Context Engineering

pip install agno openai sqlalchemy
export OPENAI_API_KEY="your-api-key"

from agno.agent import Agent
from agno.models.openai import OpenAIResponses

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    description="You are a famous short story writer asked to write for a magazine",
    instructions=["Always write 2 sentence stories."],
    markdown=True,
    debug_mode=True,  # Set to True to view the detailed logs and see the compiled system message
)
agent.print_response("Tell me a horror story.", stream=True)

You are a famous short story writer asked to write for a magazine
Always write 2 sentence stories.

<additional_information>
- Use markdown to format your answers.
</additional_information>

from agno.agent import Agent

agent = Agent(
    name="Helpful Assistant",
    role="Assistant",
    description="You are a helpful assistant",
    instructions=["Help the user with their question"],
    additional_context="""
    Here is an example of how to answer the user's question: 
        Request: What is the capital of France?
        Response: The capital of France is Paris.
    """,
    expected_output="You should format your response with `Response: <response>`",
    markdown=True,
    add_datetime_to_context=True,
    add_location_to_context=True,
    add_name_to_context=True,
    add_session_summary_to_context=True,
    add_memories_to_context=True,
    add_session_state_to_context=True,
)

You are a helpful assistant

<your_role>
Assistant
</your_role>

Help the user with their question

<additional_information>
- Use markdown to format your answers.
- The current time is 2025-09-30 12:00:00.
- Your approximate location is: New York, NY, USA.
- Your name is: Helpful Assistant.
</additional_information>

<expected_output>
You should format your response with `Response: <response>`
</expected_output>

Here is an example of how to answer the user's question: 
    Request: What is the capital of France?
    Response: The capital of France is Paris.

You have access to user info and preferences from previous interactions that you can use to personalize your response:

<memories_from_previous_interactions>
- User really likes Digimon and Japan.
- User really likes Japan.
- User likes coffee.
</memories_from_previous_interactions>

Note: this information is from previous interactions and may be updated in this conversation. You should always prefer information from this conversation over the past memories.

Here is a brief summary of your previous interactions:

<summary_of_previous_interactions>
The user asked about information about Digimon and Japan.
</summary_of_previous_interactions>

Note: this information is from previous interactions and may be outdated. You should ALWAYS prefer information from this conversation over the past summary.

<session_state> ... </session_state>

from agno.agent import Agent
from agno.models.openai import OpenAIResponses

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    additional_context="Example support policy: Standard support hours are 09:00–17:00 UTC, Monday through Friday.",
)
agent.print_response("When is standard support available?")

from agno.agent import Agent
from agno.tools.slack import SlackTools

slack_tools = SlackTools(
    instructions="Use `send_message` to send a message to the user. If the user specifies a thread, use `send_message_thread` to send a message to the thread.",
    add_instructions=True,
)
agent = Agent(
    tools=[slack_tools],
)

<updating_user_memories>
- You have access to the `update_user_memory` tool that you can use to add new memories, update existing memories, delete memories, or clear all memories.
- If the user's message includes information that should be captured as a memory, use the `update_user_memory` tool to update your memory database.
- Memories should include details that could personalize ongoing interactions with the user.
- Use this tool to add new memories or update existing memories that you identify in the conversation.
- Use this tool if the user asks to update their memory, delete a memory, or clear all memories.
- If you use the `update_user_memory` tool, remember to pass on the response to the user.
</updating_user_memories>

<knowledge_base>
You have a knowledge base you can search using the search_knowledge_base tool. Search before answering questions—don't assume you know the answer. For ambiguous questions, search first rather than asking for clarification.
The knowledge base contains documents with these metadata filters: filter1, filter2, filter3.
Always use filters when the user query indicates specific metadata.

Examples:
1. If the user asks about a specific person like "Jordan Mitchell", you MUST use the search_knowledge_base tool with the filters parameter set to {'<valid key like user_id>': '<valid value based on the user query>'}.
2. If the user asks about a specific document type like "contracts", you MUST use the search_knowledge_base tool with the filters parameter set to {'document_type': 'contract'}.
3. If the user asks about a specific location like "documents from New York", you MUST use the search_knowledge_base tool with the filters parameter set to {'<valid key like location>': 'New York'}.

General Guidelines:
- Always analyze the user query to identify relevant metadata.
- Use the most specific filter(s) possible to narrow down results.
- If multiple filters are relevant, combine them in the filters parameter (e.g., {'name': 'Jordan Mitchell', 'document_type': 'contract'}).
- Ensure the filter keys match the valid metadata filters: filter1, filter2, filter3.

