mirror of
https://github.com/NousResearch/hermes-agent.git
synced 2026-05-08 03:01:47 +00:00
feat: provider modules — ProviderProfile ABC, 33 providers, fetch_models, transport single-path
Introduces providers/ package — single source of truth for every inference provider. Adding a simple api-key provider now requires one providers/<name>.py file with zero edits anywhere else. What this PR ships: - providers/ package (ProviderProfile ABC + 33 profiles across 4 api_modes) - ProviderProfile declarative fields: name, api_mode, aliases, display_name, env_vars, base_url, models_url, auth_type, fallback_models, hostname, default_headers, fixed_temperature, default_max_tokens, default_aux_model - 4 overridable hooks: prepare_messages, build_extra_body, build_api_kwargs_extras, fetch_models - chat_completions.build_kwargs: profile path via _build_kwargs_from_profile, legacy flag path retained for lmstudio/tencent-tokenhub (which have session-aware reasoning probing that doesn't map cleanly to hooks yet) - run_agent.py: profile path for all registered providers; legacy path variable scoping fixed (all flags defined before branching) - Auto-wires: auth.PROVIDER_REGISTRY, models.CANONICAL_PROVIDERS, doctor health checks, config.OPTIONAL_ENV_VARS, model_metadata._URL_TO_PROVIDER - GeminiProfile: thinking_config translation (native + openai-compat nested) - New tests/providers/ (79 tests covering profile declarations, transport parity, hook overrides, e2e kwargs assembly) Deltas vs original PR (salvaged onto current main): - Added profiles: alibaba-coding-plan, azure-foundry, minimax-oauth (were added to main since original PR) - Skipped profiles: lmstudio, tencent-tokenhub stay on legacy path (their reasoning_effort probing has no clean hook equivalent yet) - Removed lmstudio alias from custom profile (it's a separate provider now) - Skipped openrouter/custom from PROVIDER_REGISTRY auto-extension (resolve_provider special-cases them; adding breaks runtime resolution) - runtime_provider: profile.api_mode only as fallback when URL detection finds nothing (was breaking minimax /v1 override) - Preserved main's legacy-path improvements: deepseek reasoning_content preserve, gemini Gemma skip, OpenRouter response caching, Anthropic 1M beta recovery, etc. - Kept agent/copilot_acp_client.py in place (rejected PR's relocation — main has 7 fixes landed since; relocation would revert them) - _API_KEY_PROVIDER_AUX_MODELS alias kept for backward compat with existing test imports Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com> Closes #14418
This commit is contained in:
kshitijk4poor
Teknium
parent
2b500ed68a
commit
20a4f79ed1
57 changed files with 3149 additions and 177 deletions
|
|
@ -216,7 +216,26 @@ def _fixed_temperature_for_model(
|
|||
return None
|
||||
|
||||
# Default auxiliary models for direct API-key providers (cheap/fast for side tasks)
|
||||
_API_KEY_PROVIDER_AUX_MODELS: Dict[str, str] = {
|
||||
def _get_aux_model_for_provider(provider_id: str) -> str:
|
||||
"""Return the cheap auxiliary model for a provider.
|
||||
|
||||
Reads from ProviderProfile.default_aux_model first, falling back to the
|
||||
legacy hardcoded dict for providers that predate the profiles system.
|
||||
"""
|
||||
try:
|
||||
from providers import get_provider_profile
|
||||
_p = get_provider_profile(provider_id)
|
||||
if _p and _p.default_aux_model:
|
||||
return _p.default_aux_model
|
||||
except Exception:
|
||||
pass
|
||||
return _API_KEY_PROVIDER_AUX_MODELS_FALLBACK.get(provider_id, "")
