Enhance syllabus generator with hybrid model and improved prompts #183
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Thank you for contributing it ran well, no issues. |
AaronSosaRamos
suggested changes
Mar 9, 2025
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Good approach. Although I suggest to use Pydantic Schemas to guarantee deterministic results with a given structure. This enhances responses based in few-shot prompting.
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Hey @melisasvr, don't forget to pull the latest changes from Develop to your branch. Thank you! |
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This PR enhances the syllabus generator feature by:
tools.pywith sequential chaining (Course Information → Learning Outcomes → Course Content → Assessment Criteria → Course Schedule) and parallel processing (Learning Resources, Policies & Procedures).tools.pyfor better clarity, consistency, and structured content generation.schemas.pyto includeunit_time,unit_time_value, andstart_datefields.core.pyto pass new fields to the syllabus generator.test_core.pywith tests for new sections (e.g.,learning_outcomes,assessment_criteria) and dependencies.Notes:
test_core.pymay require a Google API key forGoogleGenerativeAIto run successfully. Please advise on how to configure this (e.g.,.envsetup).sandboxorDevelopis the correct base branch.