This package uses open source models hosted on FireworksAI to do retrieval using an agent architecture. By default, this does retrieval over Arxiv.
We will use `Mixtral8x7b-instruct-v0.1`, which is shown in this blog to yield reasonable
results with function calling even though it is not fine tuned for this task: https://huggingface.co/blog/open-source-llms-as-agents
## Environment Setup
There are various great ways to run OSS models. We will use FireworksAI as an easy way to run the models. See [here](https://python.langchain.com/docs/integrations/providers/fireworks) for more information.
Set the `FIREWORKS_API_KEY` environment variable to access Fireworks.
## Usage
To use this package, you should first have the LangChain CLI installed:
```shell
pip install -U langchain-cli
```
To create a new LangChain project and install this as the only package, you can do:
```shell
langchain app new my-app --package retrieval-agent-fireworks
```
If you want to add this to an existing project, you can just run:
```shell
langchain app add retrieval-agent-fireworks
```
And add the following code to your `server.py` file:
```python
from retrieval_agent_fireworks import chain as retrieval_agent_fireworks_chain
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/retrieval-agent-fireworks/playground](http://127.0.0.1:8000/retrieval-agent-fireworks/playground)
