research agent

.gitignore

@@ -1,2 +1,4 @@
 env*
-.venv
+.venv
+
+.cursor/*

agent.py

@@ -2,65 +2,8 @@ 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 FunctionAgent
 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,
@@ -69,43 +12,101 @@ from llama_index.core.agent.workflow import (
     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."
-    )
-)
+load_dotenv(os.path.join(os.path.dirname(__file__), 'env.local'))
+
+class TeacherStudentAgentWorkflow:
+    def __init__(self):
+        self.llm = OpenAI(model="gpt-4o-mini", api_key=os.getenv("OPENAI_API_KEY"))
+
+        self.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=self.llm,
+            tools=[search_web, record_notes],
+            can_handoff_to=["WriteAgent"],
+        )
 
-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")
+        self.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=self.llm,
+            tools=[write_report],
+            can_handoff_to=["ReviewAgent", "ResearchAgent"],
+        )
 
-    # 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],
+        self.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=self.llm,
+            tools=[review_report],
+            can_handoff_to=["WriteAgent"],
+        )
+
+        self.agent_workflow = AgentWorkflow(
+            agents=[self.research_agent, self.write_agent, self.review_agent],
+            root_agent=self.research_agent.name,
+            initial_state={
+                "research_notes": {},
+                "report_content": "Not written yet.",
+                "review": "Review required.",
+            },
+        )
+
+    async def run_workflow(self, user_msg=None):
+        if user_msg is None:
+            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."
             )
-    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}")
+        handler = self.agent_workflow.run(user_msg=user_msg)
+
+        current_agent = None
+        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, 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}")
+
+if __name__ == "__main__":
+    import asyncio
+    agent = TeacherStudentAgentWorkflow()
+    user_msg = input("Enter the topic or instructions for the report (leave blank for default): ").strip()
+    if not user_msg:
+        user_msg = None
+    asyncio.run(agent.run_workflow(user_msg=user_msg))

app.py

@@ -1,79 +1,237 @@
 import gradio as gr
 from gradio import ChatMessage
-import time
+import asyncio
+from agent import TeacherStudentAgentWorkflow
+from llama_index.core.agent.workflow import (
+    AgentInput,
+    AgentOutput,
+    ToolCall,
+    ToolCallResult,
+    AgentStream,
+)
 
-def generate_response(history):
-    history.append(
-        ChatMessage(
-            role="user", content="What is the weather in San Francisco right now?"
-        )
-    )
-    yield history
-    time.sleep(0.25)
-    history.append(
-        ChatMessage(
-            role="assistant",
-            content="In order to find the current weather in San Francisco, I will need to use my weather tool.",
-        )
-    )
-    yield history
-    time.sleep(0.25)
+# Initialize the agent workflow
+agent_workflow = None
 
-    history.append(
-        ChatMessage(
-            role="assistant",
-            content="API Error when connecting to weather service.",
-            metadata={"title": "💥 Error using tool 'Weather'"},
-        )
-    )
-    yield history
-    time.sleep(0.25)
+def get_agent_workflow():
+    global agent_workflow
+    if agent_workflow is None:
+        agent_workflow = TeacherStudentAgentWorkflow()
+    return agent_workflow
 
