Parse Partial JSON Stream - Turn your slow AI app into an engaging real-time app

Name: openai-partial-stream
Rating: 5 (122 reviews)
Author: st3w4r

Convert a stream of token into a parsable JSON object before the stream ends.
Implement Streaming UI in LLM-based AI application.
Leverage OpenAI Function Calling for early stream processing.
Parse JSON streams into distinct entities.
Engage your users with a real-time experience.

Follow the Work

Install

To install dependencies:

npm install --save openai-partial-stream

Usage with simple stream

Turn a stream of tokens into a parsable JSON object as soon as possible.

import OpenAi from "openai";
import { OpenAiHandler, StreamMode } from "openai-partial-stream";
// Set your OpenAI API key as an environment variable: OPENAI_API_KEY
const openai = new OpenAi({ apiKey: process.env.OPENAI_API_KEY });
const stream = await openai.chat.completions.create({
  messages: [{ role: "system", content: "Say hello to the world." }],
  model: "gpt-3.5-turbo", // OR "gpt-4"
  stream: true, // ENABLE STREAMING
  temperature: 1,
  functions: [
    {
      name: "say_hello",
      description: "say hello",
      parameters: {
        type: "object",
        properties: {
          sentence: {
            type: "string",
            description: "The sentence generated",
          },
        },
      },
    },
  ],
  function_call: { name: "say_hello" },
});
const openAiHandler = new OpenAiHandler(StreamMode.StreamObjectKeyValueTokens);
const entityStream = openAiHandler.process(stream);for await (const item of entityStream) {
  console.log(item);
}

Output:

{ index: 0, status: 'PARTIAL', data: {} }
{ index: 0, status: 'PARTIAL', data: { sentence: '' } }
{ index: 0, status: 'PARTIAL', data: { sentence: 'Hello' } }
{ index: 0, status: 'PARTIAL', data: { sentence: 'Hello,' } }
{ index: 0, status: 'PARTIAL', data: { sentence: 'Hello, world' } }
{ index: 0, status: 'PARTIAL', data: { sentence: 'Hello, world!' } }
{ index: 0, status: 'COMPLETED', data: { sentence: 'Hello, world!' } }

Usage with stream and entity parsing

Validate the data against a schema and only return the data when it is valid.

import { z } from "zod";
import OpenAi from "openai";
import { OpenAiHandler, StreamMode, Entity } from "openai-partial-stream";
// Set your OpenAI API key as an environment variable: OPENAI_API_KEY
const openai = new OpenAi({ apiKey: process.env.OPENAI_API_KEY });
const stream = await openai.chat.completions.create({
  messages: [{ role: "system", content: "Say hello to the world." }],
  model: "gpt-3.5-turbo", // OR "gpt-4"
  stream: true, // ENABLE STREAMING
  temperature: 1,
  functions: [
    {
      name: "say_hello",
      description: "say hello",
      parameters: {
        type: "object",
        properties: {
          sentence: {
            type: "string",
            description: "The sentence generated",
          },
        },
      },
    },
  ],
  function_call: { name: "say_hello" },
});
const openAiHandler = new OpenAiHandler(StreamMode.StreamObjectKeyValueTokens);
const entityStream = openAiHandler.process(stream);
// Entity Parsing to validate the data
const HelloSchema = z.object({
  sentence: z.string().optional(),
});
const entityHello = new Entity("sentence", HelloSchema);
const helloEntityStream = entityHello.genParse(entityStream);for await (const item of helloEntityStream) {
  console.log(item);
}

Output:

{ index: 0, status: 'PARTIAL', data: {}, entity: 'sentence' }
{ index: 0, status: 'PARTIAL', data: { sentence: '' }, entity: 'sentence' }
{ index: 0, status: 'PARTIAL', data: { sentence: 'Hi' }, entity: 'sentence' }
{ index: 0, status: 'PARTIAL', data: { sentence: 'Hi,' }, entity: 'sentence' }
{ index: 0, status: 'PARTIAL', data: { sentence: 'Hi, world' }, entity: 'sentence' }
{ index: 0, status: 'PARTIAL', data: { sentence: 'Hi, world!' }, entity: 'sentence' }
{ index: 0, status: 'COMPLETED', data: { sentence: 'Hi, world!' }, entity: 'sentence'}

