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This PR adds a simple LangChain template that uses [Anthropic's Claude on Amazon Bedrock ⛰️](https://aws.amazon.com/bedrock/claude/) to behave like JCVD. --------- Co-authored-by: Erick Friis <erick@langchain.dev>
81 lines
3.3 KiB
Markdown
81 lines
3.3 KiB
Markdown
# Bedrock JCVD 🕺🥋
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## Overview
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LangChain template that uses [Anthropic's Claude on Amazon Bedrock](https://aws.amazon.com/bedrock/claude/) to behave like JCVD.
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> I am the Fred Astaire of Chatbots! 🕺
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'
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## Environment Setup
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### AWS Credentials
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This template uses [Boto3](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html), the AWS SDK for Python, to call [Amazon Bedrock](https://aws.amazon.com/bedrock/). You **must** configure both AWS credentials *and* an AWS Region in order to make requests.
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> For information on how to do this, see [AWS Boto3 documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html) (Developer Guide > Credentials).
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### Foundation Models
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By default, this template uses [Anthropic's Claude v2](https://aws.amazon.com/about-aws/whats-new/2023/08/claude-2-foundation-model-anthropic-amazon-bedrock/) (`anthropic.claude-v2`).
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> To request access to a specific model, check out the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access.html) (Model access)
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To use a different model, set the environment variable `BEDROCK_JCVD_MODEL_ID`. A list of base models is available in the [Amazon Bedrock User Guide](https://docs.aws.amazon.com/bedrock/latest/userguide/model-ids-arns.html) (Use the API > API operations > Run inference > Base Model IDs).
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> The full list of available models (including base and [custom models](https://docs.aws.amazon.com/bedrock/latest/userguide/custom-models.html)) is available in the [Amazon Bedrock Console](https://docs.aws.amazon.com/bedrock/latest/userguide/using-console.html) under **Foundation Models** or by calling [`aws bedrock list-foundation-models`](https://docs.aws.amazon.com/cli/latest/reference/bedrock/list-foundation-models.html).
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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 bedrock-jcvd
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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 bedrock-jcvd
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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 bedrock_jcvd import chain as bedrock_jcvd_chain
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add_routes(app, bedrock_jcvd_chain, path="/bedrock-jcvd")
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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 also access the playground at [http://127.0.0.1:8000/bedrock-jcvd/playground](http://127.0.0.1:8000/bedrock-jcvd/playground)
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