1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
|
"""
standalone: ChatGPT CLI — generates sentinel tokens and holds an interactive conversation
Dependencies (pip): curl_cffi
Usage:
python get_sentinel_token.py
python get_sentinel_token.py --access-token <token> --model gpt-4o
"""
import argparse
import base64
import hashlib
import json
import random
import re
import time
import uuid
from dataclasses import dataclass, field
from datetime import datetime, timedelta, timezone
from html.parser import HTMLParser
from typing import Any, Dict, Iterator, Optional, Sequence
import curl_cffi.requests as requests
# ---------------------------------------------------------------------------
# constants
# ---------------------------------------------------------------------------
BASE_URL = "https://chatgpt.com"
DEFAULT_POW_SCRIPT = f"{BASE_URL}/backend-api/sentinel/sdk.js"
CLIENT_VERSION = "prod-a194cd50d4416d3c0b47c740f206b12ce60f5887"
CLIENT_BUILD_NUMBER = "6708908"
USER_AGENT = (
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
"(KHTML, like Gecko) Chrome/143.0.0.0 Safari/537.36 Edg/143.0.0.0"
)
SEC_CH_UA = '"Microsoft Edge";v="143", "Chromium";v="143", "Not A(Brand";v="24"'
# ---------------------------------------------------------------------------
# helpers
# ---------------------------------------------------------------------------
def _new_uuid() -> str:
return str(uuid.uuid4())
# ---------------------------------------------------------------------------
# HTML bootstrap parser — extract script src list and data-build
# ---------------------------------------------------------------------------
class _ScriptSrcParser(HTMLParser):
def __init__(self) -> None:
super().__init__()
self.script_sources: list[str] = []
self.data_build = ""
def handle_starttag(self, tag: str, attrs: list[tuple[str, Optional[str]]]) -> None:
if tag != "script":
return
attrs_dict = dict(attrs)
src = attrs_dict.get("src")
if not src:
return
self.script_sources.append(src)
match = re.search(r"c/[^/]*/_", src)
if match:
self.data_build = match.group(0)
def _parse_pow_resources(html: str) -> tuple[list[str], str]:
parser = _ScriptSrcParser()
parser.feed(html)
sources = parser.script_sources or [DEFAULT_POW_SCRIPT]
data_build = parser.data_build
if not data_build:
m = re.search(r'<html[^>]*data-build="([^"]*)"', html)
if m:
data_build = m.group(1)
return sources, data_build
# ---------------------------------------------------------------------------
# proof-of-work
# ---------------------------------------------------------------------------
def _legacy_parse_time() -> str:
now = datetime.now(timezone(timedelta(hours=-5)))
return now.strftime("%a %b %d %Y %H:%M:%S") + " GMT-0500 (Eastern Standard Time)"
def _build_pow_config(
user_agent: str,
script_sources: Optional[Sequence[str]] = None,
data_build: str = "",
) -> list[Any]:
navigator_key = random.choice([
"registerProtocolHandler−function registerProtocolHandler() { [native code] }",
"storage−[object StorageManager]",
"locks−[object LockManager]",
"appCodeName−Mozilla",
"permissions−[object Permissions]",
"share−function share() { [native code] }",
"webdriver−false",
"managed−[object NavigatorManagedData]",
"canShare−function canShare() { [native code] }",
"vendor−Google Inc.",
"mediaDevices−[object MediaDevices]",
"vibrate−function vibrate() { [native code] }",
"storageBuckets−[object StorageBucketManager]",
"mediaCapabilities−[object MediaCapabilities]",
"cookieEnabled−true",
"virtualKeyboard−[object VirtualKeyboard]",
