ragbook-notebooks

This is a repository gathering all the notebooks for the Towards AI RAG book.

Chapter 2

• Transformers_Architectures.ipynb
• Understanding_Transformer.ipynb

Chapter 4

• Intro_to_Prompt_Engineering_Tips_and_Tricks.ipynb

Chapter 5

• Building_Applications_Powered_by_LLMs_with_LangChain.ipynb
• Build_a_News_Articles_Summarizer.ipynb
• LlamaIndex_Introduction.ipynb

Chapter 6

• Using_Prompt_Templates.ipynb
• Getting_the_Best_of_Few_Shot_Prompts_and_Example_Selectors.ipynb
• Managing_Outputs_with_Output_Parsers.ipynb
• Improving_Our_News_Articles_Summarizer.ipynb
• Creating_Knowledge_Graphs_from_Textual_Data_Unveiling_Hidden_Connections.ipynb

Chapter 7

• What_are_Text_Splitters_and_Why_They_are_Useful_.ipynb
• Chains_and_Why_They_Are_Used.ipynb
• Create_a_YouTube_Video_Summarizer_Using_Whisper_and_LangChain_.ipynb
• Guarding_Against_Undesirable_Outputs_with_the_Self_Critique_Chain.ipynb
• Guarding_Against_Undesirable_Outputs_with_the_Self_Critique_Chain_Example.ipynb

Chapter 8

• Mastering_Advanced_RAG.ipynb
• RAG_Metrics&Evaluation.ipynb
• LangSmith_Introduction.ipynb

Chapter 9

• Using_AutoGPT_with_LangChain.ipynb
• LlamaIndex_RAG_AGENT.ipynb
• MultiModal_Fincance_+_DeepMemory.ipynb

Chapter 10

• FineTuning_a_LLM_LIMA_CPU.ipynb
• FineTuning_a_LLM_Financial_Sentiment_CPU.ipynb
• Create_Dataset_For_Cohere_Fine_Tuning.ipynb
• Fine_Tuning_using_Cohere_for_Medical_Data.ipynb
• FineTuning_a_LLM_QLoRA.ipynb
• FineTuning_Reward_Model.ipynb
• FineTune_RLHF.ipynb

Chapter 11

• Benchmark_Inference.ipynb