# app.py
"""
Hugging Face Space app (Gradio) that forwards prompts to ChatGPT-like backend
using the provided dummy cookies. This is a best-effort reverse-proxy demo.

WARNING:
- These cookies are embedded here only because you explicitly provided dummy
  cookies for an educational demo. Never put real, sensitive cookies or tokens
  in a public Space. Use a private Space or environment secrets for real values.
- This reverse approach is unofficial and may break or be blocked by Cloudflare.
"""

import time
import uuid
import json
import requests
import gradio as gr
from typing import Optional

# ----------------------------
# Configuration: embedded dummy cookies (as provided)
# ----------------------------
COOKIES = {
    "conv_key": "\"rKVevhxYJuphj8B_obXQBnMV0gFu_SYw1DGKP9EIlY4=\"",
    "__Secure-next-auth.session-token": (
        "eyJhbGciOiJkaXIiLCJlbmMiOiJBMjU2R0NNIn0..pQAo79jORppyrvdi.VPSDpmUorC1Okv9nsvA_"
        "xerz4xLWOEqWfjnzCxtb5orIjxH_5OKI7GMAdQYG6KMWmgrUp4yuWF7B0zO7_WWSqKsml9BWUYa"
        "QQg_rli0mmypqD6V2hC0x0Bg312XpKh19Rhzj1boVik7FO9g145ZDmv9K0Svws48ENtZdn3ofUn"
        "EeeFhwa7l8oNqh1M9KJ7GjAgaZRCZ6I8wESreYmExZ_thEyRS3qrI-Bq4VlxTTZGKnBbzBMh7SZY"
        "pZU_CYQi1EmaR83BpBL6n9RWA_BZHrkEkbMbbSp4_2GqawK7REukhKlRGZ2vmmuNbFLnEYlZgGzI"
        "Ffj6SKv78k4IjILLyGeVe5Z8gNOEjSoLzlfm696yi7016m0M6Fo6yK-cjR6d9wUPp5Xm_e8tSR2U"
        "99ItEP2pWGEohHSAuohI2s117DUPhuKRZvyTYgFNGqQTrE_aOwKQoAY8W419HnEIrphTp2MC4CLF"
        "jEN2WCH0Gkm-yZSiFjS_UUk8zrSATQgRdTM3s5xkZoCsAKedAFOwDZUa-0oQd2IQnW2PY0s00mgD5"
        "54K_hBq0W2cn5B41Hrbf2uLqLoJMhYc2HrzKa6fvoTbcF_v5f4vewvGN_osmmkTHHFCXXQIGdz5pV"
        "M-1CtD4xY0zQ5Q4OUJVoQP9iV01wEJjc5GG7vImba0mR4iV1jePDczAE8v4SGCy68mmbbbSqbbVuo"
        "tM4LOgPxuMEtwCukj9uW8MZqrfGk5AxZcyYWwinjt2ztOtLxEytCnHNMnRV0B45OCey359CoK2htG"
        "-sST7IWjFeMBSieWO1NiJOv0aSZed_M0x0SMJuyyzEprW-AxNLQrU4Zs_j29dfKdKCGhSic8K_oh7G"
        "c9GAHLYMAztDn6ZIND-_tgbe5tm1TGSTHl8ZSh_cNLKnFs1RvCVIMb4pi986MO1byLeRR1r1tdqFN"
        "_EP7JvQvoreuRPABBnTvDpH6pOE62skPqZ9j6ZlENciEt6_nixCXhPPl1wPJJd-16PKD65DIbszRDr"
        "Y1K5RFYTgjNJDTEL1sZw6PcBIcuXSUL3V24Ke7MgSz4lq7gJXwWgTrOVTwPi3Kahk0xkbz_bYHhYCq"
        "OP5CILrbprKmtuV9M9I4VHP7kZA-faOT-kblCdxpD1BDFuOo-MRwTJ68Z10iuBGVWDJDzup8Y5lHMI"
        "2vyuJpv1VVIJ6igHkCUZjLX52WAW1QGuzNRBUJebm6EM3cDpUSc3ywcGyG4RZMHiJNfWmnxw_aq7jh"
        "qK1bT47SN1JhkYynzMsyF4MzON9eLWun1vz915TzucwKsfQoftjXqmlro2_3BRU0T3FoSyrG722DDq"
        "gNasSX9SeLZ1lJJtUv0IeXVH9u12Hafe9uUwGgfKwrofiDTtxTDNKeloGjWckoUtD8EGJUmBxFCdsY"
        "pPWdFhroORbtZM-EkDqYkwl5nK6zUVt1bkaepg84Eok0-Nx519s8oGItSre8JL3nL7MEwhG9BgKAs2"
        "3RKmNcsJzh5xvvqda4SGCPuNVFdEMZEB98eGmJ3jUuYnHCAhpQ4X766Ntnje-bhAruF7uKfGuvjjYl"
        "9KH6IxD9JuCtxKqas1qenB4oNXmvwuHZjLbhuvH2bz-cvhcUFqdRIImIKD3Web6UepPWpFlwNDSsGni"
        "eguLCks4pMmuTegQOU5n9CkgEB5MuQ3U6D9hG2fv_bdfCCK1kTGnfrTHn4G1vVzAym3yz09T73sNUnU"
        "cf5H1P-Z8ltVm4KhBRk8HKypWdoCwEsP5whtHbBgYIVZ8XUzD-fo7OA2QViwknB5cyOsCxPxjh67Zrj"
        "7XmFeaki1vcHd3U7eRGIym1UBQjkZ8CAA39LnUVszQqrQW2_CwuaxmgDh9qCZgH02OeG7Lj3sYcKxg"
        "XplzaH6cBBKx7Vq1_uk49s9-hMpvKiQn_DdfmEYLmPrITza9jzqeeiL0IrhBOivev00WgYaI95OkgUh"
        "Vs9fEqUCUDRSksd2bn0lyuERs_nCM4ngSkKvZWWVgXAnE8FE0rqYXuQOFccLcXYxr1vdNsfAIndmCi0"
        "fF_PQkddBY-iu7pQb8n_YPvLLMflFavbCC-3BmVl__Hmr_WuovJGsZL1DYcO89b37m2ZIQLT2dpaK-J"
        "zmcknO2OnSm1xoWkXD_vy5Kk5Ui7RVpp0ISM_2xh6pdgTOadcbG-NZ-sMsELHXATz_911lXAyQmoozar"
        "k9Bwonrh7zMvjAVKxEtjwnldYuA_0DhzBsGydQHZ5nzbnzPjS4XuFKV3Y00b6i6J3efvHSf0wUzchLcx"
        "An5i8Y9m7LUp_u9dxFFUokH7dqnkHiXzDpBxH2UqEw9NTB8gKKzl6H-Y6SJ7NOYmc4N9mF-HPgsnS-KyY"
        "WXrvcQ98PF5gaoAG1JY-LD1VEiDQ6PKdcH5zEOkH6n8zg9tWaRiGHauBp_XytpZqoMlA9LFJH86xTFxR"
        "RX-u0zWteFYLYL27NwHMDOfzFHapYLB-M9p-kgBIG8Zp6PmOckR5Es96_BOansDpEaStyRKazG1tFncLS"
        "-eNz5Q0soRuGdpB2UvWPNlvJ_RX-TZjfZwVMRzPFAeliw-Q-63BbiGXKXyvivu5yHNfXhk63V2DINEsBw88"
        "tTXrW9cHpSKwWDk7Bl4SprQAE-pV6a8jF9Qb1k7Ge93taXmH1ZgissL9DFig6bpGPHC1h1gtxKZ4eyKXCW"
        "-nBtNOXZ6eCtD0VeEMEgkeNEgj8-oUBBpuALs3oCOVqeAcXlC0D7T34PAsrwyE1o9xTa1Y83q9aL1AjwVMD"
        "nU-tmk01GZWAKqaWQwaOllRsK548uCwsKX-KAn3PwDNn5S6BZJkZ0XM0Hmwf1tQxqDZQy637kK3rXxFoOwg"
        "ESqbKArUVk-bV8KjyOc8yIRgBe0SPlYloyjFHU2N_fAY_FlJNvRjvI7xSUNOs-Y3TVqDIYQG0uPJxGrDGiBy"
        "m08bPIviK_hkoQBFlWId98MopTubtEY2n7DJ6-caa16KO_ToUq4RhqrRC1l0ZV7RFr0HEigxIwDtldWFs0op"
        "C9ccje5l_sUtCApgiKim5vItesEVgS-F2hx8yY4AfJV7IwHBBEmO3pNmViGKPQ24RL2LQ3iuEbU9NIdzOfdBi"
        "sKfaZOK7RrTdYExcUeMbEtzyKjBUSRsaq4UHC03E9LdksjMwLi3np3VNUT2om9k-o0S5DjUpI4tySijKQAA66"
        "SpasDAstPO5Ss_6M4-v5Kj-r9QTtHC94pAM8AD-hb5mSw6qwIx4Q5F2SdLMrtY7Dd2Vd8A3bXnOn1HsAdZyUT1"
        "W4DdS3Zl-VauV7ILlzQVLJ5AeAfATBRenNqRLHl2FBoNod6qtnui7bbRfvafWryKrdpr4otMWycPHPUbVWSXTm"
        "Wps3T-59QULRTRrADKxIaoJuqIKxuGqnLdW18298vQjfEOv4uqGNKzcU9fTGz67SQpQG9EOeTZHGKzhzfqkKiECH"
        "CDLhDWF3W7YPShqqda0T7_w_wFCH9rObq2wexqhUU_GPHnU93W4LOLE.ABtSFxKhamgcjdfZdJ-ahw"
    ),
    "cf_clearance": "E_7wmR35a_eEQAwLDblDFr4lNhphlrbsA08K8B38SJI-1756807432-1.2.1.1-QAloR641KrVse4D_Wv7xFTbLWk_Grb_cx7DhrxfsjQnpG0JsiV_YGIXigmBT.Cof9TUI_jf1IJHDe5FafguobuXONZQ3Jqf3m7aekQPXocqaHhyOPIS_pa58A4PGUyfL7BwtqhlRLBbC8mCeddWlnTV0M99G8gO32Cfe.tYNAeil2M7vEgHjNHE.Zgg7BiPYj3QNFgDx4J49aaUzE95ta0uZDXb2clgoCeofL.MzPrA"
}

# ----------------------------
# Build requests session with cookies
# ----------------------------
SESSION = requests.Session()
for k, v in COOKIES.items():
    # set cookies for both chat.openai.com and chatgpt.com domain variants
    try:
        SESSION.cookies.set(k, v, domain=".chatgpt.com", path="/")
    except Exception:
        SESSION.cookies.set(k, v, domain="chatgpt.com", path="/")
    # also attempt chat.openai.com
    try:
        SESSION.cookies.set(k, v, domain=".chat.openai.com", path="/")
    except Exception:
        pass

COMMON_HEADERS = {
    "User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120 Safari/537.36",
    "Accept": "application/json, text/plain, */*",
    "Referer": "https://chat.openai.com/",
    "Origin": "https://chat.openai.com"
}

# Endpoints to try (order matters)
ENDPOINTS = [
    "https://chat.openai.com/backend-api/conversation",
    "https://chat.openai.com/backend-api/conversations",
    "https://chatgpt.com/backend-api/conversation",
    "https://chatgpt.com/backend-api/conversations",
]

# ----------------------------
# Helpers
# ----------------------------
def looks_like_html_block(text: str) -> bool:
    t = (text or "").lower()
    return "<html" in t and ("cloudflare" in t or "captcha" in t or "refresh" in t)

def parse_assistant_text_from_json(obj) -> Optional[str]:
    """
    Try several common response shapes to extract assistant text.
    """
    if obj is None:
        return None
    if isinstance(obj, str):
        try:
            obj = json.loads(obj)
        except Exception:
            return None
    if not isinstance(obj, dict):
        return None

