@openassistant/duckdb
This package provides several tools for querying your data using DuckDB in browser.
Features
Tool Name | Description |
---|---|
localQuery | Query any data that has been loaded in your application using user's prompt. |
dbQuery | Query any database that you want to query. |
Installation
npm install @openassistant/duckdb @openassistant/utils ai
Quick Start
Suppose you have a dataset in your application, the data could be loaded from a csv/json/parquet/xml file. For this example, we will use the SAMPLE_DATASETS
in dataset.ts
to simulate the data.
export const SAMPLE_DATASETS = {
myVenues: [
{
index: 0,
location: 'New York',
latitude: 40.7128,
longitude: -74.006,
revenue: 12500000,
population: 8400000,
},
...
],
};
Share the meta data of your dataset in the system prompt, so the LLM can understand which datasets are available to use when creating a map.
The meta data is good enough for the AI assistant. Don't put the entire dataset in the context, and there is no need to share your dataset with the LLM models. This also helps to keep your dataset private.
const systemPrompt = `You can help users to create a map from a dataset.
Please always confirm the function calling and its arguments with the user.
Here is the dataset are available for function calling:
DatasetName: myVenues
Fields: location, longitude, latitude, revenue, population`;
localQuery Tool
import { localQuery, LocalQueryTool } from '@openassistent/duckdb';
import { convertToVercelAiTool } from '@openassistant/utils';
import { generateText } from 'ai';
const localQueryTool: LocalQueryTool = {
...localQuery,
context: {
...localQuery.context,
getValues: (datasetName: string, variableName: string) => {
return SAMPLE_DATASETS[datasetName].map((item) => item[variableName]);
},
},
};
generateText({
model: openai('gpt-4o-mini', { apiKey: key }),
system: systemPrompt,
prompt: 'what is the average revenue of the venues in dataset myVenues?',
tools: {
localQuery: convertToVercelAiTool(localQueryTool),
},
});
The localQuery
tool is not executable on server side since it requires rendering the table on the client side (in the browser). You need to use it on client, e.g.:
app/api/chat/route.ts
import { localQuery } from '@openassistant/duckdb';
import { convertToVercelAiTool } from '@openassistent/utils';
import { streamText } from 'ai';
// localQuery tool will be running on the client side
const localQueryTool = convertToVercelAiTool(localQuery, {
isExecutable: false,
});
export async function POST(req: Request) {
// ...
const result = streamText({
model: openai('gpt-4o-mini'),
system: systemPrompt,
messages: messages,
tools: { localQuery: localQueryTool },
});
}
app/page.tsx
import { useChat } from 'ai/react';
import { localQuery } from '@openassistant/duckdb';
import { convertToVercelAiTool } from '@openassistent/utils';
const myLocalQuery: LocalQueryTool = {
...localQuery,
context: {
...localQuery.context,
getValues: async (datasetName: string, variableName: string) => {
// get the values of the variable from your dataset, e.g.
return SAMPLE_DATASETS[datasetName].map((item) => item[variableName]);
},
},
};
const localQueryTool = convertToVercelAiTool(myLocalQuery);
const { messages, input, handleInputChange, handleSubmit } = useChat({
maxSteps: 20,
onToolCall: async (toolCall) => {
if (toolCall.name === 'localQuery') {
const result = await localQueryTool.execute(
toolCall.args,
toolCall.options
);
return result;
}
},
});
Use the tool with @openassistant/ui
Here is an example of using @openassistant/ui to query the data using the localQuery tool and display the result in a QueryResult component.
import { localQuery } from '@openassistant/duckdb';
import { convertToVercelAiTool } from '@openassistent/utils';
const localQueryTool: LocalQueryTool = {
...localQuery,
context: {
...localQuery.context,
getValues: async (datasetName: string, variableName: string) => {
// get the values of the variable from your dataset, e.g.
return SAMPLE_DATASETS[datasetName].map((item) => item[variableName]);
},
},
};
export function App() {
return (
<AiAssistant
apiKey={process.env.OPENAI_API_KEY || ''}
modelProvider="openai"
model="gpt-4o"
welcomeMessage="Hello! I'm your assistant."
instructions={systemPrompt}
tools={{localQuery: localQueryTool}}
useMarkdown={true}
theme="dark"
/>
);
}