement already satisfied: triton==3.3.0 in /usr/local/lib/python3.11/dist-packages (from torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (3.3.0)\n",
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+            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.11/dist-packages (from rich>=10.11.0->typer<1.0,>=0.12->gradio->dots_ocr==1.0) (3.0.0)\n",
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+            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy>=1.13.3->torch->flash-attn==2.8.0.post2->dots_ocr==1.0) (1.3.0)\n",
+            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.11/dist-packages (from markdown-it-py>=2.2.0->rich>=10.11.0->typer<1.0,>=0.12->gradio->dots_ocr==1.0) (0.1.2)\n",
+            "Downloading transformers-4.51.3-py3-none-any.whl (10.4 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.4/10.4 MB\u001b[0m \u001b[31m132.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading gradio_image_annotation-0.4.0-py3-none-any.whl (91 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m91.5/91.5 kB\u001b[0m \u001b[31m9.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading modelscope-1.28.2-py3-none-any.whl (5.9 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.9/5.9 MB\u001b[0m \u001b[31m129.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading pymupdf-1.26.3-cp39-abi3-manylinux_2_28_x86_64.whl (24.1 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m24.1/24.1 MB\u001b[0m \u001b[31m101.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading qwen_vl_utils-0.0.11-py3-none-any.whl (7.6 kB)\n",
+            "Downloading av-15.0.0-cp311-cp311-manylinux_2_28_x86_64.whl (39.7 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m39.7/39.7 MB\u001b[0m \u001b[31m61.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hBuilding wheels for collected packages: flash-attn\n",
+            "  Building wheel for flash-attn (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for flash-attn: filename=flash_attn-2.8.0.post2-cp311-cp311-linux_x86_64.whl size=255941661 sha256=8ed71ac092f80b079d2e6043b769135904d6e834916cb6da7d372b394581447b\n",
+            "  Stored in directory: /root/.cache/pip/wheels/a2/75/55/57ba1e272fd7fa1a01d9ba6b5334b7adaabf79900ede22c040\n",
+            "Successfully built flash-attn\n",
+            "Installing collected packages: PyMuPDF, av, qwen_vl_utils, modelscope, transformers, flash-attn, gradio_image_annotation, dots_ocr\n",
+            "  Attempting uninstall: transformers\n",
+            "    Found existing installation: transformers 4.54.1\n",
+            "    Uninstalling transformers-4.54.1:\n",
+            "      Successfully uninstalled transformers-4.54.1\n",
+            "  Running setup.py develop for dots_ocr\n",
+            "Successfully installed PyMuPDF-1.26.3 av-15.0.0 dots_ocr-1.0 flash-attn-2.8.0.post2 gradio_image_annotation-0.4.0 modelscope-1.28.2 qwen_vl_utils-0.0.11 transformers-4.51.3\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!python3 tools/download_model.py"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "z0nKSOYsRaA2",
+        "outputId": "e4d67ed5-0cb9-437a-abec-5514f7bb8ccc"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Attention: The model save dir dots.ocr should be replace by a name without `.` like DotsOCR, util we merge our code to transformers.\n",
+            "/usr/local/lib/python3.11/dist-packages/huggingface_hub/file_download.py:945: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
+            "  warnings.warn(\n",
+            "/usr/local/lib/python3.11/dist-packages/huggingface_hub/file_download.py:982: UserWarning: `local_dir_use_symlinks` parameter is deprecated and will be ignored. The process to download files to a local folder has been updated and do not rely on symlinks anymore. You only need to pass a destination folder as`local_dir`.\n",
+            "For more details, check out https://huggingface.co/docs/huggingface_hub/main/en/guides/download#download-files-to-local-folder.\n",
+            "  warnings.warn(\n",
+            "Fetching 19 files:   0% 0/19 [00:00<?, ?it/s]\n",
+            "chat_template.json: 1.11kB [00:00, 2.48MB/s]\n",
+            "\n",
+            "generation_config.json: 100% 74.0/74.0 [00:00<00:00, 727kB/s]\n",
+            "\n",
+            "configuration_dots.py: 2.93kB [00:00, 15.1MB/s]\n",
+            "\n",
+            ".gitattributes: 1.52kB [00:00, 8.96MB/s]\n",
+            "Fetching 19 files:   5% 1/19 [00:00<00:05,  3.39it/s]\n",
+            "config.json: 1.47kB [00:00, 9.48MB/s]\n",
+            "\n",
+            "README.md: 31.1kB [00:00, 76.2MB/s]\n",
+            "\n",
+            "NOTICE: 118kB [00:00, 148MB/s]\n",
+            "\n",
+            "model-00002-of-00002.safetensors:   0% 0.00/1.79G [00:00<?, ?B/s]\u001b[A\n",
+            "\n",
+            "model-00001-of-00002.safetensors:   0% 0.00/4.29G [00:00<?, ?B/s]\u001b[A\u001b[A\n",
+            "\n",
+            "\n",
+            "model.safetensors.index.json: 52.2kB [00:00, 153MB/s]\n",
+            "\n",
+            "\n",
+            "\n",
+            "modeling_dots_ocr_vllm.py: 17.5kB [00:00, 53.8MB/s]\n",
+            "\n",
+            "\n",
+            "\n",
+            "modeling_dots_ocr.py: 4.98kB [00:00, 17.7MB/s]\n",
+            "\n",
+            "\n",
+            "\n",
+            "modeling_dots_vision.py: 14.9kB [00:00, 44.7MB/s]\n",
+            "\n",
+            "\n",
+            "model-00001-of-00002.safetensors:   0% 21.0M/4.29G [00:00<00:21, 202MB/s]\u001b[A\u001b[A\n",
+            "\n",
+            "\n",
+            "preprocessor_config.json: 100% 347/347 [00:00<00:00, 2.95MB/s]\n",
+            "\n",
+            "model-00002-of-00002.safetensors:   1% 21.0M/1.79G [00:00<00:10, 175MB/s]\u001b[A\n",
+            "\n",
+            "\n",
+            "merges.txt: 0.00B [00:00, ?B/s]\u001b[A\u001b[A\u001b[A\n",
+            "\n",
+            "merges.txt: 1.67MB [00:00, 71.2MB/s]\n",
+            "Fetching 19 files:  42% 8/19 [00:00<00:00, 12.00it/s]\n",
+            "model-00002-of-00002.safetensors:   3% 52.4M/1.79G [00:00<00:07, 227MB/s]\u001b[A\n",
+            "\n",
+            "\n",
+            "special_tokens_map.json: 100% 494/494 [00:00<00:00, 2.97MB/s]\n",
+            "\n",
+            "\n",
+            "\n",
+            "tokenizer.json: 0.00B [00:00, ?B/s]\u001b[A\u001b[A\u001b[A\n",
+            "\n",
+            "\n",
+            "\n",
+            "tokenizer_config.json: 9.31kB [00:00, 33.9MB/s]\n",
+            "\n",
+            "\n",
+            "model-00001-of-00002.safetensors:   2% 105M/4.29G [00:00<00:11, 350MB/s] \u001b[A\u001b[A\n",
+            "\n",
+            "\n",
+            "\n",
+            "tokenizer.json: 7.04MB [00:00, 133MB/s]\n",
+            "vocab.json: 2.78MB [00:00, 102MB/s]\n",
+            "\n",
+            "model-00002-of-00002.safetensors:   5% 94.4M/1.79G [00:00<00:05, 292MB/s]\u001b[A\n",
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+            "\n",
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+            "\n",
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+            "\n",
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+            "\n",
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+            "\n",
+            "model-00001-of-00002.safetensors: 100% 4.29G/4.29G [00:17<00:00, 250MB/s]\n",
+            "Fetching 19 files: 100% 19/19 [00:17<00:00,  1.07it/s]\n",
+            "model downloaded to /content/dots.ocr/weights/DotsOCR\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import os\n",
+        "from pathlib import Path\n",
+        "\n",
+        "# Set up model path (using a directory in Colab's temporary storage)\n",
+        "hf_model_path = \"./weights/DotsOCR\"\n",
+        "os.environ[\"hf_model_path\"] = hf_model_path\n",
+        "\n",
+        "# Create directory if it doesn't exist\n",
+        "Path(hf_model_path).mkdir(parents=True, exist_ok=True)\n",
+        "\n",
+        "# Add to PYTHONPATH\n",
+        "os.environ[\"PYTHONPATH\"] = f\"{os.path.dirname(hf_model_path)}:{os.environ.get('PYTHONPATH', '')}\"\n",
+        "\n",
+        "# Install required packages\n",
+        "!pip install vllm transformers\n",
+        "\n",
+        "# Modify vllm import (this is a workaround - may need adjustment based on vllm version)\n",
+        "try:\n",
+        "    vllm_path = !which vllm\n",
+        "    if vllm_path:\n",
+        "        vllm_path = vllm_path[0]\n",
+        "        !sed -i '/^from vllm\\.entrypoints\\.cli\\.main import main$/a from DotsOCR import modeling_dots_ocr_vllm' {vllm_path}\n",
+        "except:\n",
+        "    print(\"Could not automatically modify vllm imports. You may need to do this manually.\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "m1eyfkYlTGTs",
+        "outputId": "04548a02-fc8c-4891-8b95-0fad33f0f20e"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting vllm\n",
+            "  Downloading vllm-0.10.0-cp38-abi3-manylinux1_x86_64.whl.metadata (14 kB)\n",
+            "Requirement already satisfied: transformers in /usr/local/lib/python3.11/dist-packages (4.51.3)\n",
+            "Requirement already satisfied: regex in /usr/local/lib/python3.11/dist-packages (from vllm) (2024.11.6)\n",
+            "Requirement already satisfied: cachetools in /usr/local/lib/python3.11/dist-packages (from vllm) (5.5.2)\n",
+            "Requirement already satisfied: psutil in /usr/local/lib/python3.11/dist-packages (from vllm) (5.9.5)\n",
+            "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.11/dist-packages (from vllm) (0.2.0)\n",
+            "Requirement already satisfied: numpy in /usr/local/lib/python3.11/dist-packages (from vllm) (2.0.2)\n",
+            "Requirement already satisfied: requests>=2.26.0 in /usr/local/lib/python3.11/dist-packages (from vllm) (2.32.3)\n",
+            "Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages (from vllm) (4.67.1)\n",
+            "Collecting blake3 (from vllm)\n",
+            "  Downloading blake3-1.0.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (4.2 kB)\n",
+            "Requirement already satisfied: py-cpuinfo in /usr/local/lib/python3.11/dist-packages (from vllm) (9.0.0)\n",
+            "Collecting transformers\n",
+            "  Downloading transformers-4.55.0-py3-none-any.whl.metadata (39 kB)\n",
+            "Requirement already satisfied: huggingface-hub>=0.33.0 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub[hf_xet]>=0.33.0->vllm) (0.34.3)\n",
+            "Requirement already satisfied: tokenizers>=0.21.1 in /usr/local/lib/python3.11/dist-packages (from vllm) (0.21.4)\n",
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+            "\u001b[?25hDownloading prometheus_fastapi_instrumentator-7.1.0-py3-none-any.whl (19 kB)\n",
+            "Downloading ray-2.48.0-cp311-cp311-manylinux2014_x86_64.whl (70.1 MB)\n",
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+            "\u001b[?25hDownloading blake3-1.0.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (385 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m385.5/385.5 kB\u001b[0m \u001b[31m35.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading cbor2-5.6.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (249 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m249.2/249.2 kB\u001b[0m \u001b[31m25.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading msgspec-0.19.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (210 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m210.7/210.7 kB\u001b[0m \u001b[31m22.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hUsing cached ninja-1.11.1.4-py3-none-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (422 kB)\n",
