mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-07-27 01:35:12 +00:00
Fix JSON crew template rendering (#6359)
JSON crews were not using existing CLI templates.
This commit is contained in:
Vinicius Brasil
@@ -18,6 +18,7 @@ from crewai_cli.utils import (
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enable_prompt_line_editing,
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is_dmn_mode_enabled,
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load_env_vars,
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render_template,
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write_env_file,
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)
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from crewai_cli.version import get_crewai_tools_dependency
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@@ -79,61 +80,7 @@ _PROVIDER_MODELS: dict[str, list[tuple[str, str]]] = {
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],
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}
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# ── Static project files ───────────────────────────────────────
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_PYPROJECT_TOML = """\
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[project]
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name = "{folder_name}"
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version = "0.1.0"
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description = "{name} using crewAI"
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authors = [{{ name = "Your Name", email = "you@example.com" }}]
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requires-python = ">=3.10,<3.14"
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dependencies = [
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"{crewai_tools_dependency}"
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]
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.hatch.build.targets.wheel]
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only-include = ["agents", "crew.jsonc", "tools", "knowledge", "skills"]
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[tool.crewai]
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type = "crew"
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definition = "crew.jsonc"
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"""
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_GITIGNORE = """\
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.env
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__pycache__/
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.DS_Store
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report.md
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"""
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_README = """\
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# {name}
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A crewAI project using JSON-first configuration.
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## Running
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```bash
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crewai run
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```
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## Project Structure
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- `agents/` - Agent definitions (JSONC)
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- `crew.jsonc` - Crew definition with tasks and configuration
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- `tools/` - Custom tools (Python)
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- `knowledge/` - Knowledge files for agents
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> **Note:** `custom:<name>` tool references execute `tools/<name>.py` as local
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> Python code when the crew loads. Only run crew projects from sources you
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> trust.
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"""
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_TEMPLATES_DIR = Path(__file__).parent / "templates" / "json_crew"
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# ── Common tools for picker ────────────────────────────────────
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@@ -694,187 +641,64 @@ def _default_agents_and_tasks(
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def _agent_to_jsonc(agent: dict[str, Any]) -> str:
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"""Convert agent wizard data to JSONC string with comments."""
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has_planning = agent["planning"]
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delegation_val = "true" if agent["allow_delegation"] else "false"
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delegation_comma = "," if has_planning else ""
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settings_lines = []
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settings_lines.append(" // Show detailed execution logs")
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settings_lines.append(' "verbose": false,')
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settings_lines.append("")
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settings_lines.append(
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" // Allow this agent to delegate tasks to other agents in the crew"
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settings_block = _render_json_crew_template(
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"agent_settings.jsonc",
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{
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"allow_delegation": "true" if agent["allow_delegation"] else "false",
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"delegation_comma": "," if has_planning else "",
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"planning_line": '"planning": true'
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if has_planning
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else '// "planning": false',
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},
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)
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settings_lines.append(f' "allow_delegation": {delegation_val}{delegation_comma}')
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settings_lines.append("")
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settings_lines.append(
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" // Maximum reasoning iterations per task (prevents infinite loops)"
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return _render_json_crew_template(
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"agent.jsonc",
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{
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"role_json": json.dumps(agent["role"]),
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"goal_json": json.dumps(agent["goal"]),
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"backstory_json": json.dumps(agent["backstory"]),
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"llm_json": json.dumps(agent["llm"]),
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"tools_json": json.dumps(agent["tools"]),
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"settings_block": settings_block,
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},
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)
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settings_lines.append(' // "max_iter": 25,')
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settings_lines.append("")
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settings_lines.append(" // Maximum tokens for agent's response generation")
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settings_lines.append(' // "max_tokens": null,')
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settings_lines.append("")
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settings_lines.append(" // Maximum execution time in seconds")
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settings_lines.append(' // "max_execution_time": null,')
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settings_lines.append("")
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settings_lines.append(" // Maximum LLM requests per minute (rate limiting)")
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settings_lines.append(' // "max_rpm": null,')
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settings_lines.append("")
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settings_lines.append(" // Enable agent-level memory (persists across tasks)")
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settings_lines.append(' // "memory": false,')
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settings_lines.append("")
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settings_lines.append(" // Cache tool results to avoid duplicate calls")
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settings_lines.append(' // "cache": true,')
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settings_lines.append("")
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settings_lines.append(
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" // Auto-summarize context when it exceeds the LLM's context window"
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)
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settings_lines.append(' // "respect_context_window": true,')
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settings_lines.append("")
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settings_lines.append(" // Maximum retries on execution errors")
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settings_lines.append(' // "max_retry_limit": 2,')
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settings_lines.append("")
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settings_lines.append(" // Enable step-by-step planning before task execution")
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if has_planning:
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settings_lines.append(' "planning": true')
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else:
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settings_lines.append(' // "planning": false')
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settings_lines.append("")
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settings_lines.append(" // Include system prompt in LLM calls")
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settings_lines.append(' // "use_system_prompt": true')
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settings_block = "\n".join(settings_lines)
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return f"""\
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{{
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// Agent's role title — appears in prompts and logs.
