Building Your Own Bot with GPT: Harnessing the Power of AI...
summary
Shows how to build a personal chatbot using OpenAI APIs by extracting text from files (PDFMiner), audio (Whisper), and web pages, chunking content, creating embeddings and using cosine similarity to retrieve the top-K relevant chunks, then sending those to GPT-3.5 chat completions. Explains token limits (~4,096), cost (first $18 credit), t-SNE visualization demo, why per-user fine-tuning is impractical, prompt engineering tips (e.g. "let's think step by step"), temperature tuning, and a working desktop prototype.
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chapters (20)
- 0:00Introduction and motivation
- 2:59Demo of the personal bot concept
- 4:52Understanding ChatGPT’s architecture
- 6:40Why fine-tuning isn’t the solution
- 8:06Completions API basics
- 10:16Token limits and cost challenges
- 12:02Embeddings API and vector search
- 16:20Building the embedding database
- 18:08Text extraction methods
- 19:52Chunking strategies for text
- 21:39Semantic chunking explained
- 23:07Enriching chunks with context
- 24:12Prompt engineering fundamentals
- 26:20Prompt design examples
- 28:46Prompt injection risks
- 29:52Temperature and creativity control
- 31:37Five key considerations summary
- 32:19Future trends in AI bots
- 35:33Next steps and resources
- 36:36Q&A session
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