Add user feedback buttons to UI to collect domain-specifc training data

[tholor]

Is your feature request related to a problem? Please describe.
If you work on domain corpora, collecting additional training data to improve your reader or retriever models is very helpful.
For collecting training data, there are two main options:
a) Manual Labelling
b) User feedback for "live predictions"

b) is particularly promising if you don't have enough time or resources for a) OR if you want to continuously improve your model once it is production.

We already have the API for storing user feedback and used it successfully in some deployments. In these deployments, we used proprietary user interfaces to collect feedback. Let's add those feedback buttons also to our Haystack Demo UI based on streamlit so that everybody can experiment with it more easily and understand the mechanics.

Describe the solution you'd like

• Add 👍 / 👎 buttons in the streamlit UI that allow capturing user feedback per result
• Optionally: When clicking 👎 we could distinguish between "wrong answer and wrong passage" and "wrong answer, but correct passage" (this distinction helps for the training of retriever models)

Additional context

• Current streamlit UI: https://github.com/deepset-ai/haystack/tree/master/ui
• Information about the API Endpoints to call for storing the user feedback:
  https://haystack.deepset.ai/docs/latest/domain_adaptationmd#User-Feedback

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