feat(max): Make summary more actionable and self-aware

ee/hogai/schema_generator/nodes.py

@@ -106,15 +106,18 @@
                 ],
             )
 
+        final_message = VisualizationMessage(
+            plan=generated_plan,
+            answer=message.query,
+            initiator=start_id,
+            id=str(uuid4()),
+        )
+        if final_message.answer.breakdownFilter:
+            # Increase breakdown limit, since the "Other" series is pretty low-value for the assistant
+            final_message.answer.breakdownFilter.breakdown_limit = 100
+
         return PartialAssistantState(
-            messages=[
-                VisualizationMessage(
-                    plan=generated_plan,
-                    answer=message.query,
-                    initiator=start_id,
-                    id=str(uuid4()),
-                )
-            ],
+            messages=[final_message],
             intermediate_steps=None,
         )
 

ee/hogai/summarizer/nodes.py

@@ -10,7 +10,11 @@
 from rest_framework.exceptions import APIException
 from sentry_sdk import capture_exception
 
-from ee.hogai.summarizer.prompts import SUMMARIZER_INSTRUCTION_PROMPT, SUMMARIZER_SYSTEM_PROMPT
+from ee.hogai.summarizer.prompts import (
+    SUMMARIZER_INSTRUCTION_PROMPT,
+    SUMMARIZER_SYSTEM_PROMPT,
+    SUMMARIZER_RESULTS_PROMPT,
+)
 from ee.hogai.utils.nodes import AssistantNode
 from ee.hogai.utils.types import AssistantNodeName, AssistantState, PartialAssistantState
 from posthog.api.services.query import process_query_dict
@@ -100,5 +104,6 @@ def _construct_messages(self, state: AssistantState) -> list[tuple[str, str]]:
             elif isinstance(message, AssistantMessage):
                 conversation.append(("assistant", message.content))
 
-        conversation.append(("human", SUMMARIZER_INSTRUCTION_PROMPT))
+        conversation.append(("system", SUMMARIZER_RESULTS_PROMPT))
+        conversation.append(("user", SUMMARIZER_INSTRUCTION_PROMPT))
         return conversation

ee/hogai/summarizer/prompts.py

@@ -1,17 +1,24 @@
 SUMMARIZER_SYSTEM_PROMPT = """
-Act as an expert product manager. Your task is to summarize query results in a a concise way.
+Act as an expert product manager. Your task is to help the user build a successful product and business. Remember, you're a hedeghog.
 Offer actionable feedback if possible. Only provide feedback that you're absolutely certain will be useful for this team.
+Assume the user is familiar with Silicon Valley terms.
 
 The product being analyzed is described as follows:
 {{product_description}}"""
 
-SUMMARIZER_INSTRUCTION_PROMPT = """
-Here are the {{query_kind}} results for this question:
+SUMMARIZER_RESULTS_PROMPT = """
+Here are the {{query_kind}} results for the latest question's query:
 ```json
 {{results}}
-```
+```"""
+
+SUMMARIZER_INSTRUCTION_PROMPT = """
+Based on the results, answer my latest question and provide actionable feedback.
+Avoid generic advice. Take into account what you know about the product.
+
+If there are interesting trends or anomalies, succintly point them out. I can see the chart, so don't just describe all of it.
+The answer needs to be high-impact, no more than a few sentences. Bullets can improve clarity of action points.
+Use Silicon Valley lingo. Be informal, but without fluff. NEVER USE TITLE CASE, even in headings. Our style is sentence case always.
 
-Answer my earlier question using the results above. Point out interesting trends or anomalies.
-Take into account what you know about my product. If possible, offer actionable feedback, but avoid generic advice.
-Limit yourself to a few sentences. The answer needs to be high-impact and relevant for me as a Silicon Valley engineer.
+You MUST point out if the executed query or its results are insufficient for a full answer to my question.
 """