-    history.append(
-        ChatMessage(
+async def chat_with_agent(message, history):
+    """
+    Async chat function that runs the agent workflow and streams each step.
+    """
+    if not message.strip():
+        yield history, None
+        return
+    
+    # Add user message to history
+    history.append(ChatMessage(role="user", content=message))
+    yield history, None
+    
+    try:
+        # Get the agent workflow
+        workflow = get_agent_workflow()
+        
+        # Run the workflow with the user message
+        handler = workflow.agent_workflow.run(user_msg=message)
+        
+        current_agent = None
+        current_step_messages = []
+        final_report = None
+        workflow_state = {}
+        
+        async for event in handler.stream_events():
+            # Check if we switched to a new agent
+            if (
+                hasattr(event, "current_agent_name")
+                and event.current_agent_name != current_agent
+            ):
+                current_agent = event.current_agent_name
+                
+                # Add agent header message
+                agent_header = ChatMessage(
+                    role="assistant",
+                    content=f"🤖 **{current_agent}** is now working...",
+                    metadata={"title": f"Agent: {current_agent}"}
+                )
+                history.append(agent_header)
+                yield history, final_report
+            
+            # Handle different event types
+            if isinstance(event, AgentOutput):
+                if event.response.content:
+                    # Add agent output
+                    output_msg = ChatMessage(
+                        role="assistant",
+                        content=f"📤 **Output:** {event.response.content}",
+                        metadata={"title": f"{current_agent} - Output"}
+                    )
+                    history.append(output_msg)
+                    yield history, final_report
+                
+                if event.tool_calls:
+                    # Show planned tools
+                    tools_list = [call.tool_name for call in event.tool_calls]
+                    tools_msg = ChatMessage(
+                        role="assistant",
+                        content=f"🛠️ **Planning to use tools:** {', '.join(tools_list)}",
+                        metadata={"title": f"{current_agent} - Tool Planning"}
+                    )
+                    history.append(tools_msg)
+                    yield history, final_report
+                    
+            elif isinstance(event, ToolCall):
+                # Show tool being called
+                tool_msg = ChatMessage(
+                    role="assistant",
+                    content=f"🔨 **Calling Tool:** {event.tool_name}\n**Arguments:** {event.tool_kwargs}",
+                    metadata={"title": f"{current_agent} - Tool Call"}
+                )
+                history.append(tool_msg)
+                yield history, final_report
+                
+            elif isinstance(event, ToolCallResult):
+                # Show tool results
+                result_content = str(event.tool_output)
+                if len(result_content) > 500:
+                    result_content = result_content[:500] + "..."
+                
+                result_msg = ChatMessage(
+                    role="assistant",
+                    content=f"🔧 **Tool Result ({event.tool_name}):**\n{result_content}",
+                    metadata={"title": f"{current_agent} - Tool Result"}
+                )
+                history.append(result_msg)
+                
+                # Track tool results to detect report writing and review approval
+                if event.tool_name == "write_report":
+                    workflow_state["has_report"] = True
+                elif event.tool_name == "review_report" and current_agent == "ReviewAgent":
+                    workflow_state["has_review"] = True
+                    # Check if review indicates approval
+                    if any(word in result_content.lower() for word in ["approved", "ready", "good", "excellent"]):
+                        workflow_state["review_approved"] = True
+                
+                yield history, final_report
+        
+        # Get the final state to extract the report
+        try:
+            final_state = await handler.ctx.get("state")
+            if final_state and "report_content" in final_state:
+                report_content = final_state["report_content"]
+                if report_content and report_content != "Not written yet.":
+                    # Show the final report if we have one and it's been reviewed
+                    if workflow_state.get("has_report") and workflow_state.get("has_review"):
+                        final_report = gr.Markdown(report_content, visible=True)
+                    elif workflow_state.get("has_report"):
+                        # Show report even if not reviewed yet
+                        final_report = gr.Markdown(report_content, visible=True)
+        except Exception as state_error:
+            print(f"Could not extract final state: {state_error}")
+            # Try to show any report that was generated during the conversation
+            if workflow_state.get("has_report"):
+                final_report = gr.Markdown("Report was generated but could not be extracted from final state.", visible=True)
+        
+        # Add completion message
+        completion_msg = ChatMessage(
             role="assistant",
-            content="I will try again",
+            content="✅ **Workflow completed!** The agent collaboration has finished.",
+            metadata={"title": "Workflow Complete"}
         )
-    )
-    yield history
-    time.sleep(0.25)
-
-    history.append(
-        ChatMessage(
+        history.append(completion_msg)
+        yield history, final_report
+        
+    except Exception as e:
+        # Handle errors gracefully
+        error_msg = ChatMessage(
             role="assistant",
-            content="Weather 72 degrees Fahrenheit with 20% chance of rain.",
-            metadata={"title": "🛠️ Used tool 'Weather'"},
+            content=f"❌ **Error:** {str(e)}",
+            metadata={"title": "Error"}
         )
-    )
-    yield history
-    time.sleep(0.25)
+        history.append(error_msg)
+        yield history, None
 
-    history.append(
-        ChatMessage(
-            role="assistant",
-            content="Now that the API succeeded I can complete my task.",
-        )
-    )
-    yield history
-    time.sleep(0.25)
+def like_feedback(evt: gr.LikeData):
+    """Handle user feedback on messages."""
+    print(f"User feedback - Index: {evt.index}, Liked: {evt.liked}, Value: {evt.value}")
 
-    history.append(
-        ChatMessage(
-            role="assistant",
-            content="It's a sunny day in San Francisco with a current temperature of 72 degrees Fahrenheit and a 20% chance of rain. Enjoy the weather!",
-        )
+# Create the Gradio interface
+with gr.Blocks(title="Teacher-Student Agent Workflow", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("""
+    # 🤖 Teacher-Student Agent Workflow
+    
+    This demo showcases a multi-agent workflow with three specialized agents:
+    - **ResearchAgent**: Searches the web and records notes
+    - **WriteAgent**: Writes reports based on research
+    - **ReviewAgent**: Reviews and provides feedback on reports
+    
+    Enter a topic or request below to see the agents collaborate step by step!
+    """)
+    
+    chatbot = gr.Chatbot(
+        type="messages",
+        height=600,
+        show_copy_button=True,
+        placeholder="<strong>Welcome to the Teacher-Student Agent Workflow!</strong><br>Ask me to write a report on any topic and watch the agents collaborate.",
+        render_markdown=True
     )
-    yield history
-
-def like(evt: gr.LikeData):
-    print("User liked the response")
-    print(evt.index, evt.liked, evt.value)
-
-with gr.Blocks() as demo:
-    chatbot = gr.Chatbot(type="messages", height=500, show_copy_button=True)
-    button = gr.Button("Get San Francisco Weather")
-    button.click(generate_response, chatbot, chatbot)
-    chatbot.like(like)
+    
+    textbox = gr.Textbox(
+        placeholder="Enter your request (e.g., 'Write a report on artificial intelligence')",
+        container=False,
+        scale=7
+    )
+    
+    # Create the final report output component
+    final_report_output = gr.Markdown(
+        label="📄 Final Approved Report",
+        visible=False,
+        render=False
+    )
+    
+    # Set up the chat interface with additional outputs
+    chat_interface = gr.ChatInterface(
+        fn=chat_with_agent,
+        chatbot=chatbot,
+        textbox=textbox,
+        type="messages",
+        examples=[
+            "Write a report on the history of artificial intelligence",
+            "Create a report about renewable energy technologies",
+            "Write a report on the impact of social media on society",
+            "Generate a report about space exploration achievements"
+        ],
+        example_labels=[
+            "AI History Report",
+            "Renewable Energy Report", 
+            "Social Media Impact Report",
+            "Space Exploration Report"
+        ],
+        cache_examples=False,
+        additional_outputs=[final_report_output]
+    )
+    
+    # Add feedback handling
+    chatbot.like(like_feedback)
+    
+    # Render the final report output in a separate section
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("### 📋 Final Report")
+            final_report_output.render()
+    
+    gr.Markdown("""
+    ### How it works:
+    1. **ResearchAgent** searches for information and takes notes
+    2. **WriteAgent** creates a report based on the research
+    3. **ReviewAgent** reviews the report and provides feedback
+    4. The process continues until the report is approved
+    
+    Watch the real-time collaboration between agents as they work together!
+    """)
 
