[FEATURE] Improve agent/task templating with Jinja2

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>

tests/test_templating.py

@@ -0,0 +1,88 @@
+import pytest
+import datetime
+from typing import Dict, List
+from crewai.agent import Agent
+from crewai.task import Task
+
+class TestTemplating:
+    def test_task_interpolation(self):
+        task = Task(
+            description="Research about {topic} and provide {count} key points",
+            expected_output="A list of {count} key points about {topic}"
+        )
+        
+        inputs = {"topic": "AI", "count": 5}
+        task.interpolate_inputs(inputs)
+        
+        assert task.description == "Research about AI and provide 5 key points"
+        assert task.expected_output == "A list of 5 key points about AI"
+        
+        task = Task(
+            description="Research about {topics[0]} and {topics[1]}",
+            expected_output="Analysis of {{data.main_theme}}"
+        )
+        
+        inputs = {
+            "topics": ["AI", "Machine Learning"],
+            "data": {"main_theme": "Technology Trends"}
+        }
+        
+        task.interpolate_inputs(inputs)
+        
+        assert task.description == "Research about AI and Machine Learning"
+        assert task.expected_output == "Analysis of Technology Trends"
+    
+    def test_agent_interpolation(self):
+        agent = Agent(
+            role="{industry} Researcher",
+            goal="Research {count} key developments in {industry}",
+            backstory="You are a senior researcher in the {industry} field with {experience} years of experience"
+        )
+        
+        inputs = {"industry": "Healthcare", "count": 5, "experience": 10}
+        agent.interpolate_inputs(inputs)
+        
+        assert agent.role == "Healthcare Researcher"
+        assert agent.goal == "Research 5 key developments in Healthcare"
+        assert agent.backstory == "You are a senior researcher in the Healthcare field with 10 years of experience"
+        
+        agent = Agent(
+            role="{{specialties[0]}} and {{specialties[1]}} Specialist",
+            goal="Analyze trends in {{fields.primary}} sector",
+            backstory="Expert in {{fields.primary}} and {{fields.secondary}}"
+        )
+        
+        inputs = {
+            "specialties": ["AI", "Data Science"],
+            "fields": {"primary": "Healthcare", "secondary": "Finance"}
+        }
+        
+        agent.interpolate_inputs(inputs)
+        
+        assert agent.role == "AI and Data Science Specialist"
+        assert agent.goal == "Analyze trends in Healthcare sector"
+        assert agent.backstory == "Expert in Healthcare and Finance"
+    
+    def test_conditional_templating(self):
+        task = Task(
+            description="{% if priority == 'high' %}URGENT: {% endif %}Research {topic}",
+            expected_output="A report on {topic}"
+        )
+        
+        inputs = {"topic": "AI", "priority": "high"}
+        task.interpolate_inputs(inputs)
+        assert task.description == "URGENT: Research AI"
+        
+        inputs = {"topic": "AI", "priority": "low"}
+        task.interpolate_inputs(inputs)
+        assert task.description == "Research AI"
+    
+    def test_loop_templating(self):
+        task = Task(
+            description="Research the following topics: {% for topic in topics %}{{topic}}{% if not loop.last %}, {% endif %}{% endfor %}",
+            expected_output="A report on multiple topics"
+        )
+        
+        inputs = {"topics": ["AI", "Machine Learning", "Data Science"]}
+        task.interpolate_inputs(inputs)
+        assert task.description == "Research the following topics: AI, Machine Learning, Data Science"