Amazon Kendra + ChatGLM on SageMaker/Poe 进行中文增强搜索

英文增强搜索方案请参考以下链接：

https://aws.amazon.com/cn/blogs/machine-learning/quickly-build-high-accuracy-generative-ai-applications-on-enterprise-data-using-amazon-kendra-langchain-and-large-language-models/

Installing

Clone the repository

git clone https://github.com/micxyj/amazon-kendra-langchain-cn.git

Move to the repo dir

cd amazon-kendra-langchain-cn

Install the dependencies

pip install boto3
pip install langchain
pip install streamlit
pip install poe-api

Install the classes

pip install .

Usage

Creating an Amazon Kendra index and data source

https://docs.aws.amazon.com/kendra/latest/dg/what-is-kendra.html

Running samples

For executing sample chains, install the optional dependencies

pip install ".[samples]"

Configure AWS credential

https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-files.html

If using ChatGLM

Deploy ChatGLM on SageMaker

https://catalog.us-east-1.prod.workshops.aws/workshops/1ac668b1-dbd3-4b45-bf0a-5bc36138fcf1/zh-CN/3-configuration-llm/3-1-chatglm

Configure env

Ensure that the environment variables are set for the aws region, kendra index id and the provider/model used by the sample. For example, for running the kendra_chatGLM.py sample, these environment variables must be set: AWS_REGION, KENDRA_INDEX_ID and CHATGLM_ENDPOINT. You can use commands as below to set the environment variables.

export AWS_REGION="<YOUR-AWS-REGION>"
export KENDRA_INDEX_ID="<YOUR-KENDRA-INDEX-ID>"
export CHATGLM_ENDPOINT="<YOUR-SAGEMAKER-ENDPOINT-FOR-CHATGLM>"

Running samples from the streamlit app

The samples directory is bundled with an app.py file that can be run as a web app using streamlit.

cd samples
streamlit run app.py chatglm

If using Poe

You must get your Poe token first, you can reference: https://github.com/ading2210/poe-api/tree/main#finding-your-token

Current supported models on Poe:

• claude
• chatgpt
• sage
• claude+
• gpt4
• claude-instant-100k

You need configure model in env, just like:

export POE_MODEL="claude"

Configure env

export AWS_REGION="<YOUR-AWS-REGION>"
export KENDRA_INDEX_ID="<YOUR-KENDRA-INDEX-ID>"
export POE_TOKEN="<YOUR-POE-TOKEN>"
export POE_MODEL="<POE-MODEL>"

Running samples from the streamlit app

The samples directory is bundled with an app.py file that can be run as a web app using streamlit.

cd samples
streamlit run app.py poe

Running samples from the command line

python samples/<sample-file-name.py>

Uninstall

pip uninstall aws-langchain

Limit

1. 多轮对话能力弱，会出现中英文混合的问题，主要受限于 LangChain 的 prompt 是由英文构建的；
2. Poe 请求限流。