|
||||
|
||||
|
||||
# Fallback for providers not yet migrated to ProviderProfile.default_aux_model,
|
||||
# plus providers we intentionally keep pinned here (e.g. Anthropic predates
|
||||
# profiles). New providers should set default_aux_model on their profile instead.
|
||||
_API_KEY_PROVIDER_AUX_MODELS_FALLBACK: Dict[str, str] = {
|
||||
"gemini": "gemini-3-flash-preview",
|
||||
"zai": "glm-4.5-flash",
|
||||
"kimi-coding": "kimi-k2-turbo-preview",
|
||||
|
|
@ -235,6 +254,10 @@ _API_KEY_PROVIDER_AUX_MODELS: Dict[str, str] = {
|
|||
"tencent-tokenhub": "hy3-preview",
|
||||
}
|
||||
|
||||
# Legacy alias — callers that haven't been updated to _get_aux_model_for_provider()
|
||||
# can still use this dict directly. Kept in sync with _FALLBACK above.
|
||||
_API_KEY_PROVIDER_AUX_MODELS: Dict[str, str] = _API_KEY_PROVIDER_AUX_MODELS_FALLBACK
|
||||
|
||||
# Vision-specific model overrides for direct providers.
|
||||
# When the user's main provider has a dedicated vision/multimodal model that
|
||||
# differs from their main chat model, map it here. The vision auto-detect
|
||||
|
|
@ -1157,7 +1180,7 @@ def _resolve_api_key_provider() -> Tuple[Optional[OpenAI], Optional[str]]:
|
|||
|
||||
raw_base_url = _pool_runtime_base_url(entry, pconfig.inference_base_url) or pconfig.inference_base_url
|
||||
base_url = _to_openai_base_url(raw_base_url)
|
||||
model = _API_KEY_PROVIDER_AUX_MODELS.get(provider_id)
|
||||
model = _get_aux_model_for_provider(provider_id) or None
|
||||
if model is None:
|
||||
continue # skip provider if we don't know a valid aux model
|
||||
logger.debug("Auxiliary text client: %s (%s) via pool", pconfig.name, model)
|
||||
|
|
@ -1173,6 +1196,14 @@ def _resolve_api_key_provider() -> Tuple[Optional[OpenAI], Optional[str]]:
|
|||
from hermes_cli.models import copilot_default_headers
|
||||
|
||||
extra["default_headers"] = copilot_default_headers()
|
||||
else:
|
||||
try:
|
||||
from providers import get_provider_profile as _gpf_aux
|
||||
_ph_aux = _gpf_aux(provider_id)
|
||||
if _ph_aux and _ph_aux.default_headers:
|
||||
extra["default_headers"] = dict(_ph_aux.default_headers)
|
||||
except Exception:
|
||||
pass
|
||||
_client = OpenAI(api_key=api_key, base_url=base_url, **extra)
|
||||
_client = _maybe_wrap_anthropic(_client, model, api_key, raw_base_url)
|
||||
return _client, model
|
||||
|
|
@ -1184,7 +1215,7 @@ def _resolve_api_key_provider() -> Tuple[Optional[OpenAI], Optional[str]]:
|
|||
|
||||
raw_base_url = str(creds.get("base_url", "")).strip().rstrip("/") or pconfig.inference_base_url
|
||||
base_url = _to_openai_base_url(raw_base_url)
|
||||
model = _API_KEY_PROVIDER_AUX_MODELS.get(provider_id)
|
||||
model = _get_aux_model_for_provider(provider_id) or None
|
||||
if model is None:
|
||||
continue # skip provider if we don't know a valid aux model
|
||||
logger.debug("Auxiliary text client: %s (%s)", pconfig.name, model)
|
||||
|
|
@ -1200,6 +1231,14 @@ def _resolve_api_key_provider() -> Tuple[Optional[OpenAI], Optional[str]]:
|
|||
from hermes_cli.models import copilot_default_headers
|
||||
|
||||
extra["default_headers"] = copilot_default_headers()
|
||||
else:
|
||||
try:
|
||||
from providers import get_provider_profile as _gpf_aux2
|
||||
_ph_aux2 = _gpf_aux2(provider_id)
|
||||
if _ph_aux2 and _ph_aux2.default_headers:
|
||||
extra["default_headers"] = dict(_ph_aux2.default_headers)
|
||||
except Exception:
|
||||
pass
|
||||
_client = OpenAI(api_key=api_key, base_url=base_url, **extra)
|
||||
