A very good blog post by @eugeneyan on “Patterns for building LLM based systems and products”. He covers the seven key patterns to build LLM based systems in greater detail. Link: https://
eugeneyan.com/writing/llm-pa
tterns/
… Must read for folks looking to build LLM based features / products
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Seven Key Patterns for Building LLM-Based Systems
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Fine-tuning Llama-2 with Managed Autoscaling LLM Infrastructure
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There are a lot of ways to #finetune LLaMa-2, but how many of these "solutions" address the #infra challenge? Check out our latest tutorial to learn how to fine-tune #Llama2 on top of fully managed, autoscaling #LLM infra right inside your VPC.
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LangChain New Syntax Overview Live Discussion
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A good overview of some samples of the new LangChain syntax! As a reminder, we're going live in ~25 minutes with the one and only @nfcampos to discuss the motivation, the interface, and some examples https://
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Easier Custom Chain Creation with Internal Tool
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We’ve been using it for a bit internally and it’s so much easier to create custom chains
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Hugging Face reaches 1 million repositories in 3 years
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From 0 to 1,000,000 repositories on @huggingface in 3 years!
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Summary of LLM-based Systems Building Patterns
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quick summary of @eugeneyan
's epic post on "Patterns for Building LLM-based Systems" -
LLM Patterns: Essential Design Patterns for Large Language Models
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https://
eugeneyan.com/writing/llm-pa
tterns/
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Memory Management Outside Chain Architecture
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Memory Right now memory is managed outside the chain, which makes it a bit more work to set up, but also easier to understand what's going on
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SQL Database Interaction for AI Applications
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SQL You can interact with SQL Databases – both to generate SQL queries as well as actually running the SQL
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Execute Python Code Directly from LLM Output
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Python REPL You can pipe the output of an LLM call into a Python REPL to run that code