"product−Gecko",
"presentation−[object Presentation]",
"onLine−true",
"mimeTypes−[object MimeTypeArray]",
"credentials−[object CredentialsContainer]",
"serviceWorker−[object ServiceWorkerContainer]",
"keyboard−[object Keyboard]",
"gpu−[object GPU]",
"doNotTrack",
"serial−[object Serial]",
"pdfViewerEnabled−true",
"language−zh-CN",
"geolocation−[object Geolocation]",
"userAgentData−[object NavigatorUAData]",
"getUserMedia−function getUserMedia() { [native code] }",
"sendBeacon−function sendBeacon() { [native code] }",
"hardwareConcurrency−32",
"windowControlsOverlay−[object WindowControlsOverlay]",
])
window_key = random.choice([
"0", "window", "self", "document", "name", "location",
"customElements", "history", "navigation", "innerWidth", "innerHeight",
"scrollX", "scrollY", "visualViewport", "screenX", "screenY",
"outerWidth", "outerHeight", "devicePixelRatio", "screen", "chrome",
"navigator", "onresize", "performance", "crypto", "indexedDB",
"sessionStorage", "localStorage", "scheduler", "alert", "atob", "btoa",
"fetch", "matchMedia", "postMessage", "queueMicrotask",
"requestAnimationFrame", "setInterval", "setTimeout", "caches",
"__NEXT_DATA__", "__BUILD_MANIFEST", "__NEXT_PRELOADREADY",
])
document_keys = ["__reactContainer$fzelfjyxej8", "_reactListening5dehydibo78", "location"]
cores = [8, 16, 24, 32]
script_source = random.choice(list(script_sources)) if script_sources else None
screen = [[1920, 1080], [1440, 900], [2560, 1440], [3840, 2160]]
return [
sum(random.choices(screen, k=1)[0]),
_legacy_parse_time(),
4294705152,
1,
user_agent,
script_source,
data_build,
"en-US",
"en-US,es-US,en,es",
random.random(),
navigator_key,
random.choice(document_keys),
window_key,
time.perf_counter() * 1000,
_new_uuid(),
"",
random.choice(cores),
time.time() * 1000 - (time.perf_counter() * 1000),
0, 0, 0, 0, 0, 0,
0, # 0 = edge/chrome, 1 = firefox
]
def _pow_generate(seed: str, difficulty: str, config: list[Any], limit: int = 500000) -> tuple[str, bool]:
target = bytes.fromhex(difficulty)
diff_len = len(difficulty) // 2
seed_bytes = seed.encode()
static_1 = (json.dumps(config[:3], separators=(",", ":"), ensure_ascii=False)[:-1] + ",").encode()
static_2 = ("," + json.dumps(config[4:9], separators=(",", ":"), ensure_ascii=False)[1:-1] + ",").encode()
static_3 = ("," + json.dumps(config[10:], separators=(",", ":"), ensure_ascii=False)[1:]).encode()
for i in range(limit):
final_json = static_1 + str(i).encode() + static_2 + str(i >> 1).encode() + static_3
encoded = base64.b64encode(final_json)
digest = hashlib.sha3_512(seed_bytes + encoded).digest()
if digest[:diff_len] <= target:
return encoded.decode(), True
fallback = "wQ8Lk5FbGpA2NcR9dShT6gYjU7VxZ4D" + base64.b64encode(f'"{seed}"'.encode()).decode()
return fallback, False
def _build_legacy_requirements_token(
user_agent: str,
script_sources: Optional[Sequence[str]] = None,
data_build: str = "",
) -> str:
config = _build_pow_config(user_agent, script_sources=script_sources, data_build=data_build)
return "gAAAAAC" + base64.b64encode(
json.dumps(config, separators=(",", ":"), ensure_ascii=False).encode()
).decode()
def _build_proof_token(
seed: str,
difficulty: str,
user_agent: str,
script_sources: Optional[Sequence[str]] = None,
data_build: str = "",
) -> str:
config = _build_pow_config(user_agent, script_sources=script_sources, data_build=data_build)
answer, solved = _pow_generate(seed, difficulty, config)
if not solved:
raise RuntimeError(f"failed to solve proof token: difficulty={difficulty}")
