Add generator page

docs/latest/components/generator.mdx

@@ -2,27 +2,61 @@
 
 While extractive QA highlights the span of text that answers a query,
 generative QA can return a novel text answer that it has composed.
+
 The best current approaches, such as [Retriever-Augmented Generation](https://arxiv.org/abs/2005.11401) and [LFQA](https://yjernite.github.io/lfqa.html),
 can draw upon both the knowledge it gained during language model pretraining (parametric memory)
 as well as passages provided to it with a retriever (non-parametric memory).
+
 With the advent of Transformer based retrieval methods such as [Dense Passage Retrieval](https://arxiv.org/abs/2004.04906),
 retriever and generator can be trained concurrently from the one loss signal.
 
 <div className="max-w-xl bg-yellow-light-theme border-l-8 border-yellow-dark-theme px-6 pt-6 pb-4 my-4 rounded-md dark:bg-yellow-900">
 
-**Tutorial**
-
-Checkout our tutorial notebooks for a guide on how to build your own generative QA system with RAG ([here](/tutorials/retrieval-augmented-generation))
+**Tutorial:** Checkout our tutorial notebooks for a guide on how to build your own generative QA system with RAG ([here](/tutorials/retrieval-augmented-generation))
 or with LFQA ([here](/tutorials/pipelines)).
 
 </div>
 
-Pros
+**Pros**
 
 - More appropriately phrased answers
 - Able to synthesize information from different texts
 - Can draw on latent knowledge stored in language model
 
-Cons
+**Cons**
 
 - Not easy to track what piece of information the generator is basing its response off of
+
+## Usage
+
+Initialize a Generator as follows:
+
+``` python
+from haystack.generator.transformers import RAGenerator
+
+generator = RAGenerator(
+ model_name_or_path="facebook/rag-sequence-nq",
+ retriever=dpr_retriever,
+ top_k=1,
+ min_length=2
+)
+```
+
+Running a Generator in a pipeline:
+
+``` python
+from haystack.pipeline import GenerativeQAPipeline
+
+pipeline = GenerativeQAPipeline(generator=generator, retriever=dpr_retriever)
+result = pipelines.run(query='What are the best party games for adults?', top_k_retriever=20)
+```
+
+Running a stand-alone Generator:
+
+``` python
+result = generator.predict(
+ query='What are the best party games for adults?',
+ documents=[doc1, doc2, doc3...],
+ top_k=top_k
+)
+```

docs/latest/menu.json

@@ -26,6 +26,7 @@
  {"slug": "reader", "title": "Reader"},
  {"slug": "generator", "title": "Generator" },
  {"slug": "summarizer", "title": "Summarizer"},
+ {"slug": "classifier", "title": "Classifier"},
  {"slug": "translator", "title": "Translator"},
  {"slug": "knowledge-graph", "title": "Knowledge Graph"},
  {"slug": "ranker", "title": "Ranker"},