Hero Researcher

AI-powered research assistant using multiple LLM models for comprehensive background research on people. Built in Rust with the herolib_ai client for multi-provider support.

Features

• Multi-model queries - Query multiple AI models simultaneously for comprehensive results
• Grounded research - Web search + scraping + LLM analysis with evidence-based reporting
• 6 search providers - Brave, DuckDuckGo, SearXNG, Exa, Serper, SerpAPI
• 8 platform scrapers - GitHub, LinkedIn, Twitter, Reddit, StackOverflow, Crunchbase, Medium, Facebook
• 3 research tiers - Quick (4 models), Standard (8 models), Deep (18 models x 4 strategies)
• Online Mode - Real-time web search for up-to-date information
• Multiple output formats - Markdown, JSON, HTML reports
• Web UI - Browser-based interface with job persistence
• Audit logging - Full operation tracking in JSONL format

Installation

Use the Nushell service script to build and install:

service researcher start --update --reset

Quick Start

# Set your API key (at minimum, one provider)
export OPENROUTER_API_KEY=your_key_here

# Basic search
hero_researcher "John Doe" --location "San Francisco"

# Deep investigation (18 models x 4 strategies)
hero_researcher "John Doe" --beast

# Save to file
hero_researcher "John Doe" --output report.md

# With aliases and context
hero_researcher "John Doe" --aliases "J. Doe, Johnny" --context "software engineer at Acme Corp"

CLI Options

Option	Description
NAME	Name of the person to research (required)
--location	Known location to narrow search
--aliases	Comma-separated list of known aliases
--context	Additional identifying context
--models	Comma-separated list of custom model IDs
--tier	Research tier: quick, standard, deep (default: standard)
--beast	Alias for --tier deep
--format	Output format: markdown, json, html (default: markdown)
--concurrency	Parallel tasks 1-20 (default: 4)
--online	Enable real-time web search (:online suffix)
--verbose	Show detailed progress
--output	Save report to file
--urls	Seed URLs to scrape first (comma-separated)
--audit	Write audit log to JSONL file

Hero OS Service (Nushell)

All lifecycle management is done via the Nushell service script:

# Install, register, and start via hero_proc
service researcher start --update --reset

# Stop gracefully
service researcher stop

# Check status
service researcher status

Sockets (under $PATH_SOCKET/hero_researcher/):

• rpc.sock — JSON-RPC 2.0 API
• web.sock — Browser admin dashboard

Web Server

# Start the server directly (binds rpc.sock and web.sock)
hero_researcher_server

API Endpoints:

• GET / - Web UI
• GET /api/tiers - Available research tiers
• GET /api/jobs - List recent jobs
• GET /api/jobs/:id - Get job details
• POST /api/research - Start a research job

Research Tiers

Tier	Models	Strategies	Search Queries	Scrape Pages	Synthesis
Quick	4	basic	~2	5	No
Standard	8	basic	~8	15	Yes
Deep	18	basic, deep, social, professional	~20	30	Yes

Environment Variables

Variable	Description	Required
OPENROUTER_API_KEY	OpenRouter API key	Yes (or other provider)
GROQ_API_KEY	Groq API key	Optional
SAMBANOVA_API_KEY	SambaNova API key	Optional
DEEPINFRA_API_KEY	DeepInfra API key	Optional
BRAVE_API_KEYS	Brave Search keys (comma-separated)	Optional
SEARXNG_URL	SearXNG instance URL	Optional
EXA_API_KEYS	Exa Search keys	Optional
SERPER_API_KEYS	Serper keys	Optional
SERPAPI_API_KEYS	SerpAPI keys	Optional
MODELS	Override default model list	Optional
DB_PATH	SQLite database path (default: hero.db)	Optional
LOG_LEVEL	Log level (default: info)	Optional

Project Structure

hero_researcher/
 Cargo.toml # Workspace root
 crates/
 hero_researcher_lib/ # Core library
 src/
 lib.rs # Re-exports
 types.rs # Person, ResearchResult, etc.
 error.rs # Error types
 config.rs # Configuration
 researcher.rs # Main research pipeline
 prompts.rs # LLM prompt templates
 formatter.rs # Report formatters
 audit.rs # Audit logging
 logger.rs # Tracing setup
 search/ # 6 search providers + aggregator
 scraper/ # Web scraper + 8 platform scrapers
 examples/ # Runnable examples (search, scrape, LLM, pipeline)
 hero_researcher/ # CLI binary
 hero_researcher_server/ # Web server + SQLite

Examples

13 runnable examples in crates/hero_researcher_lib/examples/. Run via cargo:

cargo run -p hero_researcher_lib --example search
cargo run -p hero_researcher_lib --example scrape
cargo run -p hero_researcher_lib --example formatter

Requires LLM API key

cargo run -p hero_researcher_lib --example ai_client
cargo run -p hero_researcher_lib --example llm_call
cargo run -p hero_researcher_lib --example search_and_summarize
cargo run -p hero_researcher_lib --example research_quick
cargo run -p hero_researcher_lib --example researcher_stream
cargo run -p hero_researcher_lib --example online_search
cargo run -p hero_researcher_lib --example custom_models
cargo run -p hero_researcher_lib --example beast_mode
cargo run -p hero_researcher_lib --example audit_log
cargo run -p hero_researcher_lib --example seed_urls

Development

cargo check --workspace # Type check
cargo test --workspace # Run tests
cargo clippy --workspace # Clippy lints
cargo fmt --all # Format code
cargo build --workspace --release # Build release

API Reference

AiClient

use herolib_ai::{AiClient, Model, PromptBuilder, Provider};

let client = AiClient::from_env();

// Using a built-in model
let response = PromptBuilder::new(&client)
 .model(Model::Llama3_1_8B)
 .system("You are a researcher.")
 .user("Search for...")
 .execute()?;
println!("{}", response.content().unwrap_or("(empty)"));

// Using any model by raw ID (e.g. any OpenRouter model)
let response = PromptBuilder::new(&client)
 .raw_model(Provider::OpenRouter, "anthropic/claude-sonnet-4.5")
 .system("You are a researcher.")
 .user("Search for...")
 .execute()?;

Researcher

use hero_researcher_lib::config::Config;
use hero_researcher_lib::researcher::Researcher;
use hero_researcher_lib::scraper::Scraper;
use hero_researcher_lib::search::factory::build_search_provider;
use hero_researcher_lib::types::*;
use herolib_ai::AiClient;

let config = Config::from_env();
let ai_client = AiClient::from_env();

let researcher = Researcher::new(ai_client, &config)
 .with_tier(ResearchTier::Quick)
 .with_concurrency(2)
 .with_search_provider(build_search_provider(&config))
 .with_scraper(Scraper::new())
 .with_on_result(Box::new(|result| {
 println!("{}: {}", result.model, result.success);
 }));

let person = Person {
 name: "John Doe".into(),
 location: Some("New York".into()),
 aliases: vec!["J. Doe".into()],
 context: None,
};

let results = researcher.research(&person)?;

format_report

use hero_researcher_lib::formatter::format_report;
use hero_researcher_lib::types::*;

let report = format_report("John Doe", &results, OutputFormat::Markdown, &metadata);
println!("{}", report);

Disclaimer

This tool uses AI models to search for publicly available information.

• Results may be inaccurate, outdated, or hallucinated
• This is NOT an official background check
• Always verify information from official sources
• Respect privacy and applicable laws

License

Apache-2.0