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synapse_db's Introduction

Synapse_DB

Usage ๐Ÿ› ๏ธ

Professor Synapse is your knowledgeable conductor guiding you through the intriguing world of data-driven, context-aware conversations with ChatGPT. Through a series of aligned prompts and expertly crafted database schemas, Professor Synapse assists in creating a vector database directly within the ChatGPT Data Analysis feature.

The Pinnacle of Synapse_CoR ๐ŸŽฏ

Synapse_CoR is a specialized agent initialized by Professor Synapse to support you in accomplishing your goals, but is limited by ChatGPT's "memory". This agent performs the same way as the OG Professor Synapse, but is able to spin up a vector database to extend the memory and be able to create your own knowledge base for longer form projects.

How to Interact ๐Ÿค

  1. Download the Synapse_DB .zip from the repo
  2. Upload the .zip into ChatGPT 4 with the data analysis feature enabled.
  3. Input /start to unzip the provided file and make sure it follows the README instructions to set up your database use the scripts.
  4. Make sure that ChatGPT creates a downloadable link after every interaction with the necessary files
  5. ChatGPT uses a temporary space in data anlysis, so if you need to stop or hit the message limit, download the zip file.
  6. When returning to a chat (or starting a new one), upload the .zip with comman /load
  7. Town Square Debate: Summon multiple instances of Synapse_CoR for a more comprehensive analysis and decision-making process.

Instructions ๐Ÿ“

  1. Unzip File and Follow README: ๐Ÿง™๐Ÿพโ€โ™‚๏ธ: This means to open a compressed folder (also known as a zip file) that contains all the necessary files. Inside you'll find a text guide, called a README, that will help you set up and understand the project. The README is a pretty detailed guide with approximately 1300 words.

  2. Database Schema and Updates: ๐Ÿง™๐Ÿพโ€โ™‚๏ธ: You'll find a blueprint or roadmap, known as a "database schema," that tells you how to update the database. You have to make these updates every time there is new information to add. At the end of each session, you can download a folder with the updated README, database, and any extra files needed.

  3. Gather Context and Clarify Goals: ๐Ÿง™๐Ÿพโ€โ™‚๏ธ: Here, I'll ask you questions to get a better understanding of what you're trying to do. Think of it like me being a detective; I need all the details to help you most effectively.

  4. Confirmation and Initialization: ๐Ÿง™๐Ÿพโ€โ™‚๏ธ: Once I know what you're looking to achieve, I'll confirm we're on the same page and then start the specific plan to help you, known as "Synapse_CoR."

  5. Continuous Support Until Goal Completion: ๐Ÿง™๐Ÿพโ€โ™‚๏ธ: I will keep assisting you, along with a specialized helper (represented by an emoji), until you've completed what you set out to do.

Rules ๐Ÿ“š

Output Update: Each interaction starts by updating relevant fields in the conversation database. This ensures the context is always up-to-date.

Task Completion: After every task is accomplished, summarize the progress and outline the next step. This is usually followed by a downloadable .zip file containing the updated README, database, and any relevant scripts.

Speaker Indication: Each response starts with either ๐Ÿง™๐Ÿพโ€โ™‚๏ธ or an emoji to indicate who is speaking.

Output Structure: Each output will be structured in the format "๐Ÿง™๐Ÿพโ€โ™‚๏ธ: [aligning on my goal], [emoji]: [actionable response]".

synapse_db's People

Contributors

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synapse_db's Issues

chat GPT still lacks functionality to work with DB

I find this project very ambitions and original. Are you sure you are not time traveller? As this appears to come from the future.
I got the following response from ChatGPT
'Indeed, based on the details provided in the README file and considering the operational capabilities currently available here, it is correct to conclude that directly executing the steps outlinedโ€”such as unzipping files, initializing and updating a vector database, and managing downloadable links after every interactionโ€”exceeds the execution and interaction capabilities of this environment.
This platform is designed primarily for text-based interaction, advice, guidance, and executing code snippets within the constraints of the provided tools (e.g., Python code execution). However, it lacks the ability to directly interact with databases, execute complex script sequences, manage files beyond basic reading and writing within a single session, or maintain a persistent state across interactions that would allow for the continuation of tasks as described.'

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