{
"project": {
"id": "7ba7aeef-4fd0-43c4-9341-b588e55279dd",
"name": "Doc Flow AI",
"slug": "doc-flow-ai",
"description": "",
"scope": "",
"product_version": "0.0.1",
"product_status": "MVP",
"github_repo_url": "https://github.com/NexOTica-GmbH/doc-flow-ai",
"linear_project_id": "db99ccb1-a86e-4da1-9bdb-be23414fac96",
"github_webhook_id": "670371286",
"linear_webhook_id": null,
"host_port": null,
"api_host_port": null,
"lifecycle_state": "scaffolded",
"mvp_scope_locked_at": null,
"created_at": "2026-08-25T16:29:27.076252",
"updated_at": "2026-08-25T16:33:07.749958"
},
"scope_chat_status": "open",
"active": true,
"locked": false,
"mvp_scope_locked_at": null,
"draft_stories": [
{
"work": "Health page",
"role": "Front-end",
"title": "Health page (Front-end)",
"product_status": "MVP",
"acceptance_criteria": [],
"description": "## Story\n\nHealth page\n\n## Acceptance criteria\n\n- [ ] Health page is implemented for the Front-end slice.\n- [ ] Automated tests cover the happy path where applicable.\n\n## Source\n\nProduct Manager scope. Product Owner must not expand business features.\n"
},
{
"work": "Health endpoint",
"role": "Back-end",
"title": "Health endpoint (Back-end)",
"product_status": "MVP",
"acceptance_criteria": [],
"description": "## Story\n\nHealth endpoint\n\n## Acceptance criteria\n\n- [ ] Health endpoint is implemented for the Back-end slice.\n- [ ] Automated tests cover the happy path where applicable.\n\n## Source\n\nProduct Manager scope. Product Owner must not expand business features.\n"
}
],
"product_status": "MVP",
"closed_at_status": null,
"messages": [
{
"id": "7dfd61c9-739c-40f2-9b49-69b23fdb4ecf",
"role": "pm",
"body": "## System Architecture & Technical Specifications\r\n```\r\n +-------------------------------------------------------+\r\n | Next.js Fullstack |\r\n | (App Router + Tailwind + shadcn/ui + TypeScript) |\r\n +---------------------------+---------------------------+\r\n |\r\n +------------------------------------+-----------------------------------+\r\n | | |\r\n v v v\r\n +-------------------+ +--------------------+ +-------------------+\r\n | Ingestion Engine | | Consensus Engine | | Cloud & Storage |\r\n | - File Parsing | | - LLM Provider API | | - Google Drive API|\r\n | (PDF/CSV/TXT/ | | (Gemini, OpenAI, | | (Service Account|\r\n | Images) | | Grok Adapter) | | Auth) |\r\n | - PDF Renamer | | - Multi-Round Loop | | - SQLite Database |\r\n +-------------------+ +--------------------+ +-------------------+\r\n\r\n```\r\n---\r\n## 1. Complete Feature Matrix\r\n### Ingestion & Processing Pipeline\r\n* **Multi-Format Ingestion:** Drag-and-drop / file picker on the landing page accepting `.pdf`, `.png`, `.jpg`, `.jpeg`, `.csv`, `.txt`, and `.md`.\r\n* **Universal Normalization:** Text/CSV/Image inputs are parsed into text representations and normalized into a standard PDF artifact for archiving.\r\n* **Smart Renaming Engine:** Generates target PDF file names following the strict pattern: `ddmmyyyy-sender-sequence.pdf` (e.g., `22082026-AcmeCorp-001.pdf`), extracting the sender and date via the AI consensus or falling back to user input.\r\n### Multi-LLM Consensus Engine (Extensible)\r\n* **Provider Abstraction Interface:** Standardized `BaseLLMProvider` contract (`generateResponse`, `streamResponse`, `modelName`) allowing zero-friction addition of new models (OpenAI, Gemini, Grok, Claude).\r\n* **Sequential Peer Review Loop (Option A):**\r\n* **Round 1:** Model A (e.g., Gemini 1.5 Pro) reads the raw document and produces an initial structured assessment and tag recommendations.\r\n* **Round 2:** Model B (e.g., OpenAI GPT-4o) critiques Model A's extraction, flags discrepancies, and refines key data points.\r\n* **Rounds 3\u201310 (Configurable):** Iterative refinement between models until both models signal consensus or the 10-round cap is reached.\r\n* **Synthesis Step:** A unified assessment report (Markdown format) is generated and delivered to the chat window.\r\n* **Tag Suggestion Mechanism:** Models return candidate tags based on document analysis; suggestions are displayed as clickable chips in the UI without modifying the database.\r\n### Tag & Metadata Management\r\n* **Dynamic User-Driven Tags:** Clean-slate tag system with zero hardcoded tags.\r\n* **Manual Tag Creation:** Dedicated \"Create Tag\" modal/button in the chat interface allowing custom tag creation on the fly.