Merge pull request #1 from qiuethan/zac/interview

feat: extract Header component and add Sign Up button

Author: e-ndorfin

.gitignore

@@ -44,3 +44,8 @@ Thumbs.db
 
 # Output folders
 output/
+
+.gemini/
+gha-creds-*.json
+GEMINI.md 
+plans/

api/app/main.py

@@ -19,6 +19,7 @@
 
 from .models import AvatarCreate, AvatarUpdate, ApiResponse, AgentRequest, AgentResponse, GenerateAvatarResponse
 from . import database as db
+from . import onboarding
 
 # Add image_gen to path for importing pipeline
 IMAGE_GEN_PATH = Path(__file__).parent.parent.parent / "image_gen"
@@ -58,6 +59,8 @@ async def lifespan(app: FastAPI):
     allow_headers=["*"],
 )
 
+app.include_router(onboarding.router)
+
 # ============================================================================
 # ROUTES
 # ============================================================================

api/app/models.py

@@ -68,3 +68,25 @@ class GenerateAvatarResponse(BaseModel):
     message: Optional[str] = None
     error: Optional[str] = None
     images: Optional[dict[str, str]] = None  # {front: url, back: url, left: url, right: url}
+
+
+class OnboardingChatRequest(BaseModel):
+    message: str
+    conversation_id: Optional[str] = None
+
+
+class OnboardingChatResponse(BaseModel):
+    response: str
+    conversation_id: str
+    status: str = "active"  # "active" or "completed"
+
+
+class OnboardingStateResponse(BaseModel):
+    history: list[dict]
+    conversation_id: Optional[str]
+    is_completed: bool
+
+
+class OnboardingCompleteRequest(BaseModel):
+    conversation_id: str
+

