from sxth_mind import Mind
from sxth_mind.storage import SQLiteStorage
from sxth_mind.providers.openai import OpenAIProvider
from sxth_mind.adapters import SalesAdapter

mind = Mind(
    adapter=SalesAdapter(),                     # Required
    provider=OpenAIProvider(),                  # Optional (defaults to OpenAI)
    storage=SQLiteStorage("mind.db"),           # Optional (defaults to memory)
)

response = await mind.chat(
    user_id="user_123",
    message="Following up with the enterprise lead",
    project_id="deal_acme",  # Optional, defaults to "default"
)

async for token in mind.chat_stream("user_123", "Hello"):
    print(token, end="", flush=True)

state = await mind.get_state("user_123", project_id="deal_acme")

# Use state to personalize any LLM call
patterns = state["user_mind"]["patterns"]
journey_stage = state["project_mind"]["journey_stage"]

summary = await mind.explain_state("user_123")
print(summary)
# "User has logged 15 interactions. Pattern: enterprise deals need 4+ touches.
#  Current stage: negotiating (tone: strategic)"

nudges = await mind.get_pending_nudges("user_123")
for nudge in nudges:
    print(f"{nudge.title}: {nudge.message}")

# Get user understanding
state = await mind.get_state("user_123")
user_patterns = state["user_mind"]["patterns"]
journey_stage = state["project_mind"]["journey_stage"]

# Use it to personalize a dashboard
if journey_stage == "onboarding":
    show_tutorial_widgets()
elif user_patterns.get("prefers_detailed"):
    show_detailed_analytics()

# Use it in your own LLM calls
system_prompt = f"""
User is in the {journey_stage} stage.
Known patterns: {user_patterns}
Adapt your response accordingly.
"""