\r\n* **Tag Assignment:** Documents can hold multiple user-confirmed tags, stored relationally in SQLite.\r\n\r\n### Chat & Interactive Workspace\r\n\r\n* **ChatGPT/Gemini-Style UI:** Responsive interface featuring a collapsible left sidebar (recent uploads and conversations) and a central chat stream.\r\n* **Post-Assessment Interactivity:** User can ask follow-up questions, request specific recalculations, or instruct the models to re-evaluate sections.\r\n* **Assessment Preview:** Split-screen or toggle view to see the source document alongside the generated Markdown assessment.\r\n* **Session Reset / Logout:** Clears current active session state and resets the workspace to the landing state.\r\n### Google Drive & Database Persistence\r\n* **Headless Service Account Integration:** Authenticates automatically using a root-level `service_account.json` credential file to access a designated Drive folder.\r\n* **Database Archival:** Persists document metadata, UUIDs, full chat transcripts, tag relationships, and Markdown/PDF assessment reports in a local SQLite database.\r\n---\r\n## 2. Dependency & Stack Assessment\r\nThis stack is selected for optimal compatibility with **Cursor** (TypeScript end-to-end type safety, unified Next.js App Router, zero-boilerplate ORM).\r\n\r\n### Recommended Tech Stack\r\n\r\n* **Framework:** Next.js 14/15 (App Router, Server Actions, Route Handlers)\r\n* **Styling & Components:** Tailwind CSS + `shadcn/ui` + `lucide-react`\r\n* **Database & ORM:** SQLite via `@libsql/client` or `better-sqlite3` + `drizzle-orm` (lightweight, zero external server requirement)\r\n* **File & PDF Processing:** `pdf-parse`, `pdf-lib`, `papaparse`, `tesseract.js` (or LLM Vision API for OCR)\r\n\r\n### Core Dependencies & Environment Configuration\r\n\r\n| Package | Purpose | Version Spec |\r\n| --- | --- | --- |\r\n| `googleapis` | Google Drive API v3 Service Account Client | `^140.0.0` |\r\n| `@google/genai` | Google Gemini SDK | Latest |\r\n| `openai` | OpenAI & Grok (xAI API is OpenAI-compatible) | `^4.50.0` |\r\n| `drizzle-orm` / `drizzle-kit` | SQLite Database Schema & Query Builder | Latest |\r\n| `better-sqlite3` | Local database engine | `^9.0.0` |\r\n| `pdf-lib` | Client/Server PDF creation & metadata manipulation | `^1.17.1` |\r\n| `papaparse` | CSV data parsing | `^5.4.1` |\r\n| `zod` | Runtime validation for LLM structured outputs | `^3.23.0` |\r\n\r\n#### Environment Variables (`.env.local`)\r\n\r\n```env\r\n# AI Providers\r\nGEMINI_API_KEY=\"AIzaSy...\"\r\nOPENAI_API_KEY=\"sk-proj-...\"\r\nGROK_API_KEY=\"xai-...\"\r\nDEFAULT_MAX_DEBATE_ROUNDS=10\r\n\r\n# Google Drive Configuration\r\nGOOGLE_APPLICATION_CREDENTIALS=\"./service_account.json\"\r\nGOOGLE_DRIVE_FOLDER_ID=\"1A2B3C4D5E6F7G8H9I0J\"\r\n\r\n# Database\r\nDATABASE_URL=\"file:./data/app.db\"\r\n```\r\n---\r\n## 3. Database Schema Design (SQLite / Drizzle)\r\n\r\n```sql\r\n-- Documents Table\r\nCREATE TABLE documents (\r\n id TEXT PRIMARY KEY, -- UUIDv4\r\n original_filename TEXT NOT NULL,\r\n gdrive_filename TEXT,\r\n gdrive_file_id TEXT,\r\n mime_type TEXT NOT NULL,\r\n local_file_path TEXT NOT NULL,\r\n sender TEXT,\r\n sequence_number INTEGER,\r\n status TEXT CHECK(status IN ('uploaded', 'analyzing', 'ready', 'exported', 'failed')) DEFAULT 'uploaded',\r\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\r\n updated_at DATETIME DEFAULT CURRENT_TIMESTAMP\r\n);\r\n\r\n-- Tags Table (User-created only)\r\nCREATE TABLE tags (\r\n id TEXT PRIMARY KEY, -- UUIDv4\r\n name TEXT UNIQUE NOT NULL,\r\n color TEXT DEFAULT '#3B82F6',\r\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP\r\n);\r\n\r\n-- Document <-> Tags Junction Table\r\nCREATE TABLE document_tags (\r\n document_id TEXT NOT NULL REFERENCES documents(id) ON DELETE CASCADE,\r\n tag_id TEXT NOT NULL REFERENCES tags(id) ON DELETE CASCADE,\r\n PRIMARY KEY (document_id, tag_id)\r\n);\r\n\r\n-- Assessments Table\r\nCREATE TABLE assessments (\r\n id TEXT PRIMARY KEY, -- UUIDv4\r\n document_id TEXT NOT NULL REFERENCES documents(id) ON DELETE CASCADE,\r\n final_markdown TEXT NOT NULL,\r\n debate_rounds_count INTEGER NOT NULL,\r\n raw_debate_transcript TEXT, -- JSON Array of internal model exchanges\r\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP\r\n);\r\n\r\n-- Chat Transcript Messages\r\nCREATE TABLE chat_messages (\r\n id TEXT PRIMARY KEY, -- UUIDv4\r\n document_id TEXT NOT NULL REFERENCES