Project Scope: AI/NLP-Powered Calendar Availability Extractor
Objective:
Develop a robust AI/NLP system to extract key scheduling parameters from unstructured natural language inputs, primarily for busy professionals and businesses. The system should interpret various scheduling requests and output structured data for integration with calendar systems.
For example:
"Check my calendar for 30 minute availabilities over the next few weeks, preferably in the afternoons. make sure it aligns with Jake's calendar. Also not on Mon or Wed. Next week is best and I'm out the following."
Key Requirements:
1. Input Processing:
- Accept natural language inputs describing scheduling needs
- Handle a wide variety of phrasings and scheduling scenarios
- Process complex and potentially ambiguous requests
2. Parameter Extraction:
- Accurately extract key scheduling parameters, including but not limited to:
-- Start and end dates
-- Start and end times
-- Duration
-- Recurrence information
-- Time zone
-- Preferences (e.g., "morning meetings", "no weekends")
3. Output Format:
- Provide extracted parameters in a structured JSON format
- Include confidence scores for each extracted parameter
4. Reliability:
- Achieve very high accuracy in parameter extraction (aiming for 99.999% reliability)
- Implement robust error handling and ambiguity resolution
5. AI Integration:
- Utilize advanced AI models (such as GPT-4o or similar) for natural language understanding
- Design an effective prompt engineering strategy for optimal AI performance
6. Scalability:
- Design the system to be easily expandable for future enhancements (e.g., multi-language support, integration with specific calendar systems)
7. Documentation:
- Provide comprehensive documentation of the system architecture, AI prompt design, and any algorithms used
Technical Considerations:
- The solution should be designed with potential integration with Microsoft Graph API and Google Calendar in mind
- Choice of programming language and framework is open, but should be justified based on project requirements
Deliverables:
1. Fully functional code for the parameter extraction system
2. JSON schema for the output format
3. Documentation including system architecture, - usage instructions, and future expansion guidelines
4. Test suite demonstrating the system's reliability across various input scenarios
Timeline: 1-2 weeks
Future Considerations (not part of current scope):
- Potential for adding interactive chat capability for complex scheduling needs and error handling
- Possible expansion to support multiple languages
Proficiency / Experience Requirements:
1. 5-10+ years of software development experience, with 3+ years focused on AI/ML projects
2. Expert-level proficiency in Natural Language Processing (NLP), LLMs, AI techniques and implementation
3. Demonstrated experience with large language models (e.g., GPT-4o, Llama, etc.), prompt engineering and other specialized models (e.g., spaCy and NLTK)
4. Strong programming skills, particularly in Python, with experience in API integrations and JSON handling
5. Proven track record of designing and developing high-reliability systems (99.99%+ uptime and accuracy)
6. Experience in extracting structured data from unstructured text, including complex scheduling information
7. Familiarity with calendar systems, time zone handling, and scheduling algorithms
8. Ability to design scalable architectures and implement robust error handling
9. Proficiency in writing comprehensive test suites and optimizing system performance
10. Excellent documentation skills and ability to communicate complex technical concepts clearly
Summary:
We are looking for a freelancer with strong expertise in AI/ML, particularly in natural language processing and prompt engineering. Experience with calendar systems and scheduling logic is a plus. The ideal candidate will be able to deliver a highly reliable solution and provide insights for future enhancements.
Location: Anywhere
Posted: Aug. 26, 2024, 1:57 a.m.
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