diff --git a/llama3-function-calling-agent/.env.example b/llama3-function-calling-agent/.env.example
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+# Rename this file to .env once you have filled in the below environment variables!
+
+# Get your GROQ API Key here -
+# https://console.groq.com/keys
+GROQ_API_KEY=
+
+# Use a GROQ model ID for a model that is good at function calling
+LLM_MODEL=llama3-groq-70b-8192-tool-use-preview
+
+# Get your personal Asana access token through the developer console in Asana. 
+# Feel free to follow these instructions -
+# https://developers.asana.com/docs/personal-access-token
+ASANA_ACCESS_TOKEN=
+
+# The Asana workspace ID is in the URL when you visit your Asana Admin Console (when logged in).
+# Go to the URL "https://app.asana.com/admin" and then your workspace ID
+# will appear in the URL as a slew of digits once the site loads.
+# If your URL is https://app.asana.com/admin/987654321/insights, then your
+# Asana workspace ID is 987654321
+ASANA_WORKPLACE_ID=
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diff --git a/llama3-function-calling-agent/llama3-task-agent.py b/llama3-function-calling-agent/llama3-task-agent.py
new file mode 100644
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+++ b/llama3-function-calling-agent/llama3-task-agent.py
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+import asana
+from asana.rest import ApiException
+from dotenv import load_dotenv
+from datetime import datetime
+import streamlit as st
+import json
+import os
+
+from langchain_groq import ChatGroq
+from langchain_core.tools import tool
+from langchain_core.messages import SystemMessage, AIMessage, HumanMessage, ToolMessage
+
+load_dotenv()
+
+model = os.getenv('LLM_MODEL', 'llama3-groq-70b-8192-tool-use-preview')
+
+configuration = asana.Configuration()
+configuration.access_token = os.getenv('ASANA_ACCESS_TOKEN', '')
+api_client = asana.ApiClient(configuration)
+
+# create an instance of the different Asana API classes
+projects_api_instance = asana.ProjectsApi(api_client)
+tasks_api_instance = asana.TasksApi(api_client)
+
+workspace_gid = os.getenv("ASANA_WORKPLACE_ID", "")
+
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~ AI Agent Tool Functions ~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+@tool
+def create_asana_task(task_name, project_gid, due_on="today"):
+    """
+    Creates a task in Asana given the name of the task and when it is due
+
+    Example call:
+
+    create_asana_task("Test Task", "2024-06-24")
+    Args:
+        task_name (str): The name of the task in Asana
+        project_gid (str): The ID of the project to add the task to (not the name but the project ID)
+        due_on (str): The date the task is due in the format YYYY-MM-DD. If not given, the current day is used
+    Returns:
+        str: The API response of adding the task to Asana or an error message if the API call threw an error
+    """
+    if due_on == "today":
+        due_on = str(datetime.now().date())
+
+    task_body = {
+        "data": {
+            "name": task_name,
+            "due_on": due_on,
+            "projects": [project_gid]
+        }
+    }
+
+    try:
+        api_response = tasks_api_instance.create_task(task_body, {})
+        # return json.dumps(api_response, indent=2)
+        return "Task created successfully!"
+    except ApiException as e:
+        return f"Exception when calling TasksApi->create_task: {e}"  
+
+@tool
+def get_asana_projects():
+    """
+    Gets all of the projects in the user's Asana workspace
+
+    Returns:
+        str: The API response from getting the projects or an error message if the projects couldn't be fetched.
+        The API response is an array of project objects, where each project object looks like:
+        {'gid': '1207789085525921', 'name': 'Project Name', 'resource_type': 'project'}
+    """    
+    opts = {
+        'limit': 50, # int | Results per page. The number of objects to return per page. The value must be between 1 and 100.
+        'workspace': workspace_gid, # str | The workspace or organization to filter projects on.
+        'archived': False # bool | Only return projects whose `archived` field takes on the value of this parameter.