documents(id) ON DELETE CASCADE,\r\n sender_role TEXT CHECK(sender_role IN ('user', 'assistant', 'system', 'gemini', 'openai', 'grok')) NOT NULL,\r\n content TEXT NOT NULL,\r\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP\r\n);\r\n```\r\n---\r\n## 4. Extensible LLM Provider Interface\r\n\r\n```typescript\r\n// lib/llm/types.ts\r\nexport interface LLMMessage {\r\n role: 'system' | 'user' | 'assistant';\r\n content: string;\r\n}\r\n\r\nexport interface LLMResponse {\r\n content: string;\r\n suggestedTags?: string[];\r\n metadata?: {\r\n sender?: string;\r\n date?: string;\r\n };\r\n}\r\n\r\nexport interface BaseLLMProvider {\r\n name: string;\r\n analyzeDocument(content: string | Buffer, mimeType: string, prompt: string): Promise<LLMResponse>;\r\n critiqueAssessment(documentContent: string, previousAssessment: string, roundNumber: number): Promise<LLMResponse>;\r\n chat(messages: LLMMessage[]): Promise<string>;\r\n}\r\n\r\n```\r\n---\r\n## 5. Comprehensive User Stories Catalog\r\n### Epic 1: Document Upload & Ingestion\r\n* **US-1.1: Multi-Format Ingestion**\r\n* **As a** user,\r\n* **I want to** drag and drop or upload PDF, Image, CSV, TXT, or Markdown files on the landing page,\r\n* **So that** I can process any document regardless of its source format.\r\n* **Acceptance Criteria:**\r\n* Landing page shows a clean upload dropzone.\r\n* Supported file formats (`.pdf`, `.png`, `.jpg`, `.jpeg`, `.csv`, `.txt`, `.md`) are accepted; all others show an error toast.\r\n* File is assigned a unique UUID and stored in local temporary storage.\r\n* **US-1.2: Transition to Active Workspace**\r\n* **As a** user,\r\n* **I want to** be automatically transitioned to the chat workspace once a file is uploaded,\r\n* **So that** I can monitor the analysis and begin interacting immediately.\r\n* **Acceptance Criteria:**\r\n* Landing page smoothly transitions to the ChatGPT/Gemini-style dual-panel workspace upon upload completion.\r\n* Document status indicators update from \"Processing\" to \"Analyzing\" to \"Ready\".\r\n---\r\n### Epic 2: Multi-LLM Collaborative Review Engine\r\n* **US-2.1: Sequential Peer Review (Gemini & OpenAI)**\r\n* **As a** user,\r\n* **I want** Gemini and OpenAI to collaboratively review the document up to a maximum of 10 rounds,\r\n* **So that** I receive a highly accurate, audited assessment report.\r\n* **Acceptance Criteria:**\r\n* Model A generates initial extraction and summary.\r\n* Model B reviews Model A's output against the raw file content, pointing out corrections or omissions.\r\n* The process repeats sequentially until models reach agreement or hit 10 rounds maximum.\r\n* Final consolidated Markdown report is rendered in the main chat viewport.\r\n* **US-2.2: Third-Party Model Extensibility (Grok / Claude)**\r\n* **As a** developer/user,\r\n* **I want** the LLM engine to follow an abstracted interface,\r\n* **So that** I can plug in Grok (xAI) or other providers without rewriting the core workflow.\r\n* **Acceptance Criteria:**\r\n* Adding a new provider requires only implementing the `BaseLLMProvider` interface and registering it in a factory map.\r\n---\r\n### Epic 3: Tagging & Metadata Control\r\n* **US-3.1: Zero-Seed Dynamic Tag Creation**\r\n* **As a** user,\r\n* **I want to** create custom tags manually whenever needed with no predefined seed tags,\r\n* **So that** my taxonomy matches my personal organization requirements.\r\n* **Acceptance Criteria:**\r\n* Initial database contains 0 tags.\r\n* \"Create Tag\" button opens a quick modal with tag name and color selection.\r\n* Newly created tag is immediately available for document association.\r\n* **US-3.2: AI Tag Suggestions (Read-Only)**\r\n* **As a** user,\r\n* **I want to** see tag recommendations from the AI without them being auto-created,\r\n* **So that** I maintain complete control over my tag taxonomy.\r\n* **Acceptance Criteria:**\r\n* LLM consensus response includes suggested tags rendered as clickable chips.\r\n* Clicking a suggestion checks if the tag exists; if not, it prompts the user to confirm creation before applying.\r\n---\r\n### Epic 4: Interactive Chat & Post-Assessment\r\n* **US-4.1: Assessment Discussion**\r\n* **As a** user,\r\n* **I want to** ask follow-up questions about the assessment in the chat interface,\r\n* **So that** I can clarify specific clauses, values, or calculations.