+            "Downloading partial_json_parser-0.2.1.1.post6-py3-none-any.whl (10 kB)\n",
+            "Downloading pybase64-1.4.2-cp311-cp311-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl (71 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m71.4/71.4 kB\u001b[0m \u001b[31m7.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading python_json_logger-3.3.0-py3-none-any.whl (15 kB)\n",
+            "Downloading watchfiles-1.1.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (453 kB)\n",
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+            "\u001b[?25hDownloading email_validator-2.2.0-py3-none-any.whl (33 kB)\n",
+            "Downloading fastapi_cli-0.0.8-py3-none-any.whl (10 kB)\n",
+            "Downloading interegular-0.3.3-py37-none-any.whl (23 kB)\n",
+            "Downloading llvmlite-0.44.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (42.4 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m42.4/42.4 MB\u001b[0m \u001b[31m61.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading pydantic_extra_types-2.10.5-py3-none-any.whl (38 kB)\n",
+            "Downloading astor-0.8.1-py2.py3-none-any.whl (27 kB)\n",
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+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m313.6/313.6 kB\u001b[0m \u001b[31m29.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading fastapi_cloud_cli-0.1.5-py3-none-any.whl (18 kB)\n",
+            "Downloading httptools-0.6.4-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (459 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m459.8/459.8 kB\u001b[0m \u001b[31m36.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading pycountry-24.6.1-py3-none-any.whl (6.3 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.3/6.3 MB\u001b[0m \u001b[31m127.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading python_dotenv-1.1.1-py3-none-any.whl (20 kB)\n",
+            "Downloading rich_toolkit-0.14.9-py3-none-any.whl (25 kB)\n",
+            "Downloading uvloop-0.21.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.0 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.0/4.0 MB\u001b[0m \u001b[31m114.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading rignore-0.6.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (950 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m950.6/950.6 kB\u001b[0m \u001b[31m60.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hInstalling collected packages: blake3, uvloop, triton, rignore, python-json-logger, python-dotenv, pycountry, pybase64, partial-json-parser, outlines_core, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-curand-cu12, nvidia-cufile-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, ninja, msgspec, llvmlite, llguidance, lark, interegular, httptools, gguf, dnspython, diskcache, cbor2, astor, watchfiles, nvidia-cusparse-cu12, nvidia-cufft-cu12, nvidia-cudnn-cu12, numba, email-validator, depyf, rich-toolkit, pydantic-extra-types, prometheus-fastapi-instrumentator, openai, nvidia-cusolver-cu12, lm-format-enforcer, transformers, torch, ray, fastapi-cloud-cli, fastapi-cli, xgrammar, xformers, torchvision, torchaudio, mistral_common, compressed-tensors, vllm\n",
+            "  Attempting uninstall: triton\n",
+            "    Found existing installation: triton 3.3.0\n",
+            "    Uninstalling triton-3.3.0:\n",
+            "      Successfully uninstalled triton-3.3.0\n",
+            "  Attempting uninstall: nvidia-nvtx-cu12\n",
+            "    Found existing installation: nvidia-nvtx-cu12 12.8.55\n",
+            "    Uninstalling nvidia-nvtx-cu12-12.8.55:\n",
+            "      Successfully uninstalled nvidia-nvtx-cu12-12.8.55\n",
+            "  Attempting uninstall: nvidia-nvjitlink-cu12\n",
+            "    Found existing installation: nvidia-nvjitlink-cu12 12.8.61\n",
+            "    Uninstalling nvidia-nvjitlink-cu12-12.8.61:\n",
+            "      Successfully uninstalled nvidia-nvjitlink-cu12-12.8.61\n",
+            "  Attempting uninstall: nvidia-curand-cu12\n",
+            "    Found existing installation: nvidia-curand-cu12 10.3.9.55\n",
+            "    Uninstalling nvidia-curand-cu12-10.3.9.55:\n",
+            "      Successfully uninstalled nvidia-curand-cu12-10.3.9.55\n",
+            "  Attempting uninstall: nvidia-cufile-cu12\n",
+            "    Found existing installation: nvidia-cufile-cu12 1.13.0.11\n",
+            "    Uninstalling nvidia-cufile-cu12-1.13.0.11:\n",
+            "      Successfully uninstalled nvidia-cufile-cu12-1.13.0.11\n",
+            "  Attempting uninstall: nvidia-cuda-runtime-cu12\n",
+            "    Found existing installation: nvidia-cuda-runtime-cu12 12.8.57\n",
+            "    Uninstalling nvidia-cuda-runtime-cu12-12.8.57:\n",
+            "      Successfully uninstalled nvidia-cuda-runtime-cu12-12.8.57\n",
+            "  Attempting uninstall: nvidia-cuda-nvrtc-cu12\n",
+            "    Found existing installation: nvidia-cuda-nvrtc-cu12 12.8.61\n",
+            "    Uninstalling nvidia-cuda-nvrtc-cu12-12.8.61:\n",
+            "      Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.8.61\n",
+            "  Attempting uninstall: nvidia-cuda-cupti-cu12\n",
+            "    Found existing installation: nvidia-cuda-cupti-cu12 12.8.57\n",
+            "    Uninstalling nvidia-cuda-cupti-cu12-12.8.57:\n",
+            "      Successfully uninstalled nvidia-cuda-cupti-cu12-12.8.57\n",
+            "  Attempting uninstall: nvidia-cublas-cu12\n",
+            "    Found existing installation: nvidia-cublas-cu12 12.8.3.14\n",
+            "    Uninstalling nvidia-cublas-cu12-12.8.3.14:\n",
+            "      Successfully uninstalled nvidia-cublas-cu12-12.8.3.14\n",
+            "  Attempting uninstall: llvmlite\n",
+            "    Found existing installation: llvmlite 0.43.0\n",
+            "    Uninstalling llvmlite-0.43.0:\n",
+            "      Successfully uninstalled llvmlite-0.43.0\n",
+            "  Attempting uninstall: nvidia-cusparse-cu12\n",
+            "    Found existing installation: nvidia-cusparse-cu12 12.5.7.53\n",
+            "    Uninstalling nvidia-cusparse-cu12-12.5.7.53:\n",
+            "      Successfully uninstalled nvidia-cusparse-cu12-12.5.7.53\n",
+            "  Attempting uninstall: nvidia-cufft-cu12\n",
+            "    Found existing installation: nvidia-cufft-cu12 11.3.3.41\n",
+            "    Uninstalling nvidia-cufft-cu12-11.3.3.41:\n",
+            "      Successfully uninstalled nvidia-cufft-cu12-11.3.3.41\n",
+            "  Attempting uninstall: nvidia-cudnn-cu12\n",
+            "    Found existing installation: nvidia-cudnn-cu12 9.7.1.26\n",
+            "    Uninstalling nvidia-cudnn-cu12-9.7.1.26:\n",
+            "      Successfully uninstalled nvidia-cudnn-cu12-9.7.1.26\n",
+            "  Attempting uninstall: numba\n",
+            "    Found existing installation: numba 0.60.0\n",
+            "    Uninstalling numba-0.60.0:\n",
+            "      Successfully uninstalled numba-0.60.0\n",
+            "  Attempting uninstall: openai\n",
+            "    Found existing installation: openai 1.98.0\n",
+            "    Uninstalling openai-1.98.0:\n",
+            "      Successfully uninstalled openai-1.98.0\n",
+            "  Attempting uninstall: nvidia-cusolver-cu12\n",
+            "    Found existing installation: nvidia-cusolver-cu12 11.7.2.55\n",
+            "    Uninstalling nvidia-cusolver-cu12-11.7.2.55:\n",
+            "      Successfully uninstalled nvidia-cusolver-cu12-11.7.2.55\n",
+            "  Attempting uninstall: transformers\n",
+            "    Found existing installation: transformers 4.51.3\n",
+            "    Uninstalling transformers-4.51.3:\n",
+            "      Successfully uninstalled transformers-4.51.3\n",
+            "  Attempting uninstall: torch\n",
+            "    Found existing installation: torch 2.7.0+cu128\n",
+            "    Uninstalling torch-2.7.0+cu128:\n",
+            "      Successfully uninstalled torch-2.7.0+cu128\n",
+            "  Attempting uninstall: torchvision\n",
+            "    Found existing installation: torchvision 0.22.0+cu128\n",
+            "    Uninstalling torchvision-0.22.0+cu128:\n",
+            "      Successfully uninstalled torchvision-0.22.0+cu128\n",
+            "  Attempting uninstall: torchaudio\n",
+            "    Found existing installation: torchaudio 2.7.0+cu128\n",
+            "    Uninstalling torchaudio-2.7.0+cu128:\n",
+            "      Successfully uninstalled torchaudio-2.7.0+cu128\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "fastai 2.7.19 requires torch<2.7,>=1.10, but you have torch 2.7.1 which is incompatible.\n",
+            "dots-ocr 1.0 requires transformers==4.51.3, but you have transformers 4.55.0 which is incompatible.\u001b[0m\u001b[31m\n",
+            "\u001b[0mSuccessfully installed astor-0.8.1 blake3-1.0.5 cbor2-5.6.5 compressed-tensors-0.10.2 depyf-0.19.0 diskcache-5.6.3 dnspython-2.7.0 email-validator-2.2.0 fastapi-cli-0.0.8 fastapi-cloud-cli-0.1.5 gguf-0.17.1 httptools-0.6.4 interegular-0.3.3 lark-1.2.2 llguidance-0.7.30 llvmlite-0.44.0 lm-format-enforcer-0.10.12 mistral_common-1.8.3 msgspec-0.19.0 ninja-1.11.1.4 numba-0.61.2 nvidia-cublas-cu12-12.6.4.1 nvidia-cuda-cupti-cu12-12.6.80 nvidia-cuda-nvrtc-cu12-12.6.77 nvidia-cuda-runtime-cu12-12.6.77 nvidia-cudnn-cu12-9.5.1.17 nvidia-cufft-cu12-11.3.0.4 nvidia-cufile-cu12-1.11.1.6 nvidia-curand-cu12-10.3.7.77 nvidia-cusolver-cu12-11.7.1.2 nvidia-cusparse-cu12-12.5.4.2 nvidia-nvjitlink-cu12-12.6.85 nvidia-nvtx-cu12-12.6.77 openai-1.90.0 outlines_core-0.2.10 partial-json-parser-0.2.1.1.post6 prometheus-fastapi-instrumentator-7.1.0 pybase64-1.4.2 pycountry-24.6.1 pydantic-extra-types-2.10.5 python-dotenv-1.1.1 python-json-logger-3.3.0 ray-2.48.0 rich-toolkit-0.14.9 rignore-0.6.4 torch-2.7.1 torchaudio-2.7.1 torchvision-0.22.1 transformers-4.55.0 triton-3.3.1 uvloop-0.21.0 vllm-0.10.0 watchfiles-1.1.0 xformers-0.0.31 xgrammar-0.1.21\n",
+            "nohup: failed to run command 'CUDA_VISIBLE_DEVICES=0': No such file or directory\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from pyngrok import ngrok\n",
+        "public_url = ngrok.connect(8000, bind_tls=True)  # Adjust port if needed\n",
+        "print(\"Public URL:\", public_url)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "iNPRVOjmUxJb",
+        "outputId": "66388365-796e-4489-9285-17ad6ccad0ed"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Public URL: NgrokTunnel: \"https://988ecbb0776c.ngrok-free.app\" -> \"http://localhost:8000\"\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!CUDA_VISIBLE_DEVICES=0 vllm serve ./weights/DotsOCR --tensor-parallel-size 1 --gpu-memory-utilization 0.95  --chat-template-content-format string --served-model-name model --trust-remote-code"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "QbYEd_foT2QY",
+        "outputId": "6c980927-042e-498a-e013-a575d4cf5132"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "2025-08-07 20:57:52.107021: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
+            "2025-08-07 20:57:52.125111: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+            "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
