Download Agent.md from Leon4gr45/agent-0: direct link, hf CLI and curl.
- Browser
- Download file 4.25 kB
-
https://huggingface.co/spaces/Leon4gr45/agent-0/resolve/main/Agent.md
- Command line
-
hf download hf://spaces/Leon4gr45/agent-0/Agent.md
-
curl -L -o Agent.md https://huggingface.co/spaces/Leon4gr45/agent-0/resolve/main/Agent.md
1. Deployment Configuration
Target Space
- Profile:
Leon4gr45 - Space:
agent-0 - Full Identifier:
Leon4gr45/agent-0 - Frontend Port:
7860(mandatory for all Hugging Face Spaces)
Deployment Method
Choose the correct SDK based on the app type based on the codebase language:
- Gradio SDK — for Gradio applications
- Streamlit SDK — for Streamlit applications
- Docker SDK — for all other applications (recommended default for flexibility)
HF Token
- The environment variable
$HF_TOKENwill always be provided at execution time. - Never hardcode the token. Always read it from the environment.
- All monitoring and log‑streaming commands rely on
$HF_TOKEN.
Required Files
Dockerfile(orapp.pyfor Gradio/Streamlit SDKs)README.mdwith Hugging Face YAML frontmatter: ```yamltitle: sdk: docker | gradio | streamlit app_port: 7860
.hfignoreto exclude unnecessary files- This
Agent.mdfile (must be committed before deployment)
2. API Exposure and Documentation
Mandatory Endpoints
Every deployment must expose:
/health- Returns HTTP 200 when the app is ready.
- Required for Hugging Face to transition the Space from starting → running.
/api-docs- Documents all available API endpoints.
- Must be reachable at:
https://HF_PROFILE-agent-0.hf.space/api-docs
Functional Endpoints
/health
- Method: GET
- Purpose: Health Check
/readiness
- Method: GET
- Purpose: Readiness Check
/pipelines/run
- Method: POST
- Purpose: Queue a dataset generation pipeline for execution.
/jobs
- Method: GET
- Purpose: List jobs from HF_WORK_REPO
/jobs/{job_id}/manifest
- Method: GET
- Purpose: Inspect job manifest
/jobs/{job_id}/checkpoints
- Method: GET
- Purpose: Inspect job checkpoints
/jobs/{job_id}/outputs
- Method: GET
- Purpose: Inspect job output references
/jobs/{job_id}/resume
- Method: POST
- Purpose: Explicitly resume a job from remote state
/jobs/{job_id}/fork
- Method: POST
- Purpose: Fork an existing job run into a new durable job
/pipelines/available
- Method: GET
- Purpose: Get available pipeline aliases from super_config.yaml.
/configs/aliases
- Method: GET
- Purpose: Get available config file aliases from super_config.yaml.
/tasks/queue
- Method: GET
- Purpose: Get lists of pending and scheduled tasks.
/tasks/{task_id}/status
- Method: GET
- Purpose: Get the status of a pipeline run.
/tasks/{task_id}/parameters
- Method: GET
- Purpose: Get the parameters a task was executed with.
/tasks/{task_id}/interrupt
- Method: POST
- Purpose: Interrupt a running pipeline task subprocess or revoke a pending task.
/tasks/{task_id}/logs
- Method: GET
- Purpose: Get logs for a specific task.
/logs
- Method: DELETE
- Purpose: Clear all task log files.
/tasks/{task_id}/outputs/download
- Method: GET
- Purpose: Download output directory for a task.
/outputs/structure/{relative_path}
- Method: GET
- Purpose: Get structure of a path within the outputs directory.
/inputs/structure/{relative_path}
- Method: GET
- Purpose: Get structure of a path within the inputs directory.
/configs/structure/{relative_path}
- Method: GET
- Purpose: Get structure of a path within the configs directory.
3. Deployment Workflow
Precondition: Use the huggingface hub cli hf to check that the space is empty of files nd delete any which are still in there and not belonging to the project to be uploaded
Standard Deployment Command
After any code change, run:
hf upload Leon4gr45/agent-0 --repo-type=space
Scan build and run logs # Get build logs (SSE) curl -N -H "Authorization: Bearer $HF_TOKEN" "https://huggingface.co/api/spaces/Leon4gr45/agent-0/logs/build"
Get run logs (SSE) once the build logs succeed curl -N -H "Authorization: Bearer $HF_TOKEN" "https://huggingface.co/api/spaces/Leon4gr45/agent-0/logs/run"
after 300 seconds to see if the deployment has been successful, and if not, fix the errors of deployment, and redeploy and monitor in a cycle until the space is running and reacts to the api endpoints you created.