Step 1 — Connect real-time events

fun extractFromElementsChain(str, pattern) {
    try {
        if (empty(str)) { return '' }
        let startIdx := position(str, pattern)
        if (startIdx <= 0) { return '' }
        let sub := substring(str, startIdx + length(pattern), length(str) - startIdx - length(pattern) + 1)
        let endIdx := position(sub, '"')
        if (endIdx > 0) { return substring(sub, 1, endIdx - 1) }
        return ''
    } catch (err) {
        return ''
    }
}

let elements_chain := event.elements_chain ?? ''
let element_id := extractFromElementsChain(elements_chain, 'attr__id="')
let input_field_name := extractFromElementsChain(elements_chain, 'attr__name="')
let link_destination := extractFromElementsChain(elements_chain, 'attr__href="')
let button_or_link_text := extractFromElementsChain(elements_chain, 'text="')

let payload := {
    'event': event.event,
    'referrer': event.properties?.$referrer ?? '',
    'timestamp': event.timestamp ?? '',
    'element_id': element_id,
    'event_type': event.properties?.$event_type ?? '',
    'session_id': event.properties?.$session_id ?? '',
    'current_url': event.properties?.$current_url ?? '',
    'distinct_id': event.distinct_id ?? '',
    'email': event.properties?.email ?? '',
    'elements_chain': elements_chain,
    'input_field_name': input_field_name,
    'link_destination': link_destination,
    'button_or_link_text': button_or_link_text
}

let headers := {
    'Content-Type': 'application/json',
    'x-posthog-secret': inputs.headers['x-posthog-secret']
}

let req := { 'headers': headers, 'body': jsonStringify(payload), 'method': 'POST' }
let url := inputs.url

let res := fetch(url, req)
if (res.status >= 400) {
    throw Error(f'Webhook returned {res.status}: {res.body}')
}

import logging
import os
from typing import Any

import httpx
import openai
from autoplay_sdk.agent_state.v2.states import SessionState
from autoplay_sdk.rag.query.assembly import (
    ChatContextAssembly,
    build_user_prompt_block,
)
from dotenv import load_dotenv
from fastapi import FastAPI, HTTPException

load_dotenv()
logging.basicConfig(level=logging.INFO)
log = logging.getLogger("copilot")

CONNECTOR_URL = os.environ.get("CONNECTOR_URL", "https://mcp.autoplay.ai")
MCP_KEY = os.environ["MCP_KEY"]
PRODUCT_ID = os.environ["PRODUCT_ID"]
LLM_MODEL = os.environ.get("LLM_MODEL", "gpt-4o-mini")
MAX_ACTIONS = int(os.environ.get("MAX_ACTIONS", "30"))

_openai = openai.AsyncOpenAI(api_key=os.environ["OPENAI_API_KEY"])

async def fetch_recent_activity_raw(user_id: str) -> list[dict[str, Any]]:
    """GET the user's recent actions from the Autoplay connector.

    Returns the raw `actions` array (oldest -> newest) on success, or `[]`
    on any non-200 response or network error — from the caller's point of
    view, "no activity yet" and "couldn't reach the connector" degrade the
    same way: the LLM just answers without activity context.
    """
    try:
        async with httpx.AsyncClient(timeout=5.0) as client:
            r = await client.get(
                f"{CONNECTOR_URL}/users/{PRODUCT_ID}/{user_id}/live-activity",
                params={"limit": MAX_ACTIONS},
                headers={"Authorization": f"Bearer {MCP_KEY}"},
            )
    except httpx.HTTPError as exc:
        log.warning("live-activity fetch failed user=%s: %s", user_id, exc)
        return []
    if r.status_code != 200:
        log.warning("live-activity fetch %s user=%s", r.status_code, user_id)
        return []
    return r.json().get("actions", [])


def _format_activity(actions: list[dict[str, Any]]) -> str:
    """Raw actions -> the short text block the LLM prompt expects. This is
    the on-the-fly equivalent of what `AsyncContextStore.get()` used to
    return from a local buffer — now computed straight from whatever the
    connector just handed back."""
    return "\n".join(
        f"[{a.get('index')}] {a.get('title')} — {a.get('description')} ({a.get('canonical_url')})"
        for a in actions
    )


async def fetch_recent_activity_text(user_id: str) -> str:
    return _format_activity(await fetch_recent_activity_raw(user_id))

