Payload and Disambiguation Improvements

text_2_sql/autogen/Iteration 5 - Agentic Vector Based Text2SQL.ipynb

@@ -50,7 +50,7 @@
       "source": [
         "import dotenv\n",
         "import logging\n",
-        "from autogen_text_2_sql import AutoGenText2Sql, QuestionPayload"
+        "from autogen_text_2_sql import AutoGenText2Sql, UserMessagePayload"
       ]
     },
     {
@@ -100,7 +100,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "async for message in agentic_text_2_sql.process_question(QuestionPayload(question=\"What is the total number of sales?\")):\n",
+        "async for message in agentic_text_2_sql.process_user_message(UserMessagePayload(user_message=\"What is the total number of sales?\")):\n",
         "    logging.info(\"Received %s Message from Text2SQL System\", message)"
       ]
     },

text_2_sql/autogen/evaluate_autogen_text2sql.ipynb

@@ -68,7 +68,7 @@
         "# Add the src directory to the path\n",
         "sys.path.append(str(notebook_dir / \"src\"))\n",
         "\n",
-        "from autogen_text_2_sql import AutoGenText2Sql, QuestionPayload\n",
+        "from autogen_text_2_sql import AutoGenText2Sql, UserMessagePayload\n",
         "from autogen_text_2_sql.evaluation_utils import get_final_sql_query\n",
         "\n",
         "# Configure logging\n",
@@ -127,7 +127,7 @@
         "    all_queries = []\n",
         "    final_query = None\n",
         "    \n",
-        "    async for message in autogen_text2sql.process_question(QuestionPayload(question=question)):\n",
+        "    async for message in autogen_text2sql.process_user_message(UserMessagePayload(user_message=question)):\n",
         "        if message.payload_type == \"answer_with_sources\":\n",
         "            # Extract from results\n",
         "            if hasattr(message.body, 'results'):\n",

text_2_sql/autogen/src/autogen_text_2_sql/__init__.py

@@ -1,6 +1,6 @@
 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT License.
 from autogen_text_2_sql.autogen_text_2_sql import AutoGenText2Sql
-from text_2_sql_core.payloads.interaction_payloads import QuestionPayload
+from text_2_sql_core.payloads.interaction_payloads import UserMessagePayload
 
-__all__ = ["AutoGenText2Sql", "QuestionPayload"]
+__all__ = ["AutoGenText2Sql", "UserMessagePayload"]

text_2_sql/autogen/src/autogen_text_2_sql/autogen_text_2_sql.py

@@ -19,9 +19,9 @@
 import re
 
 from text_2_sql_core.payloads.interaction_payloads import (
-    QuestionPayload,
+    UserMessagePayload,
     AnswerWithSourcesPayload,
-    DismabiguationRequestPayload,
+    DismabiguationRequestsPayload,
     ProcessingUpdatePayload,
     InteractionPayload,
     PayloadType,
@@ -40,16 +40,16 @@ def get_all_agents(self):
         # Get current datetime for the Query Rewrite Agent
         current_datetime = datetime.now()
 
-        self.question_rewrite_agent = LLMAgentCreator.create(
-            "question_rewrite_agent", current_datetime=current_datetime
+        self.user_message_rewrite_agent = LLMAgentCreator.create(
+            "user_message_rewrite_agent", current_datetime=current_datetime
         )
 
         self.parallel_query_solving_agent = ParallelQuerySolvingAgent(**self.kwargs)
 
         self.answer_agent = LLMAgentCreator.create("answer_agent")
 
         agents = [
-            self.question_rewrite_agent,
+            self.user_message_rewrite_agent,
             self.parallel_query_solving_agent,
             self.answer_agent,
         ]
@@ -62,7 +62,7 @@ def termination_condition(self):
         termination = (
             TextMentionTermination("TERMINATE")
             | SourceMatchTermination("answer_agent")
-            | TextMentionTermination("requires_user_information_request")
+            | TextMentionTermination("contains_disambiguation_requests")
             | MaxMessageTermination(5)
         )
         return termination
@@ -73,11 +73,11 @@ def unified_selector(self, messages):
         current_agent = messages[-1].source if messages else "user"
         decision = None
 