_client = _maybe_wrap_anthropic(_client, model, api_key, raw_base_url)
|
||||
return _client, model
|
||||
|
|
@ -1572,7 +1611,7 @@ def _try_anthropic(explicit_api_key: str = None) -> Tuple[Optional[Any], Optiona
|
|||
|
||||
from agent.anthropic_adapter import _is_oauth_token
|
||||
is_oauth = _is_oauth_token(token)
|
||||
model = _API_KEY_PROVIDER_AUX_MODELS.get("anthropic", "claude-haiku-4-5-20251001")
|
||||
model = _get_aux_model_for_provider("anthropic") or "claude-haiku-4-5-20251001"
|
||||
logger.debug("Auxiliary client: Anthropic native (%s) at %s (oauth=%s)", model, base_url, is_oauth)
|
||||
try:
|
||||
real_client = build_anthropic_client(token, base_url)
|
||||
|
|
@ -2408,7 +2447,7 @@ def resolve_provider_client(
|
|||
if explicit_base_url:
|
||||
base_url = _to_openai_base_url(explicit_base_url.strip().rstrip("/"))
|
||||
|
||||
default_model = _API_KEY_PROVIDER_AUX_MODELS.get(provider, "")
|
||||
default_model = _get_aux_model_for_provider(provider)
|
||||
final_model = _normalize_resolved_model(model or default_model, provider)
|
||||
|
||||
if provider == "gemini":
|
||||
|
|
|
|||
|
|
@ -318,6 +318,17 @@ _URL_TO_PROVIDER: Dict[str, str] = {
|
|||
"ollama.com": "ollama-cloud",
|
||||
}
|
||||
|
||||
# Auto-extend with hostnames derived from provider profiles.
|
||||
# Any provider with a base_url not already in the map gets added automatically.
|
||||
try:
|
||||
from providers import list_providers as _list_providers
|
||||
for _pp in _list_providers():
|
||||
_host = _pp.get_hostname()
|
||||
if _host and _host not in _URL_TO_PROVIDER:
|
||||
_URL_TO_PROVIDER[_host] = _pp.name
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
|
||||
def _infer_provider_from_url(base_url: str) -> Optional[str]:
|
||||
"""Infer the models.dev provider name from a base URL.
|
||||
|
|
|
|||
|
|
@ -6,9 +6,16 @@ Usage:
|
|||
result = transport.normalize_response(raw_response)
|
||||
"""
|
||||
|
||||
from agent.transports.types import NormalizedResponse, ToolCall, Usage, build_tool_call, map_finish_reason # noqa: F401
|
||||
from agent.transports.types import (
|
||||
NormalizedResponse,
|
||||
ToolCall,
|
||||
Usage,
|
||||
build_tool_call,
|
||||
map_finish_reason,
|
||||
) # noqa: F401
|
||||
|
||||
_REGISTRY: dict = {}
|
||||
_discovered: bool = False
|
||||
|
||||
|
||||
def register_transport(api_mode: str, transport_cls: type) -> None:
|
||||
|
|
@ -23,6 +30,9 @@ def get_transport(api_mode: str):
|
|||
This allows gradual migration — call sites can check for None
|
||||
and fall back to the legacy code path.
|
||||
"""
|
||||
global _discovered
|
||||
if not _discovered:
|
||||
_discover_transports()
|
||||
cls = _REGISTRY.get(api_mode)
|
||||
if cls is None:
|
||||
# The registry can be partially populated when a specific transport
|
||||
|
|
@ -38,6 +48,8 @@ def get_transport(api_mode: str):
|
|||
|
||||
def _discover_transports() -> None:
|
||||
"""Import all transport modules to trigger auto-registration."""
|
||||
global _discovered
|
||||
_discovered = True
|
||||
try:
|
||||
import agent.transports.anthropic # noqa: F401
|
||||
except ImportError:
|
||||
|
|
|
|||
|
|
@ -109,7 +109,9 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
def api_mode(self) -> str:
|
||||
return "chat_completions"
|
||||
|
||||
def convert_messages(self, messages: List[Dict[str, Any]], **kwargs) -> List[Dict[str, Any]]:
|
||||
def convert_messages(
|
||||
self, messages: list[dict[str, Any]], **kwargs
|
||||
) -> list[dict[str, Any]]:
|
||||
"""Messages are already in OpenAI format — sanitize Codex leaks only.
