Codex
Assistente de codificação de IA de terminal da OpenAI
Conecte o Codex ao QwenCloud via Token Plan (Personal Edition), Token Plan (Team Edition) ou faturamento pré-pago.
Instale o Codex
-
Instale ou atualize Node.js (v18.0 ou posterior).
-
Execute o seguinte comando em um terminal para instalar o Codex.
npm install -g @openai/codex
Execute o seguinte comando para verificar a instalação.
codex --version
Configurar credenciais de acesso
Para conectar, edite o arquivo de configuração ~/.codex/config.toml e configure a variável de ambiente OPENAI_API_KEY. Substitua os valores correspondentes com base no plano de faturamento selecionado.
Plano de token (edição pessoal)
Para model, selecione um modelo compatível. Defina o OPENAI_API_KEY variável de ambiente para o Token Plan (Personal Edition) dedicado API Key.
Etapa 1: configurar variáveis de ambiente
Defina o OPENAI_API_KEY variável de ambiente para a chave de API dedicada do Token Plan (Personal Edition).
macOS
1. Execute o seguinte comando em um terminal para verificar o tipo de shell padrão.
```bash
echo $SHELL
```
2. Defina a variável de ambiente com base no seu tipo de shell:
Zsh
```bash
# Replace YOUR_API_KEY with the Token Plan (Personal Edition) API Key
echo 'export OPENAI_API_KEY="YOUR_API_KEY"' >> ~/.zshrc
```
Bash
```bash
# Replace YOUR_API_KEY with the Token Plan (Personal Edition) API Key
echo 'export OPENAI_API_KEY="YOUR_API_KEY"' >> ~/.bash_profile
```
3. Execute o seguinte comando para aplicar a variável de ambiente.
Zsh
```bash
source ~/.zshrc
```
Bash
```bash
source ~/.bash_profile
```
Windows
CMD
1. Execute o seguinte comando no CMD para definir a variável de ambiente.
```powershell
REM Replace YOUR_API_KEY with the Token Plan (Personal Edition) API Key
setx OPENAI_API_KEY "YOUR_API_KEY"
```
2. Abra uma nova janela CMD e execute o seguinte comando para verificar se a variável de ambiente está definida.
```powershell
echo %OPENAI_API_KEY%
```
PowerShell
1. Execute o seguinte comando no PowerShell para definir a variável de ambiente.
```powershell
# Replace YOUR_API_KEY with the Token Plan (Personal Edition) API Key
[Environment]::SetEnvironmentVariable("OPENAI_API_KEY", "YOUR_API_KEY", [EnvironmentVariableTarget]::User)
```
2. Abra uma nova janela do PowerShell e execute o seguinte comando para verificar se a variável de ambiente está definida.
```powershell
echo $env:OPENAI_API_KEY
```
Passo 2: Escolha um método de acesso
Escolha um método de acesso com base na API compatível com o modelo:
API de respostas
Se o modelo selecionado for compatível com a API OpenAI Responses, você pode usar a versão mais recente do Codex.
