Rows
Get row traces
Retrieve AI extraction and enhancement traces for a row.
GET
/
v1
/
tables
/
{table_id}
/
rows
/
{row_id}
/
traces
const traces = await client.enhance.traces(
"tbl_abc123",
"row_xyz789",
"description"
);
for (const trace of traces.data) {
console.log(trace.column_key);
console.log(trace.model);
console.log(trace.confidence);
}
traces = client.enhance.traces(
"tbl_abc123",
"row_xyz789",
column_key="description",
)
for trace in traces["data"]:
print(trace["column_key"])
print(trace["model"])
print(trace["confidence"])
curl -X GET "https://hub.banditshq.com/api/v1/tables/tbl_abc123/rows/row_xyz789/traces?column_key=description" \
-H "Authorization: Bearer lasso_..."
{
"data": [
{
"column_key": "description",
"model": "gemini-pro",
"confidence": 0.92,
"request": {
"system_prompt": "You are a product data expert...",
"user_content": "Generate a description for: iPhone 15 Pro",
"tools": []
},
"response": {
"text": "The iPhone 15 Pro features...",
"iterations": 1,
"tool_calls": [],
"thought_summary": "Used product name and specs to generate description",
"sources": []
}
}
]
}
Traces provide full transparency into how AI generated or enhanced each column value, including the prompts, model used, confidence scores, and source references.
Path parameters
string
required
The unique identifier of the table.
string
required
The unique identifier of the row.
Query parameters
string
Filter traces to a specific column. Omit to get traces for all columns.
Response
array
Show Trace object
Show Trace object
string
The column this trace belongs to.
string | null
The AI model used.
number | null
Confidence score (0-1).
object
const traces = await client.enhance.traces(
"tbl_abc123",
"row_xyz789",
"description"
);
for (const trace of traces.data) {
console.log(trace.column_key);
console.log(trace.model);
console.log(trace.confidence);
}
traces = client.enhance.traces(
"tbl_abc123",
"row_xyz789",
column_key="description",
)
for trace in traces["data"]:
print(trace["column_key"])
print(trace["model"])
print(trace["confidence"])
curl -X GET "https://hub.banditshq.com/api/v1/tables/tbl_abc123/rows/row_xyz789/traces?column_key=description" \
-H "Authorization: Bearer lasso_..."
{
"data": [
{
"column_key": "description",
"model": "gemini-pro",
"confidence": 0.92,
"request": {
"system_prompt": "You are a product data expert...",
"user_content": "Generate a description for: iPhone 15 Pro",
"tools": []
},
"response": {
"text": "The iPhone 15 Pro features...",
"iterations": 1,
"tool_calls": [],
"thought_summary": "Used product name and specs to generate description",
"sources": []
}
}
]
}
⌘I
const traces = await client.enhance.traces(
"tbl_abc123",
"row_xyz789",
"description"
);
for (const trace of traces.data) {
console.log(trace.column_key);
console.log(trace.model);
console.log(trace.confidence);
}
traces = client.enhance.traces(
"tbl_abc123",
"row_xyz789",
column_key="description",
)
for trace in traces["data"]:
print(trace["column_key"])
print(trace["model"])
print(trace["confidence"])
curl -X GET "https://hub.banditshq.com/api/v1/tables/tbl_abc123/rows/row_xyz789/traces?column_key=description" \
-H "Authorization: Bearer lasso_..."
{
"data": [
{
"column_key": "description",
"model": "gemini-pro",
"confidence": 0.92,
"request": {
"system_prompt": "You are a product data expert...",
"user_content": "Generate a description for: iPhone 15 Pro",
"tools": []
},
"response": {
"text": "The iPhone 15 Pro features...",
"iterations": 1,
"tool_calls": [],
"thought_summary": "Used product name and specs to generate description",
"sources": []
}
}
]
}