GoodData AI (beta)
GoodData AI is a feature that allows you to ask questions about your data in natural language.
For more information on how to use and setup GoodData AI, see the GoodData AI documentation.
Methods
- ai_chat
- ai_chat_stream
- get_ai_chat_history
- reset_ai_chat_history
- set_ai_chat_history_feedback
- search_ai
- sync_metadata
Example
This example shows how to use the GoodData AI to get execution definition. You can also use it to get a pandas dataframe, but for that you need to use the GoodPandas.
from gooddata_sdk import GoodDataSdk # For AI chat and execution definition.
from gooddata_pandas import GoodDataPandas # For pandas dataframe.
host = "https://www.example.com"
token = "<your_personal_access_token>"
sdk = GoodDataSdk.create(host, token)
# Get execution definition from AI chat (not needed for pandas dataframe)
response = sdk.compute.ai_chat(test_workspace_id, "Display the revenue by product")
execution_definition = sdk.compute.buid_exec_def_from_chat_result(response)
# Create a pandas dataframe from the AI response.
gp = GoodDataPandas(host, token)
gdf = gp.data_frames(workspace_id)
df, df_metadata = gdf.for_created_visualization(response)
# Print the results
print(execution_definition) # Execution Definition.
print(df_metadata) # Dataframe metadata.
print(df) # Pandas dataframe.