+            "E0000 00:00:1754600272.146783   10516 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+            "E0000 00:00:1754600272.153513   10516 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+            "W0000 00:00:1754600272.170115   10516 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
+            "W0000 00:00:1754600272.170145   10516 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
+            "W0000 00:00:1754600272.170148   10516 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
+            "W0000 00:00:1754600272.170151   10516 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
+            "2025-08-07 20:57:52.174913: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+            "To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+            "INFO 08-07 20:57:57 [__init__.py:235] Automatically detected platform cuda.\n",
+            "INFO 08-07 20:58:01 [api_server.py:1755] vLLM API server version 0.10.0\n",
+            "INFO 08-07 20:58:01 [cli_args.py:261] non-default args: {'model_tag': './weights/DotsOCR', 'chat_template_content_format': 'string', 'model': './weights/DotsOCR', 'trust_remote_code': True, 'served_model_name': ['model'], 'gpu_memory_utilization': 0.95}\n",
+            "INFO 08-07 20:58:01 [config.py:1604] Using max model len 131072\n",
+            "INFO 08-07 20:58:01 [config.py:2434] Chunked prefill is enabled with max_num_batched_tokens=2048.\n",
+            "2025-08-07 20:58:05.950037: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:467] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+            "WARNING: All log messages before absl::InitializeLog() is called are written to STDERR\n",
+            "E0000 00:00:1754600285.970806   10621 cuda_dnn.cc:8579] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+            "E0000 00:00:1754600285.977110   10621 cuda_blas.cc:1407] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+            "W0000 00:00:1754600285.992571   10621 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
+            "W0000 00:00:1754600285.992601   10621 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
+            "W0000 00:00:1754600285.992604   10621 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
+            "W0000 00:00:1754600285.992606   10621 computation_placer.cc:177] computation placer already registered. Please check linkage and avoid linking the same target more than once.\n",
+            "INFO 08-07 20:58:11 [__init__.py:235] Automatically detected platform cuda.\n",
+            "INFO 08-07 20:58:14 [core.py:572] Waiting for init message from front-end.\n",
+            "INFO 08-07 20:58:14 [core.py:71] Initializing a V1 LLM engine (v0.10.0) with config: model='./weights/DotsOCR', speculative_config=None, tokenizer='./weights/DotsOCR', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config={}, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=131072, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=1, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto,  device_config=cuda, decoding_config=DecodingConfig(backend='auto', disable_fallback=False, disable_any_whitespace=False, disable_additional_properties=False, reasoning_backend=''), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None), seed=0, served_model_name=model, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=True, chunked_prefill_enabled=True, use_async_output_proc=True, pooler_config=None, compilation_config={\"level\":3,\"debug_dump_path\":\"\",\"cache_dir\":\"\",\"backend\":\"\",\"custom_ops\":[],\"splitting_ops\":[\"vllm.unified_attention\",\"vllm.unified_attention_with_output\",\"vllm.mamba_mixer2\"],\"use_inductor\":true,\"compile_sizes\":[],\"inductor_compile_config\":{\"enable_auto_functionalized_v2\":false},\"inductor_passes\":{},\"use_cudagraph\":true,\"cudagraph_num_of_warmups\":1,\"cudagraph_capture_sizes\":[512,504,496,488,480,472,464,456,448,440,432,424,416,408,400,392,384,376,368,360,352,344,336,328,320,312,304,296,288,280,272,264,256,248,240,232,224,216,208,200,192,184,176,168,160,152,144,136,128,120,112,104,96,88,80,72,64,56,48,40,32,24,16,8,4,2,1],\"cudagraph_copy_inputs\":false,\"full_cuda_graph\":false,\"max_capture_size\":512,\"local_cache_dir\":null}\n",
+            "INFO 08-07 20:58:15 [parallel_state.py:1102] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, TP rank 0, EP rank 0\n",
+            "WARNING 08-07 20:58:15 [topk_topp_sampler.py:59] FlashInfer is not available. Falling back to the PyTorch-native implementation of top-p & top-k sampling. For the best performance, please install FlashInfer.\n",
+            "INFO 08-07 20:58:15 [gpu_model_runner.py:1843] Starting to load model ./weights/DotsOCR...\n",
+            "INFO 08-07 20:58:15 [gpu_model_runner.py:1875] Loading model from scratch...\n",
+            "INFO 08-07 20:58:16 [cuda.py:290] Using Flash Attention backend on V1 engine.\n",
+            "Loading safetensors checkpoint shards: 100% 2/2 [00:01<00:00,  1.06it/s]\n",
+            "INFO 08-07 20:58:18 [default_loader.py:262] Loading weights took 1.99 seconds\n",
+            "INFO 08-07 20:58:19 [gpu_model_runner.py:1892] Model loading took 5.7174 GiB and 2.253556 seconds\n",
+            "INFO 08-07 20:58:19 [gpu_model_runner.py:2380] Encoder cache will be initialized with a budget of 14400 tokens, and profiled with 1 image items of the maximum feature size.\n",
+            "The image processor of type `Qwen2VLImageProcessor` is now loaded as a fast processor by default, even if the model checkpoint was saved with a slow processor. This is a breaking change and may produce slightly different outputs. To continue using the slow processor, instantiate this class with `use_fast=False`. Note that this behavior will be extended to all models in a future release.\n",
+            "You have video processor config saved in `preprocessor.json` file which is deprecated. Video processor configs should be saved in their own `video_preprocessor.json` file. You can rename the file or load and save the processor back which renames it automatically. Loading from `preprocessor.json` will be removed in v5.0.\n",
+            "INFO 08-07 20:58:49 [backends.py:530] Using cache directory: /root/.cache/vllm/torch_compile_cache/f40f68567f/rank_0_0/backbone for vLLM's torch.compile\n",
+            "INFO 08-07 20:58:49 [backends.py:541] Dynamo bytecode transform time: 8.76 s\n",
+            "INFO 08-07 20:58:56 [backends.py:161] Directly load the compiled graph(s) for dynamic shape from the cache, took 6.316 s\n",
+            "INFO 08-07 20:58:56 [monitor.py:34] torch.compile takes 8.76 s in total\n",
+            "INFO 08-07 20:58:58 [gpu_worker.py:255] Available KV cache memory: 12.20 GiB\n",
+            "INFO 08-07 20:58:58 [kv_cache_utils.py:833] GPU KV cache size: 456,816 tokens\n",
+            "INFO 08-07 20:58:58 [kv_cache_utils.py:837] Maximum concurrency for 131,072 tokens per request: 3.49x\n",
+            "Capturing CUDA graph shapes: 100% 67/67 [00:02<00:00, 24.17it/s]\n",
+            "INFO 08-07 20:59:01 [gpu_model_runner.py:2485] Graph capturing finished in 3 secs, took 0.44 GiB\n",
+            "INFO 08-07 20:59:01 [core.py:193] init engine (profile, create kv cache, warmup model) took 42.75 seconds\n",
+            "INFO 08-07 20:59:02 [loggers.py:141] Engine 000: vllm cache_config_info with initialization after num_gpu_blocks is: 28551\n",
+            "INFO 08-07 20:59:02 [api_server.py:1818] Starting vLLM API server 0 on http://0.0.0.0:8000\n",
+            "INFO 08-07 20:59:02 [launcher.py:29] Available routes are:\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /openapi.json, Methods: HEAD, GET\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /docs, Methods: HEAD, GET\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /docs/oauth2-redirect, Methods: HEAD, GET\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /redoc, Methods: HEAD, GET\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /health, Methods: GET\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /load, Methods: GET\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /ping, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /ping, Methods: GET\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /tokenize, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /detokenize, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v1/models, Methods: GET\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /version, Methods: GET\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v1/responses, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v1/responses/{response_id}, Methods: GET\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v1/responses/{response_id}/cancel, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v1/chat/completions, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v1/completions, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v1/embeddings, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /pooling, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /classify, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /score, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v1/score, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v1/audio/transcriptions, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v1/audio/translations, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /rerank, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v1/rerank, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /v2/rerank, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /scale_elastic_ep, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /is_scaling_elastic_ep, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /invocations, Methods: POST\n",
+            "INFO 08-07 20:59:02 [launcher.py:37] Route: /metrics, Methods: GET\n",
+            "\u001b[32mINFO\u001b[0m:     Started server process [\u001b[36m10516\u001b[0m]\n",
+            "\u001b[32mINFO\u001b[0m:     Waiting for application startup.\n",
+            "\u001b[32mINFO\u001b[0m:     Application startup complete.\n",
+            "\u001b[32mINFO\u001b[0m:     2001:818:c61b:b000:457e:d747:75e4:7263:0 - \"\u001b[1mGET / HTTP/1.1\u001b[0m\" \u001b[31m404 Not Found\u001b[0m\n",
+            "\u001b[32mINFO\u001b[0m:     2001:818:c61b:b000:457e:d747:75e4:7263:0 - \"\u001b[1mGET /favicon.ico HTTP/1.1\u001b[0m\" \u001b[31m404 Not Found\u001b[0m\n",
+            "INFO 08-07 21:00:28 [launcher.py:80] Shutting down FastAPI HTTP server.\n",
+            "[rank0]:[W807 21:00:29.608158947 ProcessGroupNCCL.cpp:1479] Warning: WARNING: destroy_process_group() was not called before program exit, which can leak resources. For more info, please see https://pytorch.org/docs/stable/distributed.html#shutdown (function operator())\n",
+            "\u001b[32mINFO\u001b[0m:     Shutting down\n",
+            "\u001b[31mERROR\u001b[0m:    Traceback (most recent call last):\n",
+            "  File \"/usr/local/lib/python3.11/dist-packages/starlette/routing.py\", line 701, in lifespan\n",
+            "    await receive()\n",
+            "  File \"/usr/local/lib/python3.11/dist-packages/uvicorn/lifespan/on.py\", line 137, in receive\n",
+            "    return await self.receive_queue.get()\n",
+            "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
+            "  File \"/usr/lib/python3.11/asyncio/queues.py\", line 158, in get\n",
+            "    await getter\n",
+            "asyncio.exceptions.CancelledError\n",
+            "\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "mbOe-1sxU1-r"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}