return "gAAAAAB" + answer
# ---------------------------------------------------------------------------
# turnstile solver
# ---------------------------------------------------------------------------
class _OrderedMap:
def __init__(self) -> None:
self.keys: list[str] = []
self.values: Dict[str, Any] = {}
def add(self, key: str, value: Any) -> None:
if key not in self.values:
self.keys.append(key)
self.values[key] = value
def _turnstile_to_str(value: Any) -> str:
if value is None:
return "undefined"
if isinstance(value, float):
return str(value)
if isinstance(value, str):
special = {
"window.Math": "[object Math]",
"window.Reflect": "[object Reflect]",
"window.performance": "[object Performance]",
"window.localStorage": "[object Storage]",
"window.Object": "function Object() { [native code] }",
"window.Reflect.set": "function set() { [native code] }",
"window.performance.now": "function () { [native code] }",
"window.Object.create": "function create() { [native code] }",
"window.Object.keys": "function keys() { [native code] }",
"window.Math.random": "function random() { [native code] }",
}
return special.get(value, value)
if isinstance(value, list) and all(isinstance(item, str) for item in value):
return ",".join(value)
return str(value)
def _xor_string(text: str, key: str) -> str:
if not key:
return text
return "".join(chr(ord(ch) ^ ord(key[i % len(key)])) for i, ch in enumerate(text))
def _solve_turnstile_token(dx: str, p: str) -> Optional[str]:
try:
decoded = base64.b64decode(dx).decode()
token_list = json.loads(_xor_string(decoded, p))
except Exception:
return None
process_map: Dict[Any, Any] = {}
start_time = time.time()
result = ""
def func_1(e: float, t: float) -> None:
process_map[e] = _xor_string(_turnstile_to_str(process_map[e]), _turnstile_to_str(process_map[t]))
def func_2(e: float, t: Any) -> None:
process_map[e] = t
def func_3(e: str) -> None:
nonlocal result
result = base64.b64encode(e.encode()).decode()
def func_5(e: float, t: float) -> None:
current = process_map[e]
incoming = process_map[t]
if isinstance(current, (list, tuple)):
process_map[e] = list(current) + [incoming]
return
if isinstance(current, (str, float)) or isinstance(incoming, (str, float)):
process_map[e] = _turnstile_to_str(current) + _turnstile_to_str(incoming)
return
process_map[e] = "NaN"
def func_6(e: float, t: float, n: float) -> None:
tv = process_map[t]
nv = process_map[n]
if isinstance(tv, str) and isinstance(nv, str):
value = f"{tv}.{nv}"
process_map[e] = "https://chatgpt.com/" if value == "window.document.location" else value
def func_7(e: float, *args: float) -> None:
target = process_map[e]
values = [process_map[arg] for arg in args]
if isinstance(target, str) and target == "window.Reflect.set":
obj, key_name, val = values
obj.add(str(key_name), val)
elif callable(target):
target(*values)
def func_8(e: float, t: float) -> None:
process_map[e] = process_map[t]
def func_14(e: float, t: float) -> None:
process_map[e] = json.loads(process_map[t])
def func_15(e: float, t: float) -> None:
process_map[e] = json.dumps(process_map[t])
def func_17(e: float, t: float, *args: float) -> None:
call_args = [process_map[arg] for arg in args]
target = process_map[t]
if target == "window.performance.now":
elapsed_ns = time.time_ns() - int(start_time * 1e9)
process_map[e] = (elapsed_ns + random.random()) / 1e6
elif target == "window.Object.create":
process_map[e] = _OrderedMap()
elif target == "window.Object.keys":
if call_args and call_args[0] == "window.localStorage":
