بنقرة واحدة
sparkgen-generate
Generate a new SparkGen-AWS project from the cookiecutter template
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Generate a new SparkGen-AWS project from the cookiecutter template
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
Develop and modify the SparkGen-AWS cookiecutter template — variables, hooks, files
Run cookiecutter matrix tests to verify template generates correctly across all variable combinations
Add, modify, remove, list, or show agents in the workflow
Send a chat message to the running agent server and display the response
Switch LLM providers, deployment modes, and manage environment configuration
Diagnose issues with Ollama, Docker, AWS, endpoints, guardrails, RAG, or general health
استنادا إلى تصنيف SOC المهني
| name | sparkgen-generate |
| description | Generate a new SparkGen-AWS project from the cookiecutter template |
| user_invokable | true |
| auto_invokable | false |
| arguments | [project_name] [--mode local|docker|aws] [--agents 1-4] [--rag yes|no] [--provider bedrock|ollama|openai] |
Generate a new project from the SparkGen-AWS cookiecutter template.
Before generating:
cookiecutter.json to understand all available template variablescookiecutter --versionMap the user's arguments to cookiecutter variables:
| Argument | cookiecutter Variable | Default |
|---|---|---|
| project_name | project_name | "My SparkGen AWS Agent" |
| --mode | deployment_mode | "all" |
| --agents | num_agents | "4" |
| --rag | enable_rag | "yes" |
| --provider | llm_provider | "bedrock" |
Build the cookiecutter command with --no-input and variable overrides:
cookiecutter . --no-input \
project_name="<name>" \
deployment_mode="<mode>" \
num_agents="<N>" \
enable_rag="<yes|no>" \
llm_provider="<provider>"
After generating:
ls <output_slug>/python -m compileall <output_slug>/app -q<output_slug>/config/ai_workflow.yaml<output_slug>/Makefile<output_slug>/app/api.py<output_slug>/.claude/skills/ (skills directory)<output_slug>/CLAUDE.mdgrep "^ - name:" <output_slug>/config/ai_workflow.yaml=== Project Generated ===
Name: <project_name>
Location: ./<output_slug>/
Mode: <deployment_mode>
Provider: <llm_provider>
Agents: <num_agents>
RAG: <enable_rag>
Guardrails: <enable_guardrails>
Next steps:
cd <output_slug>
make setup # Install dependencies
make local # Start local dev server
Available skills (in generated project):
/sparkgen-deploy Deploy to local/docker/aws
/sparkgen-test Run tests
/sparkgen-chat Test chat
/sparkgen-debug Diagnose issues
pip install cookiecutter