fix: resolve Codex provider bugs and simplify implementation

This commit is contained in:
Re-bin 2026-02-16 11:43:36 +00:00
parent 9e5f7348fe
commit 1ce586e9f5
5 changed files with 65 additions and 52 deletions

View File

@ -585,6 +585,37 @@ Config file: `~/.nanobot/config.json`
| `moonshot` | LLM (Moonshot/Kimi) | [platform.moonshot.cn](https://platform.moonshot.cn) |
| `zhipu` | LLM (Zhipu GLM) | [open.bigmodel.cn](https://open.bigmodel.cn) |
| `vllm` | LLM (local, any OpenAI-compatible server) | — |
| `openai_codex` | LLM (Codex, OAuth) | `nanobot provider login openai-codex` |
<details>
<summary><b>OpenAI Codex (OAuth)</b></summary>
Codex uses OAuth instead of API keys. Requires a ChatGPT Plus or Pro account.
**1. Login:**
```bash
nanobot provider login openai-codex
```
**2. Set model** (merge into `~/.nanobot/config.json`):
```json
{
"agents": {
"defaults": {
"model": "openai-codex/gpt-5.1-codex"
}
}
}
```
**3. Chat:**
```bash
nanobot agent -m "Hello!"
```
> Docker users: use `docker run -it` for interactive OAuth login.
</details>
<details>
<summary><b>Custom Provider (Any OpenAI-compatible API)</b></summary>

View File

@ -290,10 +290,7 @@ def _make_provider(config: Config):
# OpenAI Codex (OAuth): don't route via LiteLLM; use the dedicated implementation.
if provider_name == "openai_codex" or model.startswith("openai-codex/"):
return OpenAICodexProvider(
default_model=model,
api_base=p.api_base if p else None,
)
return OpenAICodexProvider(default_model=model)
if not model.startswith("bedrock/") and not (p and p.api_key):
console.print("[red]Error: No API key configured.[/red]")

View File

@ -192,7 +192,7 @@ class ProvidersConfig(BaseModel):
moonshot: ProviderConfig = Field(default_factory=ProviderConfig)
minimax: ProviderConfig = Field(default_factory=ProviderConfig)
aihubmix: ProviderConfig = Field(default_factory=ProviderConfig) # AiHubMix API gateway
openai_codex: ProviderConfig = Field(default_factory=ProviderConfig) # OpenAI Codex (OAuth) # AiHubMix API gateway
openai_codex: ProviderConfig = Field(default_factory=ProviderConfig) # OpenAI Codex (OAuth)
class GatewayConfig(BaseModel):
@ -252,19 +252,19 @@ class Config(BaseSettings):
model_lower = (model or self.agents.defaults.model).lower()
# Match by keyword (order follows PROVIDERS registry)
# Note: OAuth providers don't require api_key, so we check is_oauth flag
for spec in PROVIDERS:
p = getattr(self.providers, spec.name, None)
if p and any(kw in model_lower for kw in spec.keywords):
# OAuth providers don't need api_key
if spec.is_oauth or p.api_key:
return p, spec.name
# Fallback: gateways first, then others (follows registry order)
# OAuth providers are also valid fallbacks
# OAuth providers are NOT valid fallbacks — they require explicit model selection
for spec in PROVIDERS:
if spec.is_oauth:
continue
p = getattr(self.providers, spec.name, None)
if p and (spec.is_oauth or p.api_key):
if p and p.api_key:
return p, spec.name
return None, None

View File

@ -8,6 +8,7 @@ import json
from typing import Any, AsyncGenerator
import httpx
from loguru import logger
from oauth_cli_kit import get_token as get_codex_token
from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
@ -59,9 +60,9 @@ class OpenAICodexProvider(LLMProvider):
try:
content, tool_calls, finish_reason = await _request_codex(url, headers, body, verify=True)
except Exception as e:
# Certificate verification failed, downgrade to disable verification (security risk)
if "CERTIFICATE_VERIFY_FAILED" not in str(e):
raise
logger.warning("SSL certificate verification failed for Codex API; retrying with verify=False")
content, tool_calls, finish_reason = await _request_codex(url, headers, body, verify=False)
return LLMResponse(
content=content,
@ -77,6 +78,7 @@ class OpenAICodexProvider(LLMProvider):
def get_default_model(self) -> str:
return self.default_model
def _strip_model_prefix(model: str) -> str:
if model.startswith("openai-codex/"):
return model.split("/", 1)[1]
@ -94,6 +96,7 @@ def _build_headers(account_id: str, token: str) -> dict[str, str]:
"content-type": "application/json",
}
async def _request_codex(
url: str,
headers: dict[str, str],
@ -107,36 +110,25 @@ async def _request_codex(
raise RuntimeError(_friendly_error(response.status_code, text.decode("utf-8", "ignore")))
return await _consume_sse(response)
def _convert_tools(tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
# Nanobot tool definitions already use the OpenAI function schema.
"""Convert OpenAI function-calling schema to Codex flat format."""
converted: list[dict[str, Any]] = []
for tool in tools:
fn = tool.get("function") if isinstance(tool, dict) and tool.get("type") == "function" else None
if fn and isinstance(fn, dict):
name = fn.get("name")
desc = fn.get("description")
params = fn.get("parameters")
else:
name = tool.get("name")
desc = tool.get("description")
params = tool.get("parameters")
if not isinstance(name, str) or not name:
# Skip invalid tools to avoid Codex rejection.
fn = (tool.get("function") or {}) if tool.get("type") == "function" else tool
name = fn.get("name")
if not name:
continue
params = params or {}
if not isinstance(params, dict):
# Parameters must be a JSON Schema object.
params = {}
converted.append(
{
"type": "function",
"name": name,
"description": desc or "",
"parameters": params,
}
)
params = fn.get("parameters") or {}
converted.append({
"type": "function",
"name": name,
"description": fn.get("description") or "",
"parameters": params if isinstance(params, dict) else {},
})
return converted
def _convert_messages(messages: list[dict[str, Any]]) -> tuple[str, list[dict[str, Any]]]:
system_prompt = ""
input_items: list[dict[str, Any]] = []
@ -183,7 +175,7 @@ def _convert_messages(messages: list[dict[str, Any]]) -> tuple[str, list[dict[st
continue
if role == "tool":
call_id = _extract_call_id(msg.get("tool_call_id"))
call_id, _ = _split_tool_call_id(msg.get("tool_call_id"))
output_text = content if isinstance(content, str) else json.dumps(content)
input_items.append(
{
@ -196,6 +188,7 @@ def _convert_messages(messages: list[dict[str, Any]]) -> tuple[str, list[dict[st
return system_prompt, input_items
def _convert_user_message(content: Any) -> dict[str, Any]:
if isinstance(content, str):
return {"role": "user", "content": [{"type": "input_text", "text": content}]}
@ -215,12 +208,6 @@ def _convert_user_message(content: Any) -> dict[str, Any]:
return {"role": "user", "content": [{"type": "input_text", "text": ""}]}
def _extract_call_id(tool_call_id: Any) -> str:
if isinstance(tool_call_id, str) and tool_call_id:
return tool_call_id.split("|", 1)[0]
return "call_0"
def _split_tool_call_id(tool_call_id: Any) -> tuple[str, str | None]:
if isinstance(tool_call_id, str) and tool_call_id:
if "|" in tool_call_id:
@ -229,10 +216,12 @@ def _split_tool_call_id(tool_call_id: Any) -> tuple[str, str | None]:
return tool_call_id, None
return "call_0", None
def _prompt_cache_key(messages: list[dict[str, Any]]) -> str:
raw = json.dumps(messages, ensure_ascii=True, sort_keys=True)
return hashlib.sha256(raw.encode("utf-8")).hexdigest()
async def _iter_sse(response: httpx.Response) -> AsyncGenerator[dict[str, Any], None]:
buffer: list[str] = []
async for line in response.aiter_lines():
@ -252,6 +241,7 @@ async def _iter_sse(response: httpx.Response) -> AsyncGenerator[dict[str, Any],
continue
buffer.append(line)
async def _consume_sse(response: httpx.Response) -> tuple[str, list[ToolCallRequest], str]:
content = ""
tool_calls: list[ToolCallRequest] = []
@ -308,16 +298,13 @@ async def _consume_sse(response: httpx.Response) -> tuple[str, list[ToolCallRequ
return content, tool_calls, finish_reason
_FINISH_REASON_MAP = {"completed": "stop", "incomplete": "length", "failed": "error", "cancelled": "error"}
def _map_finish_reason(status: str | None) -> str:
if not status:
return "stop"
if status == "completed":
return "stop"
if status == "incomplete":
return "length"
if status in {"failed", "cancelled"}:
return "error"
return "stop"
return _FINISH_REASON_MAP.get(status or "completed", "stop")
def _friendly_error(status_code: int, raw: str) -> str:
if status_code == 429:

View File

@ -53,7 +53,6 @@ class ProviderSpec:
# OAuth-based providers (e.g., OpenAI Codex) don't use API keys
is_oauth: bool = False # if True, uses OAuth flow instead of API key
oauth_provider: str = "" # OAuth provider name for token retrieval
@property
def label(self) -> str:
@ -176,7 +175,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
strip_model_prefix=False,
model_overrides=(),
is_oauth=True, # OAuth-based authentication
oauth_provider="openai-codex", # OAuth provider identifier
),
# DeepSeek: needs "deepseek/" prefix for LiteLLM routing.