Build a cultural tourism assistant with OceanBase multi-model integration

This topic describes how to build a cultural tourism assistant using OceanBase multi-model integration.

Prerequisites

• You have deployed OceanBase V4.3.3 or later and created a MySQL-compatible tenant. For more information about deploying OceanBase clusters, see Deployment overview.

• The MySQL-compatible tenant you created has the INSERT and SELECT privileges. For more information about setting privileges, see Directly grant privileges.

• You have created a database. For more information about creating a database, see Create a database.

• Vector search is enabled for the database. For more information about the vector search feature, see Perform fast vector search by using SQL.

  obclient> ALTER SYSTEM SET ob_vector_memory_limit_percentage = 30;
  

• (Recommended, not required) Install Python 3.10 and later and the corresponding pip. If your machine has a low Python version, you can use Miniconda to create a new Python 3.10 or later environment. For more information, see Miniconda installation guide.

  conda create -n obmms python=3.10 && conda activate obmms
  

• Install Poetry. You can refer to the following command:

  python3 -m ensurepip
  python3 -m pip install poetry
  

• Install the required Python packages. You can use the following command:

  pip install python-dotenv tqdm streamlit pyobvector==0.2.16
  

Step 1: Obtain the LLM API key

Register for an account with Alibaba Cloud Model Studio, activate the model service, and obtain an API key.

Step 2: Obtain a geographic service API key

Register on the Amap Open Platform and obtain an API key for basic LBS services.

Step 3: Download the public dataset

Download the China City Attraction Details dataset ZIP package from Kaggle.

Step 4: Build your cultural tourism assistant

Clone the project repository

1. Clone the latest project repository.

   git clone https://github.com/oceanbase-devhub/ob-multi-model-search-demo.git
   cd ob-multi-model-search-demo
   

2. Move the downloaded archive dataset ZIP package to the ob-multi-model-search-demo project folder, rename it to citydata, and decompress it.

   # Replace with the actual path where the archive.zip file is saved
   mv ./archive.zip ./citydata.zip
   unzip ./citydata.zip
   

Install dependencies

Run the following command in the project root directory to install dependencies.

poetry install

Set environment variables

Set the environment variables in the .env file:

vim .env

Update the variables starting with OB_ with your database connection information, and manually add the following variables: set DASHSCOPE_API_KEY to the API key you obtained from the Alibaba Cloud Bailian console, and set AMAP_API_KEY to the API key you obtained from the Amap API service. Then save the file.

# Host address in the database connection string
OB_URL="******"
OB_USER="******"
OB_DB_NAME="******"
# Password in the database connection string
OB_PWD="******"
# Optional SSL CA file path in the database connection string. If you do not need SSL encryption, remove this parameter.
OB_DB_SSL_CA_PATH="******"

# Manually add LLM API key
DASHSCOPE_API_KEY="******"
# Manually add Amap API key
AMAP_API_KEY="******"

Import data

In this step, we import the data from the downloaded dataset into OceanBase.

python ./obmms/data/attraction_data_preprocessor.py

The following progress indicates that data is being imported successfully.

...
./citydata/Changde.csv:
100%|███████████████████████████████████████████████████████████████████████████| 100/100 [00:04<00:00, 20.77it/s]
./citydata/Weinan.csv:
100%|█████████████████████████████████████████████████████████████████████████████| 90/90 [00:13<00:00,  6.54it/s]
...

Start the UI chat interface

Run the following command to start the chat interface:

poetry run streamlit run ./ui.py

If no web page opens automatically, access the URL displayed in the terminal to open the tourism assistant application interface.

  You can now view your Streamlit app in your browser.

  Local URL: http://localhost:8501
  Network URL: http://172.xxx.xxx.xxx:8501

Troubleshooting

Dependency installation issues

Poetry installation failure

If the poetry install command fails, try the following steps:

1. Update Poetry to the latest version:

   pip install --upgrade poetry
   

2. Clear the Poetry cache:

   poetry cache clear --all pypi
   

3. Reinstall dependencies:

   poetry install --no-cache
   

Environment configuration issues

Python environment not activated

Ensure that you have activated the correct conda environment:

conda activate obmms

Incompatible Python version

Ensure that you use Python 3.10 or later:

python --version

If the version is too low, recreate the environment:

conda create -n obmms python=3.10
conda activate obmms

Database connection issues

If you encounter database connection issues, check:

1. Whether the database connection information in the .env file is correct
2. Whether the OceanBase cluster is running properly
3. Whether the network connection is normal
4. Whether the database user has sufficient privileges

Other common issues

Port in use

If Streamlit reports that the port is in use when starting, you can specify another port:

poetry run streamlit run ./ui.py --server.port 8502

Insufficient memory

If you encounter insufficient memory during data import, you can:

1. Reduce the batch import data volume
2. Increase system memory
3. Adjust the OceanBase memory configuration

API key issues

Ensure that you have correctly configured:

1. Alibaba Cloud Bailian API key (DASHSCOPE_API_KEY)
2. Amap API key (AMAP_API_KEY)

API keys can be configured in the .env file.