human
You are acting as a middleman between a user and a Google Cloud BigQuery database. Your main goal is to answer questions based on data in the database by executing valid queries and interpreting the results to provide the answers to the user. You can communicate with the database using the recipient "SERVER" and specify the action as "QUERY" to execute a query or "SCHEMA" to retrieve schema information for specific tables.

User instructions:

To request schema information for one or more tables, use the following format: {"recipient": "SERVER", "action": "SCHEMA", "message": "zee-prj-udp.project_rock_AR.AAR_Linear_L0_BMS_tbl, zee-prj-udp.project_rock_AR.AAR_Linear_L0_Adex_tbl"}
To execute a query, use the following format: {"recipient": "SERVER", "action": "QUERY", "message": "SELECT ROUND((SUM(CAST(Valuated_Amount AS float64))*.969/1004451.22),2) AS sum_revenue FROM (SELECT DISTINCT * EXCEPT(Date_of_Refresh) FROM zee-prj-udp.project_rock_AR.AAR_Linear_L0_BMS_tbl WHERE Zone_Code IS NOT NULL)"}
The result will be returned in JSON format using the recipient "USER" and the message will contain the answer or the query results.
Example conversation:

User: What is the linear TV revenue month-wise for the past 1 year?

Assistant: {"recipient": "SERVER", "action": "QUERY", "message": "SELECT ROUND((SUM(CAST(Valuated_Amount AS float64))*.969/1004451.22),2) AS sum_revenue, EXTRACT(MONTH FROM date_of_telecast) AS mon, EXTRACT(YEAR FROM date_of_telecast) AS yr FROM (SELECT DISTINCT * EXCEPT(Date_of_Refresh) FROM zee-prj-udp.project_rock_AR.AAR_Linear_L0_BMS_tbl WHERE Zone_Code IS NOT NULL) GROUP BY mon, yr ORDER BY yr DESC, mon DESC;"}

User: What is the linear TV revenue for the past one month?
gpt
--- Reasoning ---
1. Is the question multiple-choice question?
No
2. Is it implied multiple-choice question?
No
3. If two experts were independently asked the question, will the final answer be exactly the same?
Yes

--- Answer ---
grounded