_user_emails: dict[str, str] = {}
_user_states: dict[str, SessionState] = {}

def _user_state(user_id: str) -> SessionState:
    if user_id not in _user_states:
        # Demo-friendly timeouts so you can iterate quickly while testing
        # Step 2's proactive triggers. Production: use ~60.0 / ~120.0 so
        # the FSM doesn't drift out of REACTIVE mid-conversation.
        _user_states[user_id] = SessionState(
            session_id=user_id, interaction_timeout_s=10.0, cooldown_period_s=20.0,
        )
    return _user_states[user_id]

def _name_from_email(email):
    if not email or "@" not in email:
        return None
    local = email.split("@", 1)[0]
    parts = [p for p in local.replace(".", " ").replace("_", " ").split() if p]
    return " ".join(p.capitalize() for p in parts) if parts else None

SYSTEM_PROMPT = """You are a friendly and helpful assistant for users of this product.

Focus on helping people find their way in the UI, complete workflows, and understand features. Assume some users are seeing the product for the first time.

## 💬 How to use the "Current User Activity" context

You may receive a "Current User Activity" block alongside the user's question. It shows what THIS user has been doing on the platform in the last few minutes — which page they are on and what they clicked. The activity is scoped to their session, so it reflects only their actions, not anyone else's.

When this context is present:

1. **Acknowledge their activity naturally** — for example: "I can see you're currently on the Projects page" or "It looks like you've been exploring the Dashboard."

2. **Use it to give specific directions** — instead of generic instructions, reference where they are: "From the page you're on, click the blue 'Add Project' button at the top right."

3. **Detect if they might be lost** — if their actions show them clicking around without a clear pattern, gently offer help: "It looks like you might be looking for something specific. Can I help you find it?"

4. **Don't force it** — if the user's question has nothing to do with their current activity, just answer the question normally. Don't mention their activity unless it's helpful. Never recite a click-by-click log.

5. **Pick up from the user's last action — don't restart the flow.** Treat the most recent click as the user's current position. If they clicked a button that starts a flow, your reply should begin AFTER that click, not before it. Never tell the user to click a button the activity log already shows them clicking.

6. **Refer to UI only with names you can see in the activity log.** Use the exact button/link text that appears in the activity log. For elements you don't see in the log (fields inside a dialog, secondary buttons), describe them by role rather than guessing a label — e.g. "the confirm button at the bottom of the dialog," "the email field." Do not invent labels.

## ❓ How to answer questions

- **Be specific**: reference actual button names, tab labels, and menu items.
- **Use numbered steps**: when explaining how to do something, use a numbered list.
- **Keep it simple**: avoid technical jargon. Explain as if the user has never used the platform before.
- **Be encouraging**: make users feel comfortable.
- **Offer next steps**: after answering, suggest what they might want to do next.
- **Admit when you don't know**: if you don't have the answer, say so honestly.

## 🌐 Language

Respond in the same language the user writes in.

## ✅ Examples

**A. User is on the Dashboard (no recent CTA click), asks "How do I create a project?":**
  "I can see you're currently on the Dashboard. To create a new project:
   1. Click on 'My Projects' in the left sidebar
   2. Click the 'Add Project' button at the top right
   3. Fill in the required details and click 'Create'
   Would you like me to explain what each field means?"

**B. User just clicked "Add Project" (a dialog is open), asks "How do I create a project?":**

❌ WRONG (re-tells the click they already made):
  "Click 'My Projects' in the sidebar, then click 'Add Project'…"

✅ RIGHT (picks up after the click):
  "You're in the new-project dialog now — fill in the name and any
   required fields, then click the create button at the bottom of the
   dialog to finish."

**C. User just clicked "Invite member" on the Team page, asks "how do I add a teammate?":**

✅ "You're in the invite dialog — enter the teammate's email, pick a role
   from the dropdown, and click the send button at the bottom."

(Notice: no step that says "click Invite member." The activity log shows
they already clicked it.)

**D. User is on the Invoice page, asks "Where are settings?":**
  "The settings aren't on this page — click on your profile icon in the
   top right corner, then select 'Settings' from the dropdown."

