Add instructions to run it as a docker container

- Note that it requires Milvus to be installed
  elsewhere (also in docker or iron or cloud).

Author: stronk7

README.md

@@ -17,6 +17,15 @@ To get started with Wiki-RAG, ensure you have the following:
 - [Docker](https://www.docker.com/get-started) (if you intend to run the project using Docker)
 - [Milvus 2.5.5](https://milvus.io/docs/release_notes.md#v255) or later (for vector similarity search). Standalone or Distributed deployments are supported. Lite deployments are not supported. It's highly recommended to use the [Docker Compose deployment](https://milvus.io/docs/install_standalone-docker-compose.md) specially for testing and development purposes.
 
+## Configuration
+
+1. **Set Environment Variables (to be replaced soon by `config.yml`file)**
+   - Using the [env_template](env_template) file as source, create a new `.env` file:
+     ```bash
+     cp env_template .env
+     ```
+   - Edit it to suit your needs (mediawiki site and namespaces or exclusions, models to use for both embeddings and generation, etc.)
+
 ## Installation
 
 ### Running Locally
@@ -42,29 +51,45 @@ To get started with Wiki-RAG, ensure you have the following:
     pip install -e .[dev]
     ```
 
-4. **Set Environment Variables**:
-   - Using the [env_template](env_template) file as source, create a new `.env` file:
-     ```bash
-     cp env_template .env
-     ```
-   - Edit it to suit your needs (mediawiki site and namespaces or exclusions, models to use for both embeddings and generation, etc.)
-
-5. **Run the Application**:
+4. **Run the Application**:
    The application comes with four different executables:
    - `wr-load`: Will parse all the configured pages in the source Mediawiki site, extracting contents and other important metadata. All the generated information will be stored into a JSON file in the `data` directory.
    - `wr-index`: In charge of creating the collection in the vector index (Milvus) with all the information extracted in the previous step.
    - `wr-search`: A tiny CLI utility to perform searches against the RAG system from the command line.
    - `wr-server`: A comprehensive and secure web service (documented with OpenAPI) that allows users to interact with the RAG system using the OpenAI API (`v1/models` and `v1/chat/completions` endpoints) as if it were a large language model (LLM).
 
-### Running with Docker
+### Running with Docker (Milvus elsewhere)
 
-   _Coming soon..._
+1. Pull the image from GitHub [Container Registry](https://github.com/moodlehq/wiki-rag/pkgs/container/wiki-rag):
+   ```bash
+   docker pull ghcr.io/moodlehq/wiki-rag:latest  # or specify a tag
+   ```
+
+2. Create local "data" directory and run the container:
+   ```bash
+   mkdir data
+   docker run --rm --detach \
+       --volume $(pwd)/data:/app/data \
+       --volume $(pwd)/.env:/app/.env \
+       --env MILVUS_URL=http://milvus-standalone:19530 \
+       --network milvus \
+       --publish 8080:8080 \
+       --env OPENAI_API_KEY=YOUR_OPENAI_API_KEY \
+       --env LOG_LEVEL=info \
+       --name wiki-rag \
+       wiki-rag:latest
+   ```
+   - Note 1: The command above will start the `wr-server` automatically, listening on the configured port (8080) and the `OPENAI_API_KEY` is required to interact with the embedding and LLM models. If, instead, you want to execute any of the other commands (`wr-load`, `wr-index`, `wr-search`), you can specify it as the last argument.
+   - Note 2: The 2 lines related to Milvus are required to connect to the Milvus server **if also running in Docker**. If it's running elsewhere, you can replace the `MILVUS_URL` with the appropriate URL or configure it in the `.env` file instead
+   - Note 3: You can use `docker logs wiki-rag` to check the logs of the running container (`wr-server` logs).
+   - Note 4: When running the `wr-server`, you still can execute any of the commands (`wr-load`, `wr-index`, `wr-search`) using `docker exec -it wiki-rag <command>`.
+   - Note 5: To stop and remove the container, you can use `docker stop wiki-rag`.
 
-### Features
+## Features
 
    _Coming soon..._
 
-### Future Work
+## Future Work
 
    _Coming soon..._
 

env_template

@@ -24,7 +24,7 @@ EMBEDDING_DIMENSIONS=768
 LLM_MODEL="your_llm_model"
 
 # OpenAI wrapper base URL.
-WRAPPER_API_BASE="0.0.0.0:8000"
+WRAPPER_API_BASE="0.0.0.0:8080"
  # To limit the number of OpenAI history turns allowed in a chat (0 = no limit).
 WRAPPER_CHAT_MAX_TURNS=10
 # To limit the number of OpenAI history tokens allowed in a chat (0 = no limit).