|
||||
|
||||
Strips Codex Responses API fields (``codex_reasoning_items`` /
|
||||
|
|
@ -126,7 +128,9 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
tool_calls = msg.get("tool_calls")
|
||||
if isinstance(tool_calls, list):
|
||||
for tc in tool_calls:
|
||||
if isinstance(tc, dict) and ("call_id" in tc or "response_item_id" in tc):
|
||||
if isinstance(tc, dict) and (
|
||||
"call_id" in tc or "response_item_id" in tc
|
||||
):
|
||||
needs_sanitize = True
|
||||
break
|
||||
if needs_sanitize:
|
||||
|
|
@ -149,39 +153,41 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
tc.pop("response_item_id", None)
|
||||
return sanitized
|
||||
|
||||
def convert_tools(self, tools: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
|
||||
def convert_tools(self, tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
|
||||
"""Tools are already in OpenAI format — identity."""
|
||||
return tools
|
||||
|
||||
def build_kwargs(
|
||||
self,
|
||||
model: str,
|
||||
messages: List[Dict[str, Any]],
|
||||
tools: Optional[List[Dict[str, Any]]] = None,
|
||||
messages: list[dict[str, Any]],
|
||||
tools: list[dict[str, Any]] | None = None,
|
||||
**params,
|
||||
) -> Dict[str, Any]:
|
||||
) -> dict[str, Any]:
|
||||
"""Build chat.completions.create() kwargs.
|
||||
|
||||
This is the most complex transport method — it handles ~16 providers
|
||||
via params rather than subclasses.
|
||||
|
||||
params:
|
||||
params (all optional):
|
||||
timeout: float — API call timeout
|
||||
max_tokens: int | None — user-configured max tokens
|
||||
ephemeral_max_output_tokens: int | None — one-shot override (error recovery)
|
||||
ephemeral_max_output_tokens: int | None — one-shot override
|
||||
max_tokens_param_fn: callable — returns {max_tokens: N} or {max_completion_tokens: N}
|
||||
reasoning_config: dict | None
|
||||
request_overrides: dict | None
|
||||
session_id: str | None
|
||||
qwen_session_metadata: dict | None — {sessionId, promptId} precomputed
|
||||
model_lower: str — lowercase model name for pattern matching
|
||||
# Provider detection flags (all optional, default False)
|
||||
# Provider profile path (all per-provider quirks live in providers/)
|
||||
provider_profile: ProviderProfile | None — when present, delegates to
|
||||
_build_kwargs_from_profile(); all flag params below are bypassed.
|
||||
# Legacy-path flags — only used when provider_profile is None
|
||||
# (i.e. custom / unregistered providers). Known providers all go
|
||||
# through provider_profile.
|
||||
is_openrouter: bool
|
||||
is_nous: bool
|
||||
is_qwen_portal: bool
|
||||
is_github_models: bool
|
||||
is_nvidia_nim: bool
|
||||
is_kimi: bool
|
||||
is_tokenhub: bool
|
||||
is_lmstudio: bool
|
||||
is_custom_provider: bool
|
||||
ollama_num_ctx: int | None
|
||||
|
|
@ -190,6 +196,7 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
# Qwen-specific
|
||||
qwen_prepare_fn: callable | None — runs AFTER codex sanitization
|
||||
qwen_prepare_inplace_fn: callable | None — in-place variant for deepcopied lists
|
||||
qwen_session_metadata: dict | None
|
||||
# Temperature
|
||||
fixed_temperature: Any — from _fixed_temperature_for_model()
|
||||
omit_temperature: bool
|
||||
|
|
@ -199,28 +206,21 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
lmstudio_reasoning_options: list[str] | None # raw allowed_options from /api/v1/models
|
||||
# Claude on OpenRouter/Nous max output
|
||||
anthropic_max_output: int | None
|
||||
# Extra
|
||||
extra_body_additions: dict | None — pre-built extra_body entries
|
||||
extra_body_additions: dict | None
|
||||
"""
|
||||
# Codex sanitization: drop reasoning_items / call_id / response_item_id
|
||||
sanitized = self.convert_messages(messages)
