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v0.2.0

DataFoundry 0.2 expands the initial governed data-agent workbench into a stateful workflow for concurrent analysis, evidence-backed follow-ups, reusable outputs, and production-facing Web deployment.

Highlights

Data Link, our newly open-sourced data knowledge graph, now joins the DataFoundry ecosystem as a first-party semantic foundation. A schema tells an agent what columns exist; Data Link helps it understand what those columns mean, how datasets connect, and which relationships are reliable enough to use.

  • Build a dual-layer graph: structural nodes such as tables and columns remain grounded in source data, while shared Concept and Entity nodes organize business meaning.
  • Connect explicit relationships such as foreign keys and lineage with inferred relationships such as joinable, semantic_synonym, correlated, and distribution_similar, each carrying confidence information.
  • Explore unfamiliar data through an agent-oriented retrieval interface instead of injecting an entire catalog into the prompt.
  • Query Data Link through MCP and REST. DataFoundry discovers a configured Data Link/DataGraph server and exposes its graph, exploration, table-management, and rebuild workflows inside the Web workbench.
  • Give complex analysis a stronger semantic starting point: fewer blind joins, less field guessing, and a clearer path from physical schema to business concepts.

Data Link is designed as a universal graph for tables, documents, slides, and images. DataFoundry 0.2 integrates its graph and agent retrieval surface; the Data Link service is deployed and configured separately, so both projects can evolve independently.

Stateful analysis and conversation control

  • Run multiple data-task sessions without coupling their live state.
  • Queue, edit, send immediately, or remove follow-up prompts while a run is active.
  • Restore persisted messages, tool calls, run events, outputs, and terminal run status after refresh or session switching.
  • Re-ask from an earlier user turn or create a branch from a persisted checkpoint. The original path remains available, and branch navigation keeps the alternatives explicit.

Evidence, trace, and semantic exploration

  • Reference a whole output or a selected table/text region in the next question.
  • Resolve artifact, SQL audit, trace-step, schema, preview, and knowledge references on the server before they enter the governed run context.
  • Inspect a semantic Trace DAG built from runs, steps, tool calls, checkpoints, outputs, and their relationships.
  • Open the Data Link workspace graph to explore tables, columns, concepts, entities, and edges when a compatible Data Link MCP service is configured.

Outputs and workspace assets

  • Restore session outputs independently from the live conversation.
  • Preview tables, charts, reports, SQL, and files; export supported table and chart formats.
  • Upload files into the active session and promote supported files or file-backed outputs into cross-session workspace assets.
  • Mention reusable workspace assets in later questions so analysis can continue from prior material.

Web deployment and onboarding

  • Use built-in password authentication with registration, verification, login, password reset, session management, CSRF protection, and secure cookies.
  • Route browser API and CopilotKit traffic through the same-origin Next.js proxy in formal deployments.
  • Use the Web workbench in English or Simplified Chinese.
  • Create and test OpenAI-compatible model profiles before selecting them for a run.
  • Start with the guided first-run flow and the automatically provisioned DTC Growth Review SQLite case.

Runtime and terminal workflow

  • Preserve provider-compatible prompt content while keeping governed context compilation and prompt snapshot ordering deterministic.
  • Keep schema-first, read-only SQL execution and audit behavior across restored and continued runs.
  • Use the refreshed chat-first TUI, session resume, output browsing, improved tables, input history, completion, scrolling, and responsive terminal layout.

Reliability and bug fixes

  • Deterministic model context: fixed prompt snapshot ordering and provider message compatibility so restored history, the current turn, assistant tool calls, and tool results reach the model in the intended order.
  • Conversation restore: removed races around session switching, restored terminal run status from backend checkpoints, preserved tool-call/result pairing, and prevented stale sessions from overwriting the active conversation.
  • Session UX: fixed chat scroll restoration, session-switch positioning, input-window overlap, queued-prompt transitions, running indicators, and stop behavior.
  • SQL and audit stability: normalized BigInt and other non-JSON SQL values before transport, stabilized audit-log identifiers, and kept read-only results available as artifacts without serialization failures.
  • Datasource readiness: tightened datasource selection, local file-path handling, connection-state display, and schema-first execution so runs fail earlier and more clearly when required data context is unavailable.
  • Tool and trace delivery: improved streamed tool-result normalization, failure presentation, parent/step correlation, token usage display, cancellation, and recovery of outputs after refresh.
  • Production Web path: reduced the initial workbench bundle through a lightweight route entry, hardened same-origin API proxying, and improved backend startup/readiness reporting.
  • Release checks: repaired stale source-contract tests after the Web workbench split and aligned smoke tests with the new DTC case instead of the retired DuckDB demo.

Compatibility and known boundaries

  • No intentional public REST or AG-UI breaking change is introduced for existing 0.1 integrations, but the recommended deployment and demo path changed.
  • The retired api-duckdb-demo is no longer auto-created. npm install now generates the DTC Growth Review SQLite fixture, which the API provisions per user/workspace.
  • Data Link requires a separately running compatible Data Link/DataGraph MCP and REST service.
  • This is a pre-release. Validate authentication, secrets, datasource policy, backup, monitoring, and reverse-proxy behavior for your environment before production use.

Upgrade notes

  • Node.js 22 or later is required.
  • Run npm install after pulling 0.2 because workspace dependencies and the lockfile changed.
  • Formal deployment uses password auth with build / start; review the required auth variables in Quick start.
  • Rebuild the Web app after changing NEXT_PUBLIC_* values.
  • Data Link is an integration surface, not an embedded semantic service. Configure a compatible MCP server before expecting graph data.
  • Production deployments still need environment-specific secret management, access policy, audit export, monitoring, backup, and TLS termination.

Documentation map