Usage with stream and entity parsing with multiple entities

import { z } from "zod";
import OpenAi from "openai";
import { OpenAiHandler, StreamMode, Entity } from "openai-partial-stream";
// Intanciate OpenAI client with your API key
const openai = new OpenAi({
  apiKey: process.env.OPENAI_API_KEY,
});
const PostcodeSchema = z.object({
  name: z.string().optional(),
  postcode: z.string().optional(),
  population: z.number().optional(),
});
// Call the API with stream enabled and a function
const stream = await openai.chat.completions.create({
  messages: [
    {
      role: "system",
      content: "Give me 3 cities and their postcodes in California.",
    },
  ],
  model: "gpt-3.5-turbo", // OR "gpt-4"
  stream: true, // ENABLE STREAMING
  temperature: 1.1,
  functions: [
    {
      name: "set_postcode",
      description: "Set a postcode and a city",
      parameters: {
        type: "object",
        properties: {
          // The name of the entity
          postcodes: {
            type: "array",
            items: {
              type: "object",
              properties: {
                name: {
                  type: "string",
                  description: "Name of the city",
                },
                postcode: {
                  type: "string",
                  description: "The postcode of the city",
                },
                population: {
                  type: "number",
                  description: "The population of the city",
                },
              },
            },
          },
        },
      },
    },
  ],
  function_call: { name: "set_postcode" },
});
// Select the mode of the stream parser
// - StreamObjectKeyValueTokens: (REALTIME)     Stream of JSON objects, key value pairs and tokens
// - StreamObjectKeyValue:       (PROGRESSIVE)  Stream of JSON objects and key value pairs
// - StreamObject:               (ONE-BY-ONE)   Stream of JSON objects
// - NoStream:                   (ALL-TOGETHER) All the data is returned at the end of the process
const mode = StreamMode.StreamObject;
// Create an instance of the handler
const openAiHandler = new OpenAiHandler(mode);
// Process the stream
const entityStream = openAiHandler.process(stream);
// Create an entity with the schema to validate the data
const entityPostcode = new Entity("postcodes", PostcodeSchema);
// Parse the stream to an entity, using the schema to validate the data
const postcodeEntityStream = entityPostcode.genParseArray(entityStream);// Iterate over the stream of entities
for await (const item of postcodeEntityStream) {
  if (item) {
    // Display the entity
    console.log(item);
  }
}

Output:

{ index: 0, status: 'COMPLETED', data: { name: 'Los Angeles', postcode: '90001', population: 3971883 }, entity: 'postcodes' }
{ index: 1, status: 'COMPLETED', data: { name: 'San Francisco', postcode: '94102', population: 883305 }, entity: 'postcodes' }
{ index: 2, status: 'COMPLETED', data: { name: 'San Diego', postcode: '92101', population: 1425976 }, entity: 'postcodes'}

Modes

Select a mode from the list below that best suits your requirements:

NoStream
StreamObject
StreamObjectKeyValue
StreamObjectKeyValueTokens

---

NoStream

Results are returned only after the entire query completes.

| NoStream Details | | ---------------------------------------------------------------- | | ✅ Single query retrieves all data | | ✅ Reduces network traffic | | ⚠️ User experience may be compromised due to extended wait times |

StreamObject

An event is generated for each item in the list. Items appear as they become ready.

| StreamObject Details | | ------------------------------------------------------------------------------- | | ✅ Each message corresponds to a fully-formed item | | ✅ Fewer messages | | ✅ All essential fields are received at once | | ⚠️ Some delay: users need to wait until an item is fully ready to update the UI |

StreamObjectKeyValue

Objects are received in fragments: both a key and its corresponding value are sent together.

| StreamObjectKeyValue Details | | --------------------------------------------------------- | | ✅ Users can engage with portions of the UI | | ✅ Supports more regular UI updates | | ⚠️ Higher network traffic | | ⚠️ Challenges in enforcing keys due to incomplete objects |

StreamObjectKeyValueTokens

Keys are received in full, while values are delivered piecemeal until they're complete. This method offers token-by-token UI updating.

| StreamObjectKeyValueToken Details | | ------------------------------------------------------------------- | | ✅ Offers a dynamic user experience | | ✅ Enables step-by-step content consumption | | ✅ Decreases user waiting times | | ⚠️ Possible UI inconsistencies due to values arriving incrementally | | ⚠️ Augmented network traffic |

Demo

Stream of JSON object progressively by key value pairs:

https://github.com/st3w4r/openai-partial-stream/assets/4228332/55643614-b92b-4b1f-9cf9-e60d6d783a0c

Stream of JSON objects in realtime:

https://github.com/st3w4r/openai-partial-stream/assets/4228332/73289d38-8526-46cf-a68c-ac80019092ab

References

npm package

--- Tranlated By Open Ai Tx | Last indexed: 2026-06-18 ---