This commit is contained in:
jacoblee93
2024-09-26 08:32:06 -07:00
+3 -2
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@@ -14,8 +14,9 @@ This demo requires an [OpenAI API key](https://openai.com/) and a [Tavily API ke
2. Rename the existing `.env.example` file `.env` and fill in your `OPENAI_API_KEY` and `TAVILY_API_KEY`.
3. Download the latest release of LangGraph Studio [from here](https://github.com/langchain-ai/langgraph-studio/releases).
4. Log in/sign up for [LangSmith](https://smith.langchain.com/) if you haven't already.
5. Open the enclosing folder in LangGraph Studio.
6. Start testing your app!
5. Ensure Docker is running. You can [download Docker here](https://www.docker.com/) and install it if you don't have it already.
6. Open the enclosing folder in LangGraph Studio.
7. Start testing your app!
The graph has access to a web search tool powered by [Tavily](https://tavily.com) - you can try asking it about current events like `"What is the current conservation status of the Great Barrier Reef?"` and watch the model use the tool.