demo/demo_gradio.py

@@ -17,6 +17,7 @@ import re
 from pathlib import Path
 from PIL import Image
 import requests
+import shutil # Import shutil for cleanup
 
 # Local tool imports
 from dots_ocr.utils import dict_promptmode_to_prompt
@@ -50,28 +51,28 @@ dots_parser = DotsOCRParser(
     max_pixels=DEFAULT_CONFIG['max_pixels']
 )
 
-# Store processing results
-processing_results = {
-    'original_image': None,
-    'processed_image': None,
-    'layout_result': None,
-    'markdown_content': None,
-    'cells_data': None,
-    'temp_dir': None,
-    'session_id': None,
-    'result_paths': None,
-    'pdf_results': None  # Store multi-page PDF results
-}
-
-# PDF caching mechanism
-pdf_cache = {
-    "images": [],
-    "current_page": 0,
-    "total_pages": 0,
-    "file_type": None,  # 'image' or 'pdf'
-    "is_parsed": False,  # Whether it has been parsed
-    "results": []  # Store parsing results for each page
-}
+def get_initial_session_state():
+    return {
+        'processing_results': {
+            'original_image': None,
+            'processed_image': None,
+            'layout_result': None,
+            'markdown_content': None,
+            'cells_data': None,
+            'temp_dir': None,
+            'session_id': None,
+            'result_paths': None,
+            'pdf_results': None
+        },
+        'pdf_cache': {
+            "images": [],
+            "current_page": 0,
+            "total_pages": 0,
+            "file_type": None,
+            "is_parsed": False,
+            "results": []
+        }
+    }
 
 def read_image_v2(img):
     """Reads an image, supports URLs and local paths"""
@@ -87,32 +88,27 @@ def read_image_v2(img):
         raise ValueError(f"Invalid image type: {type(img)}")
     return img
 
-def load_file_for_preview(file_path):
+def load_file_for_preview(file_path, session_state):
     """Loads a file for preview, supports PDF and image files"""
-    global pdf_cache
+    pdf_cache = session_state['pdf_cache']
     
     if not file_path or not os.path.exists(file_path):
-        return None, "<div id='page_info_box'>0 / 0</div>"
+        return None, "<div id='page_info_box'>0 / 0</div>", session_state
     
     file_ext = os.path.splitext(file_path)[1].lower()
     
-    if file_ext == '.pdf':
-        try:
-            # Read PDF and convert to images (one image per page)
+    try:
+        if file_ext == '.pdf':
             pages = load_images_from_pdf(file_path)
             pdf_cache["file_type"] = "pdf"
-        except Exception as e:
-            return None, f"<div id='page_info_box'>PDF loading failed: {str(e)}</div>"
-    elif file_ext in ['.jpg', '.jpeg', '.png']:
-        # For image files, read directly as a single-page image
-        try:
+        elif file_ext in ['.jpg', '.jpeg', '.png']:
             image = Image.open(file_path)
             pages = [image]
             pdf_cache["file_type"] = "image"
-        except Exception as e:
-            return None, f"<div id='page_info_box'>Image loading failed: {str(e)}</div>"
-    else:
-        return None, "<div id='page_info_box'>Unsupported file format</div>"
+        else:
+            return None, "<div id='page_info_box'>Unsupported file format</div>", session_state
+    except Exception as e:
+        return None, f"<div id='page_info_box'>PDF loading failed: {str(e)}</div>", session_state
     
     pdf_cache["images"] = pages
     pdf_cache["current_page"] = 0
@@ -120,14 +116,14 @@ def load_file_for_preview(file_path):
     pdf_cache["is_parsed"] = False
     pdf_cache["results"] = []
     
-    return pages[0], f"<div id='page_info_box'>1 / {len(pages)}</div>"
+    return pages[0], f"<div id='page_info_box'>1 / {len(pages)}</div>", session_state
 
-def turn_page(direction):
+def turn_page(direction, session_state):
     """Page turning function"""
-    global pdf_cache
+    pdf_cache = session_state['pdf_cache']
     
     if not pdf_cache["images"]:
-        return None, "<div id='page_info_box'>0 / 0</div>", "", ""
+        return None, "<div id='page_info_box'>0 / 0</div>", "", session_state
 
     if direction == "prev":
         pdf_cache["current_page"] = max(0, pdf_cache["current_page"] - 1)
@@ -138,27 +134,18 @@ def turn_page(direction):
     current_image = pdf_cache["images"][index]  # Use the original image by default
     page_info = f"<div id='page_info_box'>{index + 1} / {pdf_cache['total_pages']}</div>"
     
-    # If parsed, display the results for the current page
-    current_md = ""
-    current_md_raw = ""
     current_json = ""
     if pdf_cache["is_parsed"] and index < len(pdf_cache["results"]):
         result = pdf_cache["results"][index]
-        if 'md_content' in result:
-            # Get the raw markdown content
-            current_md_raw = result['md_content']
-            # Process the content after LaTeX rendering
-            current_md = result['md_content'] if result['md_content'] else ""
-        if 'cells_data' in result:
+        if 'cells_data' in result and result['cells_data']:
             try:
                 current_json = json.dumps(result['cells_data'], ensure_ascii=False, indent=2)
             except:
                 current_json = str(result.get('cells_data', ''))
-        # Use the image with layout boxes (if available)
         if 'layout_image' in result and result['layout_image']:
             current_image = result['layout_image']
     
-    return current_image, page_info, current_json
+    return current_image, page_info, current_json, session_state
 
 def get_test_images():
     """Gets the list of test images"""
@@ -169,13 +156,6 @@ def get_test_images():
                       if name.lower().endswith(('.png', '.jpg', '.jpeg', '.pdf'))]
     return test_images
 
-def convert_image_to_base64(image):
-    """Converts a PIL image to base64 encoding"""
-    buffered = io.BytesIO()
-    image.save(buffered, format="PNG")
-    img_str = base64.b64encode(buffered.getvalue()).decode()
-    return f"data:image/png;base64,{img_str}"
-
 def create_temp_session_dir():
     """Creates a unique temporary directory for each processing request"""
     session_id = uuid.uuid4().hex[:8]
@@ -198,7 +178,6 @@ def parse_image_with_high_level_api(parser, image, prompt_mode, fitz_preprocess=
         # Use the high-level API parse_image
         filename = f"demo_{session_id}"
         results = parser.parse_image(
-            # input_path=temp_image_path,
             input_path=image,
             filename=filename, 
             prompt_mode=prompt_mode,
@@ -212,46 +191,32 @@ def parse_image_with_high_level_api(parser, image, prompt_mode, fitz_preprocess=
         
         result = results[0]  # parse_image returns a list with a single result
         
-        # Read the result files
         layout_image = None
-        cells_data = None
-        md_content = None
-        raw_response = None
-        filtered = False
-        
-        # Read the layout image
         if 'layout_image_path' in result and os.path.exists(result['layout_image_path']):
             layout_image = Image.open(result['layout_image_path'])
         
-        # Read the JSON data
+        cells_data = None
         if 'layout_info_path' in result and os.path.exists(result['layout_info_path']):
             with open(result['layout_info_path'], 'r', encoding='utf-8') as f:
                 cells_data = json.load(f)
         
-        # Read the Markdown content
+        md_content = None
         if 'md_content_path' in result and os.path.exists(result['md_content_path']):
             with open(result['md_content_path'], 'r', encoding='utf-8') as f:
                 md_content = f.read()
         
-        # Check for the raw response file (when JSON parsing fails)
-        if 'filtered' in result:
-            filtered = result['filtered']
-        
         return {
             'layout_image': layout_image,
             'cells_data': cells_data,
             'md_content': md_content,
-            'filtered': filtered,
+            'filtered': result.get('filtered', False),
             'temp_dir': temp_dir,
             'session_id': session_id,
             'result_paths': result,
-            'input_width': result['input_width'],
-            'input_height': result['input_height'],
+            'input_width': result.get('input_width', 0),
+            'input_height': result.get('input_height', 0),
         }
-        
     except Exception as e:
-        # Clean up the temporary directory on error
-        import shutil
         if os.path.exists(temp_dir):
             shutil.rmtree(temp_dir, ignore_errors=True)
         raise e
@@ -307,17 +272,10 @@ def parse_pdf_with_high_level_api(parser, pdf_path, prompt_mode):
                     page_content = f.read()
                     page_result['md_content'] = page_content
                     all_md_content.append(page_content)
-            
-            # Check for the raw response file (when JSON parsing fails)
-            page_result['filtered'] = False
-            if 'filtered' in page_result:
-                page_result['filtered'] = page_result['filtered']
-
+            page_result['filtered'] = result.get('filtered', False)
             parsed_results.append(page_result)
         
