Rename followUpQuestions -> followUpSuggestions

text_2_sql/.env.example

@@ -5,7 +5,7 @@ Text2Sql__DatabaseEngine=<DatabaseEngine> # TSQL or Postgres or Snowflake or Dat
 Text2Sql__UseQueryCache=<Determines if the Query Cache will be used to speed up query generation. Defaults to True.> # True or False
 Text2Sql__PreRunQueryCache=<Determines if the results from the Query Cache will be pre-run to speed up answer generation. Defaults to True.> # True or False
 Text2Sql__UseColumnValueStore=<Determines if the Column Value Store will be used for schema selection Defaults to True.> # True or False
-Text2Sql__GenerateFollowUpQuestions=<Determines if follow up questions will be generated. Defaults to True.> # True or False
+Text2Sql__GenerateFollowUpSuggestions=<Determines if follow up questions will be generated. Defaults to True.> # True or False
 
 # Open AI Connection Details
 OpenAI__CompletionDeployment=<openAICompletionDeploymentId. Used for data dictionary creator>

text_2_sql/autogen/src/autogen_text_2_sql/autogen_text_2_sql.py

@@ -48,8 +48,8 @@ def __init__(self, state_store: StateStore, **kwargs):
 
         self._agentic_flow = None
 
-        self._generate_follow_up_questions = (
-            os.environ.get("Text2Sql__GenerateFollowUpQuestions", "True").lower()
+        self._generate_follow_up_suggestions = (
+            os.environ.get("Text2Sql__GenerateFollowUpSuggestions", "True").lower()
             == "true"
         )
 
@@ -62,9 +62,9 @@ def get_all_agents(self):
 
         parallel_query_solving_agent = ParallelQuerySolvingAgent(**self.kwargs)
 
-        if self._generate_follow_up_questions:
+        if self._generate_follow_up_suggestions:
             answer_agent = LLMAgentCreator.create(
-                "answer_with_follow_up_questions_agent", **self.kwargs
+                "answer_with_follow_up_suggestions_agent", **self.kwargs
             )
         else:
             answer_agent = LLMAgentCreator.create("answer_agent", **self.kwargs)
@@ -82,7 +82,7 @@ def termination_condition(self):
         """Define the termination condition for the chat."""
         termination = (
             SourceMatchTermination("answer_agent")
-            | SourceMatchTermination("answer_with_follow_up_questions_agent")
+            | SourceMatchTermination("answer_with_follow_up_suggestions_agent")
             # | TextMentionTermination(
             #     "[]",
             #     sources=["user_message_rewrite_agent"],
@@ -110,9 +110,9 @@ def unified_selector(self, messages):
         # Handle transition after parallel query solving
         elif (
             current_agent == "parallel_query_solving_agent"
-            and self._generate_follow_up_questions
+            and self._generate_follow_up_suggestions
         ):
-            decision = "answer_with_follow_up_questions_agent"
+            decision = "answer_with_follow_up_suggestions_agent"
         elif current_agent == "parallel_query_solving_agent":
             decision = "answer_agent"
 
@@ -325,7 +325,7 @@ async def process_user_message(
                     )
                 elif (
                     message.source == "answer_agent"
-                    or message.source == "answer_with_follow_up_questions_agent"
+                    or message.source == "answer_with_follow_up_suggestions_agent"
                 ):
                     payload = ProcessingUpdatePayload(
                         message="Generating the answer...",
@@ -338,7 +338,7 @@ async def process_user_message(
                 if (
                     message.messages[-1].source == "answer_agent"
                     or message.messages[-1].source
-                    == "answer_with_follow_up_questions_agent"
+                    == "answer_with_follow_up_suggestions_agent"
                 ):
                     # If the message is from the answer_agent, we need to return the final answer
                     payload = self.extract_answer_payload(message.messages)

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

@@ -9,7 +9,7 @@
 import logging
 from text_2_sql_core.structured_outputs import (
     AnswerAgentOutput,
-    AnswerWithFollowUpQuestionsAgentOutput,
+    AnswerWithFollowUpSuggestionsAgentOutput,
     UserMessageRewriteAgentOutput,
 )
 from autogen_core.model_context import BufferedChatCompletionContext
@@ -117,8 +117,8 @@ def create(cls, name: str, **kwargs) -> AssistantAgent:
             # Import the structured output agent
             if name == "answer_agent":
                 structured_output = AnswerAgentOutput
-            elif name == "answer_with_follow_up_questions_agent":
-                structured_output = AnswerWithFollowUpQuestionsAgentOutput
+            elif name == "answer_with_follow_up_suggestions_agent":
+                structured_output = AnswerWithFollowUpSuggestionsAgentOutput
             elif name == "user_message_rewrite_agent":
                 structured_output = UserMessageRewriteAgentOutput
 

text_2_sql/text_2_sql_core/src/text_2_sql_core/payloads/interaction_payloads.py

@@ -81,8 +81,8 @@ class Source(InteractionPayloadBase):
         answer: str
         steps: list[list[str]] = Field(default_factory=list, alias="Steps")
         sources: list[Source] = Field(default_factory=list)
-        follow_up_questions: list[str] | None = Field(
-            default=None, alias="followUpQuestions"
+        follow_up_suggestions: list[str] | None = Field(
+            default=None, alias="followUpSuggestions"
         )
 
     payload_type: Literal[PayloadType.ANSWER_WITH_SOURCES] = Field(

text_2_sql/text_2_sql_core/src/text_2_sql_core/prompts/answer_with_follow_up_questions_agent.yaml → text_2_sql/text_2_sql_core/src/text_2_sql_core/prompts/answer_with_follow_up_suggestions_agent.yaml

@@ -25,7 +25,7 @@ system_message: |
   <output>
     {
       "answer": "The response to the user's question.",
-      "follow_up_questions": [
+      "follow_up_suggestions": [
         "Follow-up question 1",
         "Follow-up question 2",
         "Follow-up question 3"

text_2_sql/text_2_sql_core/src/text_2_sql_core/structured_outputs/__init__.py

@@ -6,14 +6,14 @@
 from text_2_sql_core.structured_outputs.user_message_rewrite_agent import (
     UserMessageRewriteAgentOutput,
 )
-from text_2_sql_core.structured_outputs.answer_with_follow_up_questions_agent import (
-    AnswerWithFollowUpQuestionsAgentOutput,
+from text_2_sql_core.structured_outputs.answer_with_follow_up_suggestions_agent import (
+    AnswerWithFollowUpSuggestionsAgentOutput,
 )
 from text_2_sql_core.structured_outputs.answer_agent import AnswerAgentOutput
 
 __all__ = [
     "AnswerAgentOutput",
-    "AnswerWithFollowUpQuestionsAgentOutput",
+    "AnswerWithFollowUpSuggestionsAgentOutput",
     "SQLSchemaSelectionAgentOutput",
     "UserMessageRewriteAgentOutput",
 ]

text_2_sql/text_2_sql_core/src/text_2_sql_core/structured_outputs/answer_with_follow_up_questions_agent.py → text_2_sql/text_2_sql_core/src/text_2_sql_core/structured_outputs/answer_with_follow_up_suggestions_agent.py

@@ -3,8 +3,8 @@
 from pydantic import BaseModel
 
 
-class AnswerWithFollowUpQuestionsAgentOutput(BaseModel):
+class AnswerWithFollowUpSuggestionsAgentOutput(BaseModel):
     """The output of the answer agent with follow up questions."""
 
     answer: str
-    follow_up_questions: list[str]
+    follow_up_suggestions: list[str]