PlanOpticon

AI-powered video analysis, knowledge extraction, and planning.

PlanOpticon processes video recordings, documents, and 20+ online sources into structured knowledge graphs, then helps you plan with an AI agent and interactive companion. It auto-discovers models across 15+ AI providers, runs fully offline with Ollama, and produces rich multi-format output.

Features

• 15+ AI providers -- OpenAI, Anthropic, Gemini, Ollama, Azure, Together, Fireworks, Cerebras, xAI, Bedrock, Vertex, Mistral, Cohere, AI21, HuggingFace, Qianfan, and LiteLLM. Defaults to cheap models (Haiku, GPT-4o-mini, Gemini Flash).
• 20+ source connectors -- YouTube, web pages, GitHub, Reddit, HackerNews, RSS, podcasts, arXiv, S3, Google Workspace, Microsoft 365, Obsidian, Notion, Apple Notes, Zoom, Teams, Google Meet, and more.
• Planning agent -- 11 skills including project plans, PRDs, roadmaps, task breakdowns, and GitHub integration.
• Interactive companion -- Chat REPL with 15 slash commands, auto-discovery of workspace knowledge, and runtime provider/model switching.
• Knowledge graphs -- SQLite-backed (zero external deps), entity extraction with planning taxonomy (goals, requirements, risks, tasks, milestones), merge and dedup across sources.
• Smart video analysis -- Change-detection frame extraction, face filtering, diagram classification, action item detection, checkpoint/resume.
• Document ingestion -- PDF, Markdown, and plaintext pipelines feed the same knowledge graph.
• Export everywhere -- Markdown docs (7 types, no LLM required), Obsidian vaults, Notion markdown, GitHub wiki with push, PlanOpticonExchange JSON interchange, HTML/PDF reports, Mermaid diagrams.
• OAuth-first auth -- Unified OAuth manager for Google, Dropbox, Zoom, Notion, GitHub, and Microsoft with saved-token / PKCE / API-key fallback chain.
• Batch processing -- Process entire folders with merged knowledge graphs and cross-referencing.

Quick Start

# Install
pip install planopticon

# Analyze a video
planopticon analyze -i meeting.mp4 -o ./output

# Ingest a document
planopticon ingest -i spec.pdf -o ./output

# Fetch from a source
planopticon fetch youtube "https://youtube.com/watch?v=..." -o ./output

# Process a folder of videos
planopticon batch -i ./recordings -o ./output --title "Weekly Meetings"

# Query the knowledge graph
planopticon query
planopticon query "entities --type technology"

# See available AI models
planopticon list-models

Planning Agent

Run AI-powered planning skills against your knowledge base:

# Generate a project plan from extracted knowledge
planopticon agent "Create a project plan" --kb ./results

# Build a PRD
planopticon agent "Write a PRD for the authentication system" --kb ./results

# Break down tasks
planopticon agent "Break this into tasks and estimate effort" --kb ./results

11 skills: project_plan, prd, roadmap, task_breakdown, github_integration, requirements_chat, doc_generator, artifact_export, cli_adapter, notes_export, wiki_generator.

Interactive Companion

A chat REPL that auto-discovers knowledge graphs, videos, and docs in your workspace:

# Launch the companion
planopticon companion
# or
planopticon --chat

15 slash commands: /help, /status, /skills, /entities, /search, /neighbors, /export, /analyze, /ingest, /auth, /provider, /model, /run, /plan, /prd, /tasks.

Switch providers and models at runtime, explore your knowledge graph interactively, or chat with any configured LLM.

Source Connectors

Category	Sources
Media	YouTube, Web, Podcasts, RSS
Code & Community	GitHub, Reddit, HackerNews, arXiv
Cloud Storage	S3, Google Drive, Dropbox
Google Workspace	Docs, Sheets, Slides (via gws CLI)
Microsoft 365	SharePoint, OneDrive (via m365 CLI)
Notes	Obsidian, Notion, Apple Notes, OneNote, Google Keep, Logseq
Meetings	Zoom (OAuth), Teams, Google Meet

Export & Documents

Generate documents from your knowledge graph without an LLM:

planopticon export summary -o ./docs
planopticon export meeting-notes -o ./docs
planopticon export glossary -o ./docs

7 document types: summary, meeting-notes, glossary, relationship-map, status-report, entity-index, csv.

Additional export targets: - Obsidian -- YAML frontmatter + wiki-links vault - Notion -- Compatible markdown - GitHub Wiki -- Generate and push directly - PlanOpticonExchange -- Canonical JSON interchange with merge/dedup

Local Run

PlanOpticon runs entirely offline with Ollama -- no API keys, no cloud, no cost.

13.2 hours of video content analyzed, knowledge-graphed, and summarized in ~25 hours of processing time, entirely on local hardware, for free.

18 meeting recordings processed on a single machine using llava (vision), qwen3:30b (chat), and whisper-large (transcription via Apple Silicon GPU):

Metric	Value
Recordings	18
Video duration	13.2 hours
Processing time	24.9 hours
Frames extracted	1,783
API calls (local)	1,841
Tokens processed	4.87M
Total cost	$0.00

# Fully local analysis -- no API keys needed, just Ollama running
planopticon analyze -i meeting.mp4 -o ./output \
  --provider ollama \
  --vision-model llava:latest \
  --chat-model qwen3:30b

Installation

From PyPI

pip install planopticon

# With all extras (PDF, cloud sources, GPU)
pip install planopticon[all]

From Source

git clone https://github.com/ConflictHQ/PlanOpticon.git
cd PlanOpticon
pip install -e ".[dev]"

Binary Download

Download standalone binaries (no Python required) from GitHub Releases.

Requirements

• Python 3.10+
• FFmpeg (brew install ffmpeg / apt install ffmpeg)
• At least one API key (OPENAI_API_KEY, ANTHROPIC_API_KEY, or GEMINI_API_KEY) or Ollama running locally

Output Structure

output/
├── manifest.json              # Single source of truth
├── transcript/
│   ├── transcript.json        # Full transcript with timestamps
│   ├── transcript.txt         # Plain text
│   └── transcript.srt         # Subtitles
├── frames/                    # Content frames (people filtered out)
├── diagrams/                  # Detected diagrams + mermaid code
├── captures/                  # Screengrab fallbacks
└── results/
    ├── analysis.md            # Markdown report
    ├── analysis.html          # HTML report
    ├── analysis.pdf           # PDF report
    ├── knowledge_graph.db     # SQLite knowledge graph
    ├── knowledge_graph.json   # JSON export
    ├── key_points.json        # Extracted key points
    └── action_items.json      # Tasks and follow-ups

Processing Depth

Depth	What you get
basic	Transcription, key points, action items
standard	+ Diagram extraction (10 frames), knowledge graph, full reports
comprehensive	+ More frames analyzed (20), deeper extraction

Documentation

Full documentation at planopticon.dev

License

MIT License -- Copyright (c) 2026 CONFLICT LLC