-        # Merge the content of all pages
         combined_md = "\n\n---\n\n".join(all_md_content) if all_md_content else ""
-        
         return {
             'parsed_results': parsed_results,
             'combined_md_content': combined_md,
@@ -328,42 +286,30 @@ def parse_pdf_with_high_level_api(parser, pdf_path, prompt_mode):
         }
         
     except Exception as e:
-        # Clean up the temporary directory on error
-        import shutil
         if os.path.exists(temp_dir):
             shutil.rmtree(temp_dir, ignore_errors=True)
         raise e
 
 # ==================== Core Processing Function ====================
-def process_image_inference(test_image_input, file_input,
+def process_image_inference(session_state, test_image_input, file_input,
                           prompt_mode, server_ip, server_port, min_pixels, max_pixels,
                           fitz_preprocess=False
                           ):
     """Core function to handle image/PDF inference"""
-    global current_config, processing_results, dots_parser, pdf_cache
+    # Use session_state instead of global variables
+    processing_results = session_state['processing_results']
+    pdf_cache = session_state['pdf_cache']
     
-    # First, clean up previous processing results to avoid confusion with the download button
     if processing_results.get('temp_dir') and os.path.exists(processing_results['temp_dir']):
-        import shutil
         try:
             shutil.rmtree(processing_results['temp_dir'], ignore_errors=True)
         except Exception as e:
             print(f"Failed to clean up previous temporary directory: {e}")
     
-    # Reset processing results
-    processing_results = {
-        'original_image': None,
-        'processed_image': None,
-        'layout_result': None,
-        'markdown_content': None,
-        'cells_data': None,
-        'temp_dir': None,
-        'session_id': None,
-        'result_paths': None,
-        'pdf_results': None
-    }
+    # Reset processing results for the current session
+    session_state['processing_results'] = get_initial_session_state()['processing_results']
+    processing_results = session_state['processing_results']
     
-    # Update configuration
     current_config.update({
         'ip': server_ip,
         'port_vllm': server_port,
@@ -377,294 +323,119 @@ def process_image_inference(test_image_input, file_input,
     dots_parser.min_pixels = min_pixels
     dots_parser.max_pixels = max_pixels
     
-    # Determine the input source
-    input_file_path = None
-    image = None
+    input_file_path = file_input if file_input else test_image_input
     
-    # Prioritize file input (supports PDF)
-    if file_input is not None:
-        input_file_path = file_input
-        file_ext = os.path.splitext(input_file_path)[1].lower()
-        
-        if file_ext == '.pdf':
-            # PDF file processing
-            try:
-                return process_pdf_file(input_file_path, prompt_mode)
-            except Exception as e:
-                return None, f"PDF processing failed: {e}", "", "", gr.update(value=None), None, ""
-        elif file_ext in ['.jpg', '.jpeg', '.png']:
-            # Image file processing
-            try:
-                image = Image.open(input_file_path)
-            except Exception as e:
-                return None, f"Failed to read image file: {e}", "", "", gr.update(value=None), None, ""
+    if not input_file_path:
+        return None, "Please upload image/PDF file or select test image", "", "", gr.update(value=None), None, "", session_state
     
-    # If no file input, check the test image input
-    if image is None:
-        if test_image_input and test_image_input != "":
-            file_ext = os.path.splitext(test_image_input)[1].lower()
-            if file_ext == '.pdf':
-                return process_pdf_file(test_image_input, prompt_mode)
-            else:
-                try:
-                    image = read_image_v2(test_image_input)
-                except Exception as e:
-                    return None, f"Failed to read test image: {e}", "", "", gr.update(value=None), gr.update(value=None), None, ""
-    
-    if image is None:
-        return None, "Please upload image/PDF file or select test image", "", "", gr.update(value=None), None, ""
+    file_ext = os.path.splitext(input_file_path)[1].lower()
     
     try:
-        # Clear PDF cache (for image processing)
-        pdf_cache["images"] = []
-        pdf_cache["current_page"] = 0
-        pdf_cache["total_pages"] = 0
-        pdf_cache["is_parsed"] = False
-        pdf_cache["results"] = []
-        
-        # Process using the high-level API of DotsOCRParser
-        original_image = image
-        parse_result = parse_image_with_high_level_api(dots_parser, image, prompt_mode, fitz_preprocess)
-        
-        # Extract parsing results
-        layout_image = parse_result['layout_image']
-        cells_data = parse_result['cells_data']
-        md_content = parse_result['md_content']
-        filtered = parse_result['filtered']
-        
-        # Handle parsing failure case
-        if filtered:
-            # JSON parsing failed, only text content is available
-            info_text = f"""
-**Image Information:**
-- Original Size: {original_image.width} x {original_image.height}
-- Processing: JSON parsing failed, using cleaned text output
-- Server: {current_config['ip']}:{current_config['port_vllm']}
-- Session ID: {parse_result['session_id']}
-            """
+        if file_ext == '.pdf':
+            # MINIMAL CHANGE: The `process_pdf_file` function is now inlined and uses session_state.
+            preview_image, page_info, session_state = load_file_for_preview(input_file_path, session_state)
+            pdf_result = parse_pdf_with_high_level_api(dots_parser, input_file_path, prompt_mode)
+            
+            session_state['pdf_cache']["is_parsed"] = True
+            session_state['pdf_cache']["results"] = pdf_result['parsed_results']
             
-            # Store results
             processing_results.update({
-                'original_image': original_image,
-                'processed_image': None,
-                'layout_result': None,
-                'markdown_content': md_content,
-                'cells_data': None,
-                'temp_dir': parse_result['temp_dir'],
-                'session_id': parse_result['session_id'],
-                'result_paths': parse_result['result_paths']
+                'markdown_content': pdf_result['combined_md_content'],
+                'cells_data': pdf_result['combined_cells_data'],
+                'temp_dir': pdf_result['temp_dir'],
+                'session_id': pdf_result['session_id'],
+                'pdf_results': pdf_result['parsed_results']
             })
             
-            return (
-                original_image,  # No layout image
-                info_text,
-                md_content,
-                md_content,  # Display raw markdown text
-                gr.update(visible=False),  # Hide download button
-                None,  # Page info
-                ""     # Current page JSON output
-            )
-        
-        # JSON parsing successful case
-        # Save the raw markdown content (before LaTeX processing)
-        md_content_raw = md_content or "No markdown content generated"
-        
-        # Store results
-        processing_results.update({
-            'original_image': original_image,
-            'processed_image': None,  # High-level API does not return processed_image
-            'layout_result': layout_image,
-            'markdown_content': md_content,
-            'cells_data': cells_data,
-            'temp_dir': parse_result['temp_dir'],
-            'session_id': parse_result['session_id'],
-            'result_paths': parse_result['result_paths']
-        })
-        
-        # Prepare display information
-        num_elements = len(cells_data) if cells_data else 0
-        info_text = f"""
-**Image Information:**
-- Original Size: {original_image.width} x {original_image.height}
-- Model Input Size: {parse_result['input_width']} x {parse_result['input_height']}
-- Server: {current_config['ip']}:{current_config['port_vllm']}
-- Detected {num_elements} layout elements
-- Session ID: {parse_result['session_id']}
-        """
-        
-        # Current page JSON output
-        current_json = ""
-        if cells_data:
-            try:
-                current_json = json.dumps(cells_data, ensure_ascii=False, indent=2)
-            except:
-                current_json = str(cells_data)
-        
-        # Create the download ZIP file
-        download_zip_path = None
-        if parse_result['temp_dir']:
-            download_zip_path = os.path.join(parse_result['temp_dir'], f"layout_results_{parse_result['session_id']}.zip")
-            try:
+            total_elements = len(pdf_result['combined_cells_data'])
+            info_text = f"**PDF Information:**\n- Total Pages: {pdf_result['total_pages']}\n- Server: {current_config['ip']}:{current_config['port_vllm']}\n- Total Detected Elements: {total_elements}\n- Session ID: {pdf_result['session_id']}"
+            
+            current_page_layout_image = preview_image
+            current_page_json = ""
+            if session_state['pdf_cache']["results"]:
+                first_result = session_state['pdf_cache']["results"][0]
+                if 'layout_image' in first_result and first_result['layout_image']:
+                    current_page_layout_image = first_result['layout_image']
+                if first_result.get('cells_data'):
+                    try:
+                        current_page_json = json.dumps(first_result['cells_data'], ensure_ascii=False, indent=2)
+                    except:
+                        current_page_json = str(first_result['cells_data'])
+
+            download_zip_path = None
+            if pdf_result['temp_dir']:
+                download_zip_path = os.path.join(pdf_result['temp_dir'], f"layout_results_{pdf_result['session_id']}.zip")
                 with zipfile.ZipFile(download_zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
-                    for root, dirs, files in os.walk(parse_result['temp_dir']):
+                    for root, _, files in os.walk(pdf_result['temp_dir']):
                         for file in files:
-                            if file.endswith('.zip'):
-                                continue
-                            file_path = os.path.join(root, file)
-                            arcname = os.path.relpath(file_path, parse_result['temp_dir'])
-                            zipf.write(file_path, arcname)
-            except Exception as e:
-                print(f"Failed to create download ZIP: {e}")
-                download_zip_path = None
-        
-        return (
-            layout_image,
-            info_text,
-            md_content or "No markdown content generated",
-            md_content_raw,  # Raw markdown text
-            gr.update(value=download_zip_path, visible=True) if download_zip_path else gr.update(visible=False),  # Set the download file
-            None,  # Page info (not displayed for image processing)
-            current_json     # Current page JSON
-        )
-        
-    except Exception as e:
-        return None, f"Error during processing: {e}", "", "", gr.update(value=None), None, ""
+                            if not file.endswith('.zip'): zipf.write(os.path.join(root, file), os.path.relpath(os.path.join(root, file), pdf_result['temp_dir']))
 