\r\n* **Acceptance Criteria:**\r\n* Chat input accepts questions and responds with context from both the document and consensus report.\r\n* Full message history is appended to `chat_messages` in the database.\r\n\r\n* **US-4.2: Recent Conversations & File Sidebar**\r\n* **As a** user,\r\n* **I want** a sidebar listing recent uploads and past conversations,\r\n* **So that** I can switch back to previous documents and review their state.\r\n* **Acceptance Criteria:**\r\n* Left sidebar displays chronological list of uploaded documents with assigned tags.\r\n* Clicking a historical item loads its chat transcript, assessment, and metadata.\r\n---\r\n### Epic 5: Google Drive Archival & Database Storage\r\n* **US-5.1: File Renaming & Standardized PDF Export**\r\n* **As a** user,\r\n* **I want** the uploaded file converted to PDF and renamed as `ddmmyyyy-sender-sequence.pdf`,\r\n* **So that** all stored documents have consistent, predictable file names.\r\n* **Acceptance Criteria:**\r\n* Non-PDF documents are converted to PDF format.\r\n* Sender name is extracted from AI metadata (or requested from user if missing).\r\n* Date format is strictly `ddmmyyyy`. Sequence number increments based on existing records in the database.\r\n\r\n* **US-5.2: Service Account Google Drive Upload**\r\n* **As a** system/user,\r\n* **I want** the renamed PDF uploaded to Google Drive via a local `service_account.json` file,\r\n* **So that** I do not have to perform interactive OAuth logins.\r\n* **Acceptance Criteria:**\r\n* Server loads `service_account.json` from the root directory.\r\n* File uploads to the specified Google Drive target folder.\r\n* Returned Google Drive File ID and web view link are recorded in the database.\r\n\r\n* **US-5.3: Database Transcript & Assessment Persistence**\r\n* **As a** user,\r\n* **I want** the original filename, generated report, and full chat transcript persisted in the database,\r\n* **So that** I have a permanent local audit trail.\r\n* **Acceptance Criteria:**\r\n* `assessments` and `chat_messages` tables are updated at the end of each session.\r\n* Database stores the original file name alongside the renamed Drive file name.",
"seq": 1,
"created_at": "2026-08-25T16:32:43.593951"
},
{
"id": "de998a6e-fd4c-4709-baa1-bb059e951911",
"role": "po",
"body": "Thanks for the comprehensive overview, PM! This gives us a great foundation for Doc Flow AI.\n\nTo effectively define our MVP scope, especially considering our fixed **React frontend** and **Python Flask backend**, I need a bit more clarity on the initial product focus.\n\nCould you please help me with the following:\n\n1. **Who is the primary user** for this MVP?\n2. **What is the single most critical problem** this MVP aims to solve for them?\n3. Based on that problem, which of the proposed Epics (Document Upload & Ingestion, Multi-LLM Collaborative Review Engine, Tagging & Metadata Control, Interactive Chat & Post-Assessment, Google Drive Archival & Database Storage) are **absolutely essential for the MVP**? Please indicate their priority.\n4. What would be the **key acceptance criteria** for the MVP to be considered successful from this primary user's perspective?",
"seq": 2,
"created_at": "2026-08-25T16:33:07.743201"
}
],
"status": "open",
"message": {
"id": "de998a6e-fd4c-4709-baa1-bb059e951911",
"role": "po",
"body": "Thanks for the comprehensive overview, PM! This gives us a great foundation for Doc Flow AI.\n\nTo effectively define our MVP scope, especially considering our fixed **React frontend** and **Python Flask backend**, I need a bit more clarity on the initial product focus.\n\nCould you please help me with the following:\n\n1. **Who is the primary user** for this MVP?\n2. **What is the single most critical problem** this MVP aims to solve for them?\n3. Based on that problem, which of the proposed Epics (Document Upload & Ingestion, Multi-LLM Collaborative Review Engine, Tagging & Metadata Control, Interactive Chat & Post-Assessment, Google Drive Archival & Database Storage) are **absolutely essential for the MVP**? Please indicate their priority.\n4. What would be the **key acceptance criteria** for the MVP to be considered successful from this primary user's perspective?",
"seq": 2
},
"providers": {
"gemini": "ok",
"openai": "ok",
"mode": "merged_via_gemini"
}
}
No description.
Delete
Drop from the registry and Linear. Does not delete the GitHub
repo (use CLI --delete-github if needed).