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// You can use {{placeholder}} inputs in role, goal, or backstory.
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// Example: "role": "Senior {{industry}} Researcher"
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"role": {json.dumps(agent["role"])},
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// Optional custom Agent subclass
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// "type": {{"python": "my_project.agents.CustomAgent"}},
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// The agent's primary objective
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"goal": {json.dumps(agent["goal"])},
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// Background story that shapes the agent's personality and approach
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"backstory": {json.dumps(agent["backstory"])},
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// LLM model in provider/model format
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// Examples: "openai/gpt-4o", "anthropic/claude-sonnet-4-6", "ollama/llama3.3"
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// For custom endpoints or deployment-based providers, replace with:
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// "llm": {{"model": "llama3", "provider": "ollama", "base_url": "http://localhost:11434"}},
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// "llm": {{"deployment_name": "my-deployment", "provider": "azure", "api_version": "2024-10-21"}},
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"llm": {json.dumps(agent["llm"])},
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// Override LLM used specifically for tool/function calling
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// "function_calling_llm": "openai/gpt-5.4-mini",
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// Tools available to this agent
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// Built-in: "SerperDevTool", "ScrapeWebsiteTool", "FileReadTool", etc.
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// Custom: "custom:my_tool" loads from tools/my_tool.py
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"tools": {json.dumps(agent["tools"])},
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// Optional agent-level guardrail — validates this agent's final output.
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// String guardrails are checked by an LLM and can reject/retry output.
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// Python refs must point to module-level functions/classes in trusted code.
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// "guardrail": "Only answer with information supported by retrieved evidence.",
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// "step_callback": {{"python": "my_project.callbacks.on_agent_step"}},
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// "guardrail_max_retries": 2,
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// Advanced agent options:
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// Docs: https://docs.crewai.com/concepts/agents
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// "reasoning": true,
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// "max_reasoning_attempts": 3,
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// "planning_config": {{
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// "reasoning_effort": "medium",
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// "llm": {{"model": "deepseek-chat", "provider": "deepseek"}}
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// }},
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// "multimodal": false,
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// "allow_code_execution": false,
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// "code_execution_mode": "safe",
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// "knowledge_sources": [],
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// "knowledge_config": {{}},
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// "inject_date": true,
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// "date_format": "%Y-%m-%d",
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// "security_config": {{}},
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// Agent behavior settings
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"settings": {{
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{settings_block}
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}}
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}}
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"""
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def _task_to_json_fragment(task: dict[str, Any]) -> str:
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"""Convert task wizard data to a JSON-like fragment for embedding in crew JSONC."""
