competitive_analysis_agent

Competitive Analysis Agent

Below is the recommended setup for running and inspecting the competitive analysis deep agent example

UI Setup

To visualize and interact with the competitive analysis agent, we will be using the deep-agents-ui repo.

1. In a seperate directory/terminal, clone the repo

git clone https://github.com/langchain-ai/deep-agents-ui.git
cd deep-agents-ui

2. Create a .env.local file with the following environment variables

NEXT_PUBLIC_DEPLOYMENT_URL="http://127.0.0.1:2024"
NEXT_PUBLIC_AGENT_ID=competitive_analysis_agent

3. Install dependencies and launch the server

npm install
npm run dev

Open the interface on http://localhost:3000

Agent Setup

To run the agent, we will be using the LangGraph Platform

1. Clone this repo, navigate to the example, and install the requirements

git clone https://github.com/ALucek/deep-agents-walkthrough.git
cd deep-agents-walkthrough/competitive_analysis_agent
uv sync

2. Create a .env file with the following environment variables

TAVILY_API_KEY=<your_api_key_here>
OPENAI_API_KEY=<your_api_key_here>
LANGSMITH_API_KEY=<your_api_key_here>
LANGSMITH_TRACING=true
LANGSMITH_ENDPOINT=https://api.smith.langchain.com
LANGSMITH_PROJECT=deep_competitive_analysis

3. Launch a local LangGraph platform server

uv run langgraph dev

The competitive analysis agent will now be running on the local LangGraph server, and connected to the deep-agents-ui frontend.

Note: There is no persistent file storage system included. All data, conversations, and files are cleared when the frontend is closed.