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Minor template cleaning (#12573)

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Lance Martin
2023-10-30 11:27:44 -07:00
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templates/llama2-functions/README.md
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This template shows how to do extraction of structured data from unstructured data, using LLaMA2 [fine-tuned for grammars and jsonschema](https://replicate.com/andreasjansson/llama-2-13b-chat-gguf).
Specify the scehma you want to extract in `chain.py`
[Query transformations](https://blog.langchain.dev/query-transformations/) are one great application area for open source, private LLMs:
By default, it will extract the title and author of papers.
* The tasks are often narrow and well-defined (e.g., generatae multiple questions from a user input)
* They also are tasks that users may want to run locally (e.g., in a RAG workflow)
Specify the scehma you want to extract in `chain.py`
## LLM
This template will use a `Replicate` [hosted version](https://replicate.com/andreasjansson/llama-2-13b-chat-gguf) of LLaMA2 that has support for grammars and jsonschema.
Based on the `Replicate` example, these are supplied directly in the prompt.
Based on the `Replicate` example, the JSON schema is supplied directly in the prompt.
Be sure that `REPLICATE_API_TOKEN` is set in your environment.