US-010: Add model compatibility documentation

Created comprehensive MODEL_COMPATIBILITY.md documenting:
- Kimi models is_error exclusion (prevents 400 Bad Request)
- Reasoning models tuning parameter stripping (o1, o3, o4, grok-3-mini, qwen-qwq)
- GPT-5 max_completion_tokens requirement
- Qwen model routing through DashScope

Includes implementation details, key functions table, guide for adding new
models, and testing commands. Cross-referenced with existing code comments.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Yeachan-Heo
2026-04-16 10:55:58 +00:00
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# Model Compatibility Guide
This document describes model-specific handling in the OpenAI-compatible provider. When adding new models or providers, review this guide to ensure proper compatibility.
## Table of Contents
- [Overview](#overview)
- [Model-Specific Handling](#model-specific-handling)
- [Kimi Models (is_error Exclusion)](#kimi-models-is_error-exclusion)
- [Reasoning Models (Tuning Parameter Stripping)](#reasoning-models-tuning-parameter-stripping)
- [GPT-5 (max_completion_tokens)](#gpt-5-max_completion_tokens)
- [Qwen Models (DashScope Routing)](#qwen-models-dashscope-routing)
- [Implementation Details](#implementation-details)
- [Adding New Models](#adding-new-models)
- [Testing](#testing)
## Overview
The `openai_compat.rs` provider translates Claude Code's internal message format to OpenAI-compatible chat completion requests. Different models have varying requirements for:
- Tool result message fields (`is_error`)
- Sampling parameters (temperature, top_p, etc.)
- Token limit fields (`max_tokens` vs `max_completion_tokens`)
- Base URL routing
## Model-Specific Handling
### Kimi Models (is_error Exclusion)
**Affected models:** `kimi-k2.5`, `kimi-k1.5`, `kimi-moonshot`, and any model with `kimi` in the name (case-insensitive)
**Behavior:** The `is_error` field is **excluded** from tool result messages.
**Rationale:** Kimi models (via Moonshot AI and DashScope) reject the `is_error` field with a 400 Bad Request error:
```json
{
"error": {
"type": "invalid_request_error",
"message": "Unknown field: is_error"
}
}
```
**Detection:**
```rust
fn model_rejects_is_error_field(model: &str) -> bool {
let lowered = model.to_ascii_lowercase();
let canonical = lowered.rsplit('/').next().unwrap_or(lowered.as_str());
canonical.starts_with("kimi-")
}
```
**Testing:** See `model_rejects_is_error_field_detects_kimi_models` and related tests in `openai_compat.rs`.
---
### Reasoning Models (Tuning Parameter Stripping)
**Affected models:**
- OpenAI: `o1`, `o1-*`, `o3`, `o3-*`, `o4`, `o4-*`
- xAI: `grok-3-mini`
- Alibaba DashScope: `qwen-qwq-*`, `qwq-*`, `qwen3-*-thinking`
**Behavior:** The following tuning parameters are **stripped** from requests:
- `temperature`
- `top_p`
- `frequency_penalty`
- `presence_penalty`
**Rationale:** Reasoning/chain-of-thought models use fixed sampling strategies and reject these parameters with 400 errors.
**Exception:** `reasoning_effort` is included for compatible models when explicitly set.
**Detection:**
```rust
fn is_reasoning_model(model: &str) -> bool {
let canonical = model.to_ascii_lowercase()
.rsplit('/')
.next()
.unwrap_or(model);
canonical.starts_with("o1")
|| canonical.starts_with("o3")
|| canonical.starts_with("o4")
|| canonical == "grok-3-mini"
|| canonical.starts_with("qwen-qwq")
|| canonical.starts_with("qwq")
|| (canonical.starts_with("qwen3") && canonical.contains("-thinking"))
}
```
**Testing:** See `reasoning_model_strips_tuning_params`, `grok_3_mini_is_reasoning_model`, and `qwen_reasoning_variants_are_detected` tests.
---
### GPT-5 (max_completion_tokens)
**Affected models:** All models starting with `gpt-5`
**Behavior:** Uses `max_completion_tokens` instead of `max_tokens` in the request payload.
**Rationale:** GPT-5 models require the `max_completion_tokens` field. Legacy `max_tokens` causes request validation failures:
```json
{
"error": {
"message": "Unknown field: max_tokens"
}
}
```
**Implementation:**
```rust
let max_tokens_key = if wire_model.starts_with("gpt-5") {
"max_completion_tokens"
} else {
"max_tokens"
};
```
**Testing:** See `gpt5_uses_max_completion_tokens_not_max_tokens` and `non_gpt5_uses_max_tokens` tests.
---
