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Q&A chat bot basics with LLMs: Catch-up edition

Chain-of-Thought? Retrieval Augmented Generation? Vector embedding? Hallucination? Help!

The constant influx of tech and terms caught you off-guard. Let’s catch you up shall we?

OpenAI Chat Completion API

Send the entire chat history on every loop. Assign roles to each message. Get the generated text (API response) and use that as bot response.

Semantic Similarity

Preprocess text into tokens, then encode them into embeddings (numerical vector representation) so machines can capture their semantic properties. This enables easy comparison of tokens based on their semantic similarity.

# Source - https://www.sbert.net/docs/quickstart.html

from sentence_transformers import SentenceTransformer, util
model = SentenceTransformer('all-MiniLM-L6-v2')

sentences = ['A man is eating food.',
          'A man is eating a piece of bread.',
          'The girl is carrying a baby.',
          'A man is…