process_map[e] = [
"STATSIG_LOCAL_STORAGE_INTERNAL_STORE_V4",
"STATSIG_LOCAL_STORAGE_STABLE_ID",
"client-correlated-secret",
"oai/apps/capExpiresAt",
"oai-did",
"STATSIG_LOCAL_STORAGE_LOGGING_REQUEST",
"UiState.isNavigationCollapsed.1",
]
elif target == "window.Math.random":
process_map[e] = random.random()
elif callable(target):
process_map[e] = target(*call_args)
def func_18(e: float) -> None:
process_map[e] = base64.b64decode(_turnstile_to_str(process_map[e])).decode()
def func_19(e: float) -> None:
process_map[e] = base64.b64encode(_turnstile_to_str(process_map[e]).encode()).decode()
def func_20(e: float, t: float, n: float, *args: float) -> None:
if process_map[e] == process_map[t]:
target = process_map[n]
if callable(target):
target(*[process_map[arg] for arg in args])
def func_21(*_: Any) -> None:
return
def func_23(e: float, t: float, *args: float) -> None:
if process_map[e] is not None and callable(process_map[t]):
process_map[t](*args)
def func_24(e: float, t: float, n: float) -> None:
tv = process_map[t]
nv = process_map[n]
if isinstance(tv, str) and isinstance(nv, str):
process_map[e] = f"{tv}.{nv}"
process_map.update({
1: func_1, 2: func_2, 3: func_3, 5: func_5, 6: func_6,
7: func_7, 8: func_8, 9: token_list, 10: "window",
14: func_14, 15: func_15, 16: p, 17: func_17,
18: func_18, 19: func_19, 20: func_20, 21: func_21,
23: func_23, 24: func_24,
})
for token in token_list:
try:
fn = process_map.get(token[0])
if callable(fn):
fn(*token[1:])
except Exception:
continue
return result or None
# ---------------------------------------------------------------------------
# result dataclass
# ---------------------------------------------------------------------------
@dataclass
class SentinelTokenResult:
token: str
proof_token: str = ""
turnstile_token: str = ""
so_token: str = ""
raw: Dict[str, Any] = field(default_factory=dict)
def as_headers(self) -> Dict[str, str]:
h = {"OpenAI-Sentinel-Chat-Requirements-Token": self.token}
if self.proof_token:
h["OpenAI-Sentinel-Proof-Token"] = self.proof_token
if self.turnstile_token:
h["OpenAI-Sentinel-Turnstile-Token"] = self.turnstile_token
if self.so_token:
h["OpenAI-Sentinel-SO-Token"] = self.so_token
return h
# ---------------------------------------------------------------------------
# session + bootstrap
# ---------------------------------------------------------------------------
def _build_session(access_token: str = "") -> requests.Session:
session = requests.Session(impersonate="firefox133")
session.headers.update({
"User-Agent": USER_AGENT,
"Origin": BASE_URL,
"Referer": BASE_URL + "/",
"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8,en-US;q=0.7",
"Cache-Control": "no-cache",
"Pragma": "no-cache",
"Priority": "u=1, i",
"Sec-Ch-Ua": SEC_CH_UA,
"Sec-Ch-Ua-Arch": '"x86"',
"Sec-Ch-Ua-Bitness": '"64"',
"Sec-Ch-Ua-Full-Version": '"143.0.3650.96"',
"Sec-Ch-Ua-Full-Version-List": (
'"Microsoft Edge";v="143.0.3650.96", '
'"Chromium";v="143.0.7499.147", '
'"Not A(Brand";v="24.0.0.0"'
),
"Sec-Ch-Ua-Mobile": "?0",
"Sec-Ch-Ua-Model": '""',
"Sec-Ch-Ua-Platform": '"Windows"',
"Sec-Ch-Ua-Platform-Version": '"19.0.0"',
"Sec-Fetch-Dest": "empty",
"Sec-Fetch-Mode": "cors",
"Sec-Fetch-Site": "same-origin",
"OAI-Device-Id": _new_uuid(),
"OAI-Session-Id": _new_uuid(),
"OAI-Language": "zh-CN",
"OAI-Client-Version": CLIENT_VERSION,
"OAI-Client-Build-Number": CLIENT_BUILD_NUMBER,
})
if access_token:
session.headers["Authorization"] = f"Bearer {access_token}"
return session
def _bootstrap(session: requests.Session) -> tuple[list[str], str]:
