docs: added YAML example to OpenAIGenerator

docs-website/docs/pipeline-components/generators/openaigenerator.mdx

@@ -122,7 +122,7 @@ pipe = Pipeline()
 
 pipe.add_component("retriever", InMemoryBM25Retriever(document_store=docstore))
 pipe.add_component("prompt_builder", PromptBuilder(template=template))
-pipe.add_component("llm", OpenAIGenerator(api_key=Secret.from_token("<your-api-key>"))
+pipe.add_component("llm", OpenAIGenerator(api_key=Secret.from_env_var("OPENAI_API_KEY")))
 pipe.connect("retriever", "prompt_builder.documents")
 pipe.connect("prompt_builder", "llm")
 
@@ -137,3 +137,60 @@ res=pipe.run({
 
 print(res)
 ```
+
+### In YAML
+
+This is the YAML representation of the RAG pipeline shown above. It retrieves documents based on a query, constructs a prompt using a template, and generates an answer using a chat model.
+
+```yaml
+components:
+  llm:
+    init_parameters:
+      api_base_url: null
+      api_key:
+        env_vars:
+        - OPENAI_API_KEY
+        strict: true
+        type: env_var
+      generation_kwargs: {}
+      http_client_kwargs: null
+      max_retries: null
+      model: gpt-5-mini
+      organization: null
+      streaming_callback: null
+      system_prompt: null
+      timeout: null
+    type: haystack.components.generators.openai.OpenAIGenerator
+  prompt_builder:
+    init_parameters:
+      required_variables: null
+      template: "\nGiven the following information, answer the question.\n\nContext:\n\
+        {% for document in documents %}\n    {{ document.content }}\n{% endfor %}\n\n\
+        Question: {{ query }}?\n"
+      variables: null
+    type: haystack.components.builders.prompt_builder.PromptBuilder
+  retriever:
+    init_parameters:
+      document_store:
+        init_parameters:
+          bm25_algorithm: BM25L
+          bm25_parameters: {}
+          bm25_tokenization_regex: (?u)\b\w+\b
+          embedding_similarity_function: dot_product
+          index: 64e4f9ab-87fb-47fd-b390-dabcfda61447
+          return_embedding: true
+        type: haystack.document_stores.in_memory.document_store.InMemoryDocumentStore
+      filter_policy: replace
+      filters: null
+      scale_score: false
+      top_k: 10
+    type: haystack.components.retrievers.in_memory.bm25_retriever.InMemoryBM25Retriever
+connection_type_validation: true
+connections:
+- receiver: prompt_builder.documents
+  sender: retriever.documents
+- receiver: llm.prompt
+  sender: prompt_builder.prompt
+max_runs_per_component: 100
+metadata: {}
+```