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feat: implement Z.AI endpoint detection for API key validation

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Added functionality to detect the appropriate Z.AI endpoint based on the provided API key, accommodating different billing plans and regions. The setup process now probes available endpoints and updates the configuration accordingly, enhancing user experience and reducing potential billing errors. Updated the setup model provider function to integrate this new detection logic.
This commit is contained in:
teknium1 2026-03-07 09:43:37 -08:00
parent fb0f579b16
commit 48e0dc8791
2 changed files with 85 additions and 5 deletions
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53
hermes_cli/auth.py
View file

@ -138,6 +138,59 @@ PROVIDER_REGISTRY: Dict[str, ProviderConfig] = {
}
# =============================================================================
# Z.AI Endpoint Detection
# =============================================================================
# Z.AI has separate billing for general vs coding plans, and global vs China
# endpoints. A key that works on one may return "Insufficient balance" on
# another. We probe at setup time and store the working endpoint.
ZAI_ENDPOINTS = [
# (id, base_url, default_model, label)
("global", "https://api.z.ai/api/paas/v4", "glm-5", "Global"),
("cn", "https://open.bigmodel.cn/api/paas/v4", "glm-5", "China"),
("coding-global", "https://api.z.ai/api/coding/paas/v4", "glm-4.7", "Global (Coding Plan)"),
("coding-cn", "https://open.bigmodel.cn/api/coding/paas/v4", "glm-4.7", "China (Coding Plan)"),
]
def detect_zai_endpoint(api_key: str, timeout: float = 8.0) -> Optional[Dict[str, str]]:
"""Probe z.ai endpoints to find one that accepts this API key.
Returns {"id": ..., "base_url": ..., "model": ..., "label": ...} for the
first working endpoint, or None if all fail.
"""
for ep_id, base_url, model, label in ZAI_ENDPOINTS:
try:
resp = httpx.post(
f"{base_url}/chat/completions",
headers={
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
},
json={
"model": model,
"stream": False,
"max_tokens": 1,
"messages": [{"role": "user", "content": "ping"}],
},
timeout=timeout,
)
if resp.status_code == 200:
logger.debug("Z.AI endpoint probe: %s (%s) OK", ep_id, base_url)
return {
"id": ep_id,
"base_url": base_url,
"model": model,
"label": label,
}
logger.debug("Z.AI endpoint probe: %s returned %s", ep_id, resp.status_code)
except Exception as exc:
logger.debug("Z.AI endpoint probe: %s failed: %s", ep_id, exc)
return None
# =============================================================================
# Error Types
# =============================================================================

37
hermes_cli/setup.py
View file

@ -667,16 +667,17 @@ def setup_model_provider(config: dict):
print_header("Z.AI / GLM API Key")
pconfig = PROVIDER_REGISTRY["zai"]
print_info(f"Provider: {pconfig.name}")
print_info(f"Base URL: {pconfig.inference_base_url}")
print_info("Get your API key at: https://open.bigmodel.cn/")
print()
existing_key = get_env_value("GLM_API_KEY") or get_env_value("ZAI_API_KEY")
api_key = existing_key # will be overwritten if user enters a new one
if existing_key:
print_info(f"Current: {existing_key[:8]}... (configured)")
if prompt_yes_no("Update API key?", False):
api_key = prompt(" GLM API key", password=True)
if api_key:
new_key = prompt(" GLM API key", password=True)
if new_key:
api_key = new_key
save_env_value("GLM_API_KEY", api_key)
print_success("GLM API key updated")
else:
@ -687,11 +688,32 @@ def setup_model_provider(config: dict):
else:
print_warning("Skipped - agent won't work without an API key")
# Detect the correct z.ai endpoint for this key.
# Z.AI has separate billing for general vs coding plans and
# global vs China endpoints — we probe to find the right one.
zai_base_url = pconfig.inference_base_url
if api_key:
print()
print_info("Detecting your z.ai endpoint...")
from hermes_cli.auth import detect_zai_endpoint
detected = detect_zai_endpoint(api_key)
if detected:
zai_base_url = detected["base_url"]
print_success(f"Detected: {detected['label']} endpoint")
print_info(f" URL: {detected['base_url']}")
if detected["id"].startswith("coding"):
print_info(f" Note: Coding Plan detected — GLM-5 is not available, using {detected['model']}")
save_env_value("GLM_BASE_URL", zai_base_url)
else:
print_warning("Could not verify any z.ai endpoint with this key.")
print_info(f" Using default: {zai_base_url}")
print_info(" If you get billing errors, check your plan at https://open.bigmodel.cn/")
# Clear custom endpoint vars if switching
if existing_custom:
save_env_value("OPENAI_BASE_URL", "")
save_env_value("OPENAI_API_KEY", "")
_update_config_for_provider("zai", pconfig.inference_base_url)
_update_config_for_provider("zai", zai_base_url)
elif provider_idx == 5: # Kimi / Moonshot
selected_provider = "kimi-coding"
@ -859,7 +881,12 @@ def setup_model_provider(config: dict):
save_env_value("LLM_MODEL", custom)
_update_config_for_provider("openai-codex", DEFAULT_CODEX_BASE_URL)
elif selected_provider == "zai":
zai_models = ["glm-5", "glm-4.7", "glm-4.5", "glm-4.5-flash"]
# Coding Plan endpoints don't have GLM-5
is_coding_plan = get_env_value("GLM_BASE_URL") and "coding" in (get_env_value("GLM_BASE_URL") or "")
if is_coding_plan:
zai_models = ["glm-4.7", "glm-4.5", "glm-4.5-flash"]
else:
zai_models = ["glm-5", "glm-4.7", "glm-4.5", "glm-4.5-flash"]
model_choices = list(zai_models)
model_choices.append("Custom model")
model_choices.append(f"Keep current ({current_model})")