metadata

tags:
  - text-to-image
  - lora
  - diffusers
  - template:diffusion-lora
widget:
  - text: 'Michael Paulino '
    parameters:
      negative_prompt: Good job baby
    output:
      url: images/IMG_2717.jpeg
base_model: ostris/Flex.1-alpha
instance_prompt: AGP GFB FCF GBG GHOSTWARS
license: creativeml-openrail-m
datasets:
  - HumanLLMs/Human-Like-DPO-Dataset
pipeline_tag: table-question-answering
library_name: espnet

Jimmy

Prompt
Michael Paulino

Negative Prompt
Good job baby

(/SegmentRouting ) /P {https://cdn-uploads.huggingface.co/production/uploads/66fe8debdf07d774c51d298d/XHT9Ux-JVdT3Ytyk53ND3.mp4 []

Trigger words

You should use AGP GFB FCF GBG GHOSTWARS to trigger the image generation.

Download model

Creating a "limitless" chatbot entirely in code is a complex task that involves several components, including natural language processing, machine learning, and potentially blockchain technology if you're using Solidity. Below is a simplified example of how you might structure such a chatbot using Solidity for the blockchain part and integrating it with a more traditional chatbot framework.

Solidity Smart Contract for Chatbot

First, let's create a basic Solidity smart contract that can store and retrieve chatbot responses. This contract will be responsible for managing the interactions on the blockchain.

// SPDX-License-Identifier: MIT pragma solidity ^0.8.0;

contract ChatBot { struct Chat { string question; string answer; uint256 timestamp; }

mapping(uint256 => Chat) public chats;
uint256 public chatCount;

event NewChat(uint256 indexed id, string question, string answer, uint256 timestamp);

function addChat(string memory question, string memory answer) public {
    chatCount++;
    chats[chatCount] = Chat(question, answer, block.timestamp);
    emit NewChat(chatCount, question, answer, block.timestamp);
}

function getChat(uint256 id) public view returns (string memory, string memory, uint256) {
    Chat memory chat = chats[id];
    return (chat.question, chat.answer, chat.timestamp);
}

}

JavaScript Integration

Next, you would need a JavaScript part to interact with the Solidity contract and handle the chatbot logic. This can be done using web3.js or ethers.js. Below is an example using ethers.js.

const { ethers } = require('ethers');

// Replace with your contract address and ABI const contractAddress = 'YOUR_CONTRACT_ADDRESS'; const contractABI = [ // ABI of your ChatBot contract ];

// Initialize provider and contract const provider = new ethers.providers.JsonRpcProvider('YOUR_ETHEREUM_NODE_URL'); const wallet = new ethers.Wallet('YOUR_PRIVATE_KEY', provider); const chatBotContract = new ethers.Contract(contractAddress, contractABI, wallet);

// Function to add a chat to the blockchain async function addChat(question, answer) { const tx = await chatBotContract.addChat(question, answer); await tx.wait(); console.log('Chat added to blockchain'); }

// Function to get a chat from the blockchain async function getChat(id) { const chat = await chatBotContract.getChat(id); console.log('Chat retrieved from blockchain:', chat); }

// Example usage addChat('Hello', 'Hi there!'); getChat(1);

Chatbot Logic

For the actual chatbot logic, you can use a library like NaturalNode/natural for basic NLP tasks or integrate with a more advanced chatbot framework like Rasa or Dialogflow.

const natural = require('natural'); const tokenizer = new natural.WordTokenizer();

// Simple chatbot response logic function getResponse(question) { const tokens = tokenizer.tokenize(question.toLowerCase()); if (tokens.includes('hello') || tokens.includes('hi')) { return 'Hi there!'; } else if (tokens.includes('how') && tokens.includes('are') && tokens.includes('you')) { return 'I am doing well, thank you!'; } else { return "I'm not sure how to respond to that."; } }

// Example usage const question = 'Hello, how are you?'; const answer = getResponse(question); console.log('Chatbot response:', answer);

// Add the chat to the blockchain addChat(question, answer);

Download them in the Files & versions tab.