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remove mentions of the exact domain from the content (#902)

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* remove mentions of the exact domain from the content

* fix links

* fix links
This commit is contained in:
Andrey Vasnetsov
2024-05-15 18:01:28 +02:00
committed by GitHub
parent 72016345ca
commit 9894eac76e
23 changed files with 38 additions and 38 deletions
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qdrant-landing/content/documentation/examples/rag-chatbot-red-hat-openshift-haystack.md
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@@ -25,7 +25,7 @@ To maintain complete data isolation, we need to limit ourselves to open-source t
- **LLM:** `mistralai/Mistral-7B-Instruct-v0.1`, deployed as a standalone service on OpenShift.
- **Embedding Model:** `BAAI/bge-base-en-v1.5`, lightweight embedding model deployed from within the Haystack pipeline
with [FastEmbed](https://github.com/qdrant/fastembed)
- **Vector DB:** [Qdrant Hybrid Cloud](https://qdrant.tech) running on OpenShift.
- **Vector DB:** [Qdrant Hybrid Cloud](https://hybrid-cloud.qdrant.tech) running on OpenShift.
- **Framework:** [Haystack 2.x](https://haystack.deepset.ai/) to connect all and [Hayhooks](https://docs.haystack.deepset.ai/docs/hayhooks) to serve the app through HTTP endpoints.
### Procedure
@@ -458,4 +458,4 @@ The response should be similar to the one we got in the Python before:
- [Haystack's documentation](https://docs.haystack.deepset.ai/docs/kubernetes) describes [how to deploy the Hayhooks service in a Kubernetes
environment](https://docs.haystack.deepset.ai/docs/kubernetes), so you can easily move it to your own OpenShift infrastructure.
- If you are just getting started and need more guidance on Qdrant, read the [quickstart](https://qdrant.tech/documentation/quick-start/) or try out our [beginner tutorial](https://qdrant.tech/documentation/tutorials/neural-search/).
- If you are just getting started and need more guidance on Qdrant, read the [quickstart](/documentation/quick-start/) or try out our [beginner tutorial](/documentation/tutorials/neural-search/).