first commit

.gitignore

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+env*
+.venv

.python-version

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+3.13

agent.py

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+from llama_index.llms.openai import OpenAI
+from tools.tavily_search_tool import search_web, record_notes, write_report, review_report
+from dotenv import load_dotenv
+import os
+load_dotenv()
+
+llm = OpenAI(model="gpt-4o", api_key=os.getenv("OPENAI_API_KEY"))
+
+from llama_index.core.agent.workflow import FunctionAgent, ReActAgent
+
+research_agent = FunctionAgent(
+    name="ResearchAgent",
+    description="Useful for searching the web for information on a given topic and recording notes on the topic.",
+    system_prompt=(
+        "You are the ResearchAgent that can search the web for information on a given topic and record notes on the topic. "
+        "Once notes are recorded and you are satisfied, you should hand off control to the WriteAgent to write a report on the topic. "
+        "You should have at least some notes on a topic before handing off control to the WriteAgent."
+    ),
+    llm=llm,
+    tools=[search_web, record_notes],
+    can_handoff_to=["WriteAgent"],
+)
+
+write_agent = FunctionAgent(
+    name="WriteAgent",
+    description="Useful for writing a report on a given topic.",
+    system_prompt=(
+        "You are the WriteAgent that can write a report on a given topic. "
+        "Your report should be in a markdown format. The content should be grounded in the research notes. "
+        "Once the report is written, you should get feedback at least once from the ReviewAgent."
+    ),
+    llm=llm,
+    tools=[write_report],
+    can_handoff_to=["ReviewAgent", "ResearchAgent"],
+)
+
+review_agent = FunctionAgent(
+    name="ReviewAgent",
+    description="Useful for reviewing a report and providing feedback.",
+    system_prompt=(
+        "You are the ReviewAgent that can review the write report and provide feedback. "
+        "Your review should either approve the current report or request changes for the WriteAgent to implement. "
+        "If you have feedback that requires changes, you should hand off control to the WriteAgent to implement the changes after submitting the review."
+    ),
+    llm=llm,
+    tools=[review_report],
+    can_handoff_to=["WriteAgent"],
+)
+
+from llama_index.core.agent.workflow import AgentWorkflow
+
+agent_workflow = AgentWorkflow(
+    agents=[research_agent, write_agent, review_agent],
+    root_agent=research_agent.name,
+    initial_state={
+        "research_notes": {},
+        "report_content": "Not written yet.",
+        "review": "Review required.",
+    },
+)
+
+
+# As the workflow is running, we will stream the events to get an idea of what is happening under the hood.
+from llama_index.core.agent.workflow import (
+    AgentInput,
+    AgentOutput,
+    ToolCall,
+    ToolCallResult,
+    AgentStream,
+)
+
+handler = agent_workflow.run(
+    user_msg=(
+        "Write me a report on the history of the internet. "
+        "Briefly describe the history of the internet, including the development of the internet, the development of the web, "
+        "and the development of the internet in the 21st century."
+    )
+)
+
+current_agent = None
+current_tool_calls = ""
+async for event in handler.stream_events():
+    if (
+        hasattr(event, "current_agent_name")
+        and event.current_agent_name != current_agent
+    ):
+        current_agent = event.current_agent_name
+        print(f"\n{'='*50}")
+        print(f"🤖 Agent: {current_agent}")
+        print(f"{'='*50}\n")
+
+    # if isinstance(event, AgentStream):
+    #     if event.delta:
+    #         print(event.delta, end="", flush=True)
+    # elif isinstance(event, AgentInput):
+    #     print("📥 Input:", event.input)
+    elif isinstance(event, AgentOutput):
+        if event.response.content:
+            print("📤 Output:", event.response.content)
+        if event.tool_calls:
+            print(
+                "🛠️  Planning to use tools:",
+                [call.tool_name for call in event.tool_calls],
+            )
+    elif isinstance(event, ToolCallResult):
+        print(f"🔧 Tool Result ({event.tool_name}):")
+        print(f"  Arguments: {event.tool_kwargs}")
+        print(f"  Output: {event.tool_output}")
+    elif isinstance(event, ToolCall):
+        print(f"🔨 Calling Tool: {event.tool_name}")
+        print(f"  With arguments: {event.tool_kwargs}")

main.py

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+def main():
+    print("Hello from teacher-student-agent!")
+
+
+if __name__ == "__main__":
+    main()

pyproject.toml

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+[project]
+name = "teacher-student-agent"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+dependencies = [
+    "dotenv>=0.9.9",
+    "llama-index>=0.12.40",
+    "tavily-python>=0.7.5",
+]

tools/tavily_search_tool.py

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+from tavily import AsyncTavilyClient
+from llama_index.core.workflow import Context
+
+
+async def search_web(query: str) -> str:
+    """Useful for using the web to answer questions."""
+    client = AsyncTavilyClient(api_key="tvly-...")
+    return str(await client.search(query))
+
+
+async def record_notes(ctx: Context, notes: str, notes_title: str) -> str:
+    """Useful for recording notes on a given topic. Your input should be notes with a title to save the notes under."""
+    current_state = await ctx.get("state")
+    if "research_notes" not in current_state:
+        current_state["research_notes"] = {}
+    current_state["research_notes"][notes_title] = notes
+    await ctx.set("state", current_state)
+    return "Notes recorded."
+
+
+async def write_report(ctx: Context, report_content: str) -> str:
+    """Useful for writing a report on a given topic. Your input should be a markdown formatted report."""
+    current_state = await ctx.get("state")
+    current_state["report_content"] = report_content
+    await ctx.set("state", current_state)
+    return "Report written."
+
+
+async def review_report(ctx: Context, review: str) -> str:
+    """Useful for reviewing a report and providing feedback. Your input should be a review of the report."""
+    current_state = await ctx.get("state")
+    current_state["review"] = review
+    await ctx.set("state", current_state)
+    return "Report reviewed."