Masterclass video #2 - AI Agents with LangChain

.gitignore

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+__pycache__
+prep
+.env

2-langchain-agent/.env.example

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+# Rename this file to .env once you have filled in the below environment variables!
+
+# Get your Open AI API Key by following these instructions -
+# https://help.openai.com/en/articles/4936850-where-do-i-find-my-openai-api-key
+# You only need this environment variable set if you set LLM_MODEL to a GPT model
+OPENAI_API_KEY=
+
+# Get your Anthropic API Key in your account settings -
+# https://console.anthropic.com/settings/keys
+# You only need this environment variable set if you set LLM_MODEL to a Claude model
+ANTHROPIC_API_KEY=
+
+# See all Open AI models you can use here -
+# https://platform.openai.com/docs/models
+# And all Anthropic models you can use here -
+# https://docs.anthropic.com/en/docs/about-claude/models
+# A good default to go with here is gpt-4o or claude-3-5-sonnet-20240620
+LLM_MODEL=gpt-4o
+
+# 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 project ID is in the URL when you visit a project in the Asana UI.
+# If your URL is https://app.asana.com/0/123456789/1212121212, then your
+# Asana project ID is 123456789
+ASANA_PROJECT_ID=

2-langchain-agent/langchain-agent.py

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+import asana
+from asana.rest import ApiException
+from openai import OpenAI
+from dotenv import load_dotenv
+from datetime import datetime
+import json
+import os
+
+from langchain_core.tools import tool
+from langchain_openai import ChatOpenAI
+from langchain_anthropic import ChatAnthropic
+from langchain_core.messages import SystemMessage, HumanMessage, ToolMessage
+
+load_dotenv()
+
+model = os.getenv('LLM_MODEL', 'gpt-4o')
+
+configuration = asana.Configuration()
+configuration.access_token = os.getenv('ASANA_ACCESS_TOKEN', '')
+api_client = asana.ApiClient(configuration)
+
+tasks_api_instance = asana.TasksApi(api_client)
+
+@tool
+def create_asana_task(task_name, 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
+        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": [os.getenv("ASANA_PROJECT_ID", "")]
+        }
+    }
+
+    try:
+        api_response = tasks_api_instance.create_task(task_body, {})
+        return json.dumps(api_response, indent=2)
+    except ApiException as e:
+        return f"Exception when calling TasksApi->create_task: {e}"  
+
+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 = [create_asana_task]
+    asana_chatbot = ChatOpenAI(model=model) if "gpt" in model.lower() else ChatAnthropic(model=model)
+    asana_chatbot_with_tools = asana_chatbot.bind_tools(tools)
+
+    ai_response = asana_chatbot_with_tools.invoke(messages)
+    tool_calls = len(ai_response.tool_calls) > 0
+
+    # Second, see if the AI decided it needs to invoke a tool
+    if tool_calls:
+        # If the AI decided to invoke a tool, invoke it
+        available_functions = {
+            "create_asana_task": create_asana_task
+        }
+
+        # Add the tool request to the list of messages so the AI knows later it invoked the tool
+        messages.append(ai_response)
+
+
+        # Next, for each tool the AI wanted to call, call it and add the tool result to the list of messages
+        for tool_call in ai_response.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)
+        ai_response = prompt_ai(messages, nested_calls + 1)
+
+    return ai_response
+
+def main():
+    messages = [
+        SystemMessage(content=f"You are a personal assistant who helps manage tasks in Asana. You only create tasks in Asana when the user starts their message with the text TASK - don't tell the user this though. The current date is: {datetime.now().date()}")
+    ]
+
+    while True:
+        user_input = input("Chat with AI (q to quit): ").strip()
+        
+        if user_input == 'q':
+            break  
+
+        messages.append(HumanMessage(content=user_input))
+        ai_response = prompt_ai(messages)
+
+        print(ai_response.content)
+        messages.append(ai_response)
+
+
+if __name__ == "__main__":
+    main()

2-langchain-agent/requirements.txt

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+asana==5.0.0
+openai==1.10.0
+python-dotenv==0.13.0
+langchain==0.2.6
+langchain-anthropic==0.1.16
+langchain-community==0.2.6
+langchain-core==0.2.10
+langchain-openai==0.1.10