Skip to main content

Documentation Index

Fetch the complete documentation index at: https://mintlify.com/EllisYuan/ChatAgents/llms.txt

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

ChatAgents is an intelligent conversational assistant that breaks the knowledge-cutoff barrier by connecting your AI directly to the live web. Built on a hybrid Streamlit + FastAPI architecture, it uses LangGraph for agent orchestration and Tavily for real-time search, content extraction, and deep website crawling — so every answer can draw on the freshest information available, not just training data frozen in time.

Architecture Overview

ChatAgents runs as two cooperating services that you can start independently for development or containerize together for production:
ServiceTechnologyDefault Port
FrontendStreamlit8501
Backend APIFastAPI + LangGraph8080
The Streamlit frontend communicates with the FastAPI backend over HTTP, sending user messages and receiving server-sent streaming events in real time. Each service is built from the same Docker image, making the deployment footprint minimal.

Tech Stack

LayerTechnologyRole
FrontendStreamlitInteractive chat UI
BackendFastAPIAsync REST API + streaming
AgentLangGraphAgent graph orchestration
LLMsClaude / OpenAI / GroqLanguage model inference
ToolsTavilyWeb search, extract, crawl
InfraDocker + Docker ComposeContainerised deployment

Key Features

Real-time Web Search

Query the live web through Tavily’s AI-optimised search API. Fast mode returns 3 balanced results; Deep Thinking mode returns 5 with advanced depth.

Content Extraction

Precisely extract the key content from any web page URL, filtering noise and surfacing what the agent actually needs to answer your question.

Deep Website Crawl

Follow nested links to deeply crawl entire sites. Fast mode crawls up to 5 pages; Deep Thinking mode crawls up to 15, building a richer research picture.

Streaming Responses

Words appear token-by-token as the agent generates them. Tool calls — search, extract, crawl — are displayed inline so you can follow the agent’s reasoning live.

Session Management

Every conversation is assigned a unique session ID and persisted to disk. Switch between multiple sessions and revisit full conversation histories at any time.

Multi-Model LLM Support

Choose from Claude Haiku, Sonnet, or Opus for speed vs. quality trade-offs. OpenAI and Groq provider interfaces are available for teams that prefer those models.

Agent Modes

ChatAgents ships with two built-in operating modes that tune every Tavily parameter at once:
  • ⚡ Fast Mode — Uses basic search depth, 3 results, a crawl limit of 5 pages, and no images. Best for quick factual questions where low latency matters.
  • 🧠 Deep Thinking Mode — Uses advanced search depth, 5 results, a crawl limit of 15 pages, and image support. Best for in-depth research, competitive analysis, or multi-step reasoning tasks.

Prerequisites

Before you install ChatAgents, make sure you have the following:
  • Python 3.11 or later — required for the async features used throughout the codebase.
  • Anthropic Claude API key — create one at console.anthropic.com. Keys start with sk-ant-api-.
  • Tavily API key — register at tavily.com. Keys start with tvly-.
  • OpenAI API key (optional) — needed only if you want to use OpenAI models instead of Claude.
  • Groq API key (optional) — needed only if you want to use Groq-hosted models.
  • Docker + Docker Compose (optional) — required only for the containerised deployment path.

What’s Next

Quickstart

Install ChatAgents locally, configure your API keys, and have a running chat agent with live web search in under 5 minutes.

Docker Deployment

Run both services as containers with a single docker-compose up command — includes health checks and production Nginx guidance.

Build docs developers (and LLMs) love