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# 2024-02-12-Project-Planning-Notes | ||
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## JSM | ||
### User Stories for SkellyBot Software | ||
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#### Nightly Tasks | ||
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- Configure cron jobs to: | ||
- Send messages to users | ||
- Extract data from a server | ||
- Process stored data | ||
- Configurable via DMs or as an embed in the server | ||
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#### Vector Store Memory | ||
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- Add vector store memory to the bot | ||
- Set context as part of chat functionality configuration | ||
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#### Data Analysis Jobs | ||
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- Analyze gathered data from the server | ||
- Summarize chats and extract tags | ||
- Attach analyses to cron jobs | ||
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#### Data-Based Messaging | ||
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- Send messages based on data from the server | ||
- Run analysis on user data and send reports | ||
- Set message duration and frequency through backend or config file system | ||
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### Developer Perspective on User Stories | ||
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#### Nightly Tasks Implementation | ||
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- Implement a cron job module in the core process | ||
- Trigger independently of any interface | ||
- Configuration through Discord | ||
- Use slash commands or message context commands | ||
- Accept configuration files in JSON or YAML format | ||
- Utilize Discord attachment handler for file loading | ||
- Cron job module to create and track jobs | ||
- Ensure triggering at correct intervals | ||
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#### Vector Store Memory Development | ||
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##### Processing Step | ||
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- Message processing through AI module for: | ||
- Tag extraction | ||
- Summarization | ||
- Vector embedding | ||
- Core database models to include: | ||
- Tags | ||
- Summaries | ||
- Embeddings | ||
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##### Database Integration | ||
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- Processing assumed to be part of database entry route | ||
- Option to trigger processing on the entire database | ||
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##### AI Data Extraction | ||
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- Extract AI data from messages upon changes | ||
- Options for reprocessing: | ||
- Immediate for each change | ||
- Incremental updates | ||
- Utilizing local models for cost efficiency | ||
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##### Retrieval Augmented Generation | ||
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- Set up retrievers as AI tools | ||
- Use large language models to: | ||
- Determine context relevance | ||
- Generate queries from inputs | ||
- Stuff retrieved data into chat context | ||
- Track metadata of extracted documents | ||
- Include sources in the response to users | ||
- Attach retrieval reports to messages in a presentable format | ||
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##### Data Analysis Jobs and Database Messaging | ||
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- Sending processed data to users, channels, or servers | ||
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###### Types of Analyses | ||
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- Volume and structure analyses: | ||
- Counting messages, characters, tokens, chats, channels, servers | ||
- Natural language processing tasks: | ||
- Summarizing chats | ||
- Extracting tags | ||
- Vector store embeddings | ||
- Running prompts for data processing | ||
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##### Summarization and Tag Extraction | ||
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- Raw summarization | ||
- Simple analysis tasks with basic prompts | ||
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##### Analyses Requiring Additional Documents | ||
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- Analyses dependent on external references | ||
- Example: Cron job sending feedback to a student based on rubric progress | ||
- Evaluate student's conversation and assignment data | ||
- Message students about their progress, plan adjustments, or action changes |
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# Development | ||
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Start typing here... |
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# Project Notes | ||
# 2023-12-31 Project Notes | ||
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## Services: | ||
### [Discord](Discord) | ||
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