model_provider = "Model_Studio_Token_Plan_Personal"
model = "auto"
[model_providers.Model_Studio_Token_Plan_Personal]
name = "Model_Studio_Token_Plan_Personal"
base_url = "https://token-plan.maas.qwencloudapi.com/compatible-mode/v1"
env_key = "OPENAI_API_KEY"
wire_api = "responses"
Em seguida, configure os metadados do modelo para poder alternar entre modelos. Criar ~/.codex/model-catalog.local.json com os modelos suportados por este plano:
{
"models": [
{
"slug": "auto",
"display_name": "auto",
"description": "DashScope model: auto",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 1,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.8-max",
"display_name": "qwen3.8-max",
"description": "DashScope model: qwen3.8-max",
"default_reasoning_level": "xhigh",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 983616,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 1,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.8-flash",
"display_name": "qwen3.8-flash",
"description": "DashScope model: qwen3.8-flash",
"default_reasoning_level": "xhigh",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 983616,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 2,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.7-max",
"display_name": "qwen3.7-max",
"description": "DashScope model: qwen3.7-max",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 3,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.7-plus",
"display_name": "qwen3.7-plus",
"description": "DashScope model: qwen3.7-plus",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 4,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.6-flash",
"display_name": "qwen3.6-flash",
"description": "DashScope model: qwen3.6-flash",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 5,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "glm-5.3",
"display_name": "glm-5.3",
"description": "DashScope model: glm-5.3",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": [
"text"
],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 6,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "glm-5.2",
"display_name": "glm-5.2",
"description": "DashScope model: glm-5.2",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 7,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "deepseek-v4.1-flash",
"display_name": "deepseek-v4.1-flash",
"description": "DashScope model: deepseek-v4.1-flash",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 8,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "deepseek-v4-pro",
"display_name": "deepseek-v4-pro",
"description": "DashScope model: deepseek-v4-pro",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 163840,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 9,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "deepseek-v4-pro-0813",
"display_name": "deepseek-v4-pro-0813",
"description": "DashScope model: deepseek-v4-pro-0813",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 163840,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 10,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "deepseek-v4-flash-0731",
"display_name": "deepseek-v4-flash-0731",
"description": "DashScope model: deepseek-v4-flash-0731",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 11,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
}
]
}
Adicione o seguinte a ~/.codex/config.toml para apontar para o arquivo:
model_catalog_json = "~/.codex/model-catalog.local.json"
Após a configuração, alterne entre os modelos com codex -m (por exemplo, codex -m qwen3.8-flash) ou digite /model na TUI.
API de bate-papo/conclusões (outros modelos)
Outros modelos exigem a API Chat/Completions. Instale uma versão mais antiga do Codex, como 0.80.0 (as versões mais recentes do Codex não suportam mais wire_api = "chat"; se você receber um erro após a atualização, consulte as perguntas frequentes abaixo):
npm install -g @openai/codex@0.80.0
model_provider = "Model_Studio_Token_Plan_Personal"
model = "glm-5"
[model_providers.Model_Studio_Token_Plan_Personal]
name = "Model_Studio_Token_Plan_Personal"
base_url = "https://token-plan.maas.qwencloudapi.com/compatible-mode/v1"
env_key = "OPENAI_API_KEY"
wire_api = "chat"
**qwen3.8-max modo de pensamento **:
- pensando: Suporta habilitado e desabilitado (modo de pensamento híbrido).
- temperatura: o padrão é 0,6 no modo de pensamento. Valores abaixo de 0,6 são ajustados automaticamente para 0,6.
- reasoning_effort: Controla a profundidade do raciocínio. Opções: xalto, médio, baixo. Padrão: xalto.
Plano de Token (Edição de Equipe)
Para model, selecione um modelo compatível. Defina o OPENAI_API_KEY variável de ambiente para o Token Plan (Team Edition) dedicado API Key.
Etapa 1: configurar variáveis de ambiente
Defina o OPENAI_API_KEY variável de ambiente para a chave de API dedicada do Token Plan (Team Edition).
macOS
1. Execute o seguinte comando em um terminal para verificar o tipo de shell padrão.
```bash
echo $SHELL
```
2. Defina a variável de ambiente com base no seu tipo de shell:
Zsh
```bash
# Replace YOUR_API_KEY with the Token Plan (Team Edition) API Key
echo 'export OPENAI_API_KEY="YOUR_API_KEY"' >> ~/.zshrc
```
Bash
```bash
# Replace YOUR_API_KEY with the Token Plan (Team Edition) API Key
echo 'export OPENAI_API_KEY="YOUR_API_KEY"' >> ~/.bash_profile
```
3. Execute o seguinte comando para aplicar a variável de ambiente.
Zsh
```bash
source ~/.zshrc
```
Bash
```bash
source ~/.bash_profile
```
Windows
CMD
1. Execute o seguinte comando no CMD para definir a variável de ambiente.
```powershell
REM Replace YOUR_API_KEY with the Token Plan (Team Edition) API Key
setx OPENAI_API_KEY "YOUR_API_KEY"
```
2. Abra uma nova janela CMD e execute o seguinte comando para verificar se a variável de ambiente está definida.
```powershell
echo %OPENAI_API_KEY%
```
PowerShell
1. Execute o seguinte comando no PowerShell para definir a variável de ambiente.
```powershell
# Replace YOUR_API_KEY with the Token Plan (Team Edition) API Key
[Environment]::SetEnvironmentVariable("OPENAI_API_KEY", "YOUR_API_KEY", [EnvironmentVariableTarget]::User)
```
2. Abra uma nova janela do PowerShell e execute o seguinte comando para verificar se a variável de ambiente está definida.
```powershell
echo $env:OPENAI_API_KEY
```
Passo 2: Escolha um método de acesso
Escolha um método de acesso com base na API compatível com o modelo:
API de respostas
Se o modelo selecionado for compatível com a API OpenAI Responses, você pode usar a versão mais recente do Codex.
model_provider = "Model_Studio_Token_Plan"
model = "auto"
[model_providers.Model_Studio_Token_Plan]
name = "Model_Studio_Token_Plan"
base_url = "https://token-plan.maas.qwencloudapi.com/compatible-mode/v1"
env_key = "OPENAI_API_KEY"
wire_api = "responses"
Em seguida, configure os metadados do modelo para poder alternar entre modelos. Criar ~/.codex/model-catalog.local.json com os modelos suportados por este plano:
{
"models": [
{
"slug": "auto",
"display_name": "auto",
"description": "DashScope model: auto",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 1,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.8-max",
"display_name": "qwen3.8-max",
"description": "DashScope model: qwen3.8-max",
"default_reasoning_level": "xhigh",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 983616,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 1,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.8-flash",
"display_name": "qwen3.8-flash",
"description": "DashScope model: qwen3.8-flash",
"default_reasoning_level": "xhigh",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 983616,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 2,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.7-max",
"display_name": "qwen3.7-max",
"description": "DashScope model: qwen3.7-max",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 3,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.7-plus",
"display_name": "qwen3.7-plus",
"description": "DashScope model: qwen3.7-plus",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 4,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.6-flash",
"display_name": "qwen3.6-flash",
"description": "DashScope model: qwen3.6-flash",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 5,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "glm-5.3",
"display_name": "glm-5.3",
"description": "DashScope model: glm-5.3",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": [
"text"
],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 6,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "glm-5.2",
"display_name": "glm-5.2",
"description": "DashScope model: glm-5.2",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 7,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "deepseek-v4.1-flash",
"display_name": "deepseek-v4.1-flash",
"description": "DashScope model: deepseek-v4.1-flash",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 8,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "deepseek-v4-pro",
"display_name": "deepseek-v4-pro",
"description": "DashScope model: deepseek-v4-pro",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 163840,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 9,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "deepseek-v4-pro-0813",
"display_name": "deepseek-v4-pro-0813",
"description": "DashScope model: deepseek-v4-pro-0813",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 163840,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 10,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "deepseek-v4-flash-0731",
"display_name": "deepseek-v4-flash-0731",
"description": "DashScope model: deepseek-v4-flash-0731",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 11,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.6-plus",
"display_name": "qwen3.6-plus",
"description": "DashScope model: qwen3.6-plus",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 12,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "kimi-k2.7-code",
"display_name": "kimi-k2.7-code",
"description": "DashScope model: kimi-k2.7-code",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 262144,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 15,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "kimi-k2.6",
"display_name": "kimi-k2.6",
"description": "DashScope model: kimi-k2.6",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 262144,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 16,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "kimi-k2.5",
"display_name": "kimi-k2.5",
"description": "DashScope model: kimi-k2.5",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 262144,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 17,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "glm-5.1",
"display_name": "glm-5.1",
"description": "DashScope model: glm-5.1",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 202752,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 18,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "glm-5",
"display_name": "glm-5",
"description": "DashScope model: glm-5",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 202752,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 19,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "MiniMax-M2.5",
"display_name": "MiniMax-M2.5",
"description": "DashScope model: MiniMax-M2.5",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 204800,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 20,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
}
]
}
Adicione o seguinte a ~/.codex/config.toml para apontar para o arquivo:
model_catalog_json = "~/.codex/model-catalog.local.json"
Após a configuração, alterne entre os modelos com codex -m (por exemplo, codex -m qwen3.8-flash) ou digite /model na TUI.
API de bate-papo/conclusões (outros modelos)
Outros modelos exigem a API Chat/Completions. Instale uma versão mais antiga do Codex, como 0.80.0 (as versões mais recentes do Codex não suportam mais wire_api = "chat"; se você receber um erro após a atualização, consulte as perguntas frequentes abaixo):
npm install -g @openai/codex@0.80.0
model_provider = "Model_Studio_Token_Plan"
model = "glm-5"
[model_providers.Model_Studio_Token_Plan]
name = "Model_Studio_Token_Plan"
base_url = "https://token-plan.maas.qwencloudapi.com/compatible-mode/v1"
env_key = "OPENAI_API_KEY"
wire_api = "chat"
**qwen3.8-max modo de pensamento **:
- pensando: Suporta habilitado e desabilitado (modo de pensamento híbrido).
- temperatura: o padrão é 0,6 no modo de pensamento. Valores abaixo de 0,6 são ajustados automaticamente para 0,6.
- reasoning_effort: Controla a profundidade do raciocínio. Opções: xalto, médio, baixo. Padrão: xalto.
Pague conforme o uso
Defina o OPENAI_API_KEY variável de ambiente para o seu QwenCloud Chave API e escolha entre modelos suportados.
Definir base_url para https://maas.qwencloudapi.com/compatible-mode/v1.
O pagamento conforme o uso oferece suporte à API de respostas e à API de bate-papo/conclusões. Escolha com base no modelo que você está usando:
Etapa 1: configurar variáveis de ambiente
Defina o OPENAI_API_KEY variável de ambiente para o seu QwenCloud Chave API.
macOS
1. Execute o seguinte comando em um terminal para verificar o tipo de shell padrão.
```bash
echo $SHELL
```
2. Defina a variável de ambiente com base no seu tipo de shell:
Zsh
```bash
# Replace YOUR_API_KEY with the QwenCloud API Key
echo 'export OPENAI_API_KEY="YOUR_API_KEY"' >> ~/.zshrc
```
Bash
```bash
# Replace YOUR_API_KEY with the QwenCloud API Key
echo 'export OPENAI_API_KEY="YOUR_API_KEY"' >> ~/.bash_profile
```
3. Execute o seguinte comando para aplicar a variável de ambiente.
Zsh
```bash
source ~/.zshrc
```
Bash
```bash
source ~/.bash_profile
```
Windows
CMD
1. Execute o seguinte comando no CMD para definir a variável de ambiente.
```powershell
REM Replace YOUR_API_KEY with the QwenCloud API Key
setx OPENAI_API_KEY "YOUR_API_KEY"
```
2. Abra uma nova janela CMD e execute o seguinte comando para verificar se a variável de ambiente está definida.
```powershell
echo %OPENAI_API_KEY%
```
PowerShell
1. Execute o seguinte comando no PowerShell para definir a variável de ambiente.
```powershell
# Replace YOUR_API_KEY with the QwenCloud API Key
[Environment]::SetEnvironmentVariable("OPENAI_API_KEY", "YOUR_API_KEY", [EnvironmentVariableTarget]::User)
```
2. Abra uma nova janela do PowerShell e execute o seguinte comando para verificar se a variável de ambiente está definida.
```powershell
echo $env:OPENAI_API_KEY
```
Passo 2: Escolha um método de acesso
Escolha um método de acesso com base na API compatível com o modelo:
API de respostas
Aplicável a modelos que suportam a API OpenAI Responses (como qwen3.7-max), compatível com a versão mais recente do Codex.
model_provider = "Model_Studio"
model = "qwen3.7-max"
[model_providers.Model_Studio]
name = "Model_Studio"
base_url = "https://maas.qwencloudapi.com/compatible-mode/v1"
env_key = "OPENAI_API_KEY"
wire_api = "responses"
Em seguida, configure os metadados do modelo para poder alternar entre modelos. Criar ~/.codex/model-catalog.local.json com os modelos suportados por este plano:
{
"models": [
{
"slug": "qwen3.8-max",
"display_name": "qwen3.8-max",
"description": "DashScope model: qwen3.8-max",
"default_reasoning_level": "xhigh",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 983616,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": true,
"input_modalities": ["text", "image"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 1,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "qwen3.7-max",
"display_name": "qwen3.7-max",
"description": "DashScope model: qwen3.7-max",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 2,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "deepseek-v4-pro",
"display_name": "deepseek-v4-pro",
"description": "DashScope model: deepseek-v4-pro",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 163840,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 3,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
},
{
"slug": "glm-5.2",
"display_name": "glm-5.2",
"description": "DashScope model: glm-5.2",
"default_reasoning_level": "medium",
"supported_reasoning_levels": [
{
"effort": "low",
"description": "Fast responses with lighter reasoning"
},
{
"effort": "medium",
"description": "Balances speed and reasoning depth"
},
{
"effort": "high",
"description": "Greater reasoning depth for complex problems"
},
{
"effort": "xhigh",
"description": "Extra high reasoning depth for complex problems"
}
],
"context_window": 1000000,
"effective_context_window_percent": 95,
"supports_parallel_tool_calls": false,
"supports_image_detail_original": false,
"input_modalities": ["text"],
"shell_type": "default",
"visibility": "list",
"supported_in_api": true,
"priority": 4,
"base_instructions": "",
"support_verbosity": false,
"supports_reasoning_summaries": false,
"experimental_supported_tools": [],
"truncation_policy": {
"mode": "bytes",
"limit": 10000
}
}
]
}
Adicione o seguinte a ~/.codex/config.toml para apontar para o arquivo:
model_catalog_json = "~/.codex/model-catalog.local.json"
Após a configuração, alterne entre os modelos com codex -m (por exemplo, codex -m qwen3.8-max) ou digite /model na TUI.
API de bate-papo/conclusões
Aplicável a modelos que suportam apenas a API Chat/Completions. Requer a instalação do Codex 0.80.0:
npm install -g @openai/codex@0.80.0
model_provider = "Model_Studio"
model = "qwen3.6-plus"
[model_providers.Model_Studio]
name = "Model_Studio"
base_url = "https://maas.qwencloudapi.com/compatible-mode/v1"
env_key = "OPENAI_API_KEY"
wire_api = "chat"
Verifique a configuração
Após a conclusão da configuração, abra uma nova janela de terminal e execute o seguinte comando para iniciar o Codex:
codex
Se a interface de chat for iniciada com sucesso, a configuração está correta.
Perguntas frequentes
O que devo fazer se uma ferramenta de terceiros relatar "modelos domésticos não suportados" ou "verificação rejeitada/solicitação incorreta (400)"?
Causa: algumas ferramentas de gerenciamento de terceiros (como CC-Switch) enviam uma solicitação de sondagem de "verificação de integridade/teste de conexão" ao trocar de provedor. O formato desta investigação difere do formato de solicitação que o Codex realmente usa, então o QwenCloud o gateway pode rejeitá-lo com 400 Solicitação incorreta e a ferramenta relata "modelos domésticos não suportados". Esta mensagem indica apenas que a investigação de verificação de integridade falhou; isso não significa QwenCloud não tem suporte para modelos domésticos, nem afeta o uso real do Codex.
Nota: QwenCloud apoia o uso de modelos domésticos, como qwen3.7-max, qwen3.7-plus, qwen3.6-plus, qwen3.6-flashe glm-5 através do Codex. Para obter detalhes de configuração, consulte Configurar credenciais de acesso acima.
Solução: Configure o Codex diretamente no ~/.codex/config.toml conforme descrito em Configurar credenciais de acesso, sem depender do resultado da verificação de integridade da ferramenta de terceiros. Após a configuração, inicie o Codex conforme descrito em Verificar configuração; se a interface de chat iniciar normalmente, os modelos domésticos estão funcionando.
O que devo fazer se receber um erro de configuração wire_api?
Causa: versões mais recentes do Codex não são mais compatíveis wire_api = "chat". Dependendo da versão, você poderá ver um dos seguintes erros:
wire_api = "chat" is no longer supportedunknown configuration field wire_api
Solução:
- Erro
wire_api = "chat" is no longer supported: Alterarwire_apipararesponsese verifique issobase_urlestá correto. Consulte Configurar credenciais de acesso para exemplos de configuração. - Erro
unknown configuration field wire_api: Remova owire_apilinha da seção do provedor correspondente em~/.codex/config.toml.
O que devo fazer se receber o erro "status inesperado 401 Não autorizado"?
Causa:
- Usar uma chave de API de um plano diferente (chaves de API para plano de token (edição pessoal), plano de token (edição de equipe) e pagamento conforme o uso não são intercambiáveis)
- A assinatura expirou
- A chave de API foi copiada de forma incompleta, contém espaços ou contém um erro de digitação
Solução:
- Verifique se você está usando a chave de API dedicada para o plano selecionado.
- Acesse a página de gerenciamento do plano selecionado e verifique se a assinatura expirou.
- Copie novamente a chave API e certifique-se de que esteja completa e sem espaços.
- Se o erro persistir após a verificação acima, redefina a Chave API na página de gerenciamento do plano selecionado. Após a redefinição, use a nova chave API para configuração.
O que devo fazer se receber o erro "status inesperado 404 não encontrado"?
Causa: O base_url ou wire_api no arquivo de configuração está incorreto.
Solução: verifique se base_url e wire_api corresponda à configuração do plano selecionado. Veja os exemplos de configuração do seu plano em Configurar credenciais de acesso acima.
O que devo fazer se receber o erro "stream desconectado antes da conclusão: stream fechado antes da resposta.completed"?
Causa: A conexão de streaming entre o Codex e o servidor foi interrompida antes da resposta ser concluída. Isso geralmente ocorre nos seguintes cenários:
- O thread de conversação é muito longo, causando falha na solicitação de compactação de contexto
- Rede instável fazendo com que a conexão SSE ou WebSocket caia no meio do fluxo
- Sobrecarga do servidor ou limitação de taxa que encerra a conexão antecipadamente
Solução:
- Inicie um novo tópico de conversa para evitar acúmulo excessivo de contexto em um único tópico.
- Verifique sua conexão de rede. Tente desativar a VPN ou proxy e tente novamente.
- Espere e tente novamente. O Codex possui um mecanismo de nova tentativa integrado que resolve automaticamente a maioria das falhas transitórias.
O que devo fazer se receber um erro 429 por limitação de taxa ou esgotamento de cota?
Causa: Um erro 429 ocorre em duas situações:
- Limite de taxa excedido (
429 Requests rate limit exceeded): as solicitações são muito frequentes em um curto período. - Cota esgotada (
429 Allocated quota exceededouYour token-plan 1-week quota has been exhausted): O limite semanal ou mensal do Token Plan foi atingido.
Solução:
- Limite de taxa excedido: aguarde um minuto e tente novamente com uma frequência de solicitação reduzida.
- Cota esgotada: Aguarde o término do período de janela correspondente (semanal ou mensal), após o qual a cota é zerada automaticamente; ou comprar um Pacote de Créditos (os Créditos do Pacote de Créditos não estão sujeitos a limites de janela); ou atualize seu plano. Observe que o tempo de reinicialização na mensagem de erro (por exemplo,
The quota will reset at HH:MM:SS UTC) está no Tempo Universal Coordenado (UTC).