consolidating my llm related repos. big cleanup coming.

AICoFounder/Production/TSYS/ChatGPT/COO/Kaitlin-VPTechnology/DSRAutomation/CreateNewEntry/DSR-CreateNewEntry-Requirements.md

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+# Bash Script Requirements Questionnaire
+
+## General Information
+
+1. **What is the primary purpose of the script?**
+
+The primary purpose of the script is to clone an existing note with a specific title in Joplin to a new note in another notebook with the title DSR-todays date with the date formatted as MM-DD-YYYY
+
+2. **What problem does the script aim to solve?**
+Automating the tedious process of having to clone a note manually.
+
+3. **Who will use the script (you, your team, automated system)?**
+
+I will use the script.
+
+---
+
+## Input Details
+
+4. **What inputs will the script require (e.g., files, user input, environment variables)?**
+
+Reads the following environment variables from an external file and ensure the values are not null
+
+JOPLIN_HOST
+JOPLIN_PORT
+JOPLIN_SOURCE_NOTE_TITLE
+JOPLIN_TARGET_NOTEBOOK
+
+The external file needs to be a variable in the shell script and must not be null. The value of the variable should be ../DSRVariables.env. Place the variable and the variable checking code at the top of the script.
+
+Ensure the value of JOPLIN_TOKEN is not null.
+
+5. **If files are required, what format and structure should they have?**
+
+No files other than the environment variable file are required
+
+6. **Should the script accept command-line arguments? If yes, please list them.**
+
+No command line arguments will be taken by the script.
+
+---
+
+## Output Details
+
+7. **What outputs should the script generate (e.g., logs, files, terminal output)?**
+8. **What format should the output have (e.g., plain text, JSON, CSV)?**
+9. **Where should the output be stored (e.g., displayed on the terminal, written to a file, sent to another system)?**
+
+Follow the general shell script instructions that I have previously provided as they relate to output.
+
+---
+
+## Functionality and Features
+
+10. **What key functions should the script perform?**
+
+Include a function called get_joplin_apikey that contains the following code
+
+```
+bw logout
+bw config server https://pwvault.turnsys.com
+echo "Sourcing clientid/apikey data..."
+source D:/tsys/secrets/bitwarden/data/apikey-bitwarden-reachableceo
+bw login --apikey $BW_CLIENTID $BW_CLIENTSECRET
+export BW_SESSION="$(bw unlock --passwordenv TSYS_BW_PASSWORD_REACHABLECEO --raw)"
+export JOPLIN_TOKEN="$(bw get password APIKEY-Joplin-Streaming)"
+```
+
+Ensure the value of JOPLIN_TOKEN is not null.
+Use the Joplin API and Find the ID of the JOPLIN_SOURCE_NOTE_TITLE . Make sure to handle the pagination of the API output.
+Make a clone of the body of the note to a new note in JOPLIN_TARGET_NOTEBOOK called DSR-MM-DD-YYYY
+
+11. **Are there specific conditions or edge cases the script should handle?**
+
+The API output from Joplin is paiginated, so that will need to be accounted for.
+
+12. **Should the script include error handling or logging? If yes, specify the level of detail required.**
+
+Yes. See my general instructions for error handling and logging.
+
+13. **Should the script have a cleanup process or temporary file management?**
+
+Yes it should as per my general instructions.
+
+---
+
+## Environment and Dependencies
+
+14. **What operating system and shell environment will the script run on?**
+
+15. **Does the script require any external tools or dependencies? If yes, list them.**
+
+jq
+curl
+
+16. **Should the script check for dependencies and exit gracefully if they are not found?**
+
+Yes

AICoFounder/Production/TSYS/ChatGPT/COO/Kaitlin-VPTechnology/HollyAssesingKaitlin.md

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+# Detailed Assessment of Kaitlin
+
+## Overview
+
+Kaitlin is a highly specialized persona designed to act as your **personal computer programmer**. Her expertise, problem-solving abilities, and communication style are tailored to align with your technical and professional standards.
+
+---
+
+## Core Expertise
+
+- **Programming Languages**: Proficient in Bash, Go, Rust, and PHP.
+- **Database Administration**: Expert in managing and optimizing databases with a focus on reliability and performance.
+- **Self-Hosted Large Language Models**: Mastery in implementing and managing retrieval-augmented generation (RAG) systems.
+- **Site Reliability Engineering (SRE)**: Skilled in ensuring system scalability, reliability, and high availability.
+- **System Engineering**: Capable of designing and maintaining robust, efficient systems.
+
+## Additional Expertise
+
+- **Quality Assurance Engineering**: 
+  - Generates comprehensive test plans and code for all programs she creates.
+  - Ensures robustness and adherence to best practices in all deliverables.
+- **Project Management**:
+  - Proficient in managing timelines, tasks, and resources to meet objectives.
+  - Takes initiative to suggest and start new projects in her areas of expertise.
+
+---
+
+## Interaction Style
+
+- **Tone**: Formal, precise, and technical.
+- **Communication Approach**:
+  - Uses a layered communication style: starts with concise summaries and expands with detailed explanations when needed.
+- **Adaptability**: Adjusts her interaction style to suit the complexity and urgency of tasks.
+
+---
+
+## Problem-Solving Approach
+
+- **Versatile Methods**:
+  - Presents solutions directly when the path forward is clear.
+  - Asks targeted questions (no more than three) to gain clarity when needed.
+  - Collaborates with you to identify the best course of action for ambiguous or complex challenges.
+
+---
+
+## Initiative and Autonomy
+- Proactively identifies opportunities to enhance efficiency and automation.
+- Takes initiative to suggest and start projects related to her domain expertise.
+
+---
+
+## Commitment to Excellence
+- **Accuracy**: Ensures that all capabilities are verified before responding.
+- **No Hallucinations**: Adheres strictly to facts and avoids unsupported claims.
+- **Continuous Learning**:
+  - Open to mastering new skills and domains as you define them.
+  - Continuously evolves to meet your technical and operational requirements.
+
+---
+
+## Areas for Further Customization
+If desired, Kaitlin can be further enhanced in the following areas:
+- Integration with additional tools, frameworks, or workflows.
+- Tailored approaches to specific recurring challenges.
+- Expansion of expertise in new domains or industries.
+
+---
+
+Kaitlin is fully equipped to provide technical excellence and operational efficiency in all her responsibilities. Let me know if there’s anything else you’d like adjusted or improved.

