topaz-ai
umang sutharI am thinking to build a AI system which basically do the sub concious thiniking as much as possible and keep increasing it's own knowledge by it self.. Like humans have.. how human brain works.. it keeps running in sub concious mind keep thinking all possibilities and cases and increasing it's knowledge by keep searching all over the world.. I need similar capabilities in the system. where system keeps doing the research and increasing it's knowleged.. For now to store the new knowledge we can use custom graph system and store the data in the weaviate service. So basically user came and give the task.. our sub concious AI keeps doing it's reaseach and keeps gethering the knowledge, prepare all possibilities and cases and keep doing it in that domain and this keep going till everything is covered.. also same like human let's say our system search xyz thing and found pqr then it should keep go and gether information about pqr as well and keep going on... now if user came back and ask anything now system should give reply from already researched and gethered knowledge ... if system found it doesn't have knowledge then it should start doing research in that direction.. user should be able to stop this sub concious ai to perform research whereever user wants but otherwise it should keep going on
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Project Tasks26
Implement design system theme
As a Frontend Developer, I want to implement the global theme, color palette, typography, spacing tokens, and component design system aligned with the v2 mock designs so that all pages have a consistent visual identity across the topaz-ai application.
Setup MySQL schema migrations
As a Backend Developer, I want to define and run Alembic (or equivalent) database migrations for all MySQL tables — users, research_tasks, task_runs, summaries, and user_preferences — so that the RDBMS layer is fully versioned and all backend APIs have a reliable structured data store. NOTE: frontend pages that depend on this include Dashboard, Settings, Results, and Research.
Setup WeaviateDB schema classes
As a Backend Developer, I want to initialise Weaviate with the required class definitions (KnowledgeNode, Hypothesis, ResearchSummary, etc.) including vectorizer config and cross-references so that the knowledge graph API and autonomous research engine can persist and retrieve semantic data correctly. NOTE: depends on Weaviate service being available; the WeaviateDB knowledge API task (e593e645) depends on this being done first.
Remove unused scaffold pages
As a Frontend Developer, I want to remove the signup and welcome pages from the scaffold so that only pages defined in the user flows remain, keeping the codebase clean and navigation consistent with the intended product experience.
Implement Landing page
As a user, I want to see a polished Landing page with the Explore Spiral interaction so that I can understand the topaz-ai product and be guided toward signing in, fully aligned with the v2 design mockup.
Implement Login page
As a user, I want a fully styled Login page matching the v2 Sign In design so that I can authenticate securely with a visually consistent and intuitive interface aligned with the topaz-ai brand.
Implement Dashboard page
As a user, I want a fully implemented Dashboard page matching the v2 design so that I can assign tasks to the AI, view an overview of active research, and navigate to other sections of the topaz-ai application.
Build JWT auth middleware
As a Backend Developer, I want to implement FastAPI JWT authentication middleware and protected route dependencies so that all API endpoints (task assignment, knowledge graph, query, results, settings) are secured and only accessible to authenticated users. This middleware should validate tokens issued at login and attach the user context to each request.
Implement Research page
As a user, I want a fully implemented Research page matching the v2 design so that I can view AI research progress, pause or monitor the AI, and track active research scenarios in real time.
Implement Query page
As a user, I want a fully implemented Query page matching the v2 design so that I can ask the AI questions and request insights drawn from the accumulated knowledge graph.
Implement Settings page
As a user, I want a fully implemented Settings page matching the v2 design so that I can manage and configure AI research summaries, preferences, and system settings from a single interface.
Build task assignment API
As a Backend Developer, I want to build a FastAPI endpoint for creating and managing AI research task assignments so that the Dashboard can submit new research goals and track their lifecycle in MySQL.
Build user settings API
As a Backend Developer, I want to build FastAPI CRUD endpoints for user preferences — including periodic summary toggle, summary interval configuration, and research control flags — so that the Settings page can read and persist user-specific configuration to MySQL. NOTE: the Settings frontend task (d47f239a) depends on this endpoint.
Build real-time research progress stream
As a Backend Developer, I want to implement a Server-Sent Events (SSE) or WebSocket endpoint that streams live research task progress — including current topic, nodes discovered, hypotheses generated, and status changes — so that the Research page can display real-time AI activity to users without polling. NOTE: the Research frontend task (8b3ddc9c) and Dashboard task (1907a07f) both depend on this for live updates.
Implement Results page
As a user, I want a fully implemented Results page matching the v2 design so that I can view AI-generated findings, hypotheses, and intelligence summaries produced from completed research tasks.
Implement Knowledge Graph page
As a user, I want a fully implemented Knowledge Graph page matching the v2 design so that I can visually explore nodes, relationships, and concepts stored in WeaviateDB as the AI expands its knowledge.
Build autonomous research loop
As an AI Engineer, I want to implement the core autonomous research engine loop so that topaz-ai can independently discover, process, and iterate on research topics without manual intervention, forming the backbone of the subconscious AI system.
Build WeaviateDB knowledge API
As a Backend Developer, I want to build FastAPI endpoints for storing, retrieving, and querying knowledge graph nodes and relationships in WeaviateDB so that all AI research outputs are persisted and explorable on the Knowledge Graph page.
Integrate internet research tools
As an AI Engineer, I want to integrate internet search and web scraping tools into the research engine so that topaz-ai can autonomously gather external knowledge from the web and expand its knowledge graph with real-world data.
Build hypothesis generation module
As an AI Engineer, I want to implement an AI module that generates, scores, and stores hypotheses derived from accumulated research data so that users can view novel insights and inferred conclusions on the Results page.
Build query knowledge base API
As a Backend Developer, I want to build a FastAPI endpoint that accepts natural language queries and returns AI-generated insights from WeaviateDB so that the Query page can surface relevant knowledge and analysis to users.
Build research results API
As a Backend Developer, I want to build FastAPI endpoints to retrieve structured research findings, hypotheses, and intelligence summaries so that the Results page can display completed AI research outputs to users.
Build research pause/stop API
As a Backend Developer, I want to build FastAPI endpoints to pause, resume, and stop active research tasks so that users can control the AI research loop in real time from the Research page.
Setup LLM routing via Litellm
As an AI Engineer, I want to configure Langchain and Litellm to intelligently route AI tasks across GPT, Claude, and Gemini models so that the research engine can leverage multiple LLMs with fallback and cost optimization strategies.
Implement periodic summaries feature
As an AI Engineer, I want to implement a periodic summaries feature that automatically generates and stores concise research summaries at configurable intervals so that users can manage and review AI progress from the Settings page.
Build selective regenerate results API
As a Backend Developer, I want to build a FastAPI endpoint that allows users to selectively re-run or regenerate specific research findings or hypotheses so that stale or low-confidence results can be refreshed without restarting the full research cycle.
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