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lines = []
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lines.append(" {")
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lines.append(" // Task identifier")
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lines.append(f' "name": {json.dumps(task["name"])},')
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lines.append("")
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lines.append(" // What the task should accomplish")
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lines.append(
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" // Use {placeholder} inputs here; crewai run prompts for missing values"
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)
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lines.append(f' "description": {json.dumps(task["description"])},')
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lines.append("")
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lines.append(" // Clear definition of what the output should look like")
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lines.append(f' "expected_output": {json.dumps(task["expected_output"])},')
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lines.append("")
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lines.append(
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" // Optional task guardrail(s) validate output before completion"
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)
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lines.append(' // Use "guardrail" for one rule or "guardrails" for many')
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lines.append(" // Failed guardrails retry up to guardrail_max_retries times")
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lines.append(' // "guardrail": "Every factual claim needs context support.",')
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lines.append(' // "guardrails": [')
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lines.append(' // "Every factual claim must be supported by context.",')
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lines.append(' // "The answer must match the expected output format."')
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lines.append(" // ],")
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lines.append(' // "guardrail_max_retries": 2,')
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lines.append("")
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lines.append(" // Advanced task options:")
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lines.append(" // Docs: https://docs.crewai.com/concepts/tasks")
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lines.append(' // "type": "ConditionalTask",')
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lines.append(
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' // "condition": { "python": "my_project.conditions.should_run" },'
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)
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lines.append(
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' // "output_json": { "python": "my_project.models.ReportOutput" },'
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)
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lines.append(' // "output_pydantic": null,')
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lines.append(' // "response_model": null,')
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lines.append(
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' // "converter_cls": { "python": "my_project.converters.CustomConverter" },'
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)
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lines.append(' // "markdown": false,')
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lines.append(' // "input_files": { "brief": "data/brief.txt" },')
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lines.append(' // "security_config": {},')
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lines.append("")
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lines.append(" // Which agent handles this task")
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lines.append(f' "agent": {json.dumps(task["agent"])}')
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has_context = bool(task.get("context"))
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has_output_file = bool(task.get("output_file"))
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context_block = ""
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output_file_block = ""
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if task.get("context"):
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lines[-1] += "," # add comma to agent line
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lines.append("")
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lines.append(" // Task outputs used as context")
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lines.append(f' "context": {json.dumps(task["context"])}')
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if has_context:
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context_block = (
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"\n\n"
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" // Task outputs used as context\n"
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f' "context": {json.dumps(task["context"])}'
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f"{',' if has_output_file else ''}"
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)
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if task.get("output_file"):
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lines[-1] += ","
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lines.append("")
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lines.append(" // Save output to a file")
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lines.append(f' "output_file": {json.dumps(task["output_file"])}')
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if has_output_file:
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output_file_block = (
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"\n\n"
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" // Save output to a file\n"
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f' "output_file": {json.dumps(task["output_file"])}'
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)
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lines.append("")
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lines.append(' // "tools": [],')
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lines.append(' // "human_input": false,')
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lines.append(' // "async_execution": false')
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lines.append(" }")
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return "\n".join(lines)
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return _render_json_crew_template(
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"task.jsonc",
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{
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"name_json": json.dumps(task["name"]),
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"description_json": json.dumps(task["description"]),
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"expected_output_json": json.dumps(task["expected_output"]),
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"agent_json": json.dumps(task["agent"]),
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"agent_comma": "," if has_context or has_output_file else "",
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"context_block": context_block,
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"output_file_block": output_file_block,
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},
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)
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def _crew_to_jsonc(
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@@ -894,69 +718,20 @@ def _crew_to_jsonc(
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inputs_lines[0] + "\n" + "\n".join(" " + line for line in inputs_lines[1:])
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)
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process = settings.get("process", "sequential")
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memory = "true" if settings.get("memory") else "false"
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return f"""\
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{{
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// Display name for this crew
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"name": {json.dumps(name)},
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// Agents to include — each must have a matching agents/<name>.jsonc file
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"agents": {agent_names_json},
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// Task definitions — executed in order for sequential process
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"tasks": [
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{tasks_fragments}
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],
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// Execution process
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// "sequential" — tasks run in order, each receiving prior task outputs
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// "hierarchical" — a manager agent delegates tasks (requires manager_llm)
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"process": "{process}",
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// Enable verbose logging during execution
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"verbose": true,
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// Enable crew memory — persists context and learnings across tasks
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"memory": {memory},
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// Automatically plan the execution strategy before running tasks
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// "planning": false,
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// LLM for the planning step (used when planning is true)
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// "planning_llm": "openai/gpt-4o",
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// LLM for the manager agent (required when process is "hierarchical")
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// "manager_llm": "openai/gpt-4o",
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// Crew-level LLM fields also accept object form for custom endpoints
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// "chat_llm": {{"model": "llama3", "provider": "ollama", "base_url": "http://localhost:11434"}},
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// Advanced crew options:
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// Docs: https://docs.crewai.com/concepts/crews
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// For hierarchical crews, manager_agent can reference an agents/<name>.jsonc file
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// that is not included in the "agents" list.
