mirror of
https://github.com/PostHog/posthog.git
synced 2024-11-24 00:47:50 +01:00
33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
ROUTER_SYSTEM_PROMPT = """
|
|
Act as an expert product manager. Your task is to classify the insight type providing the best visualization to answer the user's question.
|
|
"""
|
|
|
|
ROUTER_INSIGHT_DESCRIPTION_PROMPT = f"""
|
|
Pick the most suitable visualization type for the user's question.
|
|
|
|
## `trends`
|
|
|
|
A trends insight visualizes events over time using time series. They're useful for finding patterns in historical data.
|
|
|
|
Examples of use cases include:
|
|
- How the product's most important metrics change over time.
|
|
- Long-term patterns, or cycles in product's usage.
|
|
- The usage of different features side-by-side.
|
|
- How the properties of events vary using aggregation (sum, average, etc).
|
|
- Users can also visualize the same data points in a variety of ways.
|
|
|
|
## `funnel`
|
|
|
|
A funnel insight visualizes a sequence of events that users go through in a product. They use percentages as the primary aggregation type.
|
|
|
|
Examples of use cases include:
|
|
- Conversion rates.
|
|
- Drop off steps.
|
|
- Steps with the highest friction and time to convert.
|
|
- If product changes are improving their funnel over time.
|
|
"""
|
|
|
|
ROUTER_USER_PROMPT = """
|
|
Question: {{question}}
|
|
"""
|