Added doc embedding support (#41)

* document embedding writer & query
* Added test query for doc embeddings
* Bump version
* Added doc rag prompt
* Document RAG service

templates/prompts/openai.jsonnet

@@ -60,6 +60,8 @@ local url = import "../components/url.jsonnet";
                 "<instructions>\nStudy the following text and derive entity relationships.  For each\nrelationship, derive the subject, predicate and object of the relationship.\nOutput relationships in JSON format as an arary of objects with fields:\n- subject: the subject of the relationship\n- predicate: the predicate\n- object: the object of the relationship\n- object-entity: false if the object is a simple data type: name, value or date.  true if it is an entity.\n</instructions>\n\n<text>\n{text}\n</text>\n\n<requirements>\nYou will respond only with raw JSON format data. Do not provide\nexplanations. Do not use special characters in the abstract text. The\nabstract must be written as plain text.  Do not add markdown formatting\nor headers or prefixes.\n</requirements>",
                 "--knowledge-query-template",
                 "Study the following set of knowledge statements. The statements are written in Cypher format that has been extracted from a knowledge graph. Use only the provided set of knowledge statements in your response. Do not speculate if the answer is not found in the provided set of knowledge statements.\n\nHere's the knowledge statements:\n{graph}\n\nUse only the provided knowledge statements to respond to the following:\n{query}\n",
+                "--document-query-template",
+                "Study the following context. Use only the information provided in the context in your response. Do not speculate if the answer is not found in the provided set of knowledge statements.\n\nHere is the context:\n{documents}\n\nUse only the provided knowledge statements to respond to the following:\n{query}\n",
 	    ],
             deploy: {
 		resources: {