+    }
+
+    try:
+        api_response = projects_api_instance.get_projects(opts)
+        return json.dumps(list(api_response), indent=2)
+    except ApiException as e:
+        return "Exception when calling ProjectsApi->create_project: %s\n" % e
+
+@tool
+def create_asana_project(project_name, due_on=None):
+    """
+    Creates a project in Asana given the name of the project and optionally when it is due
+
+    Example call:
+
+    create_asana_project("Test Project", "2024-06-24")
+    Args:
+        project_name (str): The name of the project in Asana
+        due_on (str): The date the project is due in the format YYYY-MM-DD. If not supplied, the project is not given a due date
+    Returns:
+        str: The API response of adding the project to Asana or an error message if the API call threw an error
+    """    
+    body = {
+        "data": {
+            "name": project_name, "due_on": due_on, "workspace": workspace_gid
+        }
+    } # dict | The project to create.
+
+    try:
+        # Create a project
+        api_response = projects_api_instance.create_project(body, {})
+        return json.dumps(api_response, indent=2)
+    except ApiException as e:
+        return "Exception when calling ProjectsApi->create_project: %s\n" % e  
+
+@tool
+def get_asana_tasks(project_gid):
+    """
+    Gets all the Asana tasks in a project
+
+    Example call:
+
+    get_asana_tasks("1207789085525921")
+    Args:
+        project_gid (str): The ID of the project in Asana to fetch the tasks for
+    Returns:
+        str: The API response from fetching the tasks for the project in Asana or an error message if the API call threw an error
+        The API response is an array of tasks objects where each task object is in the format:
+        {'gid': '1207780961742158', 'created_at': '2024-07-11T16:25:46.380Z', 'due_on': None or date in format "YYYY-MM-DD", 'name': 'Test Task'}
+    """        
+    opts = {
+        'limit': 50, # int | Results per page. The number of objects to return per page. The value must be between 1 and 100.
+        'project': project_gid, # str | The project to filter tasks on.
+        'opt_fields': "created_at,name,due_on", # list[str] | This endpoint returns a compact resource, which excludes some properties by default. To include those optional properties, set this query parameter to a comma-separated list of the properties you wish to include.
+    }
+
+    try:
+        # Get multiple tasks
+        api_response = tasks_api_instance.get_tasks(opts)
+        return json.dumps(list(api_response), indent=2)
+    except ApiException as e:
+        return "Exception when calling TasksApi->get_tasks: %s\n" % e
+
+@tool
+def update_asana_task(task_gid, data):
+    """
+    Updates a task in Asana by updating one or both of completed and/or the due date
+
+    Example call:
+
+    update_asana_task("1207780961742158", {"completed": True, "due_on": "2024-07-13"})
+    Args:
+        task_gid (str): The ID of the task to update
+        data (dict): A dictionary with either one or both of the keys 'completed' and/or 'due_on'
+                    If given, completed needs to be either True or False.
+                    If given, the due date needs to be in the format 'YYYY-MM-DD'.
+    Returns:
+        str: The API response of updating the task or an error message if the API call threw an error
+    """      
+    # Data: {"completed": True or False, "due_on": "YYYY-MM-DD"}
+    body = {"data": data} # dict | The task to update.
+
+    try:
+        # Update a task
+        api_response = tasks_api_instance.update_task(body, task_gid, {})
+        return json.dumps(api_response, indent=2)
+    except ApiException as e:
+        return "Exception when calling TasksApi->update_task: %s\n" % e
+
+@tool
+def delete_task(task_gid):
+    """
+    Deletes a task in Asana
+
+    Example call:
+
+    delete_task("1207780961742158")
+    Args:
+        task_gid (str): The ID of the task to delete
+    Returns:
+        str: The API response of deleting the task or an error message if the API call threw an error
+    """        
+    try:
+        # Delete a task
+        api_response = tasks_api_instance.delete_task(task_gid)
+        return json.dumps(api_response, indent=2)
+    except ApiException as e:
+        return "Exception when calling TasksApi->delete_task: %s\n" % e   
+
+# Maps the function names to the actual function object in the script
+# This mapping will also be used to create the list of tools to bind to the agent
+available_functions = {
+    "create_asana_task": create_asana_task,
+    "get_asana_projects": get_asana_projects,
+    "create_asana_project": create_asana_project,
+    "get_asana_tasks": get_asana_tasks,
+    "update_asana_task": update_asana_task,
+    "delete_task": delete_task
+}     
+
+
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~ AI Prompting Function ~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+def prompt_ai(messages, nested_calls=0):
+    if nested_calls > 5:
+        raise "AI is tool calling too much!"
