https://github.com/prajwalsrinvas/learn_instructor
https://github.com/prajwalsrinvas/learn_instructor
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/prajwalsrinvas/learn_instructor
- Owner: Prajwalsrinvas
- Created: 2024-08-30T21:55:59.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-09-07T18:18:25.000Z (9 months ago)
- Last Synced: 2024-09-08T19:09:54.539Z (9 months ago)
- Language: Jupyter Notebook
- Size: 81.1 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Learn Instructor
This project explores various aspects of building LLM-based applications using the [instructor](ttps://github.com/jxnl/instructor/) library. It covers structured data extraction, synthetic data generation, classification and few usecases of agents.
## Projects
1. **Structured Data Extraction**
- [Data extraction techniques](1_structured_data_extraction/1_data_extraction.ipynb)
- [Synthetic data generation](1_structured_data_extraction/2_synthetic_data_generation.ipynb)
- [Classification tasks](1_structured_data_extraction/3_classification)
2. **Agents**
- [SERP (Search Engine Results Page) agent](2_agents/1_serp)
- [Financial analyst agent](2_agents/2_financial_analyst)
- [Knowledge graph creation](2_agents/3_knowledge_graphs)
- [Logical Reasoner](2_agents/4_logical_reasoner/logical_reasoner.ipynb)
## Resources and Documentation
- [Instructor GitHub Repository](https://github.com/jxnl/instructor/)
- [Instructor Documentation](https://python.useinstructor.com/)
- [Instructor Examples](https://python.useinstructor.com/examples/)
- [Instructor Concepts](https://python.useinstructor.com/concepts/models/)
- [Instructor Tutorials](https://python.useinstructor.com/tutorials/1-introduction/)
## Course Reference
This project is based on the Udemy course [Building LLM-based Applications Using Instructor](https://www.udemy.com/course/building-llm-based-applications-using-instructor/).