Skip to main content

Documentation Index

Fetch the complete documentation index at: https://mintlify.com/getcompanion-ai/feynman/llms.txt

Use this file to discover all available pages before exploring further.

Feynman’s web search tool retrieves current information from the web during research workflows. It supports multiple simultaneous queries, domain filtering, recency filtering, and full-page content retrieval. The Researcher agent uses web search alongside AlphaXiv to gather evidence from non-academic sources.

​
Default behavior

The default path is zero-config Gemini grounding via a signed-in Chromium profile. No API keys are required. This works on macOS and Linux where a Chromium-based browser is installed and signed in to a Google account. For headless environments, CI pipelines, or servers without a browser, configure an explicit API key for Perplexity or Gemini.

​
Routing modes

Feynman supports three web search backends:
ModeDescription
autoPrefer Perplexity when a key is configured, fall back to Gemini.
perplexityForce Perplexity Sonar for all web searches.
geminiForce Gemini grounding (zero-config default).

​
Configuration

Check the current search configuration: 
feynman search status
This prints the active route, configured providers, browser profile, and config file path. Edit ~/.feynman/web-search.json to configure the backend: 
{
  "route": "auto",
  "perplexityApiKey": "pplx-...",
  "geminiApiKey": "AIza..."
}
Set route to auto, perplexity, or gemini. When using auto, Feynman prefers Perplexity if a key is present, then falls back to Gemini.

​
Search features

The web search tool exposes several capabilities that the Researcher uses automatically:
  • Multiple queries — Send 2–4 varied-angle queries simultaneously for broader topic coverage. The Researcher generates queries from different angles to catch sources that use different terminology.
  • Domain filtering — Restrict results to specific domains such as arxiv.org, github.com, or nature.com using domainFilter.
  • Recency filtering — Filter results by date using recencyFilter, useful for fast-moving topics where only recent work matters.
  • Full content retrieval — Fetch complete page content for the most important results using includeContent: true, rather than relying on snippets alone.
Use web search and paper search for different kinds of questions:
  • Current products, companies, and markets
  • Model availability and pricing
  • Software releases and documentation
  • Regulations, news, and recent events
  • Anything phrased as “latest”, “current”, “recent”, or “today”
  • Engineering topics with official docs and code repositories
Never answer a latest/current question from paper search alone. Academic databases lag current events. For AI model or product claims, prefer official vendor pages and recent web sources over old papers.
For mixed topics — such as a new model that has both a launch announcement and a companion paper — the Researcher combines both channels: web sources for current reality and paper sources for the underlying research. Session search lets you recover prior Feynman work from stored session transcripts. Every Feynman session is persisted to disk at ~/.feynman/sessions/. Session search is an optional package. Install it with: 
feynman packages install session-search
Once installed, the /search slash command becomes available in all future sessions: 
/search transformer scaling laws
You can also reference prior work naturally in conversation. Feynman invokes session search automatically when you mention previous research or ask to continue earlier work — for example, “pick up where I left off on protein folding.” What session search indexes:
  • Full session transcripts including your prompts and Feynman’s responses
  • Tool outputs and agent results from workflows
  • Generated artifacts such as drafts, reports, and comparison matrices
  • Metadata like timestamps, topics, and workflow types
The search uses both keyword matching and semantic similarity. Results include the session ID, timestamp, and relevant excerpts so you can identify which session contains the information you need.
Use session search before launching a new round of research on a topic you have investigated before. It can surface prior findings, citations, and artifacts without re-running an expensive workflow.

Build docs developers (and LLMs) love

Get started for freeTalk to us