OpenAI rejects non-default temperature on gpt-5 / gpt-5-chat with
HTTP 400 ("Unsupported value: 'temperature' does not support 0.7
with this model. Only the default (1) value is supported.").
skipTemp in buildRequestBody only covered gpt-5-mini / gpt-5-nano and
the o-series, so base gpt-5 and gpt-5-chat fell through and received
config.DefaultTemperature (0.7). On channel integrations the inbound
error is suppressed, leaving the agent silently dead.
The gpt-5.X flagship variants (gpt-5.1, gpt-5.4, gpt-5.5) keep their
temperature — only the base gpt-5 and gpt-5-chat aliases are locked
to the default.
Regression cases added for gpt-5, gpt-5-chat, gpt-5-chat-latest and
provider-prefixed forms; gpt-5 moved to the locked list in
TestBuildRequestBody_TemperatureKeptForNonReasoningModels per the
maintainer triage on #1460.
Fixes#1460
Ollama has two separate request-building code paths: OllamaProvider
(native /api/chat, used for num_ctx control) and OpenAIProvider
(OpenAI-compat /v1/chat/completions). An earlier fix disabled thinking
mode by hardcoding think=false, but only in the OpenAI-compat path --
OllamaProvider.buildRequest() never set the think field at all, so
reasoning-capable models (qwq, deepseek-r1) defaulted to visible
chain-of-thought reasoning regardless of that fix. Confirmed live via
a docker-engineer agent streaming full reasoning traces despite the
existing disable.
Replaced the hardcoded always-off behavior with a provider-level
tri-state setting (llm_providers.settings.thinking_enabled: unset =
default off, explicit true/false overrides), configurable via the
provider's Advanced settings dialog. Both OllamaProvider.buildRequest()
and OpenAIProvider.buildRequestBody() now read and respect this same
setting, so the toggle works regardless of which Ollama code path a
given deployment routes through.
Added tests for setting parsing (unset/true/false/malformed) and both
provider request-builders' handling of the override.
Co-authored-by: Bruno Clermont <bruno.clermont@gmail.com>
Ollama models like qwq and deepseek-r1 have thinking enabled by default.
Disable it to prevent bloated response generation unless explicitly requested.
- Add isOllamaEndpoint() detection (providerType, name, apiBase)
- Always send think=false in Ollama requests unless OptThinkingLevel is set
- SupportsThinking() and Capabilities().Thinking return false for Ollama
- Add tests covering default-off, explicit-opt-in, and capability flags
Co-authored-by: Bruno Clermont <bruno.clermont@gmail.com>
Port PR #685 fixes for HTTP 400 on Together AI and strict OpenAI-compat hosts,
with additional improvements:
- Gate reasoning_content on assistant history to allowlisted models only
(OpenAI o-series/GPT-5, DeepSeek, Kimi) — prevents HTTP 400 on Together/Qwen
- Gate reasoning_effort to models that support it (OpenAI reasoning family)
- Skip stream_options for Together endpoints (causes HTTP 400)
- Scope DashScope enable_thinking/thinking_budget to DashScope providers only
- Reorder multimodal parts: text before images (Together/Qwen preferred order)
- Add redacted_thinking tag to sanitization patterns with early-exit guard fix
- Upgrade Together detection from URL-only to URL + providerType + name fallback
(mirrors dashScopePassthroughKeys pattern for reverse-proxy compatibility)
- Add comprehensive tests for all new behavior
Fix Mistral tool call ID formatting on the outbound OpenAI-compatible payload.
For provider `mistral` only, normalizes both `tool_calls[].id` and `tool`
message `tool_call_id` to a 9-character hex string (SHA-256 based) before
sending the request. Other providers keep the existing `truncateToolCallID`
behavior unchanged.
- Hash full ID via SHA-256 to avoid prefix-dependent collisions
- Detect Mistral via both provider name and providerType (DB-loaded support)
- Add collision uniqueness and DB provider detection tests
Closes#532
- Replace prefix truncation with SHA-256 hash-based shortening for oversized tool call IDs (40-char OpenAI/Azure limit)
- Normalize provider-prefixed model IDs (e.g. openai/o3-mini) before capability checks for temperature and max_completion_tokens
- Add regression tests for ID collision, correlation, and prefixed model routing
fchengyan