resp = session.get(
BASE_URL + "/",
headers={
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8",
"Sec-Fetch-Dest": "document",
"Sec-Fetch-Mode": "navigate",
"Sec-Fetch-Site": "none",
"Sec-Fetch-User": "?1",
"Upgrade-Insecure-Requests": "1",
},
timeout=30,
)
resp.raise_for_status()
sources, data_build = _parse_pow_resources(resp.text)
return sources or [DEFAULT_POW_SCRIPT], data_build
def _fetch_sentinel(
session: requests.Session,
script_sources: list[str],
data_build: str,
access_token: str = "",
) -> SentinelTokenResult:
p_token = _build_legacy_requirements_token(USER_AGENT, script_sources, data_build)
path = "/backend-api/sentinel/chat-requirements/prepare"
resp = session.post(
BASE_URL + path,
headers={"Content-Type": "application/json", "X-OpenAI-Target-Path": path, "X-OpenAI-Target-Route": path},
json={"p": p_token},
timeout=30,
)
resp.raise_for_status()
data = resp.json()
prepare_token = data.get("prepare_token", "")
if (data.get("arkose") or {}).get("required"):
raise RuntimeError("sentinel endpoint requires arkose token (not implemented)")
proof_token = ""
proof_info = data.get("proofofwork") or {}
if proof_info.get("required"):
proof_token = _build_proof_token(
proof_info.get("seed", ""),
proof_info.get("difficulty", ""),
USER_AGENT,
script_sources=script_sources,
data_build=data_build,
)
turnstile_token = ""
turnstile_info = data.get("turnstile") or {}
if turnstile_info.get("required") and turnstile_info.get("dx"):
turnstile_token = _solve_turnstile_token(turnstile_info["dx"], p_token) or ""
path = "/backend-api/sentinel/chat-requirements/finalize"
resp = session.post(
BASE_URL + path,
headers={"Content-Type": "application/json", "X-OpenAI-Target-Path": path, "X-OpenAI-Target-Route": path},
json={"prepare_token": prepare_token, "proof_token": proof_token, "turnstile_token": turnstile_token},
timeout=30,
)
resp.raise_for_status()
data = resp.json()
token = data.get("token", "")
if not token:
raise RuntimeError(f"missing sentinel token in response: {data}")
return SentinelTokenResult(
token=token,
proof_token=proof_token,
turnstile_token=turnstile_token,
so_token=data.get("so_token", ""),
raw=data,
)
def get_sentinel_token(access_token: str = "") -> SentinelTokenResult:
"""Convenience: bootstrap + fetch sentinel token. Returns SentinelTokenResult."""
session = _build_session(access_token)
sources, data_build = _bootstrap(session)
return _fetch_sentinel(session, sources, data_build, access_token)
# ---------------------------------------------------------------------------
# conversation
# ---------------------------------------------------------------------------
def _build_message(text: str, role: str = "user") -> Dict[str, Any]:
return {
"id": _new_uuid(),
"author": {"role": role},
"create_time": time.time(),
"content": {"content_type": "text", "parts": [text]},
"metadata": {
"developer_mode_connector_ids": [],
"selected_sources": [],
"selected_github_repos": [],
"selected_all_github_repos": False,
"serialization_metadata": {"custom_symbol_offsets": []},
},
}
def _iter_sse(response: Any) -> Iterator[str]:
for raw_line in response.iter_lines():
if not raw_line:
continue
line = raw_line.decode("utf-8", errors="ignore") if isinstance(raw_line, bytes) else str(raw_line)
if not line.startswith("data:"):
continue
payload = line[5:].strip()
if payload:
yield payload
def _extract_text(event: Dict[str, Any], current: str) -> str:
"""Extract assistant text from a raw SSE event, accumulating into `current`."""
