# retrieval-agent-fireworks 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 add_routes(app, retrieval_agent_fireworks_chain, path="/retrieval-agent-fireworks") ``` (Optional) Let's now configure LangSmith. LangSmith will help us trace, monitor and debug LangChain applications. You can sign up for LangSmith [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= export LANGCHAIN_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) We can access the template from code with: ```python from langserve.client import RemoteRunnable runnable = RemoteRunnable("http://localhost:8000/retrieval-agent-fireworks") ```