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https://github.com/hwchase17/langchain
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51c8ef6af4
- FIX templates/retrieval-agent/retireval-agent/chain.py to use the new Syntax for Azure env params - cr --------- Co-authored-by: braun-viathan <p.braun@viathan.de> Co-authored-by: Braun-viathan <121631422+braun-viathan@users.noreply.github.com>
73 lines
2.0 KiB
Markdown
73 lines
2.0 KiB
Markdown
# retrieval-agent
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This package uses Azure OpenAI to do retrieval using an agent architecture.
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By default, this does retrieval over Arxiv.
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## Environment Setup
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Since we are using Azure OpenAI, we will need to set the following environment variables:
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```shell
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export AZURE_OPENAI_ENDPOINT=...
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export AZURE_OPENAI_API_VERSION=...
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export AZURE_OPENAI_API_KEY=...
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```
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## Usage
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To use this package, you should first have the LangChain CLI installed:
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```shell
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pip install -U langchain-cli
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```
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To create a new LangChain project and install this as the only package, you can do:
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```shell
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langchain app new my-app --package retrieval-agent
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```
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If you want to add this to an existing project, you can just run:
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```shell
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langchain app add retrieval-agent
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```
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And add the following code to your `server.py` file:
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```python
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from retrieval_agent import chain as retrieval_agent_chain
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add_routes(app, retrieval_agent_chain, path="/retrieval-agent")
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```
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(Optional) Let's now configure LangSmith.
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LangSmith will help us trace, monitor and debug LangChain applications.
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LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/).
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If you don't have access, you can skip this section
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```shell
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export LANGCHAIN_TRACING_V2=true
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export LANGCHAIN_API_KEY=<your-api-key>
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export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default"
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```
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If you are inside this directory, then you can spin up a LangServe instance directly by:
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```shell
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langchain serve
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```
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This will start the FastAPI app with a server is running locally at
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[http://localhost:8000](http://localhost:8000)
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We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
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We can access the playground at [http://127.0.0.1:8000/retrieval-agent/playground](http://127.0.0.1:8000/retrieval-agent/playground)
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We can access the template from code with:
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```python
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from langserve.client import RemoteRunnable
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runnable = RemoteRunnable("http://localhost:8000/retrieval-agent")
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``` |