|
||||
|
||||
# Qwen portal prep AFTER codex sanitization. If sanitize already
|
||||
# deepcopied, reuse that copy via the in-place variant to avoid a
|
||||
# second deepcopy.
|
||||
is_qwen = params.get("is_qwen_portal", False)
|
||||
if is_qwen:
|
||||
qwen_prep = params.get("qwen_prepare_fn")
|
||||
qwen_prep_inplace = params.get("qwen_prepare_inplace_fn")
|
||||
if sanitized is messages:
|
||||
if qwen_prep is not None:
|
||||
sanitized = qwen_prep(sanitized)
|
||||
else:
|
||||
# Already deepcopied — transform in place
|
||||
if qwen_prep_inplace is not None:
|
||||
qwen_prep_inplace(sanitized)
|
||||
elif qwen_prep is not None:
|
||||
sanitized = qwen_prep(sanitized)
|
||||
# ── Provider profile: single-path when present ──────────────────
|
||||
_profile = params.get("provider_profile")
|
||||
if _profile:
|
||||
return self._build_kwargs_from_profile(
|
||||
_profile, model, sanitized, tools, params
|
||||
)
|
||||
|
||||
# ── Legacy fallback (unregistered / unknown provider) ───────────
|
||||
# Reached only when get_provider_profile() returned None.
|
||||
# Known providers always go through the profile path above.
|
||||
|
||||
# Developer role swap for GPT-5/Codex models
|
||||
model_lower = params.get("model_lower", (model or "").lower())
|
||||
|
|
@ -233,7 +233,7 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
sanitized = list(sanitized)
|
||||
sanitized[0] = {**sanitized[0], "role": "developer"}
|
||||
|
||||
api_kwargs: Dict[str, Any] = {
|
||||
api_kwargs: dict[str, Any] = {
|
||||
"model": model,
|
||||
"messages": sanitized,
|
||||
}
|
||||
|
|
@ -242,19 +242,6 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
if timeout is not None:
|
||||
api_kwargs["timeout"] = timeout
|
||||
|
||||
# Temperature
|
||||
fixed_temp = params.get("fixed_temperature")
|
||||
omit_temp = params.get("omit_temperature", False)
|
||||
if omit_temp:
|
||||
api_kwargs.pop("temperature", None)
|
||||
elif fixed_temp is not None:
|
||||
api_kwargs["temperature"] = fixed_temp
|
||||
|
||||
# Qwen metadata (caller precomputes {sessionId, promptId})
|
||||
qwen_meta = params.get("qwen_session_metadata")
|
||||
if qwen_meta and is_qwen:
|
||||
api_kwargs["metadata"] = qwen_meta
|
||||
|
||||
# Tools
|
||||
if tools:
|
||||
# Moonshot/Kimi uses a stricter flavored JSON Schema. Rewriting
|
||||
|
|
@ -278,13 +265,6 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
api_kwargs.update(max_tokens_fn(ephemeral))
|
||||
elif max_tokens is not None and max_tokens_fn:
|
||||
api_kwargs.update(max_tokens_fn(max_tokens))
|
||||
elif is_nvidia_nim and max_tokens_fn:
|
||||
api_kwargs.update(max_tokens_fn(16384))
|
||||
elif is_qwen and max_tokens_fn:
|
||||
api_kwargs.update(max_tokens_fn(65536))
|
||||
elif is_kimi and max_tokens_fn:
|
||||
# Kimi/Moonshot: 32000 matches Kimi CLI's default
|
||||
api_kwargs.update(max_tokens_fn(32000))
|
||||
elif anthropic_max_out is not None:
|
||||
api_kwargs["max_tokens"] = anthropic_max_out
|
||||
|
||||
|
|
@ -331,7 +311,7 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
api_kwargs["reasoning_effort"] = _lm_effort
|
||||
|
||||
# extra_body assembly
|
||||
extra_body: Dict[str, Any] = {}
|
||||
extra_body: dict[str, Any] = {}
|
||||
|
||||
is_openrouter = params.get("is_openrouter", False)
|
||||
is_nous = params.get("is_nous", False)
|
||||
|
|
@ -361,35 +341,7 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
if gh_reasoning is not None:
|
||||
extra_body["reasoning"] = gh_reasoning
|
||||
else:
|
||||
if reasoning_config is not None:
|
||||
rc = dict(reasoning_config)
|
||||
if is_nous and rc.get("enabled") is False:
|
||||
pass # omit for Nous when disabled
