| # Steps | |
| 1. Pre-process the knowledge base (docs) | |
| 2. Store it in a database (embeddings) | |
| 3. Inject content into GPT-3 prompt | |
| # App building specs | |
| 1. langchain - for chaining prompts | |
| 2. langflow - displays prompting with database | |
| 3. gradio - integrates with huggingface (important, to easily demo the work being done, and let people pay for the openai results) | |
| 4. pinecone (cloud vectorstore database, instead of chromadb which runs local) | |