You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
73 lines
2.2 KiB
73 lines
2.2 KiB
2 weeks ago
|
# 🌐 Deployment
|
||
|
|
|
||
|
|
This guide explains how to deploy DeepSearcher as a web service.
|
||
|
|
|
||
|
|
## ⚙️ Configure Modules
|
||
|
|
|
||
|
|
You can configure all arguments by modifying the configuration file:
|
||
|
|
|
||
|
|
```yaml
|
||
|
|
# config.yaml - https://github.com/zilliztech/deep-searcher/blob/main/config.yaml
|
||
|
|
llm:
|
||
|
|
provider: "OpenAI"
|
||
|
|
api_key: "your_openai_api_key_here"
|
||
|
|
# Additional configuration options...
|
||
|
|
```
|
||
|
|
|
||
|
|
> **Important:** Set your `OPENAI_API_KEY` in the `llm` section of the YAML file.
|
||
|
|
|
||
|
|
## 🚀 Start Service
|
||
|
|
|
||
|
|
The main script will run a FastAPI service with default address `localhost:8000`:
|
||
|
|
|
||
|
|
```shell
|
||
|
|
$ python main.py
|
||
|
|
```
|
||
|
|
|
||
|
|
Once started, you should see output indicating the service is running successfully.
|
||
|
|
|
||
|
|
## 🔍 Access via Browser
|
||
|
|
|
||
|
|
You can access the web service through your browser:
|
||
|
|
|
||
|
|
1. Open your browser and navigate to [http://localhost:8000/docs](http://localhost:8000/docs)
|
||
|
|
2. The Swagger UI will display all available API endpoints
|
||
|
|
3. Click the "Try it out" button on any endpoint to interact with it
|
||
|
|
4. Fill in the required parameters and execute the request
|
||
|
|
|
||
|
|
This interactive documentation makes it easy to test and use all DeepSearcher API functionality.
|
||
|
|
|
||
|
|
## 🐳 Docker Deployment
|
||
|
|
|
||
|
|
You can also deploy DeepSearcher using Docker for easier environment setup and management.
|
||
|
|
|
||
|
|
### Build Docker Image
|
||
|
|
|
||
|
|
To build the Docker image, run the following command from the project root directory:
|
||
|
|
|
||
|
|
```shell
|
||
|
|
docker build -t deepsearcher:latest .
|
||
|
|
```
|
||
|
|
|
||
|
|
This command builds a Docker image using the Dockerfile in the current directory and tags it as `deepsearcher:latest`.
|
||
|
|
|
||
|
|
### Run Docker Container
|
||
|
|
|
||
|
|
Once the image is built, you can run it as a container:
|
||
|
|
|
||
|
|
```shell
|
||
|
|
docker run -p 8000:8000 \
|
||
|
|
-e OPENAI_API_KEY=your_openai_api_key \
|
||
|
|
-v $(pwd)/data:/app/data \
|
||
|
|
-v $(pwd)/logs:/app/logs \
|
||
|
|
-v $(pwd)/deepsearcher/config.yaml:/app/deepsearcher/config.yaml \
|
||
|
|
deepsearcher:latest
|
||
|
|
```
|
||
|
|
|
||
|
|
This command:
|
||
|
|
- Maps port 8000 from the container to port 8000 on your host
|
||
|
|
- Sets the `OPENAI_API_KEY` environment variable
|
||
|
|
- Mounts the local `data`, `logs`, and configuration file to the container
|
||
|
|
- Runs the previously built `deepsearcher:latest` image
|
||
|
|
|
||
|
|
> **Note:** Replace `your_openai_api_key` with your actual OpenAI API key, or set any other environment variables required for your configuration.
|