Implement comprehensive streaming support for CrewAI

- Add streaming events: CrewStreamChunkEvent, TaskStreamChunkEvent, AgentStreamChunkEvent
- Extend Crew.kickoff() with stream parameter and callback support
- Propagate streaming through task and agent execution chains
- Integrate with existing LLM streaming infrastructure
- Add comprehensive tests and examples
- Maintain backward compatibility

Fixes #2950

Co-Authored-By: João <joao@crewai.com>

examples/streaming_example.py

@@ -0,0 +1,36 @@
+from crewai import Agent, Task, Crew
+from crewai.llm import LLM
+
+def stream_callback(chunk, agent_role, task_description, step_type):
+    """Callback function to handle streaming chunks."""
+    print(f"[{agent_role}] {step_type}: {chunk}", end="", flush=True)
+
+llm = LLM(model="gpt-4o-mini", stream=True)
+
+agent = Agent(
+    role="Content Writer",
+    goal="Write engaging content",
+    backstory="You are an experienced content writer who creates compelling narratives.",
+    llm=llm,
+    verbose=False
+)
+
+task = Task(
+    description="Write a short story about a robot learning to paint",
+    expected_output="A creative short story of 2-3 paragraphs",
+    agent=agent
+)
+
+crew = Crew(
+    agents=[agent],
+    tasks=[task],
+    verbose=False
+)
+
+print("Starting crew execution with streaming...")
+result = crew.kickoff(
+    stream=True,
+    stream_callback=stream_callback
+)
+
+print(f"\n\nFinal result:\n{result}")

examples/streaming_multi_agent_example.py

@@ -0,0 +1,51 @@
+from crewai import Agent, Task, Crew
+from crewai.llm import LLM
+
+def stream_callback(chunk, agent_role, task_description, step_type):
+    """Callback function to handle streaming chunks from multiple agents."""
+    print(f"[{agent_role}] {step_type}: {chunk}", end="", flush=True)
+
+llm = LLM(model="gpt-4o-mini", stream=True)
+
+researcher = Agent(
+    role="Research Analyst",
+    goal="Research and analyze topics thoroughly",
+    backstory="You are an experienced research analyst who excels at gathering and analyzing information.",
+    llm=llm,
+    verbose=False
+)
+
+writer = Agent(
+    role="Content Writer", 
+    goal="Write engaging content based on research",
+    backstory="You are a skilled content writer who creates compelling narratives from research data.",
+    llm=llm,
+    verbose=False
+)
+
+research_task = Task(
+    description="Research the latest trends in artificial intelligence and machine learning",
+    expected_output="A comprehensive research summary of AI/ML trends",
+    agent=researcher
+)
+
+writing_task = Task(
+    description="Write an engaging blog post about AI trends based on the research",
+    expected_output="A well-written blog post about AI trends",
+    agent=writer,
+    context=[research_task]
+)
+
+crew = Crew(
+    agents=[researcher, writer],
+    tasks=[research_task, writing_task],
+    verbose=False
+)
+
+print("Starting multi-agent crew execution with streaming...")
+result = crew.kickoff(
+    stream=True,
+    stream_callback=stream_callback
+)
+
+print(f"\n\nFinal result:\n{result}")