Documentation for prompts in llm-app (#8122)

Co-authored-by: berkecanrizai <[email protected]>
GitOrigin-RevId: ab7fbe4630186340c8900a6b248028fbd0c5eedc

docs/2.developers/6.ai-pipelines/60.custom-prompt.md

@@ -0,0 +1,44 @@
+---
+title: 'Customizing prompt'
+description: 'Guide to customizing prompt in the RAG templates'
+navigation: true
+heading: false
+---
+
+# Customizing prompts in RAG templates
+
+In the RAG templates, you can customize the LLM Q&A prompt directly in the YAML configuration file. You just need to set the `prompt_template` argument for the `BaseRAGQuestionAnswerer`.
+
+Using [`demo-question-answering`](https://github.com/pathwaycom/llm-app/tree/main/examples/pipelines/demo-question-answering) as an example, let's see how to customize the prompt. 
+By default, the `BaseRAGQuestionAnswerer` in the [`app.yaml`](https://github.com/pathwaycom/llm-app/blob/main/examples/pipelines/demo-question-answering/app.yaml) is initialized with:
+
+```yaml
+question_answerer: !pw.xpacks.llm.question_answering.BaseRAGQuestionAnswerer
+  llm: $llm
+  indexer: $document_store
+```
+
+Set the `prompt_template` to be the prompt you want to use. Your prompt needs to contain two placeholders: `"{query}"` and `"{context}"` – `"{query}"` will be replaced with the question being asked, whereas `"{context}"` will be replaced with the list of context documents.
+
+```yaml
+question_answerer: !pw.xpacks.llm.question_answering.BaseRAGQuestionAnswerer
+  llm: $llm
+  indexer: $document_store
+  prompt_template: "Given these documents: {context}, please answer the question: {query}"
+```
+
+If you plan to use a longer prompt, it may be more convenient to use a multiline string and store it in a variable (the syntax for variables is described in https://pathway.com/developers/ai-pipelines/configure-yaml).
+
+```yaml
+$prompt_template: |
+  Answer the question based on the given documents.
+  If you can't find the answer in the documents, say that you don't know.
+  Context documents: {context}
+  Question: {query}
+  Your answer: 
+
+question_answerer: !pw.xpacks.llm.question_answering.BaseRAGQuestionAnswerer
+  llm: $llm
+  indexer: $document_store
+  prompt_template: $prompt_template
+```