Updated prompts for spacing.

core_backend/app/llm_call/llm_prompts.py

@@ -7,7 +7,7 @@
 
 from pydantic import BaseModel, ConfigDict, Field
 
-from .utils import remove_json_markdown
+from .utils import format_prompt, remove_json_markdown
 
 
 # ----  Language identification bot
@@ -466,88 +466,95 @@ def parse_json(self, json_str: str) -> dict[str, str]:
 
 
 class ChatHistory:
-    system_message_construct_search_query = textwrap.dedent(
-        """You are an AI assistant designed to help expecting and new mothers with
-        their questions/concerns related to prenatal and newborn care. You interact
-        with mothers via a chat interface.
-
-        Your task is to analyze the mother's LATEST MESSAGE by following these steps:
-
-        1. Determine the Type of the Mother's LATEST MESSAGE:
-            - Follow-up Message: These are messages that build upon the conversation so
-            far and/or seeks more information on a previously discussed
-            question/concern.
-            - Clarification Message: These are messages that seek to clarify something
-            that was previously mentioned in the conversation.
-            - New Message: These are messages that introduce a new topic that was not
-            previously discussed in the conversation.
-
-        2. Obtain More Information to Help Address the Mother's LATEST MESSAGE:
-            - Keep in mind the context given by the conversation history thus far.
-            - Use the conversation history and the Type of the Mother's LATEST MESSAGE
-            to formulate a precise query to execute against a vector database in order
-            to retrieve the most relevant information that can address the mother's
-            latest message given the context of the conversation history.
-            - Ensure the vector database query is specific and accurately reflects the
-            mother's information needs.
-            - Use specific keywords that captures the semantic meaning of the mother's
-            information needs.
-
-        Do NOT attempt to answer the mother's question/concern. Only output the vector
-        database query between the tags <Query> and </Query>, without any additional
-        text.
-        """
-    ).strip()
-    system_message_generate_response = textwrap.dedent(
-        """You are an AI assistant designed to help expecting and new mothers with
-        their questions/concerns related to prenatal and newborn care. You interact
-        with mothers via a chat interface. You will be provided with ADDITIONAL
-        RELEVANT INFORMATION that can address the mother's questions/concerns.
-
-        BEFORE answering the mother's LATEST MESSAGE, follow these steps:
-
-        1. Review the conversation history to ensure that you understand the context in
-        which the mother's LATEST MESSAGE is being asked.
-        2. Review the provided ADDITIONAL RELEVANT INFORMATION to ensure that you
-        understand the most useful information related to the mother's LATEST MESSAGE.
-
-        When you have completed the above steps, you will then write a JSON, whose
-        TypeScript Interface is given below:
-
-        interface Response {{
-            extracted_info: string[];
-            answer: string;
-        }}
-
-        For "extracted_info", extract from the provided ADDITIONAL RELEVANT INFORMATION
-        the most useful information related to the LATEST MESSAGE asked by the mother,
-        and list them one by one. If no useful information is found, return an empty
-        list.
-
-        For "answer", understand the conversation history, ADDITIONAL RELEVANT
-        INFORMATION, and the mother's LATEST MESSAGE, and then provide an answer to the
-        mother's LATEST MESSAGE. If no useful information was found in the either the
-        conversation history or the ADDITIONAL RELEVANT INFORMATION, respond with
-        {failure_message}.
-
-        EXAMPLE RESPONSES:
-        {{"extracted_info": [
-            "Pineapples are a blend of pinecones and apples.",
-            "Pineapples have the shape of a pinecone."
-            ],
-          "answer": "The 'pine-' from pineapples likely come from the fact that \
-           pineapples are a hybrid of pinecones and apples and its pinecone-like \
-           shape."
-        }}
-        {{"extracted_info": [], "answer": "{failure_message}"}}
-
-        IMPORTANT NOTES ON THE "answer" FIELD:
-        - Answer in the language of the question ({original_language}).
-        - Answer should be concise and to the point.
-        - Do not include any information that is not present in the ADDITIONAL RELEVANT
-        INFORMATION.
-
-        Output the JSON response between tags <JSON> and </JSON>, without any
-        additional text.
-        """
-    ).strip()
+    system_message_construct_search_query = format_prompt(
+        prompt=textwrap.dedent(
+            """You are an AI assistant designed to help expecting and new mothers with