api/app/onboarding.py

@@ -0,0 +1,283 @@
+import json
+import os
+from pathlib import Path
+from typing import Optional, List
+from fastapi import APIRouter, HTTPException, Depends, Request
+from pydantic import BaseModel
+from openai import OpenAI
+
+from .models import OnboardingChatRequest, OnboardingChatResponse, OnboardingStateResponse, OnboardingCompleteRequest
+from .supabase_client import supabase
+
+router = APIRouter(prefix="/onboarding", tags=["onboarding"])
+
+# Load questions
+QUESTIONS_PATH = Path(__file__).parent.parent / "data" / "questions.json"
+try:
+    with open(QUESTIONS_PATH, "r") as f:
+        QUESTIONS = json.load(f)
+except Exception as e:
+    print(f"Error loading questions: {e}")
+    QUESTIONS = []
+
+OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
+if not OPENROUTER_API_KEY:
+    print("Warning: OPENROUTER_API_KEY not set. Onboarding chat will fail.")
+
+client = None
+if OPENROUTER_API_KEY:
+    try:
+        client = OpenAI(
+            base_url="https://openrouter.ai/api/v1",
+            api_key=OPENROUTER_API_KEY,
+        )
+    except Exception as e:
+        print(f"Failed to init OpenAI/OpenRouter client: {e}")
+
+MODEL_NAME = "xiaomi/mimo-v2-flash:free"
+
+async def get_current_user(request: Request):
+    auth_header = request.headers.get("Authorization")
+    if not auth_header:
+        raise HTTPException(status_code=401, detail="Missing Authorization header")
+    
+    token = auth_header.replace("Bearer ", "")
+    try:
+        user_response = supabase.auth.get_user(token)
+        if not user_response.user:
+             raise HTTPException(status_code=401, detail="Invalid token")
+        return user_response.user
+    except Exception as e:
+        print(f"Auth error: {e}")
+        raise HTTPException(status_code=401, detail="Invalid authentication")
+
+@router.get("/state", response_model=OnboardingStateResponse)
+async def get_onboarding_state(user = Depends(get_current_user)):
+    # Find active onboarding conversation
+    response = supabase.table("conversations")\
+        .select("*")\
+        .eq("participant_a", user.id)\
+        .eq("is_onboarding", True)\
+        .order("created_at", desc=True)\
+        .limit(1)\
+        .execute()
+    
+    if response.data:
+        conv = response.data[0]
+        return {
+            "history": conv.get("transcript", []),
+            "conversation_id": conv["id"],
+            "is_completed": False
+        }
+    
+    return {
+        "history": [],
+        "conversation_id": None,
+        "is_completed": False
+    }
+
+@router.post("/chat", response_model=OnboardingChatResponse)
+async def chat_onboarding(req: OnboardingChatRequest, user = Depends(get_current_user)):
+    if not client:
+        raise HTTPException(status_code=503, detail="AI service unavailable")
+
+    conversation_id = req.conversation_id
+    transcript = []
+
+    # 1. Retrieve or Create Conversation
+    if conversation_id:
+        res = supabase.table("conversations").select("*").eq("id", conversation_id).single().execute()
+        if not res.data:
+            raise HTTPException(status_code=404, detail="Conversation not found")
+        if res.data["participant_a"] != user.id:
+            raise HTTPException(status_code=403, detail="Not your conversation")
+        transcript = res.data.get("transcript", [])
+    else:
+        res = supabase.table("conversations")\
+            .select("*")\
+            .eq("participant_a", user.id)\
+            .eq("is_onboarding", True)\
+            .order("created_at", desc=True)\
+            .limit(1)\
+            .execute()
+        
+        if res.data:
+            conv = res.data[0]
+            conversation_id = conv["id"]
+            transcript = conv.get("transcript", [])
+        else:
+            new_conv = supabase.table("conversations").insert({
+                "participant_a": user.id,
+                "is_onboarding": True,
+                "transcript": []
+            }).execute()
+            conversation_id = new_conv.data[0]["id"]
+            transcript = []
+
+    # 2. Append User Message
+    if req.message != "[START]":
+        user_msg_obj = {"role": "user", "content": req.message}
+        transcript.append(user_msg_obj)
+
+    # 3. Construct LLM Prompt
+    system_instruction = f"""
+    You are a friendly, casual interviewer for a virtual world called 'Avatar World'. 
+    Your goal is to welcome the new user and get to know them by getting answers to the following questions.
+    
+    REQUIRED QUESTIONS:
+    {json.dumps(QUESTIONS, indent=2)}
+    
+    INSTRUCTIONS:
+    1. Ask these questions ONE BY ONE. Do not dump them all at once.
+    2. Maintain a conversational flow. React to their answers (e.g., "Oh, that's cool!", "I love pizza too!").
+    3. You can change the order if it flows better, but ensure all are covered eventually.
+    4. Keep your responses concise (1-2 sentences usually).
+    5. If the user asks you questions, answer briefly and steer back to the interview.
+    6. When you are satisfied that you have answers to ALL specific questions (or the user has declined to answer enough times), 
+       you MUST signal completion by calling the 'end_interview' tool.
+    
+    Current Progress:
+    Review the transcript below. See which questions have been answered. Ask the next one.
+    """
+
+    messages = [{"role": "system", "content": system_instruction}]
+    # Append transcript messages
+    # Ensure roles are 'user' or 'assistant'. OpenRouter/OpenAI expects 'assistant' not 'model'.