# Full message snapshot (most events carry the whole text in message.content.parts)
for candidate in (event, event.get("v")):
if not isinstance(candidate, dict):
continue
msg = candidate.get("message")
if not isinstance(msg, dict):
continue
if (msg.get("author") or {}).get("role") != "assistant":
continue
parts = (msg.get("content") or {}).get("parts") or []
text = "".join(p for p in parts if isinstance(p, str))
if text:
return text
# JSON-patch style incremental updates
if event.get("p") == "/message/content/parts/0":
op, v = event.get("o"), str(event.get("v") or "")
if op == "append":
return current + v
if op == "replace":
return v
if event.get("o") == "patch" and isinstance(event.get("v"), list):
text = current
for item in event["v"]:
if isinstance(item, dict):
text = _extract_text(item, text)
return text
# Plain string delta appended directly
v = event.get("v")
if isinstance(v, str) and not event.get("p") and not event.get("o") and current:
return current + v
return current
def _prepare_conversation(
session: requests.Session,
first_user_text: str,
model: str,
conversation_id: str = "",
access_token: str = "",
) -> str:
"""POST /backend-api/f/conversation/prepare → conduit_token."""
path = "/backend-api/f/conversation/prepare"
tz = "Asia/Shanghai" if access_token else "America/Los_Angeles"
tz_offset = -480 if access_token else 420
body: Dict[str, Any] = {
"action": "next",
"fork_from_shared_post": False,
"parent_message_id": "client-created-root",
"model": model,
"client_prepare_state": "none",
"timezone_offset_min": tz_offset,
"timezone": tz,
"conversation_mode": {"kind": "primary_assistant"},
"system_hints": [],
"partial_query": {
"id": _new_uuid(),
"author": {"role": "user"},
"content": {"content_type": "text", "parts": [first_user_text]},
},
"supports_buffering": True,
"supported_encodings": ["v1"],
"client_contextual_info": {"app_name": "chatgpt.com"},
}
if conversation_id:
body["conversation_id"] = conversation_id
resp = session.post(
BASE_URL + path,
headers={
"Content-Type": "application/json",
"Accept": "*/*",
"X-Conduit-Token": "no-token",
"X-OpenAI-Target-Path": path,
"X-OpenAI-Target-Route": path,
},
json=body,
timeout=60,
)
resp.raise_for_status()
conduit_token = str(resp.json().get("conduit_token") or "")
if not conduit_token:
raise RuntimeError(f"missing conduit_token: {resp.text}")
return conduit_token
def _stream_conversation(
session: requests.Session,
sentinel: SentinelTokenResult,
conduit_token: str,
messages: list[Dict[str, Any]],
model: str,
conversation_id: str = "",
access_token: str = "",
) -> Iterator[tuple[str, str]]:
"""Yield (text_delta, conversation_id) until the stream ends."""
