depending on how you are running Flowise, normally you sync your forked repo, then redeploy. If using Docker, git pull the latest, and start again.
@flowiseai
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Flowise Cloud Launches Evaluations and LLM Performance Tracking
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For Flowise Cloud, there are built-in Evaluations and Logging functionalities. Tokens, costs, and performance of LLMs can be traced, and also comes with versioning! Hop on to our waitlist https://
flowiseai.com/join! We're granting access to to users in batches starting today -
Flowise 2.0 Agentic Workflow Templates Released
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All the examples above are available as templates. These are just a few examples of what can be accomplished using this new agentic workflow approach. We're eager to see what you create with it! Release note: https://
github.com/FlowiseAI/Flow
ise/releases/tag/flowise2.0.0
… Docs: https://
docs.flowiseai.com/using-flowise/
agentflows
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Hierarchical Multi-Agent Teams with Supervisor Architecture
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7/7 Hierarchical Teams
— FlowiseAI (@FlowiseAI) 24 juillet 2024
Develop multiple agents from the ground up.
You can also create sub-teams with top-level supervisor, complemented by mid-level supervisors, forming a hierarchical multi agents! pic.twitter.com/lHpsC6EUSB7/7 Hierarchical Teams Develop multiple agents from the ground up. You can also create sub-teams with top-level supervisor, complemented by mid-level supervisors, forming a hierarchical multi agents!
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Flowise Multi-Agent Team Creation for Content Automation
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Using Flowise to create team of agents for Flowise video titles, descriptions and posts.
— FlowiseAI (@FlowiseAI) 2 juillet 2024
Flowiseception🌀https://t.co/oQofu3kdyg https://t.co/KSwQyYVEZe pic.twitter.com/rPemmhfSg5Using Flowise to create team of agents for Flowise video titles, descriptions and posts. Flowiseception https://
youtu.be/eAH7LDGMVEs?si
=CyUWvmjCoVWrEq1W
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Vector Embeddings and RAG Optimization Best Practices
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Upserting data as vector embeddings is important when building a RAG application. There are many factors at play, such as chunk sizes, overlap, vector dimensions, etc. Shoutout to @toi500
, who has been helping to improve our docs and his recent work on the guides for upserting -
Multi Query Retriever: Enhancing AI Answer Comprehensiveness
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📚Multi Query Retriever
— FlowiseAI (@FlowiseAI) 26 juin 2024
Here's how it works:
1. Generate multiple queries for a given user question
2. For each query, retrieves a set of relevant documents
3. Takes the unique union across all queries for relevant documents
Result: more comprehensive answers from multiple… pic.twitter.com/nyxcAAnr1MMulti Query Retriever Here's how it works:
1. Generate multiple queries for a given user question
2. For each query, retrieves a set of relevant documents
3. Takes the unique union across all queries for relevant documents Result: more comprehensive answers from multiple -
Flowise 1.8.3 Release: Latest Bugfixes and Improvements
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For more bugfixes and other improvements, take a look at the latest Github release – https://
github.com/FlowiseAI/Flow
ise/releases/tag/flowise1.8.3
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LangWatch: New AI Observability Tool for LLM Applications
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LangWatch New observability tool @LangWatchAI Docs: https://
docs.langwatch.ai/integration/fl
owise
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Firecrawl Web Scraper: Convert Websites to LLM-Ready Markdown
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🔥Firecrawl Web Scraper
— FlowiseAI (@FlowiseAI) 26 juin 2024
Crawl and convert any website into LLM-ready markdown or structured data in Flowise, thanks @mendableai team for the integration! pic.twitter.com/gqYLp2BskpFirecrawl Web Scraper Crawl and convert any website into LLM-ready markdown or structured data in Flowise, thanks @mendableai team for the integration!