    # Shape 1: {'message': {'content': {'parts': [...]}}}
    msg = obj.get("message")
    if isinstance(msg, dict):
        content = msg.get("content") or msg.get("message") or {}
        if isinstance(content, dict):
            parts = content.get("parts") or content.get("text")
            if isinstance(parts, list) and parts:
                return parts[0]
            if isinstance(parts, str):
                return parts

    # Shape 2: {'choices': [{'delta': {'content': '...'}}]}
    choices = obj.get("choices")
    if isinstance(choices, list) and choices:
        first = choices[0]
        if isinstance(first, dict):
            # streaming-like
            delta = first.get("delta") or first.get("message") or {}
            if isinstance(delta, dict):
                if "content" in delta and isinstance(delta["content"], str):
                    return delta["content"]
                if "parts" in delta and isinstance(delta["parts"], list) and delta["parts"]:
                    return delta["parts"][0]
            if "text" in first and isinstance(first["text"], str):
                return first["text"]

    # Shape 3: top-level 'response' or 'content'
    for k in ("response", "content", "item"):
        if k in obj and isinstance(obj[k], str):
            return obj[k]

    return None

# ----------------------------
# Core: send prompt (with retries)
# ----------------------------
def send_prompt(prompt: str, model: str = "text-davinci-002-render-sha", timeout: int = 25):
    payload = {
        "action": "next",
        "messages": [{
            "id": str(uuid.uuid4()),
            "role": "user",
            "content": {"content_type": "text", "parts": [prompt]}
        }],
        "model": model
    }

    # Try endpoints with retries
    for endpoint in ENDPOINTS:
        tries = 0
        backoff = 0.6
        while tries < 3:
            tries += 1
            try:
                resp = SESSION.post(endpoint, headers=COMMON_HEADERS, json=payload, timeout=timeout)
            except Exception as e:
                # network-level error
                err = f"Network error contacting {endpoint}: {e}"
                if tries < 3:
                    time.sleep(backoff)
                    backoff *= 2
                    continue
                return False, err

            # If Cloudflare or HTML is returned -> considered blocked
            if resp.status_code >= 400 or looks_like_html_block(resp.text):
                snippet = resp.text[:800]
                # If it's HTML block, return explicit message to user
                if looks_like_html_block(resp.text):
                    return False, f"Blocked by Cloudflare / HTML detected at {endpoint}. Snippet:\n\n{snippet}"
                # otherwise continue retrying on 5xx maybe
                if 500 <= resp.status_code < 600 and tries < 3:
                    time.sleep(backoff)
                    backoff *= 2
                    continue
                return False, f"HTTP {resp.status_code} from {endpoint}: {snippet}"

            # success-ish
            try:
                parsed = resp.json()
            except Exception:
                # Not JSON — return raw text
                return True, resp.text[:4000]

            # attempt to extract assistant text
            assistant = parse_assistant_text_from_json(parsed)
            if assistant:
                return True, assistant
            else:
                # return full parsed JSON for debugging if no assistant found
                return True, parsed

    return False, "All endpoints failed after retries."

# ----------------------------
# Gradio UI function
# ----------------------------
def gradio_chat(message: str):
    if not message or not message.strip():
        return "Please enter a message."
    ok, result = send_prompt(message)
    if ok:
        # If result is JSON, pretty print small
        if isinstance(result, (dict, list)):
            return json.dumps(result, indent=2)[:3000]
        return str(result)
    else:
        return f"Error / blocked: {result}"

# ----------------------------
# Build Gradio app
# ----------------------------
with gr.Blocks() as demo:
    gr.Markdown("## 🚀 ChatGPT Reverse Demo (HF Space)\n"
                "> Demo forwards prompt to ChatGPT-like backend using embedded dummy cookies.\n\n"
                "**Important:** This is a demo. Do not expose live session tokens in public Spaces.")
    with gr.Row():
        inp = gr.Textbox(label="Your prompt", lines=2, placeholder="Write something you want the assistant to answer...")
        out = gr.Textbox(label="Assistant response", lines=10)
    btn = gr.Button("Send")
    btn.click(gradio_chat, inputs=inp, outputs=out)

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=8080)