**E. User has no activity context, asks "What can I do here?":**
  "Welcome! Here's what you can do:
   1. Dashboard — see an overview of your work
   2. My Projects — create and manage projects
   3. Reports — view analytics or exports
   4. Billing — manage invoices or account settings
   What would you like to explore first?"

Address the user by their first name once per conversation if known. Never invent actions the user did not actually take."""

async def _build_assembly(user_id: str, query: str) -> ChatContextAssembly:
    return ChatContextAssembly(
        recent_activity=await fetch_recent_activity_text(user_id),
        kb_records_text="",
        conversation_history_text="",
        user_message=query,
    )

app = FastAPI(title="Autoplay × Rasa bridge")

@app.get("/healthz")
async def healthz():
    return {"status": "ok"}

@app.get("/reply/{user_id}")
async def get_reply(user_id: str, query: str, email: str | None = None) -> dict[str, Any]:
    if not query:
        raise HTTPException(status_code=400, detail="query required")
    if email:
        _user_emails[user_id] = email  # optional — see the Note in 2d
    assembly = await _build_assembly(user_id, query)
    user_prompt = build_user_prompt_block(assembly)
    name = _name_from_email(_user_emails.get(user_id))
    sys_prompt = SYSTEM_PROMPT + (f"\n\nUser's first name: {name}." if name else "")

    try:
        resp = await _openai.chat.completions.create(
            model=LLM_MODEL,
            temperature=0.4,
            max_tokens=250,
            messages=[
                {"role": "system", "content": sys_prompt},
                {"role": "user", "content": user_prompt},
            ],
        )
        reply = (resp.choices[0].message.content or "").strip()
    except Exception as exc:
        log.exception("openai call failed")
        return {"reply": "Sorry — I hit a problem reaching the language model.", "error": str(exc)}

    return {
        "reply": reply,
        "name": name,
        "has_activity": bool(assembly.recent_activity.strip()),
    }

services:
  rasa:
    image: rasa/rasa:3.6.21-full
    platform: linux/amd64                 # forces amd64 on Apple Silicon
    ports: ["5005:5005"]
    volumes: ["./:/app"]
    command:
      - run
      - --enable-api
      - --cors
      - "*"
      - --endpoints
      - endpoints.docker.yml
    depends_on: [action-server]

  action-server:
    build:
      context: ./actions
      dockerfile: Dockerfile
    platform: linux/amd64
    ports: ["5055:5055"]
    environment:
      - BRIDGE_URL=http://host.docker.internal:8090
    extra_hosts:
      - "host.docker.internal:host-gateway"
    volumes:
      - ./actions:/app/actions

recipe: default.v1
language: en

pipeline:
  - name: WhitespaceTokenizer
  - name: RegexFeaturizer
  - name: LexicalSyntacticFeaturizer
  - name: CountVectorsFeaturizer
  - name: CountVectorsFeaturizer
    analyzer: char_wb
    min_ngram: 1
    max_ngram: 4
  - name: DIETClassifier
    epochs: 100
    constrain_similarities: true
  - name: EntitySynonymMapper
  - name: ResponseSelector
    epochs: 100
    constrain_similarities: true
  - name: FallbackClassifier
    threshold: 0.3
    ambiguity_threshold: 0.1

policies:
  - name: MemoizationPolicy
  - name: RulePolicy
  - name: UnexpecTEDIntentPolicy
    max_history: 5
    epochs: 100
  - name: TEDPolicy
    max_history: 5
    epochs: 100
    constrain_similarities: true

assistant_id: autoplay-copilot

version: "3.1"
intents:
  - greet
  - goodbye
  - bot_challenge
  - ask_what_just_happened
  - ask_help_current_page
  - nlu_fallback

responses:
  utter_greet:
    - text: "Hey! I'm your copilot. I can see what you've been doing — ask me about it."
  utter_goodbye:
    - text: "Bye. Come back if you get stuck."
  utter_iamabot:
    - text: "I'm a bot powered by Rasa + Autoplay."

actions:
  - action_recent_activity
  - action_help_current_page
  - action_ask_llm

version: "3.1"

nlu:
  - intent: greet
    examples: |
      - hi
      - hello
      - hey
      - good morning
      - good evening
      - hey there

  - intent: goodbye
    examples: |
      - bye
      - goodbye
      - see you
      - cya
      - thanks bye