|
||||
else:
|
||||
extra_body["reasoning"] = rc
|
||||
else:
|
||||
extra_body["reasoning"] = {"enabled": True, "effort": "medium"}
|
||||
|
||||
if is_nous:
|
||||
extra_body["tags"] = ["product=hermes-agent"]
|
||||
|
||||
# Ollama num_ctx
|
||||
ollama_ctx = params.get("ollama_num_ctx")
|
||||
if ollama_ctx:
|
||||
options = extra_body.get("options", {})
|
||||
options["num_ctx"] = ollama_ctx
|
||||
extra_body["options"] = options
|
||||
|
||||
# Ollama/custom think=false
|
||||
if params.get("is_custom_provider", False):
|
||||
if reasoning_config and isinstance(reasoning_config, dict):
|
||||
_effort = (reasoning_config.get("effort") or "").strip().lower()
|
||||
_enabled = reasoning_config.get("enabled", True)
|
||||
if _effort == "none" or _enabled is False:
|
||||
extra_body["think"] = False
|
||||
|
||||
if is_qwen:
|
||||
extra_body["vl_high_resolution_images"] = True
|
||||
extra_body["reasoning"] = {"enabled": True, "effort": "medium"}
|
||||
|
||||
if provider_name == "gemini":
|
||||
raw_thinking_config = _build_gemini_thinking_config(model, reasoning_config)
|
||||
|
|
@ -423,6 +375,120 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
|
||||
return api_kwargs
|
||||
|
||||
def _build_kwargs_from_profile(self, profile, model, sanitized, tools, params):
|
||||
"""Build API kwargs using a ProviderProfile — single path, no legacy flags.
|
||||
|
||||
This method replaces the entire flag-based kwargs assembly when a
|
||||
provider_profile is passed. Every quirk comes from the profile object.
|
||||
"""
|
||||
from providers.base import OMIT_TEMPERATURE
|
||||
|
||||
# Message preprocessing
|
||||
sanitized = profile.prepare_messages(sanitized)
|
||||
|
||||
# Developer role swap — model-name-based, applies to all providers
|
||||
_model_lower = (model or "").lower()
|
||||
if (
|
||||
sanitized
|
||||
and isinstance(sanitized[0], dict)
|
||||
and sanitized[0].get("role") == "system"
|
||||
and any(p in _model_lower for p in DEVELOPER_ROLE_MODELS)
|
||||
):
|
||||
sanitized = list(sanitized)
|
||||
sanitized[0] = {**sanitized[0], "role": "developer"}
|
||||
|
||||
api_kwargs: dict[str, Any] = {
|
||||
"model": model,
|
||||
"messages": sanitized,
|
||||
}
|
||||
|
||||
# Temperature
|
||||
if profile.fixed_temperature is OMIT_TEMPERATURE:
|
||||
pass # Don't include temperature at all
|
||||
elif profile.fixed_temperature is not None:
|
||||
api_kwargs["temperature"] = profile.fixed_temperature
|
||||
else:
|
||||
# Use caller's temperature if provided
|
||||
temp = params.get("temperature")
|
||||
if temp is not None:
|
||||
api_kwargs["temperature"] = temp
|
||||
|
||||
# Timeout
|
||||
timeout = params.get("timeout")
|
||||
if timeout is not None:
|
||||
api_kwargs["timeout"] = timeout
|
||||
|
||||
# Tools — apply Moonshot/Kimi schema sanitization regardless of path
|
||||
if tools:
|
||||
if is_moonshot_model(model):
|
||||
tools = sanitize_moonshot_tools(tools)
|
||||
api_kwargs["tools"] = tools
|
||||
|
||||
# max_tokens resolution — priority: ephemeral > user > profile default
|
||||
max_tokens_fn = params.get("max_tokens_param_fn")
|
||||
ephemeral = params.get("ephemeral_max_output_tokens")
|
||||
user_max = params.get("max_tokens")
|
||||
anthropic_max = params.get("anthropic_max_output")
|
||||
|
||||
if ephemeral is not None and max_tokens_fn:
|
||||
api_kwargs.update(max_tokens_fn(ephemeral))
|
||||
elif user_max is not None and max_tokens_fn:
|
||||
api_kwargs.update(max_tokens_fn(user_max))
|
||||
elif profile.default_max_tokens and max_tokens_fn:
|
||||
api_kwargs.update(max_tokens_fn(profile.default_max_tokens))
|
||||
elif anthropic_max is not None:
