Test

[sshivaditya2019]

Something new issue lot of details

[sshivaditya2019]

@ubosshivaditya can you tell about UUSD ?

[test-app-ubo[bot]]

Based on the available context and information provided, I don't have specific details about UUSD. The chat history and local context don't contain any information directly related to UUSD.

UUSD could potentially refer to a stablecoin or a cryptocurrency, but without more context or information in the provided corpus, I can't make any definitive statements about its nature, use, or characteristics.

If you have more specific questions about UUSD or if there's additional context you can provide, I'd be happy to help further. Alternatively, if this is related to a particular project or documentation within the repository, you might want to check the relevant files or issues for more information.

[sshivaditya2019]

@ubosshivaditya can you tell about UUSD ?

[test-app-ubo[bot]]

Based on the available context and information provided, I don't have specific details about UUSD. The chat history and local context don't contain any information directly related to UUSD.

UUSD could potentially refer to a stablecoin or a cryptocurrency, but without more context or information in the provided corpus, I can't make any definitive statements about its nature, use, or characteristics.

If you have more specific questions about UUSD or if there's additional context you can provide, I'd be happy to assist further based on that information. Alternatively, if this is related to a specific project or documentation within the repository, you might want to check the relevant files or previous discussions for more details.

[sshivaditya2019]

@ubosshivaditya can you tell about UUSD ?

[test-app-ubo[bot]]

! Cannot destructure property 'answer' of 'response' as it is undefined.

[sshivaditya2019]

@ubosshivaditya can you tell about UUSD ?

[test-app-ubo[bot]]

! input: [Variant 0] Expected string. Received object.; [Variant 1] Expected list. Received object.

[sshivaditya2019]

@ubosshivaditya can you tell about UUSD ?

[test-app-ubo[bot]]

! Cannot destructure property 'answer' of 'response' as it is undefined.

[sshivaditya2019]

@ubosshivaditya can you tell about UUSD ?

[test-app-ubo[bot]]

! Cannot destructure property 'answer' of 'response' as it is undefined.

[sshivaditya2019]

@ubosshivaditya can you tell about UUSD ?

[test-app-ubo[bot]]

! Cannot destructure property 'answer' of 'response' as it is undefined.

[sshivaditya2019]

@ubosshivaditya can you tell about UUSD ?

[test-app-ubo[bot]]

! Cannot destructure property 'answer' of 'response' as it is undefined.

[sshivaditya2019]

@ubosshivaditya can you tell about UUSD ?

[test-app-ubo[bot]]

! Cannot destructure property 'answer' of 'response' as it is undefined.

[sshivaditya2019]

@ubosshivaditya can you tell about UUSD ?

[test-app-ubo[bot]]

Certainly! Based on the information provided, I can tell you about UUSD (Ubiquity USD):

1. Composition: UUSD is comprised of 95% LUSD (Liquity USD) and 5% UBQ (Ubiquity token).

2. Value: UUSD is designed to be worth 100% of the value of the assets you put in, maintaining its peg to the US dollar.

3. Minting and Bridging: Currently, the process to mint UUSD and use it on Gnosis Chain involves several steps:

   • Acquire 95% LUSD
   • Acquire 5% UBQ
   • Mint UUSD
   • Bridge to Gnosis Chain

4. Improvement Plans: There are plans to simplify this process for end users, potentially abstracting away the complexities and gas fees. This may involve smart contracts and UI improvements.

5. Peg Maintenance:

   • Redemptions are allowed only when UUSD is below $1.00
   • Minting is allowed only when UUSD is above $1.00
   • This mechanism helps maintain the peg to the US dollar

6. Redemption Principle: If UUSD is worth less than $1, users can always redeem it for the full value in LUSD. For example, 10 UUSD can be redeemed for 10 LUSD, regardless of UUSD's market price.

7. Future Plans: There are discussions about creating an easier "on-ramp" to UbiquityOS, potentially allowing users to start with any crypto asset and end up with UUSD on Gnosis Chain through a streamlined process.