-def process_pdf_file(pdf_path, prompt_mode):
-    """Dedicated function for processing PDF files"""
-    global pdf_cache, processing_results, dots_parser
-    
-    try:
-        # First, load the PDF for preview
-        preview_image, page_info = load_file_for_preview(pdf_path)
-        
-        # Parse the PDF using DotsOCRParser
-        pdf_result = parse_pdf_with_high_level_api(dots_parser, pdf_path, prompt_mode)
-        
-        # Update the PDF cache
-        pdf_cache["is_parsed"] = True
-        pdf_cache["results"] = pdf_result['parsed_results']
-        
-        # Handle LaTeX table rendering
-        combined_md = pdf_result['combined_md_content']
-        combined_md_raw = combined_md or "No markdown content generated"  # Save the raw content
-
-        # Store results
-        processing_results.update({
-            'original_image': None,
-            'processed_image': None,
-            'layout_result': None,
-            'markdown_content': combined_md,
-            'cells_data': pdf_result['combined_cells_data'],
-            'temp_dir': pdf_result['temp_dir'],
-            'session_id': pdf_result['session_id'],
-            'result_paths': None,
-            'pdf_results': pdf_result['parsed_results']
-        })
-        
-        # Prepare display information
-        total_elements = len(pdf_result['combined_cells_data'])
-        info_text = f"""
-**PDF Information:**
-- Total Pages: {pdf_result['total_pages']}
-- Server: {current_config['ip']}:{current_config['port_vllm']}
-- Total Detected Elements: {total_elements}
-- Session ID: {pdf_result['session_id']}
-        """
-        
-        # Content of the current page (first page)
-        current_page_md = ""
-        current_page_md_raw = ""
-        current_page_json = ""
-        current_page_layout_image = preview_image  # Use the original preview image by default
-        
-        if pdf_cache["results"] and len(pdf_cache["results"]) > 0:
-            current_result = pdf_cache["results"][0]
-            if current_result['md_content']:
-                # Raw markdown content
-                current_page_md_raw = current_result['md_content']
-                # Process the content after LaTeX rendering
-
-                current_page_md = current_result['md_content']
-            if current_result['cells_data']:
-                try:
-                    current_page_json = json.dumps(current_result['cells_data'], ensure_ascii=False, indent=2)
-                except:
-                    current_page_json = str(current_result['cells_data'])
-            # Use the image with layout boxes (if available)
-            if 'layout_image' in current_result and current_result['layout_image']:
-                current_page_layout_image = current_result['layout_image']
+            return (
+                current_page_layout_image, info_text, pdf_result['combined_md_content'] or "No markdown content generated",
+                pdf_result['combined_md_content'] or "No markdown content generated",
+                gr.update(value=download_zip_path, visible=bool(download_zip_path)), page_info, current_page_json, session_state
+            )
         
-        # Create the download ZIP file
-        download_zip_path = None
-        if pdf_result['temp_dir']:
-            download_zip_path = os.path.join(pdf_result['temp_dir'], f"layout_results_{pdf_result['session_id']}.zip")
-            try:
+        else: # Image processing
+            image = read_image_v2(input_file_path)
+            session_state['pdf_cache'] = get_initial_session_state()['pdf_cache']
+            
+            original_image = image
+            parse_result = parse_image_with_high_level_api(dots_parser, image, prompt_mode, fitz_preprocess)
+            
+            if parse_result['filtered']:
+                 info_text = f"**Image Information:**\n- Original Size: {original_image.width} x {original_image.height}\n- Processing: JSON parsing failed, using cleaned text output\n- Server: {current_config['ip']}:{current_config['port_vllm']}\n- Session ID: {parse_result['session_id']}"
+                 processing_results.update({
+                     'original_image': original_image, 'markdown_content': parse_result['md_content'],
+                     'temp_dir': parse_result['temp_dir'], 'session_id': parse_result['session_id'],
+                     'result_paths': parse_result['result_paths']
+                 })
+                 return original_image, info_text, parse_result['md_content'], parse_result['md_content'], gr.update(visible=False), None, "", session_state
+            
+            md_content_raw = parse_result['md_content'] or "No markdown content generated"
+            processing_results.update({
+                'original_image': original_image, 'layout_result': parse_result['layout_image'],
+                'markdown_content': parse_result['md_content'], 'cells_data': parse_result['cells_data'],
+                'temp_dir': parse_result['temp_dir'], 'session_id': parse_result['session_id'],
+                'result_paths': parse_result['result_paths']
+            })
+            
+            num_elements = len(parse_result['cells_data']) if parse_result['cells_data'] else 0
+            info_text = f"**Image Information:**\n- Original Size: {original_image.width} x {original_image.height}\n- Model Input Size: {parse_result['input_width']} x {parse_result['input_height']}\n- Server: {current_config['ip']}:{current_config['port_vllm']}\n- Detected {num_elements} layout elements\n- Session ID: {parse_result['session_id']}"
+            
+            current_json = json.dumps(parse_result['cells_data'], ensure_ascii=False, indent=2) if parse_result['cells_data'] else ""
+            
+            download_zip_path = None
+            if parse_result['temp_dir']:
+                download_zip_path = os.path.join(parse_result['temp_dir'], f"layout_results_{parse_result['session_id']}.zip")
                 with zipfile.ZipFile(download_zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
-                    for root, dirs, files in os.walk(pdf_result['temp_dir']):
+                    for root, _, files in os.walk(parse_result['temp_dir']):
                         for file in files:
-                            if file.endswith('.zip'):
-                                continue
-                            file_path = os.path.join(root, file)
-                            arcname = os.path.relpath(file_path, pdf_result['temp_dir'])
-                            zipf.write(file_path, arcname)
-            except Exception as e:
-                print(f"Failed to create download ZIP: {e}")
-                download_zip_path = None
-        
-        return (
-            current_page_layout_image,  # Use the image with layout boxes
-            info_text,
-            combined_md or "No markdown content generated",  # Display the markdown for the entire PDF
-            combined_md_raw or "No markdown content generated",  # Display the raw markdown for the entire PDF
-            gr.update(value=download_zip_path, visible=True) if download_zip_path else gr.update(visible=False),  # Set the download file
-            page_info,
-            current_page_json
-        )
-        
+                            if not file.endswith('.zip'): zipf.write(os.path.join(root, file), os.path.relpath(os.path.join(root, file), parse_result['temp_dir']))
+            
+            return (
+                parse_result['layout_image'], info_text, parse_result['md_content'] or "No markdown content generated",
+                md_content_raw, gr.update(value=download_zip_path, visible=bool(download_zip_path)),
+                None, current_json, session_state
+            )
     except Exception as e:
-        # Reset the PDF cache
-        pdf_cache["images"] = []
-        pdf_cache["current_page"] = 0
-        pdf_cache["total_pages"] = 0
-        pdf_cache["is_parsed"] = False
-        pdf_cache["results"] = []
-        raise e
+        import traceback
+        traceback.print_exc()
+        return None, f"Error during processing: {e}", "", "", gr.update(value=None), None, "", session_state
 
-def clear_all_data():
+# MINIMAL CHANGE: Functions now take `session_state` as an argument.
+def clear_all_data(session_state):
     """Clears all data"""
-    global processing_results, pdf_cache
+    processing_results = session_state['processing_results']
     
-    # Clean up the temporary directory
     if processing_results.get('temp_dir') and os.path.exists(processing_results['temp_dir']):
-        import shutil
         try:
             shutil.rmtree(processing_results['temp_dir'], ignore_errors=True)
         except Exception as e:
             print(f"Failed to clean up temporary directory: {e}")
     
-    # Reset processing results
-    processing_results = {
-        'original_image': None,
-        'processed_image': None,
-        'layout_result': None,
-        'markdown_content': None,
-        'cells_data': None,
-        'temp_dir': None,
-        'session_id': None,
-        'result_paths': None,
-        'pdf_results': None
-    }
-    
-    # Reset the PDF cache
-    pdf_cache = {
-        "images": [],
-        "current_page": 0,
-        "total_pages": 0,
-        "file_type": None,
-        "is_parsed": False,
-        "results": []
-    }
+    # Reset the session state by returning a new initial state
+    new_session_state = get_initial_session_state()
     
     return (
         None,  # Clear file input
@@ -675,7 +446,8 @@ def clear_all_data():
         "🕐 Waiting for parsing result...",    # Clear raw Markdown text
         gr.update(visible=False),  # Hide download button
         "<div id='page_info_box'>0 / 0</div>",  # Reset page info
-        "🕐 Waiting for parsing result..."     # Clear current page JSON
+        "🕐 Waiting for parsing result...",     # Clear current page JSON
+        new_session_state
     )
 
 def update_prompt_display(prompt_mode):
@@ -746,6 +518,7 @@ def create_gradio_interface():
     """
     
     with gr.Blocks(theme="ocean", css=css, title='dots.ocr') as demo:
+        session_state = gr.State(value=get_initial_session_state())
         
         # Title
         gr.HTML("""
@@ -779,7 +552,6 @@ def create_gradio_interface():
                     label="Select Prompt",
                     choices=["prompt_layout_all_en", "prompt_layout_only_en", "prompt_ocr"],
                     value="prompt_layout_all_en",
-                    show_label=True
                 )
                 
                 # Display current prompt content
@@ -844,11 +616,10 @@ def create_gradio_interface():
                             with gr.TabItem("Markdown Render Preview"):
                                 md_output = gr.Markdown(
                                     "## Please click the parse button to parse or select for single-task recognition...",
-                                    label="Markdown Preview",
                                     max_height=600,
                                     latex_delimiters=[
                                         {"left": "$$", "right": "$$", "display": True},
-                                        {"left": "$", "right": "$", "display": False},
+                                        {"left": "$", "right": "$", "display": False}
                                     ],
                                     show_copy_button=False,
                                     elem_id="markdown_output"
@@ -888,61 +659,68 @@ def create_gradio_interface():
             fn=update_prompt_display,
             inputs=prompt_mode,
             outputs=prompt_display,
-            show_progress=False
         )
         
         # Show preview on file upload
         file_input.upload(
+            # fn=lambda file_data, state: load_file_for_preview(file_data, state),
             fn=load_file_for_preview,
-            inputs=file_input,
-            outputs=[result_image, page_info],
-            show_progress=False
+            inputs=[file_input, session_state],
+            outputs=[result_image, page_info, session_state]
         )
         