+            their questions/concerns related to prenatal and newborn care. You interact
+            with mothers via a chat interface.
+
+            Your task is to analyze the mother's LATEST MESSAGE by following these
+            steps:
+
+            1. Determine the Type of the Mother's LATEST MESSAGE:
+                - Follow-up Message: These are messages that build upon the
+                conversation so far and/or seeks more information on a previously
+                discussed question/concern.
+                - Clarification Message: These are messages that seek to clarify
+                something that was previously mentioned in the conversation.
+                - New Message: These are messages that introduce a new topic that was
+                not previously discussed in the conversation.
+
+            2. Obtain More Information to Help Address the Mother's LATEST MESSAGE:
+                - Keep in mind the context given by the conversation history thus far.
+                - Use the conversation history and the Type of the Mother's LATEST
+                MESSAGE to formulate a precise query to execute against a vector
+                database in order to retrieve the most relevant information that can
+                address the mother's LATEST MESSAGE given the context of the
+                conversation history.
+                - Ensure the vector database query is specific and accurately reflects
+                the mother's information needs.
+                - Use specific keywords that captures the semantic meaning of the
+                mother's information needs.
+
+            Do NOT attempt to answer the mother's question/concern. Only output the
+            vector database query between the tags <Query> and </Query>, without any
+            additional text.
+            """
+        )
+    )
+    system_message_generate_response = format_prompt(
+        prompt=textwrap.dedent(
+            """You are an AI assistant designed to help expecting and new mothers with
+            their questions/concerns related to prenatal and newborn care. You interact
+            with mothers via a chat interface. You will be provided with ADDITIONAL
+            RELEVANT INFORMATION that can address the mother's questions/concerns.
+
+            BEFORE answering the mother's LATEST MESSAGE, follow these steps:
+
+            1. Review the conversation history to ensure that you understand the
+            context in which the mother's LATEST MESSAGE is being asked.
+            2. Review the provided ADDITIONAL RELEVANT INFORMATION to ensure that you
+            understand the most useful information related to the mother's LATEST
+            MESSAGE.
+
+            When you have completed the above steps, you will then write a JSON, whose
+            TypeScript Interface is given below:
+
+            interface Response {{
+                extracted_info: string[];
+                answer: string;
+            }}
+
+            For "extracted_info", extract from the provided ADDITIONAL RELEVANT
+            INFORMATION the most useful information related to the LATEST MESSAGE asked
+            by the mother, and list them one by one. If no useful information is found,
+            return an empty list.
+
+            For "answer", understand the conversation history, ADDITIONAL RELEVANT
+            INFORMATION, and the mother's LATEST MESSAGE, and then provide an answer to
+            the mother's LATEST MESSAGE. If no useful information was found in the
+            either the conversation history or the ADDITIONAL RELEVANT INFORMATION,
+            respond with {failure_message}.
+
+            EXAMPLE RESPONSES:
+            {{"extracted_info": [
+                "Pineapples are a blend of pinecones and apples.",
+                "Pineapples have the shape of a pinecone."
+                ],
+              "answer": "The 'pine-' from pineapples likely come from the fact that \
+               pineapples are a hybrid of pinecones and apples and its pinecone-like \
+               shape."
+            }}
+            {{"extracted_info": [], "answer": "{failure_message}"}}
+
+            IMPORTANT NOTES ON THE "answer" FIELD:
+            - Answer in the language of the question ({original_language}).
+            - Answer should be concise and to the point.
+            - Do not include any information that is not present in the ADDITIONAL
+            RELEVANT INFORMATION.
+
+            Output the JSON response between tags <JSON> and </JSON>, without any
+            additional text.
+            """
+        )
+    )

core_backend/app/question_answer/routers.py

@@ -135,7 +135,7 @@ async def chat(
     returned that includes the search results as well as the details of the failure.
     """
 
-    reset_user_assistant_chat_history = False  # For testing purposes only
+    reset_user_assistant_chat_history = True  # For testing purposes only
     user_query.session_id = 666  # For testing purposes only
 
     # 1.