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likelovewant
2024-12-12 13:17:55 +08:00
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examples/python-grounded-factuality-rag-check/README.md
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# RAG Hallucination Checker using Bespoke-Minicheck
This example allows the user to ask questions related to a document, which can be specified via an article url. Relevant chunks are retreived from the document and given to `llama3.2` as context to answer the question. Then each sentence in the answer is checked against the retrieved chunks using `bespoke-minicheck` to ensure that the answer does not contain hallucinations.
This example allows the user to ask questions related to a document, which can be specified via an article url. Relevant chunks are retrieved from the document and given to `llama3.2` as context to answer the question. Then each sentence in the answer is checked against the retrieved chunks using `bespoke-minicheck` to ensure that the answer does not contain hallucinations.
## Running the Example

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examples/python-grounded-factuality-rag-check/main.py
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print(f"\nRetrieved chunks: \n{sourcetext}\n")
# Give the retreived chunks and question to the chat model
# Give the retrieved chunks and question to the chat model
system_prompt = f"Only use the following information to answer the question. Do not use anything else: {sourcetext}"
ollama_response = ollama.generate(