Data Analysis

Uses the DataVoyager agent (hosted on Cloud Run, accessed via asta-gateway) to run a multi-agent data-science pipeline: the agent writes and executes code against the caller's dataset(s) in a sandboxed notebook and answers a research question. Auth is asta auth login.

Step 1 — Draft a tightened query

Before asking the user anything, analyze their request and the surrounding context (current project, conversation history, files they've been working on) to produce a tightened analytical question that:

• Names the specific dataset(s) that will be analyzed
• States what decision or insight the user is after, not just "analyze X"
• Is phrased as a question DataVoyager can actually answer with code

Examples:

• User says "look at this CSV" → inspect the file path, sample the top rows if possible, produce a concrete query like "Which columns in sales_q3.csv have the strongest correlation with quarterly revenue, controlling for region?"
• User says "what's in the titanic data" → "What features best predict survival in titanic.csv, and how do survival rates differ across passenger class and sex?"
• User gives a specific question with a specific dataset → echo it verbatim

Step 2 — Confirm with one chat question