{
"project": {
"id": "7ba7aeef-4fd0-43c4-9341-b588e55279dd",
"name": "Doc Flow AI",
"slug": "doc-flow-ai",
"description": "",
"scope": "",
"product_version": "0.0.1",
"product_status": "MVP",
"github_repo_url": "https://github.com/NexOTica-GmbH/doc-flow-ai",
"linear_project_id": "db99ccb1-a86e-4da1-9bdb-be23414fac96",
"github_webhook_id": "670371286",
"linear_webhook_id": null,
"host_port": null,
"api_host_port": null,
"lifecycle_state": "scaffolded",
"mvp_scope_locked_at": null,
"created_at": "2026-08-25T16:29:27.076252",
"updated_at": "2026-08-25T16:33:07.749958"
},
"scope_chat_status": "open",
"active": true,
"locked": false,
"mvp_scope_locked_at": null,
"draft_stories": [
{
"work": "Health page",
"role": "Front-end",
"title": "Health page (Front-end)",
"product_status": "MVP",
"acceptance_criteria": [],
"description": "## Story\n\nHealth page\n\n## Acceptance criteria\n\n- [ ] Health page is implemented for the Front-end slice.\n- [ ] Automated tests cover the happy path where applicable.\n\n## Source\n\nProduct Manager scope. Product Owner must not expand business features.\n"
},
{
"work": "Health endpoint",
"role": "Back-end",
"title": "Health endpoint (Back-end)",
"product_status": "MVP",
"acceptance_criteria": [],
"description": "## Story\n\nHealth endpoint\n\n## Acceptance criteria\n\n- [ ] Health endpoint is implemented for the Back-end slice.\n- [ ] Automated tests cover the happy path where applicable.\n\n## Source\n\nProduct Manager scope. Product Owner must not expand business features.\n"
}
],
"product_status": "MVP",
"closed_at_status": null,
"messages": [
{
"id": "7dfd61c9-739c-40f2-9b49-69b23fdb4ecf",
"role": "pm",
"body": "## System Architecture & Technical Specifications\r\n```\r\n +-------------------------------------------------------+\r\n | Next.js Fullstack |\r\n | (App Router + Tailwind + shadcn/ui + TypeScript) |\r\n +---------------------------+---------------------------+\r\n |\r\n +------------------------------------+-----------------------------------+\r\n | | |\r\n v v v\r\n +-------------------+ +--------------------+ +-------------------+\r\n | Ingestion Engine | | Consensus Engine | | Cloud & Storage |\r\n | - File Parsing | | - LLM Provider API | | - Google Drive API|\r\n | (PDF/CSV/TXT/ | | (Gemini, OpenAI, | | (Service Account|\r\n | Images) | | Grok Adapter) | | Auth) |\r\n | - PDF Renamer | | - Multi-Round Loop | | - SQLite Database |\r\n +-------------------+ +--------------------+ +-------------------+\r\n\r\n```\r\n---\r\n## 1. Complete Feature Matrix\r\n### Ingestion & Processing Pipeline\r\n* **Multi-Format Ingestion:** Drag-and-drop / file picker on the landing page accepting `.pdf`, `.png`, `.jpg`, `.jpeg`, `.csv`, `.txt`, and `.md`.\r\n* **Universal Normalization:** Text/CSV/Image inputs are parsed into text representations and normalized into a standard PDF artifact for archiving.\r\n* **Smart Renaming Engine:** Generates target PDF file names following the strict pattern: `ddmmyyyy-sender-sequence.pdf` (e.g., `22082026-AcmeCorp-001.pdf`), extracting the sender and date via the AI consensus or falling back to user input.\r\n### Multi-LLM Consensus Engine (Extensible)\r\n* **Provider Abstraction Interface:** Standardized `BaseLLMProvider` contract (`generateResponse`, `streamResponse`, `modelName`) allowing zero-friction addition of new models (OpenAI, Gemini, Grok, Claude).\r\n* **Sequential Peer Review Loop (Option A):**\r\n* **Round 1:** Model A (e.g., Gemini 1.5 Pro) reads the raw document and produces an initial structured assessment and tag recommendations.\r\n* **Round 2:** Model B (e.g., OpenAI GPT-4o) critiques Model A's extraction, flags discrepancies, and refines key data points.\r\n* **Rounds 3\u201310 (Configurable):** Iterative refinement between models until both models signal consensus or the 10-round cap is reached.\r\n* **Synthesis Step:** A unified assessment report (Markdown format) is generated and delivered to the chat window.\r\n* **Tag Suggestion Mechanism:** Models return candidate tags based on document analysis; suggestions are displayed as clickable chips in the UI without modifying the database.\r\n### Tag & Metadata Management\r\n* **Dynamic User-Driven Tags:** Clean-slate tag system with zero hardcoded tags.\r\n* **Manual Tag Creation:** Dedicated \"Create Tag\" modal/button in the chat interface allowing custom tag creation on the fly.