Knowledge base

To use a private, secure and encrypted Knowledge base:

Create a Knowledge base.

Login to PropulsionAI
Goto Knowledge base.
Create a new Knowledge base.
Upload documents to Knowledge base.

For large documents, wait for document processing to be completed.

Inference

import PropulsionAI from 'propulsionai';
import {
  ModelChatResponse,
  ModelChatParams
} from 'propulsionai/resources/models';

const p8n = new PropulsionAI({
  bearerToken: process.env['PROPULSIONAI_BEARER_TOKEN'] as string,
});

async function main() {
  try {
    let deployment_tag: string = '<deployment_tag>';
    let knowledgebases: Array<string> = ["<knowledgebase_id>"]
    let params: ModelChatParams = {
      knowledgebases: knowledgebases,
      messages: [
        {
          role: 'user',
          content: "What are the key improvements in US-X2090249-B00?",
        },
      ],
      model: 'auto',
      stream: false,
      wait: true,
    };
    let response: ModelChatResponse;
    try{
      response = await p8n.models.ep(deployment_tag, params);
    }catch(e){
      console.log('Error:', e);
      return;
    }
    console.log("Task ID:", response.task_id);
    if(response.choices) {
      response.choices.forEach((choice) => {
        console.log(`${choice.message?.role}: ${choice.message?.content}`);
      });
    }
  } catch (error) {
    console.error('Error during model call:', error);
  }
}

main();

import PropulsionAI from 'propulsionai';

const p8n = new PropulsionAI({
  bearerToken: process.env['PROPULSIONAI_BEARER_TOKEN'],
});

async function main() {
  try {
    let deployment_tag = '<deployment_tag>';
    let knowledgebases = ["<knowledgebase_id>"]
    let params = {
      knowledgebases: knowledgebases,
      messages: [
        {
          role: 'user',
          content: "What are the key improvements in US-X2090249-B00?",
        },
      ],
      model: 'auto',
      stream: false,
      wait: true,
    };
    let response;
    try{
      response = await p8n.models.ep(deployment_tag, params);
    }catch(e){
      console.log('Error:', e);
      return;
    }
    console.log("Task ID:", response.task_id);
    if(response.choices) {
      response.choices.forEach((choice) => {
        console.log(`${choice.message?.role}: ${choice.message?.content}`);
      });
    }
  } catch (error) {
    console.error('Error during model call:', error);
  }
}

main();

import os
from propulsionai import AsyncPropulsionAI
from propulsionai.models import ModelChatResponse

# Initialize AsyncPropulsionAI with bearer token from environment variables
p8n = AsyncPropulsionAI(
    bearer_token=os.environ.get("PROPULSIONAI_BEARER_TOKEN"),
)

async def main() -> None:
    try:
        response: ModelChatResponse = await p8n.models.ep_auto(
            '<deployment_tag>',
            knowledgebases=[<knowledgebase_id_1>, <knowledgebase_id_2>],
            messages=[
                {
                    "role": "user",
                    "content": "Share 3 key features about under-development KB-9982 drone.",
                },
            ],
            model="auto",
            stream=False,
            wait=True,
        )
        print(response)
    except Exception as e:
        print(f"Error during model call: {e}")

if __name__ == "__main__":
    import asyncio
    asyncio.run(main())

# Inference Call
curl -X "POST" "https://api.propulsionhq.com/api/v1/chat/<deployment_tag>?wait=true" \
     -H 'Authorization: Bearer <PROPULSIONAI_BEARER_TOKEN>' \
     -H 'Content-Type: application/json; charset=utf-8' \
     -d '{
  "knowledgebases": [<knowledgebase_id_1>, <knowledgebase_id_2>],
  "messages": [
    {
      "role": "user",
      "content": "Share 3 key features about under-development KB-9982 drone."
    }
  ],
  "model": "auto",
  "stream": false
}'

Last updated 1 year ago

import PropulsionAI from 'propulsionai';

const p8n = new PropulsionAI({
  bearerToken: process.env['PROPULSIONAI_BEARER_TOKEN'],
});

async function main() {
  try {
    let deployment_tag = '<deployment_tag>';
    let knowledgebases = ["<knowledgebase_id>"]
    let params = {
      knowledgebases: knowledgebases,
      messages: [
        {
          role: 'user',
          content: "What are the key improvements in US-X2090249-B00?",
        },
      ],
      model: 'auto',
      stream: false,
      wait: true,
    };
    let response;
    try{
      response = await p8n.models.ep(deployment_tag, params);
    }catch(e){
      console.log('Error:', e);
      return;
    }
    console.log("Task ID:", response.task_id);
    if(response.choices) {
      response.choices.forEach((choice) => {
        console.log(`${choice.message?.role}: ${choice.message?.content}`);
      });
    }
  } catch (error) {
    console.error('Error during model call:', error);
  }
}

main();

import os
from propulsionai import AsyncPropulsionAI
from propulsionai.models import ModelChatResponse

# Initialize AsyncPropulsionAI with bearer token from environment variables
p8n = AsyncPropulsionAI(
    bearer_token=os.environ.get("PROPULSIONAI_BEARER_TOKEN"),
)

async def main() -> None:
    try:
        response: ModelChatResponse = await p8n.models.ep_auto(
            '<deployment_tag>',
            knowledgebases=[<knowledgebase_id_1>, <knowledgebase_id_2>],
            messages=[
                {
                    "role": "user",
                    "content": "Share 3 key features about under-development KB-9982 drone.",
                },
            ],
            model="auto",
            stream=False,
            wait=True,
        )
        print(response)
    except Exception as e:
        print(f"Error during model call: {e}")

if __name__ == "__main__":
    import asyncio
    asyncio.run(main())

# Inference Call
curl -X "POST" "https://api.propulsionhq.com/api/v1/chat/<deployment_tag>?wait=true" \
     -H 'Authorization: Bearer <PROPULSIONAI_BEARER_TOKEN>' \
     -H 'Content-Type: application/json; charset=utf-8' \
     -d '{
  "knowledgebases": [<knowledgebase_id_1>, <knowledgebase_id_2>],
  "messages": [
    {
      "role": "user",
      "content": "Share 3 key features about under-development KB-9982 drone."
    }
  ],
  "model": "auto",
  "stream": false
}'

hashtagCreate a Knowledge base.

hashtagInference

Create a Knowledge base.

Inference