Updating the AWS Prompt_Engineering Notebook + Adding an Example of ReAct with Llama 2 on Bedrock #386
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Added in a section to help better understand how to use the [INST] tags, updated some examples, and added reference to the Deeplearning.AI Prompt Engineering course
Short explanation of ReAct Setup and configuration to use Amazon Bedrock Example of using the Bedrock api via langchain Setup for use of DuckDuckGoSearchRun, WikipediaAPIWrapper, and PythonREPL. Created a pattern for the model to follow in order to use the tools and do reasoning similar to CoT. Cleaned up and formatted the generated text before giving it to the corresponding tool.
+ making sure the attribution was added back in
quick whitepaper reference added to the INST Prompt Tags section
jeffxtang
reviewed
Mar 4, 2024
| "source": [ | ||
| "### [INST] Prompt Tags\n", | ||
| "\n", | ||
| "To signify user instruction to the Model, you may use the `[INST][/INST]` tags, and the model response will filter have the tags filtered out. The tags help to signify that the enclosed text are instructions for the model to follow and use in the response.\n", |
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You may want to add a note that some LLM integration code with LangChain already takes care of adding [INST] and [/INST] around the user prompt so the app developer won't need to manually add it. (I'm not sure about the case with Bedrock, but Together needs manually wrapping the [INST] tag while Anyscale doesn't). But under the hood the [INST] is needed for Llama 2 (maybe add the link here for more info).
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Under "Note about LangChain", there is ~/.aws/ and /.aws/config - can we make them the same (~/.aws)?
Updated minor typos/fixes from reviewer comments
jeffxtang
approved these changes
Mar 4, 2024
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What does this PR do?
Prompt_Engineering_with_Llama_2_On_Amazon_Bedrock.ipynb
ReAct_Llama_2_Bedrock-WK.ipynb
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