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# cassandra-entomology-rag
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This template will perform RAG using Apache Cassandra® or Astra DB through CQL (`Cassandra` vector store class)
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## Environment Setup
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For the setup, you will require:
- an [Astra ](https://astra.datastax.com ) Vector Database. You must have a [Database Administrator token ](https://awesome-astra.github.io/docs/pages/astra/create-token/#c-procedure ), specifically the string starting with `AstraCS:...` .
- [Database ID ](https://awesome-astra.github.io/docs/pages/astra/faq/#where-should-i-find-a-database-identifier ).
- an **OpenAI API Key** . (More info [here ](https://cassio.org/start_here/#llm-access ))
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You may also use a regular Cassandra cluster. In this case, provide the `USE_CASSANDRA_CLUSTER` entry as shown in `.env.template` and the subsequent environment variables to specify how to connect to it.
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The connection parameters and secrets must be provided through environment variables. Refer to `.env.template` for the required variables.
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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:
```shell
langchain app new my-app --package cassandra-entomology-rag
```
If you want to add this to an existing project, you can just run:
```shell
langchain app add cassandra-entomology-rag
```
And add the following code to your `server.py` file:
```python
from cassandra_entomology_rag import chain as cassandra_entomology_rag_chain
add_routes(app, cassandra_entomology_rag_chain, path="/cassandra-entomology-rag")
```
(Optional) Let's now configure LangSmith.
LangSmith will help us trace, monitor and debug LangChain applications.
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You can sign up for LangSmith [here ](https://smith.langchain.com/ ).
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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:
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```shell
langchain serve
```
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This will start the FastAPI app with a server is running locally at
[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 )
We can access the playground at [http://127.0.0.1:8000/cassandra-entomology-rag/playground ](http://127.0.0.1:8000/cassandra-entomology-rag/playground )
We can access the template from code with:
```python
from langserve.client import RemoteRunnable
runnable = RemoteRunnable("http://localhost:8000/cassandra-entomology-rag")
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```
## Reference
Stand-alone repo with LangServe chain: [here ](https://github.com/hemidactylus/langserve_cassandra_entomology_rag ).