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ADDITIONAL_README.md

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+# Multilingual Colbert embeddings as a service
+
+## Goal
+
+- Deploy [Antoine Louis](https://huggingface.co/antoinelouis)' [colbert-xm](https://huggingface.co/antoinelouis/colbert-xm) as an inference service: text(s) in, vector(s) out
+
+## Motivation
+
+- use the service in a broader RAG solution
+
+## Steps followed
+
+- Clone the original repo following [this procedure](https://huggingface.co/docs/hub/repositories-next-steps#how-to-duplicate-or-fork-a-repo-including-lfs-pointers)
+- Add a custom handler script as described [here](https://huggingface.co/docs/inference-endpoints/guides/custom_handler)
+
+## Local development and testing
+
+### Build and start docker container hf_endpoints_emulator
+
+See [hf_endpoints_emulator](https://pypi.org/project/hf-endpoints-emulator/)
+
+````bash
+docker-compose up -d --build
+````
+
+This can take a few moments to load, given the size of the model (> 3 GB)!
+
+## How to test locally
+
+```bash
+./embed_single_query.sh
+./embed_two_chunks.sh
+```
+
+```bash
+docker-compose exec hf_endpoints_emulator pytest
+```
+
+## Check output
+
+```bash
+docker-compose logs --follow hf_endpoints_emulator
+```