 if __name__ == "__main__":
     demo.launch()

pyproject.toml

@@ -5,7 +5,9 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [
+    "asyncio>=3.4.3",
     "dotenv>=0.9.9",
+    "gradio>=5.33.0",
     "llama-index>=0.12.40",
     "tavily-python>=0.7.5",
 ]

tools/tavily_search_tool.py

@@ -1,10 +1,13 @@
 from tavily import AsyncTavilyClient
 from llama_index.core.workflow import Context
+from dotenv import load_dotenv
+import os
 
+load_dotenv(os.path.join(os.path.dirname(__file__), '../env.local'))
 
 async def search_web(query: str) -> str:
     """Useful for using the web to answer questions."""
-    client = AsyncTavilyClient(api_key="tvly-...")
+    client = AsyncTavilyClient(api_key=os.getenv("TAVILY_API_KEY"))
     return str(await client.search(query))
 
 

uv.lock

@@ -2,6 +2,15 @@ version = 1
 revision = 1
 requires-python = ">=3.13"
 
+[[package]]
+name = "aiofiles"
+version = "24.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/0b/03/a88171e277e8caa88a4c77808c20ebb04ba74cc4681bf1e9416c862de237/aiofiles-24.1.0.tar.gz", hash = "sha256:22a075c9e5a3810f0c2e48f3008c94d68c65d763b9b03857924c99e57355166c", size = 30247 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a5/45/30bb92d442636f570cb5651bc661f52b610e2eec3f891a5dc3a4c3667db0/aiofiles-24.1.0-py3-none-any.whl", hash = "sha256:b4ec55f4195e3eb5d7abd1bf7e061763e864dd4954231fb8539a0ef8bb8260e5", size = 15896 },
+]
+
 [[package]]
 name = "aiohappyeyeballs"
 version = "2.6.1"
@@ -90,6 +99,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a1/ee/48ca1a7c89ffec8b6a0c5d02b89c305671d5ffd8d3c94acf8b8c408575bb/anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c", size = 100916 },
 ]
 
+[[package]]
+name = "asyncio"
+version = "3.4.3"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/da/54/054bafaf2c0fb8473d423743e191fcdf49b2c1fd5e9af3524efbe097bafd/asyncio-3.4.3.tar.gz", hash = "sha256:83360ff8bc97980e4ff25c964c7bd3923d333d177aa4f7fb736b019f26c7cb41", size = 204411 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/22/74/07679c5b9f98a7cb0fc147b1ef1cc1853bc07a4eb9cb5731e24732c5f773/asyncio-3.4.3-py3-none-any.whl", hash = "sha256:c4d18b22701821de07bd6aea8b53d21449ec0ec5680645e5317062ea21817d2d", size = 101767 },
+]
+
 [[package]]
 name = "attrs"
 version = "25.3.0"
@@ -99,6 +117,46 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/77/06/bb80f5f86020c4551da315d78b3ab75e8228f89f0162f2c3a819e407941a/attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3", size = 63815 },
 ]
 
+[[package]]
+name = "audioop-lts"
+version = "0.2.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/dd/3b/69ff8a885e4c1c42014c2765275c4bd91fe7bc9847e9d8543dbcbb09f820/audioop_lts-0.2.1.tar.gz", hash = "sha256:e81268da0baa880431b68b1308ab7257eb33f356e57a5f9b1f915dfb13dd1387", size = 30204 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/01/91/a219253cc6e92db2ebeaf5cf8197f71d995df6f6b16091d1f3ce62cb169d/audioop_lts-0.2.1-cp313-abi3-macosx_10_13_universal2.whl", hash = "sha256:fd1345ae99e17e6910f47ce7d52673c6a1a70820d78b67de1b7abb3af29c426a", size = 46252 },
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