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vectorvault
Advanced tools
VectorVault API - JavaScript Client: Streamline your front-end development with the powerful combination of OpenAI's API and VectorVault's Cloud Vector Database. This JavaScript client provides seamless integration for building advanced RAG (Retrieve and
VectorVault API - JavaScript Client: Streamline your front-end development with the powerful capabilities of VectorVault's Cloud Vector Database. This JavaScript client provides seamless integration for building advanced RAG (Retrieve and Generate) applications. Whether you're working with JavaScript, HTML, or other web technologies, our API simplifies the process of fetching RAG responses through API POST requests. This package is the key to unlocking quick and efficient development for AI-powered web applications, ensuring a secure and robust connection to the VectorVault ecosystem. Start crafting exceptional RAG apps with minimal effort and maximum efficiency.
Install VectorVault via npm:
npm install vectorvault --save
To use VectorVault, you need to import it, instantiate it, and log in with your user credentials:
import VectorVault from 'vectorvault';
// Create a VectorVault instance
const vectorVault = new VectorVault();
// Log in with your email and password
await vectorVault.login('your_email@example.com', 'your_password');
After logging in, you can perform various operations with your vaults.
const params = {
vault: 'your_vault_name',
text: 'Your query here',
// ...other optional parameters
};
vectorVault
.getChat(params)
.then(response => console.log(response))
.catch(error => console.error(error));
const vault = 'your_vault_name';
const itemIds = [1, 2, 3]; // IDs of the items you want to retrieve
vectorVault
.getItems(vault, itemIds)
.then(items => console.log(items))
.catch(error => console.error(error));
const params = {
vault: 'your_vault_name',
text: 'Your text data here',
// ...other optional parameters
};
vectorVault
.addCloud(params)
.then(response => console.log(response))
.catch(error => console.error(error));
The getChatStream
function allows you to stream data from the VectorVault API. It requires two arguments: params
, which is an object containing the parameters for your request, and callback
, which is a function that will be called with each piece of data received from the stream.
Here's how you can use getChatStream
:
// Define your callback function
function handleStreamedData(data) {
// Process the streamed data here
console.log(data);
}
// Set up the parameters for your request
const streamParams = {
vault: 'your_vault_name',
text: 'Your query here',
// ...other optional parameters
};
// Start streaming data
vectorVault
.getChatStream(streamParams, handleStreamedData)
.then(() => console.log('Streaming completed.'))
.catch(error => console.error('Streaming error:', error));
getChatStream
The params
object can include any of the following properties:
vault
: The name of your vault.text
: The input text for the chat.history
: The chat history, if applicable.summary
: A boolean indicating if the response should be a summary.get_context
: A boolean to indicate if you want to receive context information.n_context
: The number of context turns you want to receive.return_context
: A boolean to include the context in the response.smart_history_search
: A boolean to enable smart history searching.model
: The model you want to use, e.g., "gpt-3.5-turbo"
.include_context_meta
: A boolean to include metadata about the context.metatag
, metatag_prefixes
, metatag_suffixes
: Arrays for advanced context tagging.custom_prompt
: A custom prompt to be used instead of the default.temperature
: The creativity temperature.timeout
: The timeout for the model response wait time.Make sure to replace "Your query here"
with the actual text you want to send to the API.
Note: getChatStream
is an asynchronous function and should be handled with async/await
or .then().catch()
for proper error handling.