+
+    # First, prompt the AI with the latest user message
+    tools = [tool for _, tool in available_functions.items()]
+    asana_chatbot = ChatGroq(model=model)
+    asana_chatbot_with_tools = asana_chatbot.bind_tools(tools)
+
+    stream = asana_chatbot_with_tools.stream(messages)
+    first = True
+    for chunk in stream:
+        if first:
+            gathered = chunk
+            first = False
+        else:
+            gathered = gathered + chunk
+
+        yield chunk
+
+    has_tool_calls = len(gathered.tool_calls) > 0
+
+    # Second, see if the AI decided it needs to invoke a tool
+    if has_tool_calls:
+        # Add the tool request to the list of messages so the AI knows later it invoked the tool
+        messages.append(gathered)
+
+        # If the AI decided to invoke a tool, invoke it
+        # For each tool the AI wanted to call, call it and add the tool result to the list of messages
+        for tool_call in gathered.tool_calls:
+            tool_name = tool_call["name"].lower()
+            selected_tool = available_functions[tool_name]
+            tool_output = selected_tool.invoke(tool_call["args"])
+            messages.append(ToolMessage(tool_output, tool_call_id=tool_call["id"]))                
+
+        # Call the AI again so it can produce a response with the result of calling the tool(s)
+        additional_stream = prompt_ai(messages, nested_calls + 1)
+        for additional_chunk in additional_stream:
+            yield additional_chunk
+
+
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~ Main Function with UI Creation ~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+system_message = f"""
+You are a personal assistant who helps manage tasks in Asana. 
+You never give IDs to the user since those are just for you to keep track of. 
+When a user asks to create a task and you don't know the project to add it to for sure, clarify with the user.
+The current date is: {datetime.now().date()}
+"""
+
+def main():
+    st.title("Asana Chatbot")
+
+    # Initialize chat history
+    if "messages" not in st.session_state:
+        st.session_state.messages = [
+            SystemMessage(content=system_message)
+        ]    
+
+    # Display chat messages from history on app rerun
+    for message in st.session_state.messages:
+        message_json = json.loads(message.json())
+        message_type = message_json["type"]
+        if message_type in ["human", "ai", "system"]:
+            with st.chat_message(message_type):
+                st.markdown(message_json["content"])        
+
+    # React to user input
+    if prompt := st.chat_input("What would you like to do today?"):
+        # Display user message in chat message container
+        st.chat_message("user").markdown(prompt)
+        # Add user message to chat history
+        st.session_state.messages.append(HumanMessage(content=prompt))
+
+        # Display assistant response in chat message container
+        with st.chat_message("assistant"):
+            stream = prompt_ai(st.session_state.messages)
+            response = st.write_stream(stream)
+        
+        st.session_state.messages.append(AIMessage(content=response))
+
+
+if __name__ == "__main__":
+    main()
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diff --git a/llama3-function-calling-agent/requirements.txt b/llama3-function-calling-agent/requirements.txt
new file mode 100644
index 0000000..3fee9f2
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+++ b/llama3-function-calling-agent/requirements.txt
@@ -0,0 +1,7 @@
+asana==5.0.7
+python-dotenv==0.13.0
+langchain==0.2.6
+langchain-groq==0.1.5
+langchain-community==0.2.6
+langchain-core==0.2.10
+streamlit==1.36.0
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