Deconstructing the RAG stack We repeatedly hear that navigating the idea maze around RAG is a challenge. We've overhauled our RAG docs and made a series of guides to organize / explain key RAG strategies. As an entry point, see our new RAG docs: https://
python.langchain.com/docs/use_cases
/question_answering/
…
TOOLS
-
RAG Stack Documentation: Organizing Key Strategies
By
–
-
Tuna: No-Code LLM Fine-Tuning Dataset Generation Tool
By
–
Tuna: a no-code tool for quickly generating LLM fine-tuning datasets from scratch built by Student Hacker, @itsandrewgao
-
GPT-Crawler: Building Custom AI Chatbots for Websites
By
–
GPT-crawler template Easily building chat assistants for websites (documentation, etc) is an extremely popular use-case. GPT-crawler from @builderio is rapidly growing in popularity for building custom GPTs for sites: https://
builder.io/blog/custom-gpt This template shows how to -
Leveraging APIs and Domain Expertise for AI Innovation
By
–
Startups and developers should leverage existing APIs and refine them with quality data. Paige notes that domain expertise can drive AI innovation, even without a CS background.
-
Claude 2.1 API now available with 200K context window
By
–
Claude 2.1 is available now in our API, and is powering http://
claude.ai for both the free and Pro tiers. Usage of the 200K context window is reserved for Claude Pro users. Read more in our blog post: -
Claude API Workbench and System Prompts Launch
By
–
We’re enhancing our developer experience with a new Workbench feature in the Console that makes it easier for Claude API users to test prompts. We’re also introducing system prompts, which allow users to provide custom instructions to structure responses in a more consistent way. pic.twitter.com/28xwVF6CB8
— Anthropic (@AnthropicAI) 21 novembre 2023We’re enhancing our developer experience with a new Workbench feature in the Console that makes it easier for Claude API users to test prompts. We’re also introducing system prompts, which allow users to provide custom instructions to structure responses in a more consistent way.
-
Claude Now Processes 150K Words Entire Documents Analysis
By
–
You can now relay roughly 150K words or over 500 pages of information to Claude. This means you can upload entire codebases, financial statements, or long literary works for Claude to summarize, perform Q&A, forecast trends, compare and contrast multiple documents, and more.
-
MLOps Real-Time Model Monitoring and Performance Metrics
By
–
“Through our MLOps solution, we’ve fine-tuned the process of monitoring machine learning models in real-time. It facilitates a comprehensive view of model performance metrics and how they align with business objectives. If there’s an anomaly in a specific region or sector, it can
-
Switching LLM Providers: Prompting Strategies and LangSmith Hub
By
–
Wondering how to switch LLM providers? It's not as simple as changing the endpoint Different LLMs often require different prompting strategies. One way to explore different prompting strategies? LangSmith Prompt Hub – a collection of different prompts for
-
Prepare to switch from OpenAI API to other LLMs
By
–
To all AI teams and individuals who have built services on #OpenAI #API, you must be ready at any moment to switch your service to another service. (Anthropic, LLama, any LLM locally on an instance with guardrails in