What is LangChain? 101 Beginner's Guide Explained with Animations
ฝัง
- เผยแพร่เมื่อ 20 มิ.ย. 2024
- A fast-paced introduction to LangChain describing its modules: prompts, models, indexes, chains, memory and agents. It is packed with examples and animations to get the main points across as simply as possible. The agent section will be covered in more depth in a following video.
🔗 Links
Source code: github.com/edrickdch/langchai...
LangChain: python.langchain.com/en/lates...
Self-Ask Paper: ofir.io/self-ask.pdf
ReAct Paper: arxiv.org/abs/2210.03629
⏳ Timestamps
00:00 Intro
00:04 What is it?
00:11 Where is it?
00:18 Why is it needed?
00:42 What it provides
01:28 Why connecting LLM to data and making it agentic is useful
01:43 Introducing LangChain modules
01:51 Models - Intro
01:58 Embeddings Models
02:11 Semantic Search
02:18 Open AI Embedding Model
02:35 HuggingFace's Open Source Embedding Model
03:00 Language Models
03:27 Prompts - Intro
03:44 Prompt Templates
04:12 Substitution Engine
04:23 Prompts - Common use cases
04:25 LLM Few shot learning
05:06 LLM Output parsing
06:10 Example Selectors - Motivation
06:24 Example Selectors
06:55 Chat Prompt Template
07:38 Indexes - Intro
07:46 Document Loaders
08:10 Text splitter
08:34 Vector DB PDF Ingestion Example
08:39 Vectorstores
08:58 Retrievers
09:21 Self-querying with Chroma DB
09:34 Recap
09:39 Chains
09:47 Chain with Memory
10:10 Chain use cases
10:17 Chaining Chains together
10:41 Chain
10:45 Agents
10:56 Thank you
💌 Link to the newsletter
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🙋♂️ Need help?
You can reach out by email at edrick@daceflow.ai if you're looking to improve your business workflows using AI or build an AI app. - วิทยาศาสตร์และเทคโนโลยี
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Bruh you got that Fireship vibe to ya. I dig it. Can't wait to see more vids from you!
Great video! I enjoyed the simplicity of the explanation
Great and clear explanation!! Congrats!!
Stoked for the agents video 🙌🏾💜
This video deserves more attentions, so I decide to leave a comment here!
Hi Edrick, great content! Please more more more!!!
very informative and to the point
Excellent presentation...thanks
Great Presentation style mate keep it up, you can make it in the big leagues
Nice video, great work!
Thanks Jason!
the content and quality of the video is amazing! I liked the fireship style, the amount of information you covered was super!
keep going
Awesome video, thanks
This is a pretty informative video. I’m now subscribed to your channel
I find Langchain to be most useful for vectorizing data and interacting with vectorDBs. I've tried to use the other prompt and chianing features but they add a huge amount of boilerplate and complexity to what is already easily solved by string interpolation. In most cases you really can't even afford to waste tokens on the bloat langchain injects into your prompts
amazing thank you😍
Keep up the good work you got another subscription from me.
You're the best 👍😃
Fluffless and awesome video! Nice work!
Good, thanks
Banger video
Indeed
Nice 👍 tutorial
Please teach how to translate pdf above 5mb and maintaining the order of text and photos using the langchain library
Dankeschön
did you make this video tutorial?
subscribed
Great
bro is a second Fireship
how the holy fuck do I link my MusicGen baseten model into langchain with a chat interface?? Where does the god damn python file go?
Just make a PromptTemplate, which we wont show you an example of for audio. have fun ;)
nice intro, but annoying reading (no breaks between sentences).
What a video 🥹🥹❤️❤️❤️ the meme content 🤌🏻
Great video! I enjoyed the simplicity of the explanation