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Updated titles into a consistent format. Fixed links to the diagrams. Fixed typos. Note: The Templates menu in the navbar is now sorted by the file names. I'll try sorting the navbar menus by the page titles, not the page file names.
78 lines
2.9 KiB
Markdown
78 lines
2.9 KiB
Markdown
# Cassandra - synonym caching
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This template provides a simple chain template showcasing the usage
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of LLM Caching backed by `Apache Cassandra®` or `Astra DB` through `CQL`.
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## Environment Setup
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To set up your environment, you will need the following:
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- an [Astra](https://astra.datastax.com) Vector Database (free tier is fine!). **You need a [Database Administrator token](https://awesome-astra.github.io/docs/pages/astra/create-token/#c-procedure)**, in particular the string starting with `AstraCS:...`;
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- likewise, get your [Database ID](https://awesome-astra.github.io/docs/pages/astra/faq/#where-should-i-find-a-database-identifier) ready, you will have to enter it below;
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- an **OpenAI API Key**. (More info [here](https://cassio.org/start_here/#llm-access), note that out-of-the-box this demo supports OpenAI unless you tinker with the code.)
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_Note:_ you can alternatively use a regular Cassandra cluster: to do so, make sure you 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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## 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 cassandra-synonym-caching
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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 cassandra-synonym-caching
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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 cassandra_synonym_caching import chain as cassandra_synonym_caching_chain
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add_routes(app, cassandra_synonym_caching_chain, path="/cassandra-synonym-caching")
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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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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
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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/cassandra-synonym-caching/playground](http://127.0.0.1:8000/cassandra-synonym-caching/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/cassandra-synonym-caching")
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```
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## Reference
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Stand-alone LangServe template repo: [here](https://github.com/hemidactylus/langserve_cassandra_synonym_caching).
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