Build Agents with Open Source Models! Explore the latest in context-aware search with our new template by @tjaffri
, powered by @MistralAI 's open-source mixtral model & hosted on @FireworksAI_HQ . It searches academic papers on Arxiv out of the box, and customize it with
@langchain
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Build AI Agents with Open Source Mixtral Models
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Corrective RAG meets Mistral: Revolutionary RAG technique
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Corrective RAG Mistral Corrective RAG was a new RAG technique published a few weeks ago Mistral models are taking the world by storm A perfect combination!
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Corrective RAG: Self-Reflection Improves Retrieval Quality
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Corrective RAG Corrective RAG (CRAG) is a recent paper that uses self-reflection to identify and correct problems in retrieval. It first uses a retrieval evaluator to assess the quality of retrieved documents relative to the query. It filters out irrelevant documents and
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Human-in-the-Loop Agents: Interrupt and Authorize Features
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Human-in-the-loop with OpenGPTs and LangGraph Today we’re launching two “human in the loop” features in OpenGPTs (powered by LangGraph): Interrupt
Authorize What do these do and why is this "human-in-the-loop" important for agents? Interrupt This allows the user to -
LangSmith Adds Token-Based Cost Tracking Feature
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Cost Tracking in LangSmith Looking for deeper insights into your spending patterns for your LLM application to avoid costly surprises? This is now doable in LangSmith with the addition of token-based cost tracking! You can drill down to view costs by project,
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OpenGPTs Custom Actions Integration with Connery Platform
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Summarize a webpage and send it by email from OpenGPTs using @connery_io actions Cool tutorial from the Connery team on how to use their platform to add arbitrary actions to OpenGPTs!
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Self-Reflective RAG Enhancement Using LangGraph
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Self-Reflective RAG using LangGraph Self-reflection can enhance RAG, enabling correction of poor quality retrieval or generations. Several recent papers focus on this theme, but implementing the ideas can be tricky. Here is a video and two cookbooks that show how to engineer
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Building LLM Agents with Plugin Access and Personalization
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Connery Plugins + OpenGPTs Blog + video links at the end! Some of the coolest LLM-powered apps involve granting the model agentic access to third-party systems, but there are a few things to think about when shipping: Personalization: How do you manage linked
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WebVoyager: AI Agent for Autonomous Web Navigation
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2/ To jump straight to the code, check out the links below. Python Code:
https://
github.com/langchain-ai/l
anggraph/blob/main/examples/web-navigation/web_voyager.ipynb
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WebVoyager Paper:
https://
arxiv.org/abs/2401.13919
Set-of-Mark Paper:
https://
arxiv.org/abs/2310.11441 -
Developing AI Agents Easier with LangSmith
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3/ Developing agents like WebVoyager is easier with easier with LangSmith. Sign up at
https://
smith.langchain.com to get started.