InstructLab and Deepsearch

docs/instructlab-deepsearch-integration.md

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+# DeepSearch + InstructLab Integration Proposal
+
+<https://github.com/DS4SD>
+
+## Why is a Conversion Tool Necessary?
+
+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.
+
+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.
+
+## Why DeepSearch?
+
+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.
+
+## Integration Proposal
+
+To maintain the open-source nature of the project while leveraging the strengths of DeepSearch, we propose a
+two-pronged approach:
+
+### 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.
+
+### 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.
+
+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.
+
+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.
+
+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.