Login
await vectorVault.login('your_email@example.com', 'your_password');
Logout
vectorVault.logout();
Get Vaults
vectorVault
.getVaults()
.then(vaults => console.log(vaults))
.catch(error => console.error(error));
Delete Vault
const vault = 'your_vault_name';
vectorVault
.deleteVault(vault)
.then(response => console.log(response))
.catch(error => console.error(error));
Edit an Item
const vault = 'your_vault_name';
const itemId = 123;
const newText = 'Updated text content';
vectorVault
.editItem(vault, itemId, newText)
.then(response => console.log(response))
.catch(error => console.error(error));
Delete Items
const vault = 'your_vault_name';
const itemIds = [1, 2, 3];
vectorVault
.deleteItems(vault, itemIds)
.then(response => console.log(response))
.catch(error => console.error(error));
Get Total Items
const vault = 'your_vault_name';
vectorVault
.getTotalItems(vault)
.then(total => console.log(`Total items: ${total}`))
.catch(error => console.error(error));
Get Distance Between Two Items
const vault = 'your_vault_name';
const id1 = 1;
const id2 = 2;
vectorVault
.getDistance(vault, id1, id2)
.then(distance => console.log(`Distance: ${distance}`))
.catch(error => console.error(error));
Get Similar Items
const params = {
vault: 'your_vault_name',
text: 'Sample text to find similarities',
num_items: 4,
include_distances: true,
// ...other optional parameters
};
vectorVault
.getSimilar(params)
.then(similarItems => console.log(similarItems))
.catch(error => console.error(error));
Get Account Data
vectorVault
.getAccountData()
.then(data => console.log(data))
.catch(error => console.error(error));
Download Vault Data to JSON
const params = {
vault: 'your_vault_name',
return_meta: true,
};
vectorVault
.downloadToJson(params)
.then(jsonData => console.log(jsonData))
.catch(error => console.error(error));
Upload Data from JSON
const vault = 'your_vault_name';
const jsonData = {/* Your JSON data */};
vectorVault
.uploadFromJson(vault, jsonData)
.then(response => console.log(response))
.catch(error => console.error(error));
Save Personality Message
const vault = 'your_vault_name';
const personalityMessage = 'Your personality message here';
vectorVault
.savePersonalityMessage(vault, personalityMessage)
.then(response => console.log(response))
.catch(error => console.error(error));
Fetch Personality Message
const vault = 'your_vault_name';
vectorVault
.fetchPersonalityMessage(vault)
.then(message => console.log(message))
.catch(error => console.error(error));
Save Custom Prompt
const vault = 'your_vault_name';
const customPrompt = 'Your custom prompt here';
vectorVault
.saveCustomPrompt(vault, customPrompt)
.then(response => console.log(response))
.catch(error => console.error(error));
Fetch Custom Prompt
const vault = 'your_vault_name';
vectorVault
.fetchCustomPrompt(vault)
.then(prompt => console.log(prompt))
.catch(error => console.error(error));
Fetch 3D Map Data
const vault = 'your_vault_name';
const highlightId = null; // or specify an item ID to highlight
vectorVault
.fetch3DMap(vault, highlightId)
.then(mapData => console.log(mapData))
.catch(error => console.error(error));
Run Flow with Streaming Response
const flowName = 'your_flow_name';
const message = 'Your message here';
const history = ''; // optional
const callbacks = {
onLog: logData => {
console.log('Log:', logData);
},
onMessage: messageData => {
console.log('Message:', messageData);
},
};
vectorVault
.runFlowStream(flowName, message, history, callbacks)
.then(result => {
console.log('Flow completed:', result);
})
.catch(error => {
console.error('Flow error:', error);
});
Most methods return promises and should be handled with .then().catch()
or async/await
syntax. Proper error handling ensures your application can handle exceptions gracefully.
'your_email@example.com'
, 'your_password'
, 'your_vault_name'
, etc.) with your actual account and vault information.With the VectorVault JavaScript client, you can easily integrate advanced vector-based operations into your web applications. Whether you're building AI Agents, recommendation systems, or any AI-powered application, VectorVault provides the tools you need for efficient and secure development.
FAQs
VectorVault API - JavaScript Client: Streamline your front-end development with the powerful combination of OpenAI's API and VectorVault's Cloud Vector Database. This JavaScript client provides seamless integration for building advanced RAG (Retrieve and
The npm package vectorvault receives a total of 2 weekly downloads. As such, vectorvault popularity was classified as not popular.
We found that vectorvault demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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