diff --git a/docs/_src/usage/usage/faq.md b/docs/_src/usage/usage/faq.md index cf7d9682e..37b09ff9b 100644 --- a/docs/_src/usage/usage/faq.md +++ b/docs/_src/usage/usage/faq.md @@ -9,7 +9,7 @@ id: "faqmd" #Frequently Asked Questions -**Why am I seeing duplicate answers being returned?** +##Why am I seeing duplicate answers being returned? The ElasticsearchDocumentStore and MilvusDocumentStore rely on Elasticsearch and Milvus backend services which persist after your Python script has finished running. @@ -21,12 +21,12 @@ to ensure that you are working with an empty DocumentStore. DocumentStores also have a `duplicate_documents` argument in their `__init__()` and `write_documents` methods where you can define whether you'd like skip writing duplicates, overwrite existing duplicates or raise an error when there are duplicates. -**How can I make sure that my GPU is being engaged when I use Haystack?** +##How can I make sure that my GPU is being engaged when I use Haystack? You will want to ensure that a CUDA enabled GPU is being engaged when Haystack is running (you can check by running `nvidia-smi -l` on your command line). Components which can be sped up by GPU have a `use_gpu` argument in their constructor which you will want to set to `True`. -**How do I speed up my predictions?** +##How do I speed up my predictions? There are many different ways to speed up the performance of your Haystack system. @@ -42,31 +42,31 @@ your documents into smaller chunks by using the `PreProcessor` (see [tutorial](h For more optimization suggestions, have a look at our [optimization page](https://haystack.deepset.ai/docs/latest/optimizationmd) and also our [blogs](https://medium.com/deepset-ai) -**How do I use Haystack for my language?** +##How do I use Haystack for my language? The components in Haystack, such as the `Retriever` or the `Reader`, are designed in a language agnostic way. However you may have to set certain parameters or load models pretrained for your language in order to get good performance out of Haystack. See our [languages page](https://haystack.deepset.ai/docs/latest/languagesmd) for more details. -**How can I add metadata to my documents so that I can apply filters?** +##How can I add metadata to my documents so that I can apply filters? When providing your documents in the input format (see [here](https://haystack.deepset.ai/docs/latest/documentstoremd#Input-Format)) you can provide metadata information as a dictionary under the `meta` key. At query time, you can provide a `filters` argument (most likely through `Pipelines.run()`) that specifies the accepted values for a certain metadata field (for an example of what a `filters` dictionary might look like, please refer to [this example](https://haystack.deepset.ai/docs/latest/apiretrievermd#__init__)) -**How can I see predictions during evaluation?** +##How can I see predictions during evaluation? To see predictions during evaluation, you want to initialize the `EvalDocuments` or `EvalAnswers` with `debug=True`. This causes their `EvalDocuments.log` or `EvalAnswers.log` to be populated with a record of each prediction made. -**How can I serve my Haystack model?** +##How can I serve my Haystack model? Haystack models can be wrapped in a REST API. For basic details on how to set this up, please refer to this section on our [Github page](https://github.com/deepset-ai/haystack/blob/master/README.md#7-rest-api). More comprehensive documentation coming soon! -**How can I interpret the confidence scores being returned by the Reader?** +##How can I interpret the confidence scores being returned by the Reader? The confidence scores are in the range of 0 and 1 and reflect how confident the model is in each prediction that it makes. Having a confidence score is particularly useful in cases where you need Haystack to work with a certain accuracy threshold. @@ -74,14 +74,14 @@ Many of our users have built systems where predictions below a certain confidenc For more information on model confidence and how to tune it, please refer to [this section](https://haystack.deepset.ai/docs/latest/readermd#Confidence-Scores). -**My documents aren't showing up in my DocumentStore even though I've called `DocumentStore.write_documents()`** +##My documents aren't showing up in my DocumentStore even though I've called `DocumentStore.write_documents()` When indexing, retrieving or querying for documents from a DocumentStore, you can specify an `index` on which to perform this action. This can be specified in almost all methods of `DocumentStore` as well as `Retriever.retrieve()`. Ensure that you are performing these operations on the one index! Note that this also applies at evaluation where labels are written into their own separate DocumentStore index. -**What is the difference between the FARMReader and the TransformersReader?** +##What is the difference between the FARMReader and the TransformersReader? In short, the FARMReader using a QA pipeline implementation that comes from our own [FARM framework](https://github.com/deepset-ai/FARM) that we can more easily update and also optimize for performance.