Building Multi-Turn Conversations & State Management

from google import genai
from google.genai import types

client = genai.Client()
model = "gemini-2.5-flash"

contents = []

# --- Turn 1: Initial User Inquiry ---
contents.append(
    types.Content(
        role="user",
        parts=[types.Part(text="I want to return the jacket I bought last week.")]
    )
)

response1 = client.models.generate_content(
    model=model,
    contents=contents
)

print("--- Turn 1 Model Response ---")
print(response1.text.strip())

# Append model's actual response to conversation state
contents.append(
    types.Content(
        role="model",
        parts=[types.Part(text=response1.text)]
    )
)

# --- Turn 2: User Follow-up with Order ID ---
contents.append(
    types.Content(
        role="user",
        parts=[types.Part(text="Sure, my order number is ORD-99214.")]
    )
)

response2 = client.models.generate_content(
    model=model,
    contents=contents
)

print("\n--- Turn 2 Model Response (With Accumulated Context) ---")
print(response2.text.strip())

# --- Execution Output ---
# --- Turn 1 Model Response ---
# I can certainly help you with returning your jacket. To get started and verify
# your return window, could you please provide your order number?
#
# --- Turn 2 Model Response (With Accumulated Context) ---
# Thank you for providing order number ORD-99214. I have verified your purchase of the jacket.
# To proceed with generating your pre-paid shipping label, could you let me know the reason for the return?

from google import genai
from google.genai import types

client = genai.Client()
model = "gemini-2.5-flash"

def add_user_message(history: list[types.Content], text: str) -> None:
    """Appends a user message to the conversation history."""
    history.append(
        types.Content(role="user", parts=[types.Part(text=text)])
    )

def add_model_message(history: list[types.Content], text: str) -> None:
    """Appends a model message to the conversation history."""
    history.append(
        types.Content(role="model", parts=[types.Part(text=text)])
    )

def chat(history: list[types.Content], system_instruction: str | None = None) -> str:
    """Dispatches the conversation history with optional system instructions."""
    config = (
        types.GenerateContentConfig(system_instruction=system_instruction)
        if system_instruction else None
    )
    
    response = client.models.generate_content(
        model=model,
        contents=history,
        config=config
    )
    
    reply = response.text or ""
    add_model_message(history, reply)
    return reply

# Session initialization
history = []

# Turn 1
add_user_message(history, "Hi! I ordered a blue jacket but received a red one.")
reply1 = chat(history)
print(f"Assistant: {reply1}\n")

# Turn 2
add_user_message(history, "My order number is ORD-44582.")
reply2 = chat(history)
print(f"Assistant: {reply2}\n")

system_prompt = """
You are EcommAssist AI, the customer support specialist for ModernWear.
Operating Guidelines:
1. Always maintain a professional, calm, and helpful demeanor.
2. Never guarantee a monetary refund before verifying the order status.
3. If information is missing (like order ID), ask for one missing detail at a time.
4. Keep all responses concise (under 75 words).
"""

history = []
add_user_message(history, "Can you immediately refund my order ORD-771?")
reply = chat(history, system_instruction=system_prompt)
print(reply)