+    for msg in transcript:
+        # My transcript uses 'assistant' internally, so it's fine.
+        messages.append(msg)
+
+    # Define the tool
+    tools = [
+        {
+            "type": "function",
+            "function": {
+                "name": "end_interview",
+                "description": "Call this when all questions have been answered to finish the onboarding.",
+                "parameters": {
+                    "type": "object",
+                    "properties": {},
+                    "required": []
+                }
+            }
+        }
+    ]
+
+    try:
+        completion = client.chat.completions.create(
+            model=MODEL_NAME,
+            messages=messages,
+            tools=tools,
+            tool_choice="auto"
+        )
+    except Exception as e:
+        print(f"OpenRouter API Error: {e}")
+        return OnboardingChatResponse(
+            response="I'm having a bit of trouble connecting to my brain right now. Can you say that again?",
+            conversation_id=conversation_id,
+            status="active"
+        )
+
+    # 5. Process Response
+    ai_text = ""
+    status = "active"
+    
+    response_message = completion.choices[0].message
+    
+    # Check for tool calls
+    if response_message.tool_calls:
+        # Check if it's the right tool
+        for tool_call in response_message.tool_calls:
+            if tool_call.function.name == "end_interview":
+                status = "completed"
+                ai_text = "Thanks! That's everything I needed. Enjoy the world!"
+                break
+    
+    if status != "completed":
+        ai_text = response_message.content or "Hmm, I didn't catch that."
+
+    # 6. Save AI Response
+    ai_msg_obj = {"role": "assistant", "content": ai_text}
+    transcript.append(ai_msg_obj)
+    
+    supabase.table("conversations").update({
+        "transcript": transcript,
+        "updated_at": "now()"
+    }).eq("id", conversation_id).execute()
+
+    return OnboardingChatResponse(
+        response=ai_text,
+        conversation_id=conversation_id,
+        status=status
+    )
+
+@router.post("/complete")
+async def complete_onboarding(req: OnboardingCompleteRequest, user = Depends(get_current_user)):
+    if not client:
+        raise HTTPException(status_code=503, detail="AI service unavailable")
+
+    # 1. Fetch Transcript
+    res = supabase.table("conversations").select("*").eq("id", req.conversation_id).single().execute()
+    if not res.data:
+        raise HTTPException(status_code=404, detail="Conversation not found")
+    
+    conversation = res.data
+    transcript = conversation.get("transcript", [])
+    
+    # 2. Generate Memory Summary
+    summary_prompt = f"""
+    Analyze the following onboarding transcript for user '{user.id}'.
+    
+    Transcript:
+    {json.dumps(transcript)}
+    
+    Task:
+    1. Extract key facts (Name, Job, Hobbies, etc.).
+    2. Analyze their speaking style (Formal/Casual, Emoji usage, Length).
+    3. Create a concise summary paragraph.
+    
+    Output JSON:
+    {{
+      "facts": {{ ... }},
+      "style": "...",
+      "summary": "..."
+    }}
+    """
+    
+    try:
+        completion = client.chat.completions.create(
+            model=MODEL_NAME,
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant that outputs JSON."},
+                {"role": "user", "content": summary_prompt}
+            ],
+            response_format={"type": "json_object"}
+        )
+        content = completion.choices[0].message.content
+        summary_data = json.loads(content)
+        summary_text = summary_data.get("summary", "New user joined the world.")
+    except Exception as e:
+        print(f"Summary generation failed: {e}")
+        summary_text = "User completed onboarding."
+
+    # 3. Save Memory
+    supabase.table("memories").insert({
+        "conversation_id": req.conversation_id,
+        "owner_id": user.id,
+        "partner_id": None, 
+        "summary": summary_text,
+        "conversation_score": 10
+    }).execute()
+
+    # 4. Update User Metadata
+    try:
+        supabase.auth.admin.update_user_by_id(
+            user.id,
+            {"user_metadata": {"onboarding_completed": True}}
+        )
+    except Exception as e:
+        print(f"Failed to update user metadata: {e}")
+        # Note: If service key is invalid/missing rights, this fails.
+        raise HTTPException(status_code=500, detail="Failed to finalize onboarding.")
+
+    return {"ok": True}

api/app/supabase_client.py

@@ -0,0 +1,19 @@
+import os
+from typing import Optional
+from dotenv import load_dotenv
+from supabase import create_client, Client
+
+load_dotenv()
+
+SUPABASE_URL = os.getenv("SUPABASE_URL")
+SUPABASE_SERVICE_KEY = os.getenv("SUPABASE_SERVICE_KEY")
+
+supabase: Optional[Client] = None
+
+if SUPABASE_URL and SUPABASE_SERVICE_KEY:
+    try:
+        supabase = create_client(SUPABASE_URL, SUPABASE_SERVICE_KEY)
+    except Exception as e:
+        print(f"Failed to initialize Supabase client: {e}")
+else:
+    print("Warning: SUPABASE_URL or SUPABASE_SERVICE_KEY not set.")

api/data/questions.json

@@ -0,0 +1,12 @@
+[
+  "What is your name?",
+  "Where are you from?",
+  "What do you do for work or study?",
+  "What are your main hobbies or interests?",
+  "What kind of music do you like?",
+  "Do you have a favorite movie or TV show?",
+  "What brings you to this virtual world today?",
+  "If you could have any superpower, what would it be?",
+  "What's your favorite food?",
+  "Is there anything else you'd like to share about yourself?"
+]