Demo

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Build a Demo

At a minimum, Akcio requires Large Language Model (LLM) API and a vector database to work properly. Before getting started, you need to have an LLM API token at hand from one of the [supported LLM API providers] and a running vector database that Akcio can establish connection with.

For example, if you're using default modules, you should prepare:

• LLM: OpenAI API Key. You can get your key here.
• Vector Databases: Milvus or Zilliz Cloud vector database.

Follow steps below to build a demo with Gradio web UI:

1. Download

   $ git clone https://github.com/zilliztech/akcio.git
   $ cd akcio

2. Installation

   $ pip install -r requirements.txt

3. Configuration

   • Set up LLM API and the connection with a vector database:

     $ export OPENAI_API_KEY=your_keys_here  # Make sure your API key has access/credits for the selected service (default: gpt-3.5-turbo)
     $ export ZILLIZ_URI=https://localhost:19530  # For local-hosted Milvus at port 19530. If using Zilliz Cloud, replace with the endpoint shown on the cluster page.
     $ export ZILLIZ_TOKEN=your_cluster_api_key # Only required if using Zilliz Cloud vector database.
     $ export SQL_URI=sqlite:///./sqlite.db  # This will use SQLite with storage at ./sqlite.db

   • [Optional] Enable scalar store using Elastic:

     $ export USE_SCALAR=True
     $ export ES_CLOUD_ID=your_elastic_cloud_id
     $ export ES_USER=your_elastic_username
     $ export ES_PASSWORD=your_elastic_password

   Refer to Configuration for more detailed instructions.

4. Start Gradio

   python gradio_demo.py --towhee
   # python gradio_demo.py --langchain

   

5. Open in browser

   Open local or public url returned by step 4 to access the online demo.

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