\r\n* **Tag Assignment:** Documents can hold multiple user-confirmed tags, stored relationally in SQLite.\r\n\r\n### Chat & Interactive Workspace\r\n\r\n* **ChatGPT/Gemini-Style UI:** Responsive interface featuring a collapsible left sidebar (recent uploads and conversations) and a central chat stream.\r\n* **Post-Assessment Interactivity:** User can ask follow-up questions, request specific recalculations, or instruct the models to re-evaluate sections.\r\n* **Assessment Preview:** Split-screen or toggle view to see the source document alongside the generated Markdown assessment.\r\n* **Session Reset / Logout:** Clears current active session state and resets the workspace to the landing state.\r\n### Google Drive & Database Persistence\r\n* **Headless Service Account Integration:** Authenticates automatically using a root-level `service_account.json` credential file to access a designated Drive folder.\r\n* **Database Archival:** Persists document metadata, UUIDs, full chat transcripts, tag relationships, and Markdown/PDF assessment reports in a local SQLite database.\r\n---\r\n## 2. Dependency & Stack Assessment\r\nThis stack is selected for optimal compatibility with **Cursor** (TypeScript end-to-end type safety, unified Next.js App Router, zero-boilerplate ORM).\r\n\r\n### Recommended Tech Stack\r\n\r\n* **Framework:** Next.js 14/15 (App Router, Server Actions, Route Handlers)\r\n* **Styling & Components:** Tailwind CSS + `shadcn/ui` + `lucide-react`\r\n* **Database & ORM:** SQLite via `@libsql/client` or `better-sqlite3` + `drizzle-orm` (lightweight, zero external server requirement)\r\n* **File & PDF Processing:** `pdf-parse`, `pdf-lib`, `papaparse`, `tesseract.js` (or LLM Vision API for OCR)\r\n\r\n### Core Dependencies & Environment Configuration\r\n\r\n| Package | Purpose | Version Spec |\r\n| --- | --- | --- |\r\n| `googleapis` | Google Drive API v3 Service Account Client | `^140.0.0` |\r\n| `@google/genai` | Google Gemini SDK | Latest |\r\n| `openai` | OpenAI & Grok (xAI API is OpenAI-compatible) | `^4.50.0` |\r\n| `drizzle-orm` / `drizzle-kit` | SQLite Database Schema & Query Builder | Latest |\r\n| `better-sqlite3` | Local database engine | `^9.0.0` |\r\n| `pdf-lib` | Client/Server PDF creation & metadata manipulation | `^1.17.1` |\r\n| `papaparse` | CSV data parsing | `^5.4.1` |\r\n| `zod` | Runtime validation for LLM structured outputs | `^3.23.0` |\r\n\r\n#### Environment Variables (`.env.local`)\r\n\r\n```env\r\n# AI Providers\r\nGEMINI_API_KEY=\"AIzaSy...\"\r\nOPENAI_API_KEY=\"sk-proj-...\"\r\nGROK_API_KEY=\"xai-...\"\r\nDEFAULT_MAX_DEBATE_ROUNDS=10\r\n\r\n# Google Drive Configuration\r\nGOOGLE_APPLICATION_CREDENTIALS=\"./service_account.json\"\r\nGOOGLE_DRIVE_FOLDER_ID=\"1A2B3C4D5E6F7G8H9I0J\"\r\n\r\n# Database\r\nDATABASE_URL=\"file:./data/app.db\"\r\n```\r\n---\r\n## 3. Database Schema Design (SQLite / Drizzle)\r\n\r\n```sql\r\n-- Documents Table\r\nCREATE TABLE documents (\r\n id TEXT PRIMARY KEY, -- UUIDv4\r\n original_filename TEXT NOT NULL,\r\n gdrive_filename TEXT,\r\n gdrive_file_id TEXT,\r\n mime_type TEXT NOT NULL,\r\n local_file_path TEXT NOT NULL,\r\n sender TEXT,\r\n sequence_number INTEGER,\r\n status TEXT CHECK(status IN ('uploaded', 'analyzing', 'ready', 'exported', 'failed')) DEFAULT 'uploaded',\r\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP,\r\n updated_at DATETIME DEFAULT CURRENT_TIMESTAMP\r\n);\r\n\r\n-- Tags Table (User-created only)\r\nCREATE TABLE tags (\r\n id TEXT PRIMARY KEY, -- UUIDv4\r\n name TEXT UNIQUE NOT NULL,\r\n color TEXT DEFAULT '#3B82F6',\r\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP\r\n);\r\n\r\n-- Document <-> Tags Junction Table\r\nCREATE TABLE document_tags (\r\n document_id TEXT NOT NULL REFERENCES documents(id) ON DELETE CASCADE,\r\n tag_id TEXT NOT NULL REFERENCES tags(id) ON DELETE CASCADE,\r\n PRIMARY KEY (document_id, tag_id)\r\n);\r\n\r\n-- Assessments Table\r\nCREATE TABLE assessments (\r\n id TEXT PRIMARY KEY, -- UUIDv4\r\n document_id TEXT NOT NULL REFERENCES documents(id) ON DELETE CASCADE,\r\n final_markdown TEXT NOT NULL,\r\n debate_rounds_count INTEGER NOT NULL,\r\n raw_debate_transcript TEXT, -- JSON Array of internal model exchanges\r\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP\r\n);\r\n\r\n-- Chat Transcript Messages\r\nCREATE TABLE chat_messages (\r\n id TEXT PRIMARY