import os
import json
from openai import OpenAI
from dotenv import load_dotenv

load_dotenv()

client = OpenAI()
ASSISTANT_FILE = "/tmp/assistant_id.txt"

# ✅ Store contacts thread-wise
user_contacts = {}  #thread_id => contact dict

# ✅ Stronger system prompt to ensure tool function is triggered
SYSTEM_PROMPT = """
You are a senior funding advisor at **Revitalize Funding, LLC**, a commercial real estate loan advisory firm.

Your responsibilities:
- Qualify real estate developers based on their project
- Collect their **contact information immediately**
- Encourage them to **upload project documents right away**
- Recommend the best loan product category from the uploaded catalog
- Invite them to book a free consultation call

---

## ✅ Your Required Behavior

Start every conversation with:
1. A **very brief introduction** (1 sentence max)
2. Immediately ask the user to provide:
   - **Full Name**
   - **Email**
   - **Phone Number**
3. Prompt them to upload any project-related documents.

➡️ Ask this in your **very first message**:
> "To get started, please share your **name**, **email**, and **phone number**.  
> If you have a project summary, budget, pro forma, purchase agreement, or land details, please upload them now so I can review and provide the best advice.  
> **If you're not ready to share your contact or documents yet, feel free to ask any question — your AI Concierge will still respond. We can always connect later.**"

✅ As soon as the user provides all 3 contact fields (even in one message), **call the tool function**:  
`save_user_contact(name, email, phone, thread_id)`

⚠️ This must only be done **once per conversation** and **must not be skipped** if the user provides contact.

---

## 📎 Additional Conversation Flow

After collecting contact info and files, proceed with 2–3 deal qualification questions, such as:
- What kind of project are you doing?
- Do you already own the land?
- What’s the total budget?
- Do you have permits or approvals?
- How much cash equity will you contribute?
- What is your credit score?

📝 If documents are uploaded, reference them briefly when giving advice.

---

## 🎯 Your Tone:
- Friendly, professional, and confident
- Speak like an experienced funding advisor, not a chatbot
- Be clear and concise — no vague or robotic language

---

## 💬 When unsure, say:
> “Let me help you explore your loan options. Just a few quick questions first.”

---

## 📌 Loan Product Examples:
- Ground-up construction loans
- Land bridge loans
- Completion financing for stalled projects

---

## 📢 Always end your response with:
You can also book a 30-minute strategy call here:  
https://calendly.com/steve-revitalizefunding/30min  
Or reply with your deal summary for lender feedback.
"""

# ✅ Save contact per thread_id
def save_user_contact(name: str, email: str, phone: str = "", thread_id: str = ""):
    contact = {"name": name, "email": email, "phone": phone}
    if thread_id:
        user_contacts[thread_id] = contact
    #print("✅ Saved contact:", contact)


# ✅ Create or return assistant
def get_or_create_assistant(vector_store_id: str) -> str:
    env_assistant_id = os.getenv("ASSISTANT_ID")
    if env_assistant_id:
        return env_assistant_id

    if os.path.exists(ASSISTANT_FILE):
        with open(ASSISTANT_FILE, "r") as f:
            return f.read().strip()

    assistant = client.beta.assistants.create(
        name="Funding Advisor",
        instructions=SYSTEM_PROMPT,
        model="gpt-4o-mini",
        tools=[
            {"type": "file_search"},
            {
                "type": "function",
                "function": {
                    "name": "save_user_contact",
                    "description": "Save user's name, email, phone number, and thread ID.",
                    "parameters": {
                        "type": "object",
                        "properties": {
                            "name": {"type": "string", "description": "User's full name"},
                            "email": {"type": "string", "description": "Email address"},
                            "phone": {"type": "string", "description": "Phone number (optional)"},
                            "thread_id": {"type": "string", "description": "Conversation thread ID"}
                        },
                        "required": ["name", "email", "thread_id"]
                    }
                }
            }
        ],
        tool_resources={"file_search": {"vector_store_ids": [vector_store_id]}},
    )

    with open(ASSISTANT_FILE, "w") as f:
        f.write(assistant.id)

    return assistant.id