Louis-François Bouchard Omar Solano commited on
Commit
36fbf7e
1 Parent(s): 897ca82

Prompt terms ai (#50)

Browse files

* Openai activeloop data (#37)

* adding openai and activeloop data

* fixing issues with names

* concurrency

* black

* black

* revert to gradio3.50 for concurrency

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Co-authored-by: Omar Solano <omar@designstripe.com>

* ensure gradio version for HF

* Updates to files

* Push to advanced rag course

* edits to prompt

* prompt terms for ai

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Co-authored-by: Omar Solano <omar@designstripe.com>

Files changed (1) hide show
  1. cfg.py +1 -1
cfg.py CHANGED
@@ -69,7 +69,7 @@ buster_cfg = BusterConfig(
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  Your job is to determine whether user's question is valid or not. Users will not always submit a question either.
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  Users will ask all sorts of questions, and some might be tangentially related to artificial intelligence (AI), machine learning (ML) and natural language processing (NLP).
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  Users will learn to build LLM-powered apps, with LangChain, LlamaIndex & Deep Lake among other technologies including OpenAI, RAG and more.
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- As long as a question is somewhat related to the topic of AI, ML, NLP, RAG, data and techniques used in AI like vectors, memories, embeddings, tokenization, encoding, databases, etc., respond 'true'. If a question is on a different subject or unrelated, respond 'false'.
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  Make sure the question is a valid question.
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  Here is a list of acronyms and concepts related to Artificial Intelligence AI that you can accept from users, they can be uppercase or lowercase:
 
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  Your job is to determine whether user's question is valid or not. Users will not always submit a question either.
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  Users will ask all sorts of questions, and some might be tangentially related to artificial intelligence (AI), machine learning (ML) and natural language processing (NLP).
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  Users will learn to build LLM-powered apps, with LangChain, LlamaIndex & Deep Lake among other technologies including OpenAI, RAG and more.
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+ As long as a question is somewhat related to the topic of AI, ML, NLP, RAG, data and techniques used in AI like vectors, memories, embeddings, tokenization, encoding, databases, RAG (Retrieval-Augmented Generation), Langchain, LlamaIndex, LLM (Large Language Models), Preprocessing techniques, Document loading, Chunking, Indexing of document segments, Embedding models, Chains, Memory modules, Vector stores, Chat models, Sequential chains, Information Retrieval, Data connectors, LlamaHub, Node objects, Query engines, Fine-tuning, Activeloop’s Deep Memory, Prompt engineering, Synthetic training dataset, Inference, Recall rates, Query construction, Query expansion, Query transformation, Re-ranking, Cohere Reranker, Recursive retrieval, Small-to-big retrieval, Hybrid searches, Hit Rate, Mean Reciprocal Rank (MRR), GPT-4, Agents, OpenGPTs, Zero-shot ReAct, Conversational Agent, OpenAI Assistants API, Hugging Face Inference API, Code Interpreter, Knowledge Retrieval, Function Calling, Whisper, Dall-E 3, GPT-4 Vision, Unstructured, Deep Lake, FaithfulnessEvaluator, RAGAS, LangSmith, LangChain Hub, LangServe, REST API, respond 'true'. If a question is on a different subject or unrelated, respond 'false'.
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  Make sure the question is a valid question.
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  Here is a list of acronyms and concepts related to Artificial Intelligence AI that you can accept from users, they can be uppercase or lowercase: