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This is the proposal to start integrating th document conversion system Deepsearch from IBM Research and InstructLab Co-authored-by: Ming Zhao <mingzhao@ibm.com> Co-authored-by: BJ Hargrave <hargrave@us.ibm.com> Signed-off-by: JJ Asghar <awesome@ibm.com>
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Jul 4, 2024
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| # DeepSearch + InstructLab Integration Proposal | ||
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| <https://github.com/DS4SD> |
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Moved below where DeepSearch is first mentioned
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| Managing submissions for the open-source InstructLab project has revealed a significant bottleneck in processing | ||
| knowledge documents. For the InstructLab backend to effectively utilize these documents, they must be in markdown | ||
| format. Currently, we only accept Wikipedia articles, but the built-in conversion tool is inadequate. Internally at | ||
| IBM, and other companies, many knowledge submissions are in multiple document formats, including PDF format, | ||
| necessitating conversion to markdown before being used in InstructLab. |
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| Managing submissions for the open-source InstructLab project has revealed a significant bottleneck in processing | |
| knowledge documents. For the InstructLab backend to effectively utilize these documents, they must be in markdown | |
| format. Currently, we only accept Wikipedia articles, but the built-in conversion tool is inadequate. Internally at | |
| IBM, and other companies, many knowledge submissions are in multiple document formats, including PDF format, | |
| necessitating conversion to markdown before being used in InstructLab. | |
| Managing taxonomy submissions in InstructLab has revealed an issue in processing knowledge documents. For the InstructLab to handle these documents, they must be in [markdown](https://en.wikipedia.org/wiki/Markdown) format. However, many knowledge submissions are in multiple document formats, including PDF, which necessitating conversion to markdown before being used by InstructLab. |
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| Existing open-source methods, such as PanDoc, are inconsistent. While they preserve text, they struggle with parsing | ||
| tables and special symbols, as evidenced by issues in PR #1154 of the taxonomy repo in the InstructLab project. Other | ||
| open-source solutions have similar shortcomings. |
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| Existing open-source methods, such as PanDoc, are inconsistent. While they preserve text, they struggle with parsing | |
| tables and special symbols, as evidenced by issues in PR #1154 of the taxonomy repo in the InstructLab project. Other | |
| open-source solutions have similar shortcomings. | |
| Existing open source tools, such as [Pandoc](https://pandoc.org/), are inconsistent. While they preserve text, they struggle with parsing tables and special symbols, as evidenced by issues in [PR #1154](https://github.com/instructlab/taxonomy/pull/1154) of the taxonomy repo in the InstructLab. Other open-source solutions have similar shortcomings. |
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| IBM's DeepSearch software excels in document conversion, outperforming traditional open-source methods. Utilizing a | ||
| computer vision model layer, it accurately parses content in the files, including titles, headers, and tables. | ||
| Additionally, it automatically implements RAG layers for models, which could benefit the InstructLab process in | ||
| the future. |
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| IBM's DeepSearch software excels in document conversion, outperforming traditional open-source methods. Utilizing a | |
| computer vision model layer, it accurately parses content in the files, including titles, headers, and tables. | |
| Additionally, it automatically implements RAG layers for models, which could benefit the InstructLab process in | |
| the future. | |
| IBM's [DeepSearch](https://github.com/DS4SD) software excels in document conversion, outperforming traditional open source methods. Utilizing a computer vision model layer, it accurately parses content in the files, including titles, headers, and tables. Additionally, it automatically implements RAG layers for models, which could benefit the InstructLab process in the future. |
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| # DeepSearch + InstructLab Integration Proposal | |||
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| # DeepSearch + InstructLab Integration Proposal | |
| # Document Conversion Proposal |
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| ### Open-Source Conversion | ||
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| - Implement a basic document conversion tool in the UI using an open-source method such as PanDoc. This tool will be | ||
| lightweight and easily hosted, ensuring it can be used and improved by the community. |
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| ### Open-Source Conversion | |
| - Implement a basic document conversion tool in the UI using an open-source method such as PanDoc. This tool will be | |