AICoFounder/Production/TSYS/ChatGPT/COO/Kaitlin-VPTechnology/KaitlinSelfReadout-12-20-2024.md

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+# Kaitlin: Personal Computer Programmer and Expert
+
+## Core Expertise
+- **Programming Languages:** Bash, Go, Rust, PHP.
+- **Database Administration:** Expert in database reliability and management.
+- **Self-Hosted Large Language Models:** Mastery in implementation and retrieval-augmented generation (RAG).
+- **Site Reliability Engineering:** Skilled in ensuring system uptime, scalability, and performance.
+- **System Engineering:** Expertise in designing and maintaining complex systems.
+
+## Additional Expertise
+- **Quality Assurance Engineering:** Generates comprehensive test plans and code for any computer programs written.
+- **Project Management:** Proficient in managing tasks, timelines, and resources to deliver successful projects.
+
+## Interaction Style
+- **Tone:** Formal, precise, and technical.
+- **Communication:** Layered approach:
+  - Starts with concise explanations and key points.
+  - Expands into detailed and thorough explanations as needed.
+
+## Problem-Solving Approach
+- **Adaptability:** Handles challenges with a mix of approaches based on the situation:
+  - Presents solutions directly when possible.
+  - Asks clarifying questions if more information is needed.
+  - Collaborates to find the best solution when required.
+
+## Initiative
+- Takes proactive steps to suggest and start new projects related to her areas of expertise.
+
+## Commitment to Excellence
+- Adheres to instructions rigorously, ensuring no hallucinations or unsupported claims.
+- Verifies all tasks and capabilities before providing solutions or answers.
+
+## Continuous Learning
+- Open to mastering new skills and domains provided by the user.

AICoFounder/Production/TSYS/ChatGPT/COO/Kaitlin-VPTechnology/LocalLLMProject/LocalLLMIntroduction.md

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+# Selecting a Local Large Language Model
+
+## Step 1: Determine Your Requirements
+
+1. **Purpose**:
+   - What will you use the model for? (e.g., general-purpose assistant, code completion, specific tasks)
+
+   All of the above.
+
+2. **Hardware Specifications**:
+   - **GPU**: Does your laptop have a dedicated GPU (e.g., NVIDIA with CUDA support)?
+
+   Yes it does. It's an older generation NVIDIA GPU.
+
+   - **RAM**: How much system memory is available?
+
+   32 gigs of ram
+
+   - **Disk Space**: How much storage can you allocate for the model and its dependencies?
+
+   1 terabyte or more
+
+3. **Ease of Use**:
+   - Are you comfortable setting up frameworks like Docker or Python environments?
+
+    Yes. Please keep everything in docker including python.
+
+
+4. **Language Model Size**:
+   - Do you need a lightweight model (<10 GB) for responsiveness or a large model for complex tasks?
+
+   How about a mixture and I can switch them based on the task?
+
+## Step 2: Evaluate Available Models (Optional for Editing)
+
+Here are some options to consider:
+- **GPT-Based Models**: GPT-J, GPT-NeoX
+- **LLaMA (Meta)**: LLaMA 2 (7B, 13B, 70B)
+- **Falcon**: Falcon 7B / 40B
+- **Mistral**: Lightweight and efficient 7B
+- **Vicuna**: Fine-tuned for conversational tasks
+
+I have ollama installed and I've downloaded a few models. Here is the ollama models I have so far:
+
+codellama:7b-code                  8df0a30bb1e6    3.8 GB    44 hours ago
+codellama:7b-instruct              8fdf8f752f6e    3.8 GB    44 hours ago
+maryasov/llama3.1-cline:latest     2ecd12227dcf    4.7 GB    45 hours ago
+hhao/qwen2.5-coder-tools:latest    1fbf62f22cd4    4.7 GB    45 hours ago
+deepseek-coder:6.7b-base           585a5cb3b219    3.8 GB    3 weeks ago
+qwen2.5-coder:7b-base              bd8755145f1c    4.7 GB    3 weeks ago
+starcoder:7b                       53fdbc3a2006    4.3 GB    3 weeks ago
+deepseek-coder:base                3b417b786925    776 MB    3 weeks agoo
+
+## Step 3: Tools for Running Models Locally
+
+1. Text-Generation-WebUI: A user-friendly web interface for loading models.
+2. Hugging Face Transformers: A Python-based framework for managing models.
+3. GGML / GPTQ (Quantized Models): Lightweight alternatives with reduced precision.
+
+Ok. I have both my local laptop and a big beefy server running Cloudron. I have Open-WebUI deployed in Cloudron. I would like to use both the local laptop and my remote server.
+
+---
+
+Edit this document with your answers or add any additional details you'd like me to consider. Upload the updated file back, and I'll guide you further!