-        # If this is the first message start with question_rewrite_agent
+        # If this is the first message start with user_message_rewrite_agent
         if current_agent == "user":
-            decision = "question_rewrite_agent"
+            decision = "user_message_rewrite_agent"
         # Handle transition after query rewriting
-        elif current_agent == "question_rewrite_agent":
+        elif current_agent == "user_message_rewrite_agent":
             decision = "parallel_query_solving_agent"
         # Handle transition after parallel query solving
         elif current_agent == "parallel_query_solving_agent":
@@ -102,15 +102,6 @@ def agentic_flow(self):
         )
         return flow
 
-    def extract_disambiguation_request(
-        self, messages: list
-    ) -> DismabiguationRequestPayload:
-        """Extract the disambiguation request from the answer."""
-        disambiguation_request = messages[-1].content
-        return DismabiguationRequestPayload(
-            disambiguation_request=disambiguation_request,
-        )
-
     def parse_message_content(self, content):
         """Parse different message content formats into a dictionary."""
         if isinstance(content, (list, dict)):
@@ -134,6 +125,49 @@ def parse_message_content(self, content):
         # If all parsing attempts fail, return the content as-is
         return content
 
+    def extract_decomposed_user_messages(self, messages: list) -> list[list[str]]:
+        """Extract the decomposed messages from the answer."""
+        # Only load sub-message results if we have a database result
+        sub_message_results = self.parse_message_content(messages[1].content)
+        logging.info("Decomposed Results: %s", sub_message_results)
+
+        decomposed_user_messages = sub_message_results.get(
+            "decomposed_user_messages", []
+        )
+
+        logging.debug(
+            "Returning decomposed_user_messages: %s", decomposed_user_messages
+        )
+
+        return decomposed_user_messages
+
+    def extract_disambiguation_request(
+        self, messages: list
+    ) -> DismabiguationRequestsPayload:
+        """Extract the disambiguation request from the answer."""
+        all_disambiguation_requests = self.parse_message_content(messages[-1].content)
+
+        decomposed_user_messages = self.extract_decomposed_user_messages(messages)
+        request_payload = DismabiguationRequestsPayload(
+            decomposed_user_messages=decomposed_user_messages
+        )
+
+        for per_question_disambiguation_request in all_disambiguation_requests[
+            "disambiguation_requests"
+        ].values():
+            for disambiguation_request in per_question_disambiguation_request:
+                logging.info(
+                    "Disambiguation Request Identified: %s", disambiguation_request
+                )
+
+                request = DismabiguationRequestsPayload.Body.DismabiguationRequest(
+                    agent_question=disambiguation_request["agent_question"],
+                    user_choices=disambiguation_request["user_choices"],
+                )
+                request_payload.body.disambiguation_requests.append(request)
+
+        return request_payload
+
     def extract_answer_payload(self, messages: list) -> AnswerWithSourcesPayload:
         """Extract the sources from the answer."""
         answer = messages[-1].content
@@ -145,41 +179,35 @@ def extract_answer_payload(self, messages: list) -> AnswerWithSourcesPayload:
         except json.JSONDecodeError:
             logging.warning("Unable to read SQL query results: %s", sql_query_results)
             sql_query_results = {}
-            sub_question_results = {}
-        else:
-            # Only load sub-question results if we have a database result
-            sub_question_results = self.parse_message_content(messages[1].content)
-            logging.info("Sub-Question Results: %s", sub_question_results)
 
         try:
-            sub_questions = [
-                sub_question
-                for sub_question_group in sub_question_results.get("sub_questions", [])
-                for sub_question in sub_question_group
-            ]
+            decomposed_user_messages = self.extract_decomposed_user_messages(messages)
 
             logging.info("SQL Query Results: %s", sql_query_results)
             payload = AnswerWithSourcesPayload(
-                answer=answer, sub_questions=sub_questions
+                answer=answer, decomposed_user_messages=decomposed_user_messages
             )
 
             if not isinstance(sql_query_results, dict):
                 logging.error(f"Expected dict, got {type(sql_query_results)}")
                 return payload
 
-            if "results" not in sql_query_results:
+            if "database_results" not in sql_query_results:
                 logging.error("No 'results' key in sql_query_results")
                 return payload
 
