cleanup

docs/concepts/flows.mdx

@@ -48,8 +48,6 @@ class ExampleFlow(Flow):
             ],
         )
 
-        #TODO: NEED TO ADD AN EXAMPLE AGENT IN HERE AS WELL.
-
         random_city = response["choices"][0]["message"]["content"]
         # Store the city in our state
         self.state["city"] = random_city
@@ -547,6 +545,97 @@ The `third_method` and `fourth_method` listen to the output of the `second_metho
 
 When you run this Flow, the output will change based on the random boolean value generated by the `start_method`.
 
+## Adding LiteAgent to Flows
+
+LiteAgents can be seamlessly integrated into your flows, providing a lightweight alternative to full Crews when you need simpler, focused task execution. Here's an example of how to use a LiteAgent within a flow to perform market research:
+
+```python
+from typing import List, cast
+from crewai_tools.tools.website_search.website_search_tool import WebsiteSearchTool
+from pydantic import BaseModel, Field
+from crewai.flow.flow import Flow, listen, start
+from crewai.lite_agent import LiteAgent
+
+# Define a structured output format
+class MarketAnalysis(BaseModel):
+    key_trends: List[str] = Field(description="List of identified market trends")
+    market_size: str = Field(description="Estimated market size")
+    competitors: List[str] = Field(description="Major competitors in the space")
+
+# Define flow state
+class MarketResearchState(BaseModel):
+    product: str = ""
+    analysis: MarketAnalysis | None = None
+
+class MarketResearchFlow(Flow[MarketResearchState]):
+    @start()
+    def initialize_research(self):
+        print(f"Starting market research for {self.state.product}")
+
+    @listen(initialize_research)
+    def analyze_market(self):
+        # Create a LiteAgent for market research
+        analyst = LiteAgent(
+            role="Market Research Analyst",
+            goal=f"Analyze the market for {self.state.product}",
+            backstory="You are an experienced market analyst with expertise in "
+            "identifying market trends and opportunities.",
+            llm="gpt-4o",
+            tools=[WebsiteSearchTool()],
+            verbose=True,
+            response_format=MarketAnalysis,
+        )
+
+        # Define the research query
+        query = f"""
+        Research the market for {self.state.product}. Include:
+        1. Key market trends
+        2. Market size
+        3. Major competitors
+        
+        Format your response according to the specified structure.
+        """
+
+        # Execute the analysis
+        result = analyst.kickoff(query)
+        self.state.analysis = cast(MarketAnalysis, result.pydantic)
+        return result.pydantic
+
+    @listen(analyze_market)
+    def present_results(self):
+        analysis = self.state.analysis
+        if analysis is None:
+            print("No analysis results available")
+            return
+
+        print("\nMarket Analysis Results")
+        print("=====================")
+
+        print("\nKey Market Trends:")
+        for trend in analysis.key_trends:
+            print(f"- {trend}")
+
+        print(f"\nMarket Size: {analysis.market_size}")
+
+        print("\nMajor Competitors:")
+        for competitor in analysis.competitors:
+            print(f"- {competitor}")
+
+# Usage example
+flow = MarketResearchFlow()
+result = flow.kickoff(inputs={"product": "AI-powered chatbots"})
+```
+
+This example demonstrates several key features of using LiteAgents in flows:
+
+1. **Structured Output**: Using Pydantic models to define the expected output format (`MarketAnalysis`) ensures type safety and structured data throughout the flow.
+
+2. **State Management**: The flow state (`MarketResearchState`) maintains context between steps and stores both inputs and outputs.
+
+3. **Tool Integration**: LiteAgents can use tools (like `WebsiteSearchTool`) to enhance their capabilities.
+
+If you want to learn more about LiteAgents, check out the [LiteAgent](/concepts/lite-agent) page.
+
 ## Adding Crews to Flows
 
 Creating a flow with multiple crews in CrewAI is straightforward.