content.raw: I'm very proud to have supported 
content.type: text
content.value: I'm very proud to have supported 
content.raw: @CGIAR
content.type: mention
content.user: CGIAR
content.raw:  and 
content.type: text
content.value:  and 
content.raw: @Digigreen
content.type: mention
content.user: Digigreen
content.raw:  in making 
content.type: text
content.value:  in making 
content.href: http://Farmer.chat
content.raw: http://Farmer.chat
content.type: link
content.raw: , an app that supports 20k smallholder farmers on a daily basis 🌾
content.type: text
content.value: , an app that supports 20k smallholder farmers on a daily basis 🌾
content.type: new_line
content.type: new_line
content.raw: There are ~500 million smallholder farmers globally, playing a critical role in global food security. Having access to accurate information is essential for them.
content.type: text
content.value: There are ~500 million smallholder farmers globally, playing a critical role in global food security. Having access to accurate information is essential for them.
content.type: new_line
content.type: new_line
content.raw: 💬 An “agricultural extension service” offers technical advice on agriculture, and also supplies farmers with the necessary inputs and services to support their agricultural production.
content.type: text
content.value: 💬 An “agricultural extension service” offers technical advice on agriculture, and also supplies farmers with the necessary inputs and services to support their agricultural production.
content.type: new_line
content.type: new_line
content.raw: But agriculture extension agents are not in large enough numbers to cope with all the requests, especially in countries like Kenya, India, Ethiopia, and Nigeria.
content.type: text
content.value: But agriculture extension agents are not in large enough numbers to cope with all the requests, especially in countries like Kenya, India, Ethiopia, and Nigeria.
content.type: new_line
content.type: new_line
content.raw: 🚀 So the team set out to build an app called 
content.type: text
content.value: 🚀 So the team set out to build an app called 
content.href: http://Farmer.Chat
content.raw: http://Farmer.Chat
content.type: link
content.raw: , to provide an agricultural extension service, by building on the immense knowledge accumulated by CGIAR.
content.type: text
content.value: , to provide an agricultural extension service, by building on the immense knowledge accumulated by CGIAR.
content.type: new_line
content.type: new_line
content.raw: ✨ The app is technically impressive: behind the Whatsapp-type UX, an agent interprets the user's intent, and identifies which tool to call to best answer their request: weather API, RAG on a CGIAR-provided knowledge base, market data, etc. The RAG on the knowledge base is in itself a work of art.
content.type: text
content.value: ✨ The app is technically impressive: behind the Whatsapp-type UX, an agent interprets the user's intent, and identifies which tool to call to best answer their request: weather API, RAG on a CGIAR-provided knowledge base, market data, etc. The RAG on the knowledge base is in itself a work of art.
content.type: new_line
content.type: new_line
content.raw: 🎯 A key part of building such a complex system is to be able to evaluate it properly. During our bi-weekly sessions with the team, I could support them in  implementing the method called "LLM-as-a-judge" to tackle this problem.
content.type: text
content.value: 🎯 A key part of building such a complex system is to be able to evaluate it properly. During our bi-weekly sessions with the team, I could support them in  implementing the method called "LLM-as-a-judge" to tackle this problem.
content.type: new_line
content.type: new_line
content.raw: It worked really well : thanks to the amazing work of the team, the app now successfully answered over 300 thousand requests, in 6 different languages, and it keeps growing!
content.type: text
content.value: It worked really well : thanks to the amazing work of the team, the app now successfully answered over 300 thousand requests, in 6 different languages, and it keeps growing!
content.type: new_line
content.type: new_line
content.raw: ➡️ 
content.type: text
content.value: ➡️ 
content.raw: @Vinsingh
content.type: mention
content.user: Vinsingh
content.raw: , 
content.type: text
content.value: , 
content.raw: @rajgreen
content.type: mention
content.user: rajgreen
content.raw:  and I just wrote a blog post to describe how the app works, especially the LLM-as-a-judge system!
content.type: text
content.value:  and I just wrote a blog post to describe how the app works, especially the LLM-as-a-judge system!
content.type: new_line
content.type: new_line
content.raw: Read it here 👉 
content.type: text
content.value: Read it here 👉 
content.href: https://huggingface.co/blog/digital-green-llm-judge
content.raw: https://huggingface.co/blog/digital-green-llm-judge
content.type: link
rawContent: I'm very proud to have supported @CGIAR and @Digigreen in making http://Farmer.chat, an app that supports 20k smallholder farmers on a daily basis 🌾
  
  There are ~500 million smallholder farmers globally, playing a critical role in global food security. Having access to accurate information is essential for them.
  
  💬 An “agricultural extension service” offers technical advice on agriculture, and also supplies farmers with the necessary inputs and services to support their agricultural production.
  
  But agriculture extension agents are not in large enough numbers to cope with all the requests, especially in countries like Kenya, India, Ethiopia, and Nigeria.
  
  🚀 So the team set out to build an app called http://Farmer.Chat, to provide an agricultural extension service, by building on the immense knowledge accumulated by CGIAR.
  
  ✨ The app is technically impressive: behind the Whatsapp-type UX, an agent interprets the user's intent, and identifies which tool to call to best answer their request: weather API, RAG on a CGIAR-provided knowledge base, market data, etc. The RAG on the knowledge base is in itself a work of art.
  
  🎯 A key part of building such a complex system is to be able to evaluate it properly. During our bi-weekly sessions with the team, I could support them in  implementing the method called "LLM-as-a-judge" to tackle this problem.
  
  It worked really well : thanks to the amazing work of the team, the app now successfully answered over 300 thousand requests, in 6 different languages, and it keeps growing!
  
  ➡️ @Vinsingh, @rajgreen and I just wrote a blog post to describe how the app works, especially the LLM-as-a-judge system!
  
  Read it here 👉 https://huggingface.co/blog/digital-green-llm-judge
reactions.reaction: 👀
reactions.users: John6666 AtAndDev darkzbaron
reactions.reaction: 😎
reactions.users: monsoon-nlp AtAndDev