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>

docs/streaming.md

@@ -0,0 +1,68 @@
+# Streaming Support in CrewAI
+
+CrewAI now supports real-time streaming output during crew execution, allowing you to see the progress of agents and tasks as they work.
+
+## Basic Usage
+
+```python
+from crewai import Agent, Task, Crew
+from crewai.llm import LLM
+
+def stream_callback(chunk, agent_role, task_description, step_type):
+    print(f"[{agent_role}] {step_type}: {chunk}", end="", flush=True)
+
+llm = LLM(model="gpt-4o-mini", stream=True)
+
+agent = Agent(
+    role="Writer",
+    goal="Write content",
+    backstory="You are a skilled writer.",
+    llm=llm
+)
+
+task = Task(
+    description="Write a short story",
+    expected_output="A creative story",
+    agent=agent
+)
+
+crew = Crew(agents=[agent], tasks=[task])
+
+result = crew.kickoff(
+    stream=True,
+    stream_callback=stream_callback
+)
+```
+
+## Multi-Agent Streaming
+
+```python
+def enhanced_callback(chunk, agent_role, task_description, step_type):
+    print(f"[{agent_role}] {task_description[:20]}... - {step_type}: {chunk}")
+
+researcher = Agent(role="Researcher", ...)
+writer = Agent(role="Writer", ...)
+
+research_task = Task(description="Research topic", agent=researcher)
+write_task = Task(description="Write article", agent=writer, context=[research_task])
+
+crew = Crew(agents=[researcher, writer], tasks=[research_task, write_task])
+result = crew.kickoff(stream=True, stream_callback=enhanced_callback)
+```
+
+## Stream Callback Parameters
+
+- `chunk`: The streaming text chunk
+- `agent_role`: Role of the agent producing the chunk  
+- `task_description`: Description of the current task
+- `step_type`: Type of step ("agent_thinking", "final_answer", "llm_response")
+
+## Events
+
+The streaming system emits `CrewStreamChunkEvent`, `TaskStreamChunkEvent`, and `AgentStreamChunkEvent` that can be handled using the event bus.
+
+## Requirements
+
+- Enable streaming on your LLM: `LLM(model="...", stream=True)`
+- Use the `stream=True` parameter in `crew.kickoff()`
+- Provide a callback function to handle streaming chunks