Director Video Workflows
Natural-language orchestration for video search, editing, generation, and delivery workflows.
- Source repo
- video-db/Director
- Stars
- ★ 1.6k
- Last updated
- 9mo ago
- License
- MIT
- Primary language
- Python
- FA score
- 30/100 · Major gaps
At a glance
- How it runs
- Works with
- Platform-specific
- Cost
- Free software; you pay for model usage
- Setup effort
- Medium · a few setup steps
- You'll need
- Typical use
- A video-content team needs to find a specific moment in uploaded footage and produce a shareable clip quickly.
- Not a fit if
- Teams that need video infrastructure without VideoDB cloud dependency
- Users unwilling to configure Python, Node.js, and .env API keys
- Developers needing documented HTTP API examples for automation
- Source review
- 30/100 · Major gaps 8 safety controls not found
What does this agent do, and when should you use it?
Director is a framework for building video agents for complex tasks such as search, editing, compilation, and generation. Its backend Reasoning Engine interprets inputs, breaks work into steps, and coordinates agents, while the chat UI and video player are sourced from the related videodb-chat and videodb-player projects. The framework is built on VideoDB's “video-as-data” infrastructure for cloud storage, indexing, and streaming. When run locally, the backend serves at 127.0.0.1:8000 and the frontend at 127.0.0.1:8080, with progress updates and text, video, image, or search-result content. It fits developers and media teams that want a self-hosted interaction layer and are comfortable using VideoDB as the underlying video platform.
A user submits a video task through the chat interface, and the Reasoning Engine maintains context, selects relevant agents, and divides the request into executable steps. Documented operations include video summarization, finding moments in a media library, clipping, generating voiced movies from scripts, dubbing, translating and subtitling video, adding overlays, and extracting frames. Agents can connect LLMs, databases, and other GenAI APIs, while VideoDB handles cloud video storage, indexing, and streaming. Custom agents start by copying backend/director/agents/sample_agent.py; their run() method can use TextContent, VideoContent, ImageContent, or SearchResultContent, emit progress through push_update(), publish final state with self.output_message.publish(), and return an AgentResponse.
- A video-content team needs to find a specific moment in uploaded footage and produce a shareable clip quickly.
- A marketing or creator team needs to turn a script into a complete video with voiceover.
- A media team with a large asset library wants conversational search over indexed video content.
- A localization team needs to translate videos and add subtitles in another language.
- A developer needs to add a custom video agent for a workflow that can reuse shared tools.
How do you install or deploy this agent?
Requirements are Python 3.9 or later, Node.js 22.8.0 or later, and npm. Run:
git clone https://github.com/video-db/Director.git
cd Director
./setup.shThe setup script installs Node.js 22.8.0 through nvm, installs Python and pip, and creates frontend and backend virtual environments. Then edit the .env files with API keys and other configuration. The supplied material does not name the environment variables or provide a complete required-key list.
How do you use this agent?
After configuring .env, run make run to start both services. Use the frontend at http://127.0.0.1:8080 and the backend at http://127.0.0.1:8000, then submit a video task through the chat interface. Run make run-be for only the backend or make run-fe for only the frontend. No copyable HTTP API request is documented, so the local frontend is the first documented working interaction path.
What are this agent's strengths and limitations?
- Brings video search, clipping, summarization, generation, dubbing, and subtitling into one multi-agent orchestration framework.
- Provides a concrete extension model based on sample_agent.py, AgentResponse, content types, and push_update() progress events.
- Frontend and backend can run separately, and the README includes deployment entry points for Render and Railway.
- Uses VideoDB for cloud video storage, indexing, and streaming instead of requiring the application to build that video infrastructure.
- Its core architecture depends on VideoDB infrastructure, creating a clear platform dependency.
- Adoption requires Python, a specified Node.js version, npm, and .env API-key configuration.
- The supplied documentation does not identify exact environment-variable names, service-account permissions, or the complete API-key set.
- There is no documented HTTP API request example, so automated integrations require further code or hosted-documentation investigation.
How does this agent compare with similar options?
