Readme rewrite (#12615)

Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
This commit is contained in:
Erick Friis
2023-10-31 00:06:02 -07:00
committed by GitHub
parent 00766c9f31
commit a1fae1fddd
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# OpenAI Functions Agent
This template creates an agent that uses OpenAI function calling to communicate its decisions of what actions to take.
This example creates an agent that can optionally look up things on the internet using Tavily's search engine.
# openai-functions-agent
## LLM
This template creates an agent that uses OpenAI function calling to communicate its decisions on what actions to take.
This template will use `OpenAI` by default.
This example creates an agent that can optionally look up information on the internet using Tavily's search engine.
Be sure that `OPENAI_API_KEY` is set in your environment.
## Environment Setup
## Tools
The following environment variables need to be set:
This template will use `Tavily` by default.
Set the `OPENAI_API_KEY` environment variable to access the OpenAI models.
Be sure that `TAVILY_API_KEY` is set in your environment.
Set the `TAVILY_API_KEY` environment variable to access Tavily.
## Usage
To use this package, you should first have the LangChain CLI installed:
```shell
pip install -U "langchain-cli[serve]"
```
To create a new LangChain project and install this as the only package, you can do:
```shell
langchain app new my-app --package openai-functions-agent
```
If you want to add this to an existing project, you can just run:
```shell
langchain app add openai-functions-agent
```
And add the following code to your `server.py` file:
```python
from openai_functions_agent import chain as openai_functions_agent_chain
add_routes(app, openai_functions_agent_chain, path="/openai-functions-agent")
```
(Optional) Let's now configure LangSmith.
LangSmith will help us trace, monitor and debug LangChain applications.
LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/).
If you don't have access, you can skip this section
```shell
export LANGCHAIN_TRACING_V2=true
export LANGCHAIN_API_KEY=<your-api-key>
export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
```
If you are inside this directory, then you can spin up a LangServe instance directly by:
```shell
langchain serve
```
This will start the FastAPI app with a server is running locally at
[http://localhost:8000](http://localhost:8000)
We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
We can access the playground at [http://127.0.0.1:8000/openai-functions-agent/playground](http://127.0.0.1:8000/openai-functions-agent/playground)
We can access the template from code with:
```python
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/openai-functions-agent")
```