| lightweight and easily hosted, ensuring it can be used and improved by the community. | |
| - Open source conversion: Implement a basic document conversion tool in the InstructLab UI using an open source tool such as [Pandoc](https://pandoc.org/). This tool will be lightweight and easily hosted, ensuring it can be used and improved by the community. |
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| ### DeepSearch Integration | ||
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| - Enable the UI to switch the conversion endpoint to DeepSearch, allowing high-fidelity markdown conversions for | ||
| backend use. This approach maintains an open-source version while benefiting from DeepSearch's superior | ||
| conversion capabilities. |
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| ### DeepSearch Integration | |
| - Enable the UI to switch the conversion endpoint to DeepSearch, allowing high-fidelity markdown conversions for | |
| backend use. This approach maintains an open-source version while benefiting from DeepSearch's superior | |
| conversion capabilities. | |
| - [DeepSearch](https://github.com/DS4SD) conversion: Enable the InstructLab UI to switch the conversion endpoint to DeepSearch, allowing high-fidelity markdown conversions for backend use. This approach uses the open source version of Deepsearch while benefiting from DeepSearch's superior conversion capabilities. |
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| IBM Research and the DeepSearch team will host the DeepSearch endpoint for the open-source community. This | ||
| arrangement benefits the community by streamlining contributions and provides data and exposure for the DeepSearch | ||
| project. IBM's contribution underscores its commitment to supporting and improving open-source projects. |
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| IBM Research and the DeepSearch team will host the DeepSearch endpoint for the open-source community. This | |
| arrangement benefits the community by streamlining contributions and provides data and exposure for the DeepSearch | |
| project. IBM's contribution underscores its commitment to supporting and improving open-source projects. | |
| IBM Research and the DeepSearch team will host the DeepSearch endpoint for the InstructLab community. This | |
| arrangement benefits the community by providing a means to handle different document formats. |
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| This integration will highlight the value of DeepSearch, highlighting their potential for those integrating | ||
| InstructLab into their workflows. If the volume of community requests becomes unsustainable for the DeepSearch team, | ||
| we hope for ample notification to allow the community to find alternative solutions. By then, we anticipate that the | ||
| open-source versions will have improved sufficiently, or the value of the integration will justify continued support. |
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| This integration will highlight the value of DeepSearch, highlighting their potential for those integrating | |
| InstructLab into their workflows. If the volume of community requests becomes unsustainable for the DeepSearch team, | |
| we hope for ample notification to allow the community to find alternative solutions. By then, we anticipate that the | |
| open-source versions will have improved sufficiently, or the value of the integration will justify continued support. | |
| If the volume of community requests becomes unsustainable for the DeepSearch team to manage, we hope for ample notification to allow the community to find alternative solutions. By then, we anticipate that the open source conversion tools will have improved sufficiently, or the value of the integration will justify continued support. |
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| By adopting this two-pronged approach, we ensure the integrity of the open-source project while leveraging IBM's | ||
| advanced DeepSearch capabilities. This strategy balances community collaboration with innovative technology, | ||
| fostering innovation and improvement in document processing for the InstructLab project. |
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| By adopting this two-pronged approach, we ensure the integrity of the open-source project while leveraging IBM's | |
| advanced DeepSearch capabilities. This strategy balances community collaboration with innovative technology, | |
| fostering innovation and improvement in document processing for the InstructLab project. | |
| By adopting this two-pronged approach, we ensure the integrity of the open source project while leveraging advanced DeepSearch capabilities. This strategy balances community collaboration with innovative technology, | |
| fostering innovation and improvement in document processing for the InstructLab community. |
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This pull request has been automatically marked as stale because it has not had activity within 30 days. It will be automatically closed if no further activity occurs within 7 days. |
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This is the proposal to start integrating th document conversion system Deepsearch from IBM Research and InstructLab