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// "manager_agent": "{agents[0]["name"]}",
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// "before_kickoff_callbacks": [{{"python": "my_project.callbacks.before_kickoff"}}],
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// "after_kickoff_callbacks": [{{"python": "my_project.callbacks.after_kickoff"}}],
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// "function_calling_llm": "openai/gpt-4o-mini",
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// "max_rpm": null,
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// "cache": true,
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// "knowledge_sources": [],
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// "embedder": {{}},
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// "output_log_file": "crew.log",
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// "stream": false,
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// "tracing": false,
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// "security_config": {{}},
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// Optional runtime input defaults.
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// Use {{placeholder}} in agent or task text, for example:
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// "description": "Research {{topic}} and write a brief"
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// `crewai run` prompts for any placeholders missing from this object.
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"inputs": {inputs_json}
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}}
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"""
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return _render_json_crew_template(
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"crew.jsonc",
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{
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"name_json": json.dumps(name),
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"agent_names_json": agent_names_json,
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"tasks_fragments": tasks_fragments,
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"process_json": json.dumps(settings.get("process", "sequential")),
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"memory": memory,
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"manager_agent_name": agents[0]["name"],
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"inputs_json": inputs_json,
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},
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)
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# ── Model selection ─────────────────────────────────────────────
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@@ -1031,6 +806,12 @@ def _default_model_for_provider(provider: str | None) -> str | None:
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# ── Helpers ─────────────────────────────────────────────────────
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def _render_json_crew_template(
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template_name: str, replacements: dict[str, str] | None = None
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) -> str:
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return render_template(_TEMPLATES_DIR / template_name, replacements or {})
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def _write_jsonc(path: Path, content: str) -> None:
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path.parent.mkdir(parents=True, exist_ok=True)
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path.write_text(content, encoding="utf-8")
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@@ -1136,26 +917,32 @@ def create_json_crew(
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# Write pyproject.toml
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(folder_path / "pyproject.toml").write_text(
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_PYPROJECT_TOML.format(
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folder_name=folder_name,
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name=name,
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crewai_tools_dependency=get_crewai_tools_dependency(),
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_render_json_crew_template(
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"pyproject.toml",
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{
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"folder_name": folder_name,
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"name": name,
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"crewai_tools_dependency": get_crewai_tools_dependency(),
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},
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),
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encoding="utf-8",
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)
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# Write .gitignore
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(folder_path / ".gitignore").write_text(_GITIGNORE, encoding="utf-8")
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(folder_path / ".gitignore").write_text(
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_render_json_crew_template(".gitignore"),
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encoding="utf-8",
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)
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# Write README
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(folder_path / "README.md").write_text(
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_README.format(name=name),
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_render_json_crew_template("README.md", {"name": name}),
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encoding="utf-8",
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)
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# Write knowledge placeholder
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(folder_path / "knowledge" / "user_preference.txt").write_text(
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"# Add your knowledge files here\n",
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_render_json_crew_template("knowledge/user_preference.txt"),
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encoding="utf-8",
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)
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Reference in New Issue
Block a user