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Here’s how to perform retrieval-augmented (RAG) with two new open-source Python packages I just released. I included a full article below that provides a step-by-step guide on how to build a vector database with this wikimedia/wikipedia dump and use it to perform RAG with openai/gpt-oss-20b.
FULL ARTICLE: https://www.vennify.ai/vector-eric-search/
vennify
FULL ARTICLE: https://www.vennify.ai/vector-eric-search/
pip install erictransformer ericsearchimport json
from ericsearch import EricSearch
from erictransformer import EricChat
eric_search = EricSearch()
with open("data.jsonl", "w", encoding="utf-8") as f:
sample_case = {"text": "This contains example data. It should contain at least two sentences."}
f.write(json.dumps(sample_case)+ "\n")
eric_search.train("data.jsonl")
eric_search = EricSearch(data_name="eric_search/")
eric_chat = EricChat(model_name="openai/gpt-oss-20b", eric_search=eric_search)
result = eric_chat("Tell me about artificial intelligence ")
print(result.text)