ADVANCED Python AI Agent Tutorial - Using RAG
126,352
Published 2024-02-14
Note: This video refers to llamaindex version 0.9. On Feb 12th, 2024 llamaindex version 0.10 was released which is mostly the same but has some added functionality :)
π Video Resources π
Check out Llama Index: www.llamaindex.ai/
Llama Index Docs: docs.llamaindex.ai/en/stable/
Population Dataset: www.kaggle.com/datasets/joebeachcapital/world-popuβ¦
Llama Hub: llamahub.ai/
Code in this video: github.com/techwithtim/PythonAgentAI/tree/main
β³ Timestamps β³
00:00 | Overview
00:27 | Project Demos
03:54 | Understanding Agents & RAG
06:29 | Installation/Setup
09:00 | Data Sources
13:18 | Querying Pandas Data
19:17 | Building Agent Capabilities
29:18 | Querying Unstructured Data
39:38 | Next Steps
Hashtags
#PythonAI
#TechWithTim
#AICoding
All Comments (21)
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Just a tip for whoever is following along.The code, from llama_index.query_engine needs to be llama_index.core.query_engine.
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Guys! The llama-index package format has changed, try importing this way and it should work: from llama_index.core.query_engine import ... Like so everyone can see!
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Detailed, no-nonense, topical. One of the best coding channels on youtube. Always looking forward to a new video.
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If you are running this blindly without using Tim's requirements file, please note that due to security `from llama_index.query_engine import PandasQueryEngine` is no longer the right import, try pip installing `llama-index-experimental` and then using the PandasQueryEngine class from `from llama_index.experimental.query_engine import PandasQueryEngine`. This is for py3.10. Finally, the PromptTemplate class is now at `from llama_index.core import PromptTemplate`. The documentation will really help though. Thanks Tim.
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This channel is a Godsend, which instilled the fundamentals of Python within me, which helped me to obtain a certification in robotics. You never cease to amaze me. π
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5 mins into the video and I am already excited about the future!
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thank you very much for your feedback β€β€β€β€
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Amazing video ,tim ...i always wanted a fast an ld easy way to understand llamaindex...now I can build my own project fast ... Thanks a million brother
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This is the gold standard for this kind of coding tutorials.π― I hope more Youtubers would be like him. Please keep up the good work.
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To add context in order to refer to previous response like "save the response to my notes", you can add context = " ".join([f"role: {exchange['role']} content: {exchange['content']}" for exchange in st.session_state.messages]) response = agent.query(context + "\n" + prompt)
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Excellent tutorial. Its clear enough to follow and implement. Keep up your good work.
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one of the best videos on internet regarding AI agents
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Tim we need more content like this or a course... and as always awesome work β€
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Tim you saved my day, you are awesome. I will write in details later how, but for now thanks for the brilliant working code
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Thanks for sharing Tim.
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This is brilliant. Thank you.
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Thank you for the video. It is interesting and clear
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Great tutorial Tim!
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awesome great explanation i spended days to read the docs i know the efforts you in to generate this content, thanks
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This looks like a helpful tutorial, hope I can learn something!