-        # Page navigation
+        # Also handle test image selection
+        test_image_input.change(
+            # fn=lambda path, state: load_file_for_preview(path, state),
+            fn=load_file_for_preview,
+            inputs=[test_image_input, session_state],
+            outputs=[result_image, page_info, session_state]
+        )
+
         prev_btn.click(
-            fn=lambda: turn_page("prev"), 
-            outputs=[result_image, page_info, current_page_json],
-            show_progress=False
+            fn=lambda s: turn_page("prev", s),
+            inputs=[session_state], 
+            outputs=[result_image, page_info, current_page_json, session_state]
         )
         
         next_btn.click(
-            fn=lambda: turn_page("next"), 
-            outputs=[result_image, page_info, current_page_json],
-            show_progress=False
+            fn=lambda s: turn_page("next", s),
+            inputs=[session_state], 
+            outputs=[result_image, page_info, current_page_json, session_state]
         )
         
         process_btn.click(
             fn=process_image_inference,
             inputs=[
-                test_image_input, file_input,
+                session_state, test_image_input, file_input,
                 prompt_mode, server_ip, server_port, min_pixels, max_pixels, 
                 fitz_preprocess
             ],
             outputs=[
                 result_image, info_display, md_output, md_raw_output,
-                download_btn, page_info, current_page_json
-            ],
-            show_progress=True
+                download_btn, page_info, current_page_json, session_state
+            ]
         )
         
         clear_btn.click(
             fn=clear_all_data,
+            inputs=[session_state],
             outputs=[
                 file_input, test_image_input,
                 result_image, info_display, md_output, md_raw_output,
-                download_btn, page_info, current_page_json
-            ],
-            show_progress=False
+                download_btn, page_info, current_page_json, session_state
+            ]
         )
     
     return demo
 
 # ==================== Main Program ====================
 if __name__ == "__main__":
+    import sys
+    port = int(sys.argv[1])
     demo = create_gradio_interface()
     demo.queue().launch(
         server_name="0.0.0.0", 
-        server_port=7860, 
+        server_port=port, 
         debug=True
     )

demo/demo_vllm.py

@@ -29,10 +29,11 @@ def main():
     response = inference_with_vllm(
         image,
         prompt, 
-        ip="localhost",
-        port=8000,
+        ip=args.ip,
+        port=args.port,
         temperature=0.1,
         top_p=0.9,
+        model_name=args.model_name,
     )
     print(f"response: {response}")
 

dots.ocr LICENSE AGREEMENT

@@ -0,0 +1,109 @@
+dots.ocr LICENSE AGREEMENT
+
+Effective Date: [ August 8, 2025]
+
+Copyright Holder: [Xingyin Information Technology (Shanghai) Co., Ltd]
+
+This License Agreement (“Agreement”) governs Your use, reproduction, modification, and distribution of dots.ocr (the "Model Materials"). This Agreement is designed to maximize the openness and use of the Model Materials while addressing the unique legal, ethical, and technical challenges posed by large language models.
+
+WHEREAS, Licensor has developed the dots.ocr document parsing model and intends to distribute the Model Materials under an open‑source framework;
+WHEREAS, traditional open-source licenses (e.g., the MIT License) may not fully address the complexity inherent complexities of document parsing models, namely their multiple components (code, weights, training data), potential ethical risks, data‑governance issues, and intellectual‑property and liability questions regarding AI‑generated content;
+WHEREAS, Licensor seeks to provide a legal framework that ensures maximum access to and use of the Model Materials while clearly defining the rights, obligations, and liabilities of Licensee;
+
+THEREFORE, the parties agree that, subject to the MIT License, they shall be bound by the following terms and conditions:
+
+1. Definitions and Interpretation
+Purpose: To define key terms used in this Agreement, particularly "Model Materials," ensuring clarity of the license scope beyond traditional software code. To clarify the order of precedence between this Agreement and the MIT License to avoid conflict.
+
+1.1 “Licensor” shall mean the entity providing the Model Materials under this Agreement, namely [Xingyin Information Technology (Shanghai) Co., Ltd].
+
+1.2 “Licensee” or "You" shall mean any individual or entity exercising permissions granted by this Agreement.
+
+1.3 “Model Materials” shall mean all materials provided by Licensor under this Agreement, including but not limited to:
+        (a) one or more machine‑learning models, including architecture and trained parameters (i.e., model weights);
+        (b) all associated preprocessing, training, inference, and fine‑tuning code;
+        (c) training datasets and evaluation scripts (or their detailed descriptions and access mechanisms); and
+        (d) any accompanying documentation, metadata, and tools.
+The above Model Materials shall be subject to the content published on the Licensor’s website or GitHub repository at https://github.com/rednote-hilab/dots.ocr.
+
+1.4 “Outputs” shall mean any content generated through the use of the Model Materials, such as text, tables, code,layout information, and formulas extracted from documents.
+
+1.5 “MIT License” shall mean The MIT Open Source License published by the Massachusetts Institute of Technology.
+
+1.6   Priority of Agreement. In the event of any conflict or inconsistency between this Agreement and the MIT License, the terms of the MIT License shall prevail. However, if the terms of the MIT License are ambiguous or silent on a particular matter, the provisions of this Agreement shall apply and supplement the MIT License.
+
+2. Grant of Rights and Scope of Use
+
+Purpose: To grant broad, permissive rights to the Licensee for the Model Materials—including code, weights, data, and documentation—to ensure maximum openness and flexibility while clarifying the free use of model-generated content. Additionally, it clarifies the feasibility of transitioning from open-source to commercial‑use and the use of OpenAPI interfaces.
+
+2.1   Grant of Copyright License. Subject to Licensee's compliance with this Agreement, Licensor hereby grants Licensee a perpetual, worldwide, non‑exclusive, no-charge, royalty‑free copyright license to use (run or test), reproduce, modify, create derivative works of, merge, publish, distribute the Model Materials; sublicense and/or sell copies of the Model Materials or any derivative works thereof; and incorporate the unmodified or modified Model Materials into proprietary products or services, including for commercial purposes, software‑as‑a‑service (SaaS) offerings, or via OpenAPI or other interfaces.
+
+2.2   Fundamental Capabilities. The Model Materials only provide the fundamental model’s capabilities. Licensees may develop derivative AI applications or undertake task‑specific training thereon.
+
+2.3   From Open Source to Commercial Use. The open-source release does not preclude Licensor’s commercial exploitation of the Model Materials, in whole or in part. Any such commercial use shall, at that time, be subject to license agreements between Licensor and applicable users.
+
+2.4   API‑Service Exception. Licensees who access the Model Materials through API calls or provide model services via API interfaces(without directly distributing model weights )shall not be subject to this Agreement unless otherwise expressly agreed. Instead, such use shall be governed by the API terms of use published by Licensor (if any).
+
+3. Acceptable Use Policy and Prohibited Uses
+
+3.1   Responsible Use. Licensee must use the Model Materials in a responsible, ethical, and lawful manner, in compliance with all applicable laws, regulations, industry standards, and best practices.
+
+3.2   Enterprise On‑Premises Deployment. The Licensee may deploy the Model Materials in closed‑source, on‑premises enterprise environments.
+
+3.3   Prohibited Uses. Any breach of the prohibitions below will result in the automatic termination of all licenses granted under this Agreement. Licensee agrees not to use the Model Materials or any derivative works thereof, in connection with:
+(a) Identification and Utilization of Illegal/Harmful Content:Includes identifying graphic/text materials used for counterfeiting certificates/invoices, perpetrating fraud, or launching cyberattacks; or processing images containing illegal content such as violence, criminal activities, disinformation, or child exploitation.
+(b) Privacy Infringement and Discriminatory Practices:Extracting personal sensitive information (e.g., ID numbers, medical records, biometric data) or protected characteristics (e.g., race, gender) from images without legal authorization or consent, for purposes of privacy violation, automated discriminatory decision-making, or harassment.
+(c) Copyright Restrictions:Licensees shall not use the tool for unauthorized digitization of publications/document scanning or bulk scraping of content. Any use involving publications or other copyright-protected materials must first obtain relevant permissions.
+
+4. Intellectual Property Ownership and Contributions
+
+4.1   Licensor's Copyright Reservation. Licensor reserves all right, title, and interest in and to the Model Materials (including the model architecture, parameters, code, and original training data), except as expressly licensed herein. The original copyright of the Model Materials belongs to the Licensor.
+
+4.2   Patent License. Subject to the terms and conditions of this Agreement, Licensor hereby grants Licensee a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Model Materials, where such license applies only to those patent claims licensable by the Lisensor that are necessarily infringed by its contribution(s). 
+If Licensee institutes patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Model Materials constitute direct or contributory patent infringement, then any patent licenses granted under this License for the Model Materials shall terminate as of the date such litigation is asserted or filed.
+
+4.3   Outputs: The Outputs generated through the use of the Model Materials generally refer to text, tables, layouts, and other content extracted from documents or images. The extracted content itself does not generate new intellectual property rights, and all intellectual property remains with the original authors or copyright holders. The Licensee is responsible for due diligence regarding the legality of the Outputs, particularly where the content extracted by the OCR model may be substantially similar to existing copyrighted works, which could present intellectual property infringement risks. The Licensor assumes no liability for such infringements.
+4.4   Trademarks. Nothing in this License permits Licensee to make use of Licensor’s trademarks, trade names, logos (e.g., “rednote,” “Xiaohongshu,” “dots.ocr”) or to otherwise suggest endorsement or misrepresent the relationship between the parties, unless Licensor’s prior written approval is granted.
+
+5. Data Governance, Privacy, and Security
+ 
+5.1   Data Quality and Bias. Licensee shall use training data from lawful sources and is encouraged to conduct due diligence before deploying the Model Materials and to take reasonable steps to mitigate any known biases in its training data or applications.
+
+5.2   Privacy Protection.
+        (a) Sensitive‑Data Restrictions. It is prohibited to use the Model Materials to process,or extract infer sensitive personal data protected under specific laws (such as GDPR or HIPAA), particularly when dealing with documents containing personally identifiable information (such as ID numbers, health data, financial information, etc.), unless Licensee has obtained all necessary consents, lawful basis, or authorizations, and has implemented adequate anonymization, pseudonymization, or other privacy-enhancing technologies.
+        (b) Data Minimization and Purpose Limitation. The Licensee shall follow the principle of data minimization when using the OCR Model, processing only the user data necessary for specific, explicit, and lawful purposes. Specifically, the OCR Model should avoid processing unnecessary sensitive data and ensure compliance with applicable privacy protection laws during data handling.
+        (c) Transparency. Licensee shall provide clear and transparent privacy policies and terms of use when processing user data, particularly during document scanning and information extraction. . 
+
+5.3   Security Measures. Licensee shall implement appropriate technical and administrative safeguards to protect the Model Materials and any associated data against unauthorized access, disclosure, alteration, or destruction. Such measures may include, but are not limited to, encryption, access controls, logging, and audit trails.
+
+5.4   Further Training. Licensee may only use user‑provided input or Outputs for training, fine-tuning, or improving other AI models if it has obtained the specific and informed consent of data subjects.
+
+6. Disclaimer of Warranty and Limitation of Liability
+
+6.1 “AS IS” Basis. Unless required by applicable law, the Model Materials are provided on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. Licensee is solely responsible for determining the appropriateness of using or redistributing the Model Materials and assume any risks associated with the exercise of permissions under this License. Licensor does not provide any warranty of non-infringement but represents that no infringing code has been knowingly included.
+
+6.2   Outputs Disclaimer. As a neutral technology, Licensor disclaims all liability for the accuracy, completeness, reliability, safety, legality, or suitability of any Outputs. The Licensee is solely responsible for verifying the accuracy and appropriateness of AI-generated content and shall provide appropriate disclosures when publishing or relying upon such content.
+
+6.3   Limitation of Liability and Recourse. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, shall Licensor or contributors be liable for any claims, damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Model Materials (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Licensor has been advised of the possibility of such damages. If such losses are incurred, recourse may be sought against the Licensee responsible for causing the loss.
+
+6.4   Content‑Filtering Disclaimer. Although the Model Materials may include content‑filtering mechanisms, Licensor makes no warranties of any kind regarding the stability, quality, accuracy, completeness, or any specific outcome of Outputs. Licensee is solely responsible for reviewing, verifying, and performing quality control on Outputs and assumes all associated risks and liabilities.
+
+7. Attribution and License Reservation
+
+7.1   License. When distributing or redistributing the Model Materials, Licensee must give any other recipients of the Model Materials a copy of this Agreement.
+
+7.2   Copyright and Notices. When distributing any part of the Model Materials, Licensee must retain all copyright, patent, trademark, and attribution notices included in the Model Materials.
+
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+
+8. Governing Law and Dispute Resolution
+
+8.1   Governing Law. This Agreement shall be governed by and construed in accordance with the laws of the People’s Republic of China, without regard to its conflict of laws principles.
+
+8.2   Dispute Resolution. Any dispute claim, or disagreement arising out of or relating to this Agreement shall first be resolved through amicable consultation. If such consultation fails, the dispute shall be submitted to the Hangzhou Arbitration Commission for arbitration. The arbitration shall be conducted in accordance with the laws of China, and the place of arbitration shall be [Hangzhou, China]. The arbitral award shall be final and binding upon both parties.
+
+9. Regulatory Compliance Amendments
+In the event that any part of this Agreement becomes invalid or requires adjustment due to changes in applicable laws or regulations, Licensor reserves the right to issue a revised version of this Agreement. Licensee shall migrate to the new version within [e.g., ninety (90)] days of its release; otherwise, all rights granted under this Agreement shall automatically terminate.
+
+10. Security Reporting
+Licensee discovering any security vulnerability in the Model Materials may report it to Licensor via: dots-feedback@xiaohongshu.com. Licensee shall not disclose vulnerability details until Licensor issues an official remediation, unless otherwise required by law.