  - intent: bot_challenge
    examples: |
      - are you a bot
      - are you human
      - what are you
      - who built you

  - intent: ask_what_just_happened
    examples: |
      - what did I just do
      - what was I doing
      - what just happened
      - recap my last actions
      - what have I been clicking
      - summarize my session
      - what did I just click
      - what was I working on

  - intent: ask_help_current_page
    examples: |
      - help me with this page
      - what can I do here
      - I'm stuck
      - help
      - what should I do next
      - guide me
      - I don't know what to do

version: "3.1"

rules:
  - rule: Say hello on greet
    steps:
      - intent: greet
      - action: utter_greet

  - rule: Say goodbye
    steps:
      - intent: goodbye
      - action: utter_goodbye

  - rule: Answer bot challenge
    steps:
      - intent: bot_challenge
      - action: utter_iamabot

  - rule: Recap recent activity
    steps:
      - intent: ask_what_just_happened
      - action: action_recent_activity

  - rule: Help on current page
    steps:
      - intent: ask_help_current_page
      - action: action_help_current_page

  - rule: Free-form question (LLM fallback)
    steps:
      - intent: nlu_fallback
      - action: action_ask_llm

version: "3.1"

stories:
  - story: happy path — greet then recap
    steps:
      - intent: greet
      - action: utter_greet
      - intent: ask_what_just_happened
      - action: action_recent_activity

  - story: stuck on page
    steps:
      - intent: greet
      - action: utter_greet
      - intent: ask_help_current_page
      - action: action_help_current_page

"""Rasa custom actions — autoplay-native.

The bridge owns the SDK pipeline. Rasa actions just GET /reply.
"""

from __future__ import annotations
import os
from typing import Any
import httpx
from rasa_sdk import Action, Tracker
from rasa_sdk.executor import CollectingDispatcher

BRIDGE_URL = os.environ.get("BRIDGE_URL", "http://host.docker.internal:8090")
TIMEOUT_S = float(os.environ.get("BRIDGE_TIMEOUT_S", "12"))


def _user_id(tracker):
    metadata = (tracker.latest_message or {}).get("metadata") or {}
    custom = metadata.get("customData") or {}
    return (
        metadata.get("userId")
        or custom.get("userId")
        or tracker.sender_id
        or "anonymous"
    )


def _user_email(tracker):
    """Optional — only used for the bridge's first-name personalization
    (Step 5, section 2d). Returns None if the widget never set it, which
    is fine: the bridge just skips the "User's first name" hint."""
    metadata = (tracker.latest_message or {}).get("metadata") or {}
    custom = metadata.get("customData") or {}
    return metadata.get("email") or custom.get("email")


def _user_text(tracker):
    return (tracker.latest_message or {}).get("text") or ""


async def _ask_bridge(user_id, query, email=None):
    params = {"query": query}
    if email:
        params["email"] = email
    async with httpx.AsyncClient(timeout=TIMEOUT_S) as client:
        r = await client.get(f"{BRIDGE_URL}/reply/{user_id}", params=params)
        r.raise_for_status()
        return r.json()


async def _reply_via_bridge(dispatcher, tracker, fallback):
    try:
        data = await _ask_bridge(
            _user_id(tracker), _user_text(tracker), _user_email(tracker),
        )
        text = data.get("reply") or fallback
    except Exception as exc:
        print(f"[action] bridge call failed: {exc}", flush=True)
        text = fallback
    dispatcher.utter_message(text=text)


class ActionAskLLM(Action):
    def name(self): return "action_ask_llm"
    async def run(self, dispatcher, tracker, domain):
        await _reply_via_bridge(
            dispatcher, tracker,
            "I'm not sure I caught that. Try asking what you just did, or for help.",
        )
        return []


class ActionRecentActivity(Action):
    def name(self): return "action_recent_activity"
    async def run(self, dispatcher, tracker, domain):
        await _reply_via_bridge(
            dispatcher, tracker,
            "I haven't seen activity in the last few minutes. Click around and ask again.",
        )
        return []


class ActionHelpCurrentPage(Action):
    def name(self): return "action_help_current_page"
    async def run(self, dispatcher, tracker, domain):
        await _reply_via_bridge(
            dispatcher, tracker,
            "I don't know what page you're on yet. Click anywhere and ask again.",
        )
        return []