|
||||
api_kwargs["max_tokens"] = anthropic_max
|
||||
|
||||
# Provider-specific api_kwargs extras (reasoning_effort, metadata, etc.)
|
||||
reasoning_config = params.get("reasoning_config")
|
||||
extra_body_from_profile, top_level_from_profile = (
|
||||
profile.build_api_kwargs_extras(
|
||||
reasoning_config=reasoning_config,
|
||||
supports_reasoning=params.get("supports_reasoning", False),
|
||||
qwen_session_metadata=params.get("qwen_session_metadata"),
|
||||
model=model,
|
||||
ollama_num_ctx=params.get("ollama_num_ctx"),
|
||||
)
|
||||
)
|
||||
api_kwargs.update(top_level_from_profile)
|
||||
|
||||
# extra_body assembly
|
||||
extra_body: dict[str, Any] = {}
|
||||
|
||||
# Profile's extra_body (tags, provider prefs, vl_high_resolution, etc.)
|
||||
profile_body = profile.build_extra_body(
|
||||
session_id=params.get("session_id"),
|
||||
provider_preferences=params.get("provider_preferences"),
|
||||
model=model,
|
||||
base_url=params.get("base_url"),
|
||||
reasoning_config=reasoning_config,
|
||||
)
|
||||
if profile_body:
|
||||
extra_body.update(profile_body)
|
||||
|
||||
# Profile's reasoning/thinking extra_body entries
|
||||
if extra_body_from_profile:
|
||||
extra_body.update(extra_body_from_profile)
|
||||
|
||||
# Merge any pre-built extra_body additions from the caller
|
||||
additions = params.get("extra_body_additions")
|
||||
if additions:
|
||||
extra_body.update(additions)
|
||||
|
||||
# Request overrides (user config)
|
||||
overrides = params.get("request_overrides")
|
||||
if overrides:
|
||||
for k, v in overrides.items():
|
||||
if k == "extra_body" and isinstance(v, dict):
|
||||
extra_body.update(v)
|
||||
else:
|
||||
api_kwargs[k] = v
|
||||
|
||||
if extra_body:
|
||||
api_kwargs["extra_body"] = extra_body
|
||||
|
||||
return api_kwargs
|
||||
|
||||
def normalize_response(self, response: Any, **kwargs) -> NormalizedResponse:
|
||||
"""Normalize OpenAI ChatCompletion to NormalizedResponse.
|
||||
|
||||
|
|
@ -444,7 +510,7 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
# Gemini 3 thinking models attach extra_content with
|
||||
# thought_signature — without replay on the next turn the API
|
||||
# rejects the request with 400.
|
||||
tc_provider_data: Dict[str, Any] = {}
|
||||
tc_provider_data: dict[str, Any] = {}
|
||||
extra = getattr(tc, "extra_content", None)
|
||||
if extra is None and hasattr(tc, "model_extra"):
|
||||
extra = (tc.model_extra or {}).get("extra_content")
|
||||
|
|
@ -455,12 +521,14 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
except Exception:
|
||||
pass
|
||||
tc_provider_data["extra_content"] = extra
|
||||
tool_calls.append(ToolCall(
|
||||
id=tc.id,
|
||||
name=tc.function.name,
|
||||
arguments=tc.function.arguments,
|
||||
provider_data=tc_provider_data or None,
|
||||
))
|
||||
tool_calls.append(
|
||||
ToolCall(
|
||||
id=tc.id,
|
||||
name=tc.function.name,
|
||||
arguments=tc.function.arguments,
|
||||
provider_data=tc_provider_data or None,
|
||||
)
|
||||
)
|
||||
|
||||
usage = None
|
||||
if hasattr(response, "usage") and response.usage:
|
||||
|
|
@ -508,7 +576,7 @@ class ChatCompletionsTransport(ProviderTransport):
|
|||
return False
|
||||
return True
|
||||
|
||||
def extract_cache_stats(self, response: Any) -> Optional[Dict[str, int]]:
|
||||
def extract_cache_stats(self, response: Any) -> dict[str, int] | None:
|
||||
"""Extract OpenRouter/OpenAI cache stats from prompt_tokens_details."""