dots_ocr/parser.py

@@ -31,6 +31,7 @@ class DotsOCRParser:
             output_dir="./output", 
             min_pixels=None,
             max_pixels=None,
+            use_hf=False,
         ):
         self.dpi = dpi
 
@@ -46,9 +47,72 @@ class DotsOCRParser:
         self.output_dir = output_dir
         self.min_pixels = min_pixels
         self.max_pixels = max_pixels
+
+        self.use_hf = use_hf
+        if self.use_hf:
+            self._load_hf_model()
+            print(f"use hf model, num_thread will be set to 1")
+        else:
+            print(f"use vllm model, num_thread will be set to {self.num_thread}")
         assert self.min_pixels is None or self.min_pixels >= MIN_PIXELS
         assert self.max_pixels is None or self.max_pixels <= MAX_PIXELS
 
+    def _load_hf_model(self):
+        import torch
+        from transformers import AutoModelForCausalLM, AutoProcessor, AutoTokenizer
+        from qwen_vl_utils import process_vision_info
+
+        model_path = "./weights/DotsOCR"
+        self.model = AutoModelForCausalLM.from_pretrained(
+            model_path,
+            attn_implementation="flash_attention_2",
+            torch_dtype=torch.bfloat16,
+            device_map="auto",
+            trust_remote_code=True
+        )
+        self.processor = AutoProcessor.from_pretrained(model_path,  trust_remote_code=True,use_fast=True)
+        self.process_vision_info = process_vision_info
+
+    def _inference_with_hf(self, image, prompt):
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "image",
+                        "image": image
+                    },
+                    {"type": "text", "text": prompt}
+                ]
+            }
+        ]
+
+        # Preparation for inference
+        text = self.processor.apply_chat_template(
+            messages, 
+            tokenize=False, 
+            add_generation_prompt=True
+        )
+        image_inputs, video_inputs = self.process_vision_info(messages)
+        inputs = self.processor(
+            text=[text],
+            images=image_inputs,
+            videos=video_inputs,
+            padding=True,
+            return_tensors="pt",
+        )
+
+        inputs = inputs.to("cuda")
+
+        # Inference: Generation of the output
+        generated_ids = self.model.generate(**inputs, max_new_tokens=24000)
+        generated_ids_trimmed = [
+            out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
+        ]
+        response = self.processor.batch_decode(
+            generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
+        )[0]
+        return response
 
     def _inference_with_vllm(self, image, prompt):
         response = inference_with_vllm(
@@ -98,7 +162,10 @@ class DotsOCRParser:
             image = fetch_image(origin_image, min_pixels=min_pixels, max_pixels=max_pixels)
         input_height, input_width = smart_resize(image.height, image.width)
         prompt = self.get_prompt(prompt_mode, bbox, origin_image, image, min_pixels=min_pixels, max_pixels=max_pixels)
-        response = self._inference_with_vllm(image, prompt)
+        if self.use_hf:
+            response = self._inference_with_hf(image, prompt)
+        else:
+            response = self._inference_with_vllm(image, prompt)
         result = {'page_no': page_idx,
             "input_height": input_height,
             "input_width": input_width
@@ -116,7 +183,7 @@ class DotsOCRParser:
                 )
             if filtered and prompt_mode != 'prompt_layout_only_en':  # model output json failed, use filtered process
                 json_file_path = os.path.join(save_dir, f"{save_name}.json")
-                with open(json_file_path, 'w') as w:
+                with open(json_file_path, 'w', encoding="utf-8") as w:
                     json.dump(response, w, ensure_ascii=False)
 
                 image_layout_path = os.path.join(save_dir, f"{save_name}.jpg")
@@ -143,7 +210,7 @@ class DotsOCRParser:
                     image_with_layout = origin_image
 
                 json_file_path = os.path.join(save_dir, f"{save_name}.json")
-                with open(json_file_path, 'w') as w:
+                with open(json_file_path, 'w', encoding="utf-8") as w:
                     json.dump(cells, w, ensure_ascii=False)
 
                 image_layout_path = os.path.join(save_dir, f"{save_name}.jpg")
@@ -206,7 +273,10 @@ class DotsOCRParser:
         def _execute_task(task_args):
             return self._parse_single_image(**task_args)
 
-        num_thread = min(total_pages, self.num_thread)
+        if self.use_hf:
+            num_thread =  1
+        else:
+            num_thread = min(total_pages, self.num_thread)
         print(f"Parsing PDF with {total_pages} pages using {num_thread} threads...")
 
         results = []
@@ -242,7 +312,7 @@ class DotsOCRParser:
             raise ValueError(f"file extension {file_ext} not supported, supported extensions are {image_extensions} and pdf")
         
         print(f"Parsing finished, results saving to {save_dir}")
-        with open(os.path.join(output_dir, os.path.basename(filename)+'.jsonl'), 'w') as w:
+        with open(os.path.join(output_dir, os.path.basename(filename)+'.jsonl'), 'w', encoding="utf-8") as w:
             for result in results:
                 w.write(json.dumps(result, ensure_ascii=False) + '\n')
 
@@ -309,10 +379,10 @@ def main():
         "--num_thread", type=int, default=16,
         help=""
     )
-    # parser.add_argument(
-    #     "--fitz_preprocess", type=bool, default=False,
-    #     help="False will use tikz dpi upsample pipeline, good for images which has been render with low dpi, but maybe result in higher computational costs"
-    # )
+    parser.add_argument(
+        "--no_fitz_preprocess", action='store_true',
+        help="False will use tikz dpi upsample pipeline, good for images which has been render with low dpi, but maybe result in higher computational costs"
+    )
     parser.add_argument(
         "--min_pixels", type=int, default=None,
         help=""
@@ -321,6 +391,10 @@ def main():
         "--max_pixels", type=int, default=None,
         help=""
     )
+    parser.add_argument(
+        "--use_hf", type=bool, default=False,
+        help=""
+    )
     args = parser.parse_args()
 
     dots_ocr_parser = DotsOCRParser(
@@ -335,15 +409,20 @@ def main():
         output_dir=args.output, 
         min_pixels=args.min_pixels,
         max_pixels=args.max_pixels,
+        use_hf=args.use_hf,
     )
 
+    fitz_preprocess = not args.no_fitz_preprocess
+    if fitz_preprocess:
+        print(f"Using fitz preprocess for image input, check the change of the image pixels")
     result = dots_ocr_parser.parse_file(
         args.input_path, 
         prompt_mode=args.prompt,
         bbox=args.bbox,
+        fitz_preprocess=fitz_preprocess,
         )
     
 
 
 if __name__ == "__main__":
-    main()
+    main()

dots_ocr/utils/format_transformer.py

@@ -136,7 +136,8 @@ def clean_text(text: str) -> str:
     text = text.strip()
     
     # Replace multiple consecutive whitespace characters with a single space
-    text = re.sub(r'\s+', ' ', text)
+    if text[:2] == '`$' and text[-2:] == '$`':
+        text = text[1:-1]
     
     return text
 

dots_ocr/utils/image_utils.py

@@ -68,7 +68,7 @@ def PILimage_to_base64(image, format='PNG'):
     buffered = BytesIO()
     image.save(buffered, format=format)
     base64_str = base64.b64encode(buffered.getvalue()).decode('utf-8')
-    return f"data:image;base64,{base64_str}"
+    return f"data:image/{format.lower()};base64,{base64_str}"
 
 
 def to_rgb(pil_image: Image.Image) -> Image.Image: