cleanup

examples/flow_lite_agent.py

@@ -20,7 +20,6 @@ class MarketResearchState(BaseModel):
     analysis: MarketAnalysis | None = None
 
 
-# Create a flow class
 class MarketResearchFlow(Flow[MarketResearchState]):
     @start()
     def initialize_research(self):

examples/lite_agent_example_2.py

@@ -0,0 +1,46 @@
+from typing import List, cast
+
+from crewai_tools.tools.website_search.website_search_tool import WebsiteSearchTool
+from pydantic import BaseModel, Field
+
+from crewai.lite_agent import LiteAgent
+
+
+# Define a structured output format
+class MovieReview(BaseModel):
+    title: str = Field(description="The title of the movie")
+    rating: float = Field(description="Rating out of 10")
+    pros: List[str] = Field(description="List of positive aspects")
+    cons: List[str] = Field(description="List of negative aspects")
+
+
+# Create a LiteAgent
+critic = LiteAgent(
+    role="Movie Critic",
+    goal="Provide insightful movie reviews",
+    backstory="You are an experienced film critic known for balanced, thoughtful reviews.",
+    tools=[WebsiteSearchTool()],
+    verbose=True,
+    response_format=MovieReview,
+)
+
+# Use the agent
+query = """
+Review the movie 'Inception'. Include:
+1. Your rating out of 10
+2. Key positive aspects
+3. Areas that could be improved
+"""
+
+result = critic.kickoff(query)
+
+# Access the structured output
+review = cast(MovieReview, result.pydantic)
+print(f"\nMovie Review: {review.title}")
+print(f"Rating: {review.rating}/10")
+print("\nPros:")
+for pro in review.pros:
+    print(f"- {pro}")
+print("\nCons:")
+for con in review.cons:
+    print(f"- {con}")