Make sure to pass the filters as [Dict[str: Any]] to the tool. FOLLOW THIS STRUCTURE STRICTLY.
</knowledge_base>

from agno.agent import Agent

agent = Agent(system_message="Share a 2 sentence story about")
agent.print_response("Love in the year 12000.")

from agno.agent import Agent
agent = Agent(add_knowledge_to_context=True, add_dependencies_to_context=True)
agent.print_response("What is the capital of France?", dependencies={"name": "John Doe"})

What is the capital of France?

<additional context>
{"name": "John Doe"}
</additional context>

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses

db = SqliteDb(db_file="tmp/agent.db")

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    session_id="chat_history",
    instructions="You are a helpful assistant that can answer questions about space and oceans.",
    add_history_to_context=True,
    num_history_runs=2,
)

agent.print_response("Where is the sea of tranquility?", stream=True)

agent.print_response("What was my first question?", stream=True)

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
import random

def get_weather_for_city(city: str) -> str:
    conditions = ["Sunny", "Cloudy", "Rainy", "Snowy", "Foggy", "Windy"]
    temperature = random.randint(-10, 35)
    condition = random.choice(conditions)

    return f"{city}: {temperature}°C, {condition}"

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    tools=[get_weather_for_city],
    db=SqliteDb(db_file="tmp/agent.db"),
    add_history_to_context=True,
    num_history_runs=6,  # Load last 6 runs from history
    max_tool_calls_from_history=3,  # Keep only last 3 tool calls in context
)
agent.print_response("What's the weather in Tokyo?")
agent.print_response("What's the weather in Paris?")  
agent.print_response("What's the weather in London?")
agent.print_response("What's the weather in Berlin?")
agent.print_response("What's the weather in Mumbai?")
agent.print_response("What's the weather in Miami?")
agent.print_response("What's the weather in New York?")
agent.print_response("What's the weather in above cities?")

from agno.agent import Agent
from agno.models.message import Message
from agno.models.openai import OpenAIResponses

# Few-shot examples showing good support patterns
support_examples = [
    # Example 1: Simple issue resolution
    Message(role="user", content="I forgot my password and can't log in"),
    Message(
        role="assistant",
        content="""
    I'll help you reset your password right away.

    **Steps to Reset Your Password:**
    . Go to the login page and click "Forgot Password"
    . Enter your email address
    . Check your email for the reset link
    . Follow the link to create a new password
    . Use a strong password with uppercase, lowercase, numbers, and symbols

    f you don't receive the email within 5 minutes, please check your spam folder. Let me know if you need any assistance with these steps!
    """.strip(),
    ),
    # Example 2: Billing issue pattern
    Message(
        role="user",
        content="I've been charged twice for the same order and I'm frustrated!",
    ),
    Message(
        role="assistant",
        content="""
    I sincerely apologize for the billing error and the frustration this has caused you.

    **Immediate Action Plan:**
    1. I'll investigate your account to confirm the duplicate charge
    2. Process a full refund for the duplicate transaction
    3. Ensure this doesn't happen again by checking your payment method settings
    4. Provide you with a confirmation number once the refund is processed

    The refund typically takes 3-5 business days to appear on your statement. As an apology for this inconvenience, I'd also like to offer you a 10% discount on your next order.

    Is there anything else I can help you with regarding this issue?
    """.strip(),
    ),
    # Example 3: Technical support pattern
    Message(role="user", content="Your app keeps crashing when I try to upload photos"),
    Message(
        role="assistant",
        content="""
    I'm sorry you're experiencing crashes with photo uploads. Let me help you troubleshoot this issue.

    **Troubleshooting Steps:**
    1. **Check App Version:** Ensure you have the latest version from the app store
    2. **Restart the App:** Close completely and reopen the application
    3. **Check Storage:** Make sure you have sufficient device storage (at least 1GB free)
    4. **Photo Size:** Try uploading smaller photos (under 10MB each)
    5. **Network Connection:** Ensure you have a stable internet connection

    **If the issue persists:**
    - Try uploading one photo at a time instead of multiple
    - Clear the app cache in your device settings
    - Restart your device

    If none of these steps resolve the issue, please let me know your device type and OS version, and I'll escalate this to our technical team for further investigation.
    """.strip(),
    ),
]

if __name__ == "__main__":
    # Create agent with few-shot learning
    agent = Agent(
        name="Customer Support Specialist",
        model=OpenAIResponses(id="gpt-5.2"),
        add_name_to_context=True,
        additional_input=support_examples,  # few-shot learning examples
        instructions=[
            "You are an expert customer support specialist.",
            "Always be empathetic, professional, and solution-oriented.",
            "Provide clear, actionable steps to resolve customer issues.",
            "Follow the established patterns for consistent, high-quality support.",
        ],
        markdown=True,
    )

    agent.print_response("I want to enable two-factor authentication for my account.")