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| Director Video Workflows This agent | 30 · Major gaps | Self-hosted serviceFree + model costs | ★ 1.6k | 9mo ago | Python | — |
| Hypit Video Workflows | 71 · Some gaps | Agent plugin / skillFree + model costs | ★ 28k | 1d ago | TypeScript | Codex · Claude Code |
| Wonda CLI | 56 · Major gaps | CLIPaid | ★ 159 | 6d ago | TypeScript | Codex · Claude Code |
| Video Use | 54 · Major gaps | Agent plugin / skillFree + model costs | ★ 31k | 28d ago | Python | Codex · Claude Code |
How does FollowAgents rate this agent?
Why each dimension lost points
Evidence shows: The repository provides no permission model, user confirmation mechanism, data flow transparency, sensitive data handling, dependency security, external effects, rollback, or source attribution. All trust criteria are unsupported, hence score 0.
Evidence shows: README and docs provide architecture and feature descriptions, but no tests or verification evidence; self-consistency is only partially supported. Dependency availability: Python and Node.js requirements are listed, but no dependency locking or integrity checks. Failure messages: No error handling or user feedback mechanisms are provided.
Evidence shows: README identifies target audience (developers, creators, teams) and multiple scenarios (search, editing, generation, etc.), but lacks detailed boundary descriptions. Capability boundaries: Unclear which tasks are not supported. Trigger precision: Natural language command examples, but no precise trigger conditions defined. Environment fit: Supports Mac, Linux, Windows (WSL), but no detailed deployment configuration.
Evidence shows: README provides architecture overview, installation steps, guide for creating new agents, but lacks known limitations, version changelog, and clear maintenance responsibility. License is MIT, but copyright is attributed to an individual (Ashutosh Trivedi), unverified.
Evidence shows: README describes output types (TextContent, VideoContent, etc.) and progress update mechanisms, but no actual output examples. Marginal value: Provides 20+ pre-built agents and customization, but no comparison with alternatives. Cost-benefit: No performance or cost data.
Evidence shows: Claims in README (e.g., '20+ pre-built agents') lack specific lists or verification. Cross-source corroboration: YouTube demos and documentation links provided, but no independent verification. Fact-inference separation: README mixes facts and marketing language without clear distinction.
- Not found in source: least-privilege scopingGrant only what the task needs: a dedicated account or read-only token, scoped to specific directories and repos.
- Not found in source: confirmation before actingTurn on (or add) a confirmation step before it acts, and try it in a sandbox or test environment before real data.
- Not found in source: data-flow disclosureWatch which external services it contacts (proxy or firewall logs) and keep sensitive data out until you know where it goes.
- Not found in source: sensitive-data handlingUse dedicated, low-privilege, revocable API keys — never production credentials — and keep secrets out of logs.
- Not found in source: dependency securityPin versions and run a dependency audit (npm audit, pip-audit) before installing; prefer running it in a container.
- Not found in source: disclosed external effectsEstablish which external systems it writes to, sends to or changes, and verify with test accounts or repos before production.
- Not found in source: rollback or recovery pathBack up first, or work on a git branch or snapshot, so its changes can be undone.
- Not found in source: verifiable attributionInstall from the official repo or registry and check the publisher and URL to avoid look-alike packages.
- The repository provides no security or permission documentation; assess risks before deployment.
- Dependencies are not version-locked, posing supply chain security risks.
- Feature claims in README lack verification; test before use.
Recent releases
Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.
-
First v0.1.1
Release notes excerpt
What's Changed * Add agents and config endpoint by @ashish-spext in https://github.com/video-db/Director/pull/1 * Ankit/add agents by @ankit-v2-3 in https://github.com/video-db/Director/pull/2 * fix: prompt clip by @ankit-v2-3 in https://github.com/video-db/Director/pull/3 * cleanup fe by @0xrohitgarg in https://github.com/video-db/Director/pull/4 * bump videodb-chat by @0xrohitgarg in https://github.com/video-db/Director/pull/5 * Agents: Add stream video agent, minor update in sample agent. by @ashish-spext in https://github.com/video-db/Director/pull/6 …View on GitHub ↗