lakshyakumar / lakshyakumar/Knowledge-Base-AI
📊 Advanced Reporting
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- Dominant language
- Python
- Stars
- 0
- Forks
- 1
- PR merge metrics
- No merged PRs in 30d
Description
Description:
The current report generator provides general summaries based on scraped content and AI analysis. We want to enhance it by enabling query-driven, sectioned, and semantic report generation. Users should be able to request specific types of reports, and the system should dynamically structure the report with labeled sections (e.g., Insights, Data Points, Sentiment Analysis, Action Items).
Acceptance Criteria:
- Dynamically generate section-based reports based on user query.
- Content must be markdown formatted and user-friendly.
- Include content-specific visual elements where applicable (e.g., tables, bullet points).
- Must be reusable for various content types and queries.
📘 Note: Please read and follow the Contribution Guide before starting work on any of the tasks listed below.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Read CONTRIBUTING.md first, then locate the current report generator in the repository and trace how scraped content, AI analysis, and user queries reach it. Define how query-driven sections, markdown formatting, and content-specific tables or bullet points should work across content types; done means the acceptance criteria are met for reusable report generation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- fastapi, python
- Domain
- ai, backend
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100