KEY, -- UUIDv4\r\n document_id TEXT NOT NULL REFERENCES documents(id) ON DELETE CASCADE,\r\n sender_role TEXT CHECK(sender_role IN ('user', 'assistant', 'system', 'gemini', 'openai', 'grok')) NOT NULL,\r\n content TEXT NOT NULL,\r\n created_at DATETIME DEFAULT CURRENT_TIMESTAMP\r\n);\r\n```\r\n---\r\n## 4. Extensible LLM Provider Interface\r\n\r\n```typescript\r\n// lib/llm/types.ts\r\nexport interface LLMMessage {\r\n role: 'system' | 'user' | 'assistant';\r\n content: string;\r\n}\r\n\r\nexport interface LLMResponse {\r\n content: string;\r\n suggestedTags?: string[];\r\n metadata?: {\r\n sender?: string;\r\n date?: string;\r\n };\r\n}\r\n\r\nexport interface BaseLLMProvider {\r\n name: string;\r\n analyzeDocument(content: string | Buffer, mimeType: string, prompt: string): Promise<LLMResponse>;\r\n critiqueAssessment(documentContent: string, previousAssessment: string, roundNumber: number): Promise<LLMResponse>;\r\n chat(messages: LLMMessage[]): Promise<string>;\r\n}\r\n\r\n```\r\n---\r\n## 5. Comprehensive User Stories Catalog\r\n### Epic 1: Document Upload & Ingestion\r\n* **US-1.1: Multi-Format Ingestion**\r\n* **As a** user,\r\n* **I want to** drag and drop or upload PDF, Image, CSV, TXT, or Markdown files on the landing page,\r\n* **So that** I can process any document regardless of its source format.\r\n* **Acceptance Criteria:**\r\n* Landing page shows a clean upload dropzone.\r\n* Supported file formats (`.pdf`, `.png`, `.jpg`, `.jpeg`, `.csv`, `.txt`, `.md`) are accepted; all others show an error toast.\r\n* File is assigned a unique UUID and stored in local temporary storage.\r\n* **US-1.2: Transition to Active Workspace**\r\n* **As a** user,\r\n* **I want to** be automatically transitioned to the chat workspace once a file is uploaded,\r\n* **So that** I can monitor the analysis and begin interacting immediately.\r\n* **Acceptance Criteria:**\r\n* Landing page smoothly transitions to the ChatGPT/Gemini-style dual-panel workspace upon upload completion.\r\n* Document status indicators update from \"Processing\" to \"Analyzing\" to \"Ready\".\r\n---\r\n### Epic 2: Multi-LLM Collaborative Review Engine\r\n* **US-2.1: Sequential Peer Review (Gemini & OpenAI)**\r\n* **As a** user,\r\n* **I want** Gemini and OpenAI to collaboratively review the document up to a maximum of 10 rounds,\r\n* **So that** I receive a highly accurate, audited assessment report.\r\n* **Acceptance Criteria:**\r\n* Model A generates initial extraction and summary.\r\n* Model B reviews Model A's output against the raw file content, pointing out corrections or omissions.\r\n* The process repeats sequentially until models reach agreement or hit 10 rounds maximum.\r\n* Final consolidated Markdown report is rendered in the main chat viewport.\r\n* **US-2.2: Third-Party Model Extensibility (Grok / Claude)**\r\n* **As a** developer/user,\r\n* **I want** the LLM engine to follow an abstracted interface,\r\n* **So that** I can plug in Grok (xAI) or other providers without rewriting the core workflow.\r\n* **Acceptance Criteria:**\r\n* Adding a new provider requires only implementing the `BaseLLMProvider` interface and registering it in a factory map.\r\n---\r\n### Epic 3: Tagging & Metadata Control\r\n* **US-3.1: Zero-Seed Dynamic Tag Creation**\r\n* **As a** user,\r\n* **I want to** create custom tags manually whenever needed with no predefined seed tags,\r\n* **So that** my taxonomy matches my personal organization requirements.\r\n* **Acceptance Criteria:**\r\n* Initial database contains 0 tags.\r\n* \"Create Tag\" button opens a quick modal with tag name and color selection.\r\n* Newly created tag is immediately available for document association.\r\n* **US-3.2: AI Tag Suggestions (Read-Only)**\r\n* **As a** user,\r\n* **I want to** see tag recommendations from the AI without them being auto-created,\r\n* **So that** I maintain complete control over my tag taxonomy.\r\n* **Acceptance Criteria:**\r\n* LLM consensus response includes suggested tags rendered as clickable chips.\r\n* Clicking a suggestion checks if the tag exists; if not, it prompts the user to confirm creation before applying.\r\n---\r\n### Epic 4: Interactive Chat & Post-Assessment\r\n* **US-4.1: Assessment Discussion**\r\n* **As a** user,\r\n* **I want to** ask follow-up questions about the assessment in the chat interface,\r\n* **So that** I can clarify specific clauses, values, or calculations.