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1 | | -# FUNDus! MuRAG |
| 1 | +# CollEx |
2 | 2 |
|
3 | | -This repo contains the code for the FUNUus! MuRAG System -- a multimodal RAG-based Assistant to explore the FUNDus! database. |
| 3 | +This repo contains the code for the CollEx System -- a multimodal RAG-based Assistant to explore the CollEx database. |
4 | 4 |
|
5 | 5 | ## Starting the system in Production Mode |
6 | 6 |
|
7 | 7 | ### Prerequisites |
8 | 8 |
|
9 | 9 | #### Getting the data |
10 | 10 |
|
11 | | -_Note that this only works for LT and HCDS members. If you are not a member, you can request access to the data by contacting the [Florian Schneider](mailto:florian.schneider-1@uni-hamburg.de)._ |
| 11 | +_Note that this only works for REDACTED members. If you are not a member, you can request access to the data by contacting [ANOYMIZED](mailto:anonymized@anonoymous.org)._ |
12 | 12 |
|
13 | 13 | 1. Create a folder `data` in the root of the project |
14 | 14 | 2. Copy the DataFrames from `/ltstorage/shares/projects/fundus-murag/data` to the `data` folder |
@@ -54,11 +54,9 @@ You only need to do this if you want to run the ML service locally, e.g., to cha |
54 | 54 | 1. Navigate to the `docker` folder |
55 | 55 | 2. (Optional) If you run the ML service in development mode, remove the `fundusml` profile from the `.env.dev` |
56 | 56 | 3. Run `docker compose --env-file .env.dev up` in a `tmux` or similar shell to start the dev containers (i.e., Weaviate) |
57 | | -4. Run `curl http://localhost:<YOUR_FUNDUS_ML_EXPOSED_PORT>/embed` to check whether the FUNDus ML Service is up and running. This should print sth. like `{"detail":"Method Not Allowed"}` |
| 57 | +4. Run `curl http://localhost:<YOUR_FUNDUS_ML_EXPOSED_PORT>/embed` to check whether the CollEx ML Service is up and running. This should print sth. like `{"detail":"Method Not Allowed"}` |
58 | 58 |
|
59 | | -### Starting the FUNDus MuRAG Application for Development |
| 59 | +### Starting the CollEx Application for Development |
60 | 60 |
|
61 | | -1. Navigate to repository root |
62 | | -2. Select a port of your choice (e.g., the `FUNDUS_UI_EXPOSED` defined in the `docker/.env` file) |
63 | | -3. Run `FUNDUS_CONFIG_FILE=config.dev.yaml PYTHONPATH=src mesop --port <PORT OF YOUR CHOICE> src/fundus_murag/ui/main.py` to start the FUNDus MuRAG application. |
64 | | -4. Open your browser and navigate to `http://localhost:<PORT OF YOUR CHOICE>` to see the application. Don't forget to forward the port if you are running the application on a remote server. |
| 61 | +1. Open the project in VS Code |
| 62 | +2. Run the application as defined in the `launch.json` |
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