mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-01-11 09:08:31 +00:00
15dd15fcab
Fixes #2650 - Add support for container types (List, Dict, Set) - Add support for standard objects (datetime) - Add support for custom objects - Add support for conditional and loop statements - Add support for filtering options - Maintain backward compatibility with existing templates - Add comprehensive tests - Add documentation with examples Co-Authored-By: Joe Moura <joao@crewai.com>
134 lines
2.8 KiB
Markdown
134 lines
2.8 KiB
Markdown
# Enhanced Templating with Jinja2
|
|
|
|
CrewAI now supports enhanced templating using Jinja2, while maintaining compatibility with the existing templating system.
|
|
|
|
## Basic Usage
|
|
|
|
The basic templating syntax remains the same:
|
|
|
|
```python
|
|
from crewai import Agent, Task, Crew
|
|
|
|
# Define inputs
|
|
inputs = {
|
|
"topic": "Artificial Intelligence",
|
|
"year": 2024,
|
|
"count": 5
|
|
}
|
|
|
|
# Create an agent with template variables
|
|
researcher = Agent(
|
|
role="{topic} Researcher",
|
|
goal="Research the latest developments in {topic} for {year}",
|
|
backstory="You're an expert in {topic} with years of experience"
|
|
)
|
|
|
|
# Create a task with template variables
|
|
research_task = Task(
|
|
description="Research {topic} and provide {count} key insights",
|
|
expected_output="A list of {count} key insights about {topic} in {year}",
|
|
agent=researcher
|
|
)
|
|
|
|
# Create a crew and pass inputs
|
|
crew = Crew(
|
|
agents=[researcher],
|
|
tasks=[research_task],
|
|
inputs=inputs
|
|
)
|
|
|
|
# Run the crew
|
|
result = crew.kickoff()
|
|
```
|
|
|
|
## Advanced Features
|
|
|
|
The new templating system adds support for container types, object attributes, conditional statements, loops, and filters:
|
|
|
|
### Container Types
|
|
|
|
```python
|
|
inputs = {
|
|
"topics": ["AI", "Machine Learning", "Data Science"],
|
|
"details": {"main_theme": "Technology Trends", "subtopics": ["Ethics", "Applications"]}
|
|
}
|
|
|
|
# Access list items
|
|
task = Task(
|
|
description="Research {{topics[0]}} and {{topics[1]}}",
|
|
expected_output="Analysis of the topics"
|
|
)
|
|
|
|
# Access dictionary items
|
|
task = Task(
|
|
description="Research {{details.main_theme}} with focus on {{details.subtopics[0]}}",
|
|
expected_output="Detailed analysis"
|
|
)
|
|
```
|
|
|
|
### Conditional Statements
|
|
|
|
```python
|
|
inputs = {
|
|
"topic": "AI",
|
|
"priority": "high",
|
|
"deadline": "2024-12-31"
|
|
}
|
|
|
|
task = Task(
|
|
description="{% if priority == 'high' %}URGENT: {% endif %}Research {topic}{% if deadline %} by {{deadline}}{% endif %}",
|
|
expected_output="A report on {topic}"
|
|
)
|
|
```
|
|
|
|
### Loop Statements
|
|
|
|
```python
|
|
inputs = {
|
|
"topics": ["AI", "Machine Learning", "Data Science"]
|
|
}
|
|
|
|
task = Task(
|
|
description="Research the following topics: {% for topic in topics %}{{topic}}{% if not loop.last %}, {% endif %}{% endfor %}",
|
|
expected_output="A report covering multiple topics"
|
|
)
|
|
```
|
|
|
|
### Filters
|
|
|
|
```python
|
|
from datetime import datetime
|
|
|
|
inputs = {
|
|
"topic": "AI",
|
|
"date": datetime.now()
|
|
}
|
|
|
|
task = Task(
|
|
description="Research {topic} as of {{date|date('%Y-%m-%d')}}",
|
|
expected_output="A report on {topic}"
|
|
)
|
|
```
|
|
|
|
### Custom Objects
|
|
|
|
```python
|
|
from pydantic import BaseModel
|
|
|
|
class Person(BaseModel):
|
|
name: str
|
|
age: int
|
|
|
|
def __str__(self):
|
|
return f"{self.name} ({self.age})"
|
|
|
|
inputs = {
|
|
"author": Person(name="John Doe", age=35)
|
|
}
|
|
|
|
task = Task(
|
|
description="Write a report authored by {author}",
|
|
expected_output="A report by {{author.name}}"
|
|
)
|
|
```
|