|
||||
usage = getattr(response, "usage", None)
|
||||
if usage is None:
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ from __future__ import annotations
|
|||
|
||||
import json
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Any, Dict, List, Optional
|
||||
from typing import Any
|
||||
|
||||
|
||||
@dataclass
|
||||
|
|
@ -32,10 +32,10 @@ class ToolCall:
|
|||
* Others: ``None``
|
||||
"""
|
||||
|
||||
id: Optional[str]
|
||||
id: str | None
|
||||
name: str
|
||||
arguments: str # JSON string
|
||||
provider_data: Optional[Dict[str, Any]] = field(default=None, repr=False)
|
||||
provider_data: dict[str, Any] | None = field(default=None, repr=False)
|
||||
|
||||
# ── Backward compatibility ──────────────────────────────────
|
||||
# The agent loop reads tc.function.name / tc.function.arguments
|
||||
|
|
@ -47,17 +47,17 @@ class ToolCall:
|
|||
return "function"
|
||||
|
||||
@property
|
||||
def function(self) -> "ToolCall":
|
||||
def function(self) -> ToolCall:
|
||||
"""Return self so tc.function.name / tc.function.arguments work."""
|
||||
return self
|
||||
|
||||
@property
|
||||
def call_id(self) -> Optional[str]:
|
||||
def call_id(self) -> str | None:
|
||||
"""Codex call_id from provider_data, accessed via getattr by _build_assistant_message."""
|
||||
return (self.provider_data or {}).get("call_id")
|
||||
|
||||
@property
|
||||
def response_item_id(self) -> Optional[str]:
|
||||
def response_item_id(self) -> str | None:
|
||||
"""Codex response_item_id from provider_data."""
|
||||
return (self.provider_data or {}).get("response_item_id")
|
||||
|
||||
|
|
@ -101,18 +101,18 @@ class NormalizedResponse:
|
|||
* Others: ``None``
|
||||
"""
|
||||
|
||||
content: Optional[str]
|
||||
tool_calls: Optional[List[ToolCall]]
|
||||
content: str | None
|
||||
tool_calls: list[ToolCall] | None
|
||||
finish_reason: str # "stop", "tool_calls", "length", "content_filter"
|
||||
reasoning: Optional[str] = None
|
||||
usage: Optional[Usage] = None
|
||||
provider_data: Optional[Dict[str, Any]] = field(default=None, repr=False)
|
||||
reasoning: str | None = None
|
||||
usage: Usage | None = None
|
||||
provider_data: dict[str, Any] | None = field(default=None, repr=False)
|
||||
|
||||
# ── Backward compatibility ──────────────────────────────────
|
||||
# The shim _nr_to_assistant_message() mapped these from provider_data.
|
||||
# These properties let NormalizedResponse pass through directly.
|
||||
@property
|
||||
def reasoning_content(self) -> Optional[str]:
|
||||
def reasoning_content(self) -> str | None:
|
||||
pd = self.provider_data or {}
|
||||
return pd.get("reasoning_content")
|
||||
|
||||
|
|
@ -136,8 +136,9 @@ class NormalizedResponse:
|
|||
# Factory helpers
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def build_tool_call(
|
||||
id: Optional[str],
|
||||
id: str | None,
|
||||
name: str,
|
||||
arguments: Any,
|
||||
**provider_fields: Any,
|
||||
|
|
@ -151,7 +152,7 @@ def build_tool_call(
|
|||
return ToolCall(id=id, name=name, arguments=args_str, provider_data=pd)
|
||||
|
||||
|
||||
def map_finish_reason(reason: Optional[str], mapping: Dict[str, str]) -> str:
|
||||
def map_finish_reason(reason: str | None, mapping: dict[str, str]) -> str:
|
||||
"""Translate a provider-specific stop reason to the normalised set.
|
||||
|
||||
Falls back to ``"stop"`` for unknown or ``None`` reasons.
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue