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feat: GPT-5.2 support

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Fahad
2025-12-11 19:11:50 +00:00
parent 5c3dd75ca6
commit 8b16405f06
33 changed files with 216 additions and 119 deletions
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docs/configuration.md
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@@ -63,7 +63,7 @@ CUSTOM_MODEL_NAME=llama3.2 # Default model
**Default Model Selection:**
```env
# Options: 'auto', 'pro', 'flash', 'gpt5.1', 'gpt5.1-codex', 'gpt5.1-codex-mini', 'o3', 'o3-mini', 'o4-mini', etc.
# Options: 'auto', 'pro', 'flash', 'gpt5.2', 'gpt5.1-codex', 'gpt5.1-codex-mini', 'o3', 'o3-mini', 'o4-mini', etc.
DEFAULT_MODEL=auto # Claude picks best model for each task (recommended)
```
@@ -81,13 +81,13 @@ DEFAULT_MODEL=auto # Claude picks best model for each task (recommended)
| Provider | Canonical Models | Notable Aliases |
|----------|-----------------|-----------------|
| OpenAI | `gpt-5.1`, `gpt-5.1-codex`, `gpt-5.1-codex-mini`, `gpt-5`, `gpt-5-pro`, `gpt-5-mini`, `gpt-5-nano`, `gpt-5-codex`, `gpt-4.1`, `o3`, `o3-mini`, `o3-pro`, `o4-mini` | `gpt5.1`, `gpt-5.1`, `5.1`, `gpt5.1-codex`, `codex-5.1`, `codex-mini`, `gpt5`, `gpt5pro`, `mini`, `nano`, `codex`, `o3mini`, `o3pro`, `o4mini` |
| OpenAI | `gpt-5.2`, `gpt-5.1-codex`, `gpt-5.1-codex-mini`, `gpt-5`, `gpt-5.2-pro`, `gpt-5-mini`, `gpt-5-nano`, `gpt-5-codex`, `gpt-4.1`, `o3`, `o3-mini`, `o3-pro`, `o4-mini` | `gpt5.2`, `gpt-5.2`, `5.2`, `gpt5.1-codex`, `codex-5.1`, `codex-mini`, `gpt5`, `gpt5pro`, `mini`, `nano`, `codex`, `o3mini`, `o3pro`, `o4mini` |
| Gemini | `gemini-2.5-pro`, `gemini-2.5-flash`, `gemini-2.0-flash`, `gemini-2.0-flash-lite` | `pro`, `gemini-pro`, `flash`, `flash-2.0`, `flashlite` |
| X.AI | `grok-4`, `grok-3`, `grok-3-fast` | `grok`, `grok4`, `grok3`, `grok3fast`, `grokfast` |
| OpenRouter | See `conf/openrouter_models.json` for the continually evolving catalogue | e.g., `opus`, `sonnet`, `flash`, `pro`, `mistral` |
| Custom | User-managed entries such as `llama3.2` | Define your own aliases per entry |
Latest OpenAI entries (`gpt-5.1`, `gpt-5.1-codex`, `gpt-5.1-codex-mini`) mirror the official model cards released on November 13, 2025: all three expose 400K-token contexts with 128K-token outputs, reasoning-token support, and multimodal inputs. `gpt-5.1-codex` is Responses-only with streaming disabled, while the base `gpt-5.1` and Codex mini support streaming along with full code-generation flags. Update your manifests if you run custom deployments so these capability bits stay accurate.
Latest OpenAI entries (`gpt-5.2`, `gpt-5.1-codex`, `gpt-5.1-codex-mini`, `gpt-5.2-pro`) expose 400K-token contexts with large outputs, reasoning-token support, and multimodal inputs. `gpt-5.1-codex` and `gpt-5.2-pro` are Responses-only with streaming disabled, while the base `gpt-5.2` and Codex mini support streaming along with full code-generation flags. Update your manifests if you run custom deployments so these capability bits stay accurate.
> **Tip:** Copy the JSON file you need, customise it, and point the corresponding `*_MODELS_CONFIG_PATH` environment variable to your version. This lets you enable or disable capabilities (JSON mode, function calling, temperature support, code generation) without editing Python.
@@ -107,7 +107,7 @@ The `allow_code_generation` capability enables models to generate complete, prod
**When to Enable:**
- **Enable for**: Models MORE capable than your primary CLI's model (e.g., GPT-5.1 Codex, GPT-5 Pro, GPT-5.1 when using Claude Code with Sonnet 4.5)
- **Enable for**: Models MORE capable than your primary CLI's model (e.g., GPT-5.1 Codex, GPT-5.2 Pro, GPT-5.2 when using Claude Code with Sonnet 4.5)
- **Purpose**: Get complete implementations from a more powerful reasoning model that your primary CLI can then review and apply
- **Use case**: Large-scale implementations, major refactoring, complete module creation
@@ -132,7 +132,7 @@ The `allow_code_generation` capability enables models to generate complete, prod
...
},
{
"model_name": "gpt-5-pro",
"model_name": "gpt-5.2-pro",
"allow_code_generation": true,
"intelligence_score": 19,
...
@@ -142,8 +142,8 @@ The `allow_code_generation` capability enables models to generate complete, prod
```
**Typical Workflow:**
1. You ask your AI agent to implement a complex new feature using `chat` with a higher-reasoning model such as **gpt-5-pro**
2. GPT-5-Pro generates structured implementation and shares the complete implementation with PAL
1. You ask your AI agent to implement a complex new feature using `chat` with a higher-reasoning model such as **gpt-5.2-pro**
2. GPT-5.2-Pro generates structured implementation and shares the complete implementation with PAL
3. PAL saves the code to `pal_generated.code` and asks AI agent to implement the plan
4. AI agent continues from the previous context, reads the file, applies the implementation
@@ -198,7 +198,7 @@ OPENAI_ALLOWED_MODELS=o4-mini
GOOGLE_ALLOWED_MODELS=flash
# High-performance setup
OPENAI_ALLOWED_MODELS=gpt-5.1-codex,gpt-5.1
OPENAI_ALLOWED_MODELS=gpt-5.1-codex,gpt-5.2
GOOGLE_ALLOWED_MODELS=pro
# Single model standardization