The core ethos of Ubiquity is to abstract the technical complexities from end users, focusing on providing a seamless user experience that solves real problems.

[sshivaditya2019]

@ubosshivaditya what do you know about the diamond contract for UUSD ?

[test-app-ubo[bot]]

Based on the information available in the provided context, I don't have specific details about the diamond contract for UUSD. The diamond contract pattern is not explicitly mentioned in the given context about UUSD.

However, I can share some general information about UUSD from the context:

1. UUSD is a stablecoin in the Ubiquity ecosystem.

2. The composition of UUSD is:

   • 95% LUSD (Liquity USD)
   • 5% UBQ (Ubiquity token)

3. UUSD is designed to be worth 100% of the value of the assets put in, which comprises the 95% LUSD and 5% UBQ.

4. There are plans to simplify the minting process for UUSD, which currently involves multiple steps including acquiring LUSD and UBQ, minting UUSD, and bridging to Gnosis Chain.

5. The project aims to abstract away the technical complexities from end users, focusing on providing a smooth user experience.

If there are specific details about a diamond contract for UUSD, they are not provided in the given context. The diamond contract pattern is typically used for upgradeable smart contracts, but without more information, I cannot confirm its use or implementation details for UUSD.

[sshivaditya2019]

@ubosshivaditya I want to implment embeddings based RAG using https://github.com/voyage-ai/voyage-large-2-instruct/blob/main/instruct.json could you help me with that ?

[test-app-ubo[bot]]

Certainly! I'd be happy to help you implement embeddings-based RAG (Retrieval-Augmented Generation) using the Voyage AI model. Here's a general approach you can follow:

1. First, you'll need to set up your environment:

import { OpenAI } from 'openai'
import { SupabaseVectorStore } from 'langchain/vectorstores/supabase'
import { OpenAIEmbeddings } from 'langchain/embeddings/openai'
import { createClient } from '@supabase/supabase-js'

2. Initialize the OpenAI client and Supabase client:

const openai = new OpenAI({ apiKey: 'your-openai-api-key' })
const supabase = createClient('your-supabase-url', 'your-supabase-api-key')

3. Create a function to generate embeddings:

async function generateEmbeddings(text: string) {
  const embeddings = new OpenAIEmbeddings()
  return await embeddings.embedQuery(text)
}

4. Store your documents and their embeddings in Supabase:

async function storeDocuments(documents: string[]) {
  const vectorStore = await SupabaseVectorStore.fromTexts(
    documents,
    {},
    new OpenAIEmbeddings(),
    { client: supabase, tableName: 'documents', queryName: 'match_documents' }
  )
  return vectorStore
}

5. Implement the RAG query function:

async function queryRAG(query: string, vectorStore: SupabaseVectorStore) {
  const queryEmbedding = await generateEmbeddings(query)
  const similarDocs = await vectorStore.similaritySearch(query, 3)

  const context = similarDocs.map(doc => doc.pageContent).join('\n')

  const response = await openai.chat.completions.create({
    model: 'voyage-large-2-instruct',
    messages: [
      { role: 'system', content: 'You are a helpful assistant.' },
      { role: 'user', content: `Context: ${context}\n\nQuestion: ${query}` }
    ]
  })

  return response.choices[0].message.content
}

6. Use the functions:

async function main() {
  const documents = ['Your document texts here']
  const vectorStore = await storeDocuments(documents)

  const query = 'Your query here'
  const answer = await queryRAG(query, vectorStore)
  console.log(answer)
}

main()

This implementation uses OpenAI for embeddings and the Voyage AI model for generation. You'll need to adjust the model name and API calls according to the specific requirements of the Voyage AI model.

Remember to handle errors, implement proper authentication, and follow best practices for production use. Also, make sure you have the necessary permissions and API access for both OpenAI and the Voyage AI model.