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#### 4. **Deploying in a Containerized Environment**
#If you're using Docker or Podman, ensure the containers can communicate with each other. For example:
#- **Docker Compose**:
# Create a `docker-compose.yml` file to define both the model server and the chat application:
#```yaml
version: "3"
services:
model_server:
image: my_model_server_image
ports:
- "8001:8001"
environment:
- PORT=8001
networks:
- my_network
chat_app:
image: my_chat_app_image
environment:
- MODEL_ENDPOINT=http://model_server:8001
depends_on:
- model_server
networks:
- my_network
networks:
my_network:
#```
#- The `MODEL_ENDPOINT` for the chat application is set to `http://model_server:8001`, which uses Docker's internal DNS to resolve the model server's container name.
#- **Docker Networking**:
# If you're not using Docker Compose, you can create a custom network and attach both containers to it:
# ```bash
# Create a custom network
# docker network create my_network
# Run the model server container
# docker run -d --name model_server --network my_network -p 8001:8001 my_model_server_image
# Run the chat application container
# docker run -d --name chat_app --network my_network -e MODEL_ENDPOINT=http://model_server:8001 my_chat_app_image
#### 5. **Testing the Endpoint**
#To ensure the model server is working as expected, you can test the endpoint directly using `curl` or a tool like Postman:
#```bash
#curl -X POST http://localhost:8001/generate -H "Content-Type: application/json" -d '{"prompt": "Hello, model!"}'
#```
#Expected response:
#```json
#{
# "response": "Generated response for: Hello, model!"
#}
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