\r\n* **Acceptance Criteria:**\r\n* Chat input accepts questions and responds with context from both the document and consensus report.\r\n* Full message history is appended to `chat_messages` in the database.\r\n\r\n* **US-4.2: Recent Conversations & File Sidebar**\r\n* **As a** user,\r\n* **I want** a sidebar listing recent uploads and past conversations,\r\n* **So that** I can switch back to previous documents and review their state.\r\n* **Acceptance Criteria:**\r\n* Left sidebar displays chronological list of uploaded documents with assigned tags.\r\n* Clicking a historical item loads its chat transcript, assessment, and metadata.\r\n---\r\n### Epic 5: Google Drive Archival & Database Storage\r\n* **US-5.1: File Renaming & Standardized PDF Export**\r\n* **As a** user,\r\n* **I want** the uploaded file converted to PDF and renamed as `ddmmyyyy-sender-sequence.pdf`,\r\n* **So that** all stored documents have consistent, predictable file names.\r\n* **Acceptance Criteria:**\r\n* Non-PDF documents are converted to PDF format.\r\n* Sender name is extracted from AI metadata (or requested from user if missing).\r\n* Date format is strictly `ddmmyyyy`. Sequence number increments based on existing records in the database.\r\n\r\n* **US-5.2: Service Account Google Drive Upload**\r\n* **As a** system/user,\r\n* **I want** the renamed PDF uploaded to Google Drive via a local `service_account.json` file,\r\n* **So that** I do not have to perform interactive OAuth logins.\r\n* **Acceptance Criteria:**\r\n* Server loads `service_account.json` from the root directory.\r\n* File uploads to the specified Google Drive target folder.\r\n* Returned Google Drive File ID and web view link are recorded in the database.\r\n\r\n* **US-5.3: Database Transcript & Assessment Persistence**\r\n* **As a** user,\r\n* **I want** the original filename, generated report, and full chat transcript persisted in the database,\r\n* **So that** I have a permanent local audit trail.\r\n* **Acceptance Criteria:**\r\n* `assessments` and `chat_messages` tables are updated at the end of each session.\r\n* Database stores the original file name alongside the renamed Drive file name.",
"seq": 1,
"created_at": "2026-08-25T16:32:43.593951"
},
{
"id": "de998a6e-fd4c-4709-baa1-bb059e951911",
"role": "po",
"body": "Thanks for the comprehensive overview, PM! This gives us a great foundation for Doc Flow AI.\n\nTo effectively define our MVP scope, especially considering our fixed **React frontend** and **Python Flask backend**, I need a bit more clarity on the initial product focus.\n\nCould you please help me with the following:\n\n1. **Who is the primary user** for this MVP?\n2. **What is the single most critical problem** this MVP aims to solve for them?\n3. Based on that problem, which of the proposed Epics (Document Upload & Ingestion, Multi-LLM Collaborative Review Engine, Tagging & Metadata Control, Interactive Chat & Post-Assessment, Google Drive Archival & Database Storage) are **absolutely essential for the MVP**? Please indicate their priority.\n4. What would be the **key acceptance criteria** for the MVP to be considered successful from this primary user's perspective?",
"seq": 2,
"created_at": "2026-08-25T16:33:07.743201"
}
],
"status": "open",
"message": {
"id": "de998a6e-fd4c-4709-baa1-bb059e951911",
"role": "po",
"body": "Thanks for the comprehensive overview, PM! This gives us a great foundation for Doc Flow AI.\n\nTo effectively define our MVP scope, especially considering our fixed **React frontend** and **Python Flask backend**, I need a bit more clarity on the initial product focus.\n\nCould you please help me with the following:\n\n1. **Who is the primary user** for this MVP?\n2. **What is the single most critical problem** this MVP aims to solve for them?\n3. Based on that problem, which of the proposed Epics (Document Upload & Ingestion, Multi-LLM Collaborative Review Engine, Tagging & Metadata Control, Interactive Chat & Post-Assessment, Google Drive Archival & Database Storage) are **absolutely essential for the MVP**? Please indicate their priority.\n4. What would be the **key acceptance criteria** for the MVP to be considered successful from this primary user's perspective?",
"seq": 2
},
"providers": {
"gemini": "ok",
"openai": "ok",
"mode": "merged_via_gemini"
}
}
Terminal