-            for question, sql_query_result_list in sql_query_results["results"].items():
+            for message, sql_query_result_list in sql_query_results[
+                "database_results"
+            ].items():
                 if not sql_query_result_list:  # Check if list is empty
-                    logging.warning(f"No results for question: {question}")
+                    logging.warning(f"No results for message: {message}")
                     continue
 
                 for sql_query_result in sql_query_result_list:
                     if not isinstance(sql_query_result, dict):
                         logging.error(
-                            f"Expected dict for sql_query_result, got {type(sql_query_result)}"
+                            "Expected dict for sql_query_result, got %s",
+                            type(sql_query_result),
                         )
                         continue
 
@@ -208,47 +236,47 @@ def extract_answer_payload(self, messages: list) -> AnswerWithSourcesPayload:
                 answer=f"{answer}\nError processing results: {str(e)}"
             )
 
-    async def process_question(
+    async def process_user_message(
         self,
-        question_payload: QuestionPayload,
+        message_payload: UserMessagePayload,
         chat_history: list[InteractionPayload] = None,
     ) -> AsyncGenerator[InteractionPayload, None]:
-        """Process the complete question through the unified system.
+        """Process the complete message through the unified system.
 
         Args:
         ----
-            task (str): The user question to process.
+            task (str): The user message to process.
             chat_history (list[str], optional): The chat history. Defaults to None.
             injected_parameters (dict, optional): Parameters to pass to agents. Defaults to None.
 
         Returns:
         -------
             dict: The response from the system.
         """
-        logging.info("Processing question: %s", question_payload.body.question)
+        logging.info("Processing message: %s", message_payload.body.user_message)
         logging.info("Chat history: %s", chat_history)
 
         agent_input = {
-            "question": question_payload.body.question,
+            "message": message_payload.body.user_message,
             "chat_history": {},
-            "injected_parameters": question_payload.body.injected_parameters,
+            "injected_parameters": message_payload.body.injected_parameters,
         }
 
         if chat_history is not None:
             # Update input
             for idx, chat in enumerate(chat_history):
-                if chat.root.payload_type == PayloadType.QUESTION:
+                if chat.root.payload_type == PayloadType.USER_MESSAGE:
                     # For now only consider the user query
                     chat_history_key = f"chat_{idx}"
-                    agent_input[chat_history_key] = chat.root.body.question
+                    agent_input[chat_history_key] = chat.root.body.user_message
 
         async for message in self.agentic_flow.run_stream(task=json.dumps(agent_input)):
             logging.debug("Message: %s", message)
 
             payload = None
 
             if isinstance(message, TextMessage):
-                if message.source == "question_rewrite_agent":
+                if message.source == "user_message_rewrite_agent":
                     payload = ProcessingUpdatePayload(
                         message="Rewriting the query...",
                     )
@@ -271,10 +299,10 @@ async def process_question(
                 elif message.messages[-1].source == "parallel_query_solving_agent":
                     # Load into disambiguation request
                     payload = self.extract_disambiguation_request(message.messages)
-                elif message.messages[-1].source == "question_rewrite_agent":
+                elif message.messages[-1].source == "user_message_rewrite_agent":
                     # Load into empty response
                     payload = AnswerWithSourcesPayload(
-                        answer="Apologies, I cannot answer that question as it is not relevant. Please try another question or rephrase your current question."
+                        answer="Apologies, I cannot answer that message as it is not relevant. Please try another message or rephrase your current message."
                     )
             else:
                 logging.error("Unexpected TaskResult: %s", message)

text_2_sql/autogen/src/autogen_text_2_sql/creators/llm_agent_creator.py

@@ -43,7 +43,7 @@ def get_tool(cls, sql_helper, tool_name: str):
         elif tool_name == "sql_get_entity_schemas_tool":
             return FunctionToolAlias(
                 sql_helper.get_entity_schemas,
-                description="Gets the schema of a view or table in the SQL Database by selecting the most relevant entity based on the search term. Extract key terms from the user question and use these as the search term. Several entities may be returned. Only use when the provided schemas in the message history are not sufficient to answer the question.",
+                description="Gets the schema of a view or table in the SQL Database by selecting the most relevant entity based on the search term. Extract key terms from the user input and use these as the search term. Several entities may be returned. Only use when the provided schemas in the message history are not sufficient to answer the question.",
             )
         elif tool_name == "sql_get_column_values_tool":
             return FunctionToolAlias(