| --- |
| title: Agentic Space Factory |
| sdk: gradio |
| app_file: app.py |
| hf_oauth: true |
| hf_oauth_expiration_minutes: 480 |
| hf_oauth_scopes: |
| - read-repos |
| - write-repos |
| - manage-repos |
| - gated-repos |
| - inference-api |
| - jobs |
| - read-billing |
| --- |
| |
| # Agentic Space Factory |
|
|
| Agentic Space Factory turns a Hugging Face model card into a **private, testable Gradio Space** using a Hugging Face Job, Pi, a coding model through Hugging Face Inference Providers, and a private Storage Bucket for run state, traces, reports, generated files, and validation artifacts. |
|
|
| It is designed as a Hugging Face-native version of the local agent workflow described in the ZeroGPU Spaces article: |
|
|
| ```text |
| model card → agentic job → generated private Space → hardware if available → live validation → report |
| ``` |
|
|
| ## Main workflow |
|
|
| ### 1. Build from model card |
|
|
| Paste a Hugging Face model ID or model-card URL. The app launches an HF Job that: |
|
|
| - fetches model metadata and repo information; |
| - asks Pi + Qwen Coder to build a Gradio app; |
| - creates a private Space under your namespace; |
| - uploads the generated workspace; |
| - attempts ZeroGPU first, then fixed-GPU fallback if enabled; |
| - validates `/health` or Gradio API availability; |
| - classifies the result honestly; |
| - returns quick links to the Job page, generated Space, Space settings, and run artifacts. |
|
|
| ### 2. Validate existing Space |
|
|
| If automatic hardware assignment fails, set the hardware manually in the generated Space settings, then run validation. The validation job: |
|
|
| - waits for the existing Space; |
| - calls the configured generation endpoint; |
| - checks the returned output type; |
| - stores returned artifacts in the Bucket; |
| - measures latency; |
| - recommends a conservative ZeroGPU duration; |
| - returns quick links to the validation Job, target Space, Space settings, and run artifacts. |
|
|
| ## Result statuses |
|
|
| - `full_inference_success`: a live generation smoke test returned the expected output type. |
| - `manual_hardware_required`: the Space was generated but automatic ZeroGPU/fixed-GPU assignment failed; set hardware manually, then validate. |
| - `full_inference_candidate_health_passed`: the Space boots and contains inference signals, but generation was not smoke-tested yet. |
| - `health_only`: the Space boots, but no real inference path was validated. |
| - `technical_blocker`: the agent found concrete blockers such as multi-GPU requirements, missing licenses, custom CUDA, or unclear usage. |
| - `failed`: the build, runtime, or validation job failed. |
|
|
| ## What this app guarantees |
|
|
| - Generated Spaces are private by default. |
| - Nothing is published automatically. |
| - Runs are persisted in the configured Storage Bucket. |
| - The app distinguishes bootability from real inference. |
| - Hardware assignment is treated as best effort, not as an assumed capability. |
|
|
| ## What this app does not guarantee |
|
|
| It does not guarantee that every model card becomes a working Space. Some models require multi-GPU execution, Docker, unavailable CUDA extensions, external services, accepted licenses, very large hardware, or manual fixes. |
|
|
| ## Required environment |
|
|
| Each signed-in user writes to their own private Storage Bucket by default. The app can now check and create this private bucket for the user from the **Run storage** section before launching Jobs. The default bucket is: |
|
|
| ```text |
| https://huggingface.co/buckets/<your-username>/space-factory-runs |
| ``` |
|
|
| For local dev or deployment, configure only the bucket **name**; the namespace is derived from the signed-in OAuth user: |
|
|
| ```bash |
| SPACE_FACTORY_BUCKET_NAME=space-factory-runs |
| SPACE_FACTORY_BUCKET_MOUNT=/output |
| ``` |
|
|
| Do not configure a shared owner/name bucket for a public Space. The app uses HF OAuth; no global admin token should be stored in the Space. |
|
|