### Qwen Models (DashScope Routing)
**Affected models:** All models with `qwen` prefix
**Behavior:** Routed to DashScope (`https://dashscope.aliyuncs.com/compatible-mode/v1`) rather than default providers.
**Rationale:** Qwen models are hosted by Alibaba Cloud's DashScope service, not OpenAI or Anthropic.
**Configuration:**
```rust
pub const DEFAULT_DASHSCOPE_BASE_URL: &str = "https://dashscope.aliyuncs.com/compatible-mode/v1";
```
**Authentication:** Uses `DASHSCOPE_API_KEY` environment variable.
**Note:** Some Qwen models are also reasoning models (see [Reasoning Models](#reasoning-models-tuning-parameter-stripping) above) and receive both treatments.
## Implementation Details
### File Location
All model-specific logic is in:
```
rust/crates/api/src/providers/openai_compat.rs
```
### Key Functions
| Function | Purpose |
|----------|---------|
| `model_rejects_is_error_field()` | Detects models that don't support `is_error` in tool results |
| `is_reasoning_model()` | Detects reasoning models that need tuning param stripping |
| `translate_message()` | Converts internal messages to OpenAI format (applies `is_error` logic) |
| `build_chat_completion_request()` | Constructs full request payload (applies all model-specific logic) |
### Provider Prefix Handling
All model detection functions strip provider prefixes (e.g., `dashscope/kimi-k2.5``kimi-k2.5`) before matching:
```rust
let canonical = model.to_ascii_lowercase()
.rsplit('/')
.next()
.unwrap_or(model);
```
This ensures consistent detection regardless of whether models are referenced with or without provider prefixes.
## Adding New Models
When adding support for new models:
1. **Check if the model is a reasoning model**
- Does it reject temperature/top_p parameters?
- Add to `is_reasoning_model()` detection
2. **Check tool result compatibility**
- Does it reject the `is_error` field?
- Add to `model_rejects_is_error_field()` detection
3. **Check token limit field**
- Does it require `max_completion_tokens` instead of `max_tokens`?
- Update the `max_tokens_key` logic
4. **Add tests**
- Unit test for detection function
- Integration test in `build_chat_completion_request`
5. **Update this documentation**
- Add the model to the affected lists
- Document any special behavior
## Testing
### Running Model-Specific Tests
```bash
# All OpenAI compatibility tests
cargo test --package api providers::openai_compat
# Specific test categories
cargo test --package api model_rejects_is_error_field
cargo test --package api reasoning_model
cargo test --package api gpt5
cargo test --package api qwen
```
### Test Files
- Unit tests: `rust/crates/api/src/providers/openai_compat.rs` (in `mod tests`)
- Integration tests: `rust/crates/api/tests/openai_compat_integration.rs`
### Verifying Model Detection
To verify a model is detected correctly without making API calls:
```rust
#[test]
fn my_new_model_is_detected() {
// is_error handling
assert!(model_rejects_is_error_field("my-model"));
// Reasoning model detection
assert!(is_reasoning_model("my-model"));
// Provider prefix handling
assert!(model_rejects_is_error_field("provider/my-model"));
}
```
---
*Last updated: 2026-04-16*
For questions or updates, see the implementation in `rust/crates/api/src/providers/openai_compat.rs`.

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"Document qwen model routing through dashscope",
"Cross-reference with existing code comments"
],
"passes": false,
"passes": true,
"priority": "P2"
},
{

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@@ -94,3 +94,16 @@ US-009 COMPLETED (Add unit tests for kimi model compatibility fix)
4. build_chat_completion_request_kimi_vs_non_kimi_tool_results - full integration test for request building
- Tests: 4 new tests, 119 unit tests total in api crate (+4), all passing
- Integration tests: 29 passing (no regressions)
US-010 COMPLETED (Add model compatibility documentation)
- Files: docs/MODEL_COMPATIBILITY.md
- Created comprehensive documentation covering:
1. Kimi Models (is_error Exclusion) - documents the 400 Bad Request issue and solution
2. Reasoning Models (Tuning Parameter Stripping) - covers o1, o3, o4, grok-3-mini, qwen-qwq, qwen3-thinking
3. GPT-5 (max_completion_tokens) - documents max_tokens vs max_completion_tokens requirement
4. Qwen Models (DashScope Routing) - explains routing and authentication
- Added implementation details section with key functions
- Added "Adding New Models" guide for future contributors
- Added testing section with example commands
- Cross-referenced with existing code comments in openai_compat.rs
- cargo clippy passes