path = "/backend-api/f/conversation"
tz = "Asia/Shanghai" if access_token else "America/Los_Angeles"
tz_offset = -480 if access_token else 420
payload: Dict[str, Any] = {
"action": "next",
"messages": messages,
"parent_message_id": "client-created-root",
"model": model,
"client_prepare_state": "success",
"timezone_offset_min": tz_offset,
"timezone": tz,
"conversation_mode": {"kind": "primary_assistant"},
"enable_message_followups": True,
"system_hints": [],
"supports_buffering": True,
"supported_encodings": ["v1"],
"client_contextual_info": {
"is_dark_mode": False,
"time_since_loaded": 120,
"page_height": 900,
"page_width": 1400,
"pixel_ratio": 2,
"screen_height": 1440,
"screen_width": 2560,
"app_name": "chatgpt.com",
},
"paragen_cot_summary_display_override": "allow",
"force_parallel_switch": "auto",
}
if conversation_id:
payload["conversation_id"] = conversation_id
headers = {
"Accept": "text/event-stream",
"Content-Type": "application/json",
"X-Conduit-Token": conduit_token,
"X-OpenAI-Target-Path": path,
"X-OpenAI-Target-Route": path,
**sentinel.as_headers(),
}
resp = session.post(BASE_URL + path, headers=headers, json=payload, timeout=300, stream=True)
resp.raise_for_status()
current_text = ""
active_cid = conversation_id
try:
for payload_str in _iter_sse(resp):
if payload_str == "[DONE]":
break
try:
event = json.loads(payload_str)
except Exception:
continue
if not isinstance(event, dict):
continue
if event.get("type") in ("stream_handoff", "resume_conversation_token"):
continue
cid = event.get("conversation_id") or ""
if cid:
active_cid = cid
new_text = _extract_text(event, current_text)
if new_text != current_text:
yield new_text[len(current_text):], active_cid
current_text = new_text
finally:
resp.close()
# ---------------------------------------------------------------------------
# interactive chat
# ---------------------------------------------------------------------------
def chat(access_token: str = "", model: str = "auto") -> None:
mode = "authenticated" if access_token else "anonymous"
print(f"[ChatGPT CLI] model={model} mode={mode}")
print("Type a message and press Enter. Empty line or Ctrl-C to quit.\n")
session = _build_session(access_token)
print("Bootstrapping...", end=" ", flush=True)
sources, data_build = _bootstrap(session)
print("ok")
conversation_id = ""
history: list[Dict[str, Any]] = []
while True:
try:
user_input = input("You: ").strip()
except (EOFError, KeyboardInterrupt):
print()
break
if not user_input:
break
history.append(_build_message(user_input))
# Fresh sentinel token every turn (they are short-lived)
try:
sentinel = _fetch_sentinel(session, sources, data_build, access_token)
except Exception as e:
print(f"[sentinel error] {e}")
break
try:
conduit_token = _prepare_conversation(
session, user_input, model, conversation_id, access_token
)
except Exception as e:
print(f"[prepare error] {e}")
break
print("Assistant: ", end="", flush=True)
assistant_text = ""
try:
for delta, cid in _stream_conversation(
session, sentinel, conduit_token, history, model, conversation_id, access_token
):
print(delta, end="", flush=True)
assistant_text += delta
if cid:
conversation_id = cid
except Exception as e:
print(f"\n[stream error] {e}")
finally:
print()
if assistant_text:
history.append(_build_message(assistant_text, "assistant"))
# ---------------------------------------------------------------------------
# CLI
# ---------------------------------------------------------------------------
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="ChatGPT CLI powered by sentinel token generation")
parser.add_argument("--access-token", default="", help="Bearer access token (omit for anonymous)")
parser.add_argument("--model", default="auto", help="Model slug, e.g. gpt-4o, auto (default: auto)")
parser.add_argument(
"--token-only",
action="store_true",
help="Just print the sentinel token and exit (no interactive chat)",
)
args = parser.parse_args()
if args.token_only:
result = get_sentinel_token(access_token=args.access_token)
print("=== SentinelTokenResult ===")
print(f"token : {result.token}")
print(f"proof_token : {result.proof_token or '(not required)'}")
print(f"turnstile_token: {result.turnstile_token or '(not required)'}")
print(f"so_token : {result.so_token or '(not present)'}")
print()
print("=== Headers ===")
for k, v in result.as_headers().items():
print(f"{k}: {v}")
else:
chat(access_token=args.access_token, model=args.model)
|
猜测可能是为了省ws的连接数，选择了一个页面只开一个ws链接，所有的请求响应都走的同一个ws进行返回。当然ai响应的文本除了这种获取方式，还有一个接口为：
通过这个接口我们也可以发现，OpenAI其实把每部分都分的很开，而不是一个整体。
原始脚本如下：
让ai分析了一下：
