DataLens Agent (Opus) developed the project goal field design proposal. The project goal concept is represented by the scope field in the data model although renamed in UI. The project goal is used to inform the file summary prompt replacing the previous hardcoded budget analysis description. The Project Dashboard UI displays the project goal to the user.

A key epic for setting project scope, priorities, and goals, under development and testing.

Phase 2 requirement: automated creation of project-specific goals, validated and integrated into the platform, enabling targeted data analysis.

The ProjectCreate pydantic model is modified to make the scope field required with word count validation. The catalog.py:_generate_ai_summary function is modified to replace hardcoded budget analysis text with the Project's scope in prompts. File Summary Generation uses the project's scope instead of a hardcoded string to contextualize the summaries. The Project Creation UI includes a textarea for the scope (project goal) with word count validation and generation support. The Project Dashboard displays the project's scope as the Project Goal for users. Analysis Recommendations generation uses the project scope and file catalog to suggest specific analysis questions. The Backend API for Projects validates the scope field with a minimum 20-word count requirement. Frontend UI Components implement the user interface elements for editing and displaying the scope as the Project Goal.

Authentication services cooperate with Project services in the backend Project services cooperate with Database services in the backend

Project Storage is used by the DuckDB Service to store project-specific DuckDB files. DockerDB file storage is represented as Project Storage for DuckDB database files.

PostgreSQL project_14 schema contains 72 migrated tables from DuckDB as part of the backend migration. The project_14 schema in PostgreSQL stores extracted data from the 132 SVGV dataset files. PostgreSQL hosts the project_14 schema which stores extracted SVGV dataset tables. project_14 schema consists of 72 tables now hosted in the PostgreSQL backend after migration. The full SVGV dataset reset and re-extraction process involves dropping and recreating the project_14 schema to an empty state. PostgreSQL database stores the project_14 schema used for SVGV data storage and extraction results.

DuckDBService manages Project 14 DuckDB file for extracted data operations. Migration script reads data from Project 14 DuckDB file with read-only access during migration.

project_gdpr_flags stores GDPR sensitivity detection results for files and columns, indicating potential PII, with confidence scores and timestamps for compliance. The project_gdpr_flags table stores GDPR flags linked to projects via project_id. GDPR flags reference files through the file_id column in project_gdpr_flags. GDPR PII detection results are recorded in the project_gdpr_flags table to track personal data sensitivity. ProjectGdprFlag data entity uses SchemaProfile data entity to define schema-related GDPR flags. AgentSession data entity uses ProjectGdprFlag data entity to manage GDPR compliance flags. Projects contain project_gdpr_flags tables that flag GDPR-related data for the project.

The scope field is required in the ProjectCreate pydantic model as per design. ProjectCreate validation for scope applies to the ProjectCreate pydantic model to enforce a minimum word count. The ProjectCreate pydantic model is modified to make the scope field required with word count validation.

ProjectCreate validation for scope applies to the ProjectCreate pydantic model to enforce a minimum word count. ProjectCreate validation for scope requires word count validation to enforce text length. ProjectCreate validation for scope validates that the scope field meets minimum word count requirements.

The scope field is included in the ProjectResponse to ensure it is always present.

The Backend handles projects The DataLens Platform has a Projects module to handle project creation and management. The projects tables contain agent_sessions tables providing session data for analysis. Projects contain project_gdpr_flags tables that flag GDPR-related data for the project. Projects include schema_profiles tables which hold profile data of database schemas associated with the project. Projects include processing_jobs tables that track background jobs related to files or data processing for the project. Organizations contain projects tables which list all projects under the organization. Projects include file_uploads tables which track files uploaded to the project. Projects track queries tables that record SQL queries run against project data. Projects possess insights tables which store generated insights tied to project data analysis. projects page is implemented as a SvelteKit page. projects page is built using the SvelteKit framework. projects page is part of the DataLens system. The projects page is part of the DataLens project.

The page projects > :id > agent is part of the projects > :id page. The page projects > :id > analyze is part of the projects > :id page. The page projects > :id > workflow is part of the projects > :id page. The page projects > :id is part of the projects page. project details page is implemented as a SvelteKit page. projects > :id page is built using the SvelteKit framework. projects > :id page is part of the DataLens system. The projects > :id page is part of the DataLens project.

projects > :id > agent page is built using the SvelteKit framework. projects > :id > agent page is part of the DataLens system. The projects > :id > agent page is part of the DataLens project.

projects > :id > analyze page is built using the SvelteKit framework. projects > :id > analyze page is part of the DataLens system. The projects > :id > analyze page is implemented as a SvelteKit page. The projects > :id > analyze page is part of the DataLens project.

The page projects > :id > workflow is part of the projects > :id page. project workflow page is implemented as a SvelteKit page. projects > :id > workflow page is built using the SvelteKit framework. projects > :id > workflow page is part of the DataLens system. The projects > :id > workflow page is part of the DataLens project.

DataLens Platform supports CRUD functionality for managing projects. The Backend API for Projects validates the scope field with a minimum 20-word count requirement.

The Frontend UI Translation use case includes a language selector on the Projects page. The page projects > :id is part of the projects page. The page projects > new is part of the projects page. The Frontend contains a projects list page

Contains 33 of 35 answered analytical questions, verified budget of 328.5M DKK, includes sources, and is part of report derivation.

Defines a unified interface to support multiple data sources and APIs, enabling flexible, scalable integration of diverse data inputs and provider systems, simplifying platform extensibility and maintainability.

SQLAlchemy depends on psycopg2-binary as a PostgreSQL database driver.

The environment variable is not specified or set. It is required for frontend backend communication but currently not met. DataLens Platform requires setting PUBLIC_API_URL environment variable to the public backend API URL for frontend connectivity. Frontend requires backend API URL configured as PUBLIC_API_URL environment variable to connect to backend. DataLens Platform requires setting PUBLIC_API_URL environment variable to the public backend API URL for frontend connectivity. Frontend requires backend API URL configured as PUBLIC_API_URL environment variable to connect to backend.