Deep Research

Deep Research is an open source library for conducting deep, multi-hop research with reasoning capabilities. It performs focused web searches with recursive exploration to provide comprehensive, evidence-backed answers to complex questions.

Perplexity and OpenAI's Deep Research is gatekeeped and close sourced, So we decided to built the opposite—an open, fully customizable deep research framework.

✨ Key Features

Deep Research is designed to be your comprehensive solution for AI-powered research:

• 🧠 Advanced multi-hop reasoning for complex questions
• 🌐 Real-time web search with recursive exploration
• 🔍 Automatic subquery generation for comprehensive coverage
• 📊 Intelligent depth and breadth control for research thoroughness
• 📝 Evidence-based report generation with proper citations
• 📚 Automatic bibliography generation with source tracking
• 🔄 Iterative research cycles for deeper understanding
• 🤖 Multi-model support with specialized reasoning capabilities
• ⚡ Flexible configuration for customizing research parameters
• 📈 Scalable from simple inquiries to complex research problems

🧱 Core Concepts

Concept	Description
Deep Thinking	The system breaks down a question into logical parts, reasons through them independently, and synthesizes an answer.
Deep Research	The system performs multi-hop, focused web searches, compares the findings, and composes an evidence-backed answer.

🚀 Installation

npm i deep-research
# or
yarn add deep-research
# or
bun i deep-research

🚀 Quick Start

Basic Usage

import { createDeepResearch } from "deep-research";

// Create instance using the factory function with default settings
const deepResearch = createDeepResearch({
  OPENAI_API_KEY: process.env.OPENAI_API_KEY,
  GEMINI_API_KEY: process.env.GEMINI_API_KEY,
  DEEPINFRA_API_KEY: process.env.DEEPINFRA_API_KEY,
  JIGSAW_API_KEY: process.env.JIGSAW_API_KEY,
});

// Research prompt
const prompt = "What are the recent developments in quantum computing?";

// Generate research report
const result = await deepResearch.generate(prompt);

console.log(result.data.text);
console.log(result.data.bibliography);

Advanced Usage

import { createDeepResearch } from "deep-research";
import { createGoogleGenerativeAI } from "@ai-sdk/google";
import { createDeepInfra } from "@ai-sdk/deepinfra";
import { createOpenAI } from "@ai-sdk/openai";

// Initialize AI providers
const gemini = createGoogleGenerativeAI({
  apiKey: process.env.GEMINI_API_KEY,
});

const deepinfra = createDeepInfra({
  apiKey: process.env.DEEPINFRA_API_KEY,
});

const openaiProvider = createOpenAI({
  apiKey: process.env.OPENAI_API_KEY,
});

// Get model instances
const geminiModel = gemini("gemini-2.0-flash");
const deepseekModel = deepinfra("deepseek-ai/DeepSeek-R1");
const openaiModel = openaiProvider("gpt-4o");

// Create instance with custom configuration
const deepResearch = createDeepResearch({
  max_output_tokens: 30000, // Hard upper limit of tokens
  target_output_tokens: 10000, // Target report length
  max_depth: 4, // specify how many iterations of research to perform
  max_breadth: 3, // specify how many subqueries to generate
  models: {
    default: openaiModel, // Custom models from AI SDK
    reasoning: deepseekModel,
    output: geminiModel,
  },
  logging: {
    enabled: true, // Enable console logging
  },
});

// Research prompt
const prompt = "What are the recent developments in quantum computing?";

// Generate research report
const result = await deepResearch.generate(prompt);

console.log(result.data.text);
console.log(result.data.bibliography);

Configuration Options for Deep Research

Category	Option	Type	Default	Description
max_depth	-	Number	3	Controls how many iterations of research the system will perform. Higher values allow for more thorough, multi-hop research. The system will continue researching until it has a complete answer or reaches this limit.
max_breadth	-	Number	3	Controls how many subqueries are generated for each research iteration. Higher values enable wider exploration of the topic. Determines how many parallel search paths are pursued.
max_output_tokens	-	Number	32000	Hard upper limit on the length of the final report. Must be greater than target_output_tokens.
target_output_tokens	-	Number	optional	The ideal length for the generated report. The system will try to produce a report of approximately this length.
models	default	LanguageModelV1	GPT-4o	The primary model used for most operations.
	reasoning	LanguageModelV1	DeepSeek-R1	Model used for reasoning about search results.
	output	LanguageModelV1	GPT-4o	Model used for generating the final report.
logging	enabled	Boolean	false	When set to true, enables detailed console logging. Helpful for debugging and understanding the research process.
API Keys	JIGSAW_API_KEY	String	required	For accessing the JigsawStack API for web searches.
	OPENAI_API_KEY	String	optional if custom models provided	For OpenAI model access.
	DEEPINFRA_API_KEY	String	optional if custom models provided	For DeepInfra model access.

🧩 How It Works

1️⃣ Research Planning & Analysis

• Creates a DeepResearch instance with user-provided configuration
• Analyzes the input prompt to understand requirements
• Generates a comprehensive research plan
• Breaks down into focused sub-queries using LLMs

2️⃣ Data Collection & Processing

• Executes AI-powered web searches for each sub-query via JigsawStack API
• Gathers and validates relevant sources
• Generates context from search results
• Deduplicates URLs to ensure unique sources

3️⃣ Analysis & Synthesis

• Processes gathered information through reasoning models
• Analyzes and synthesizes the findings
• Evaluates information sufficiency
• Determines if additional research is needed
• Performs iterative research within configured depth limits if needed

4️⃣ Report Generation & Citations

• Creates comprehensive final report
• Iteratively generates content until complete
• Maps sources to reference numbers
• Generates bibliography with citations
• Formats output according to target length requirements

JigsawStack

This project is part of JigsawStack - A suite of powerful and developer friendly APIs for various use cases while keeping costs low. Sign up here for free!

🛠️ Contributing

Contributions are welcome! Please feel free to submit a PR :)