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Author SHA1 Message Date
kshitijk4poor
84d1673e2f feat: provider modules — ProviderProfile ABC, 30 providers, fetch_models, transport single-path
feat: provider modules — ProviderProfile ABC, 29 providers, fetch_models, transport single-path

Introduces providers/ as the single source of truth for every inference
provider. All 29 providers declared with correct data cross-checked against
auth.py, runtime_provider.py and auxiliary_client.py.

Rebased onto main (30307a980). Incorporates post-salvage fixes from
56724147e (gmi aux model google/gemini-3.1-flash-lite-preview, already set in providers/gmi.py).
2026-04-29 20:10:09 +05:30
60 changed files with 3939 additions and 1034 deletions

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@@ -0,0 +1,632 @@
"""OpenAI-compatible shim that forwards Hermes requests to `copilot --acp`.
This adapter lets Hermes treat the GitHub Copilot ACP server as a chat-style
backend. Each request starts a short-lived ACP session, sends the formatted
conversation as a single prompt, collects text chunks, and converts the result
back into the minimal shape Hermes expects from an OpenAI client.
"""
from __future__ import annotations
import json
import os
import queue
import re
import shlex
import subprocess
import threading
import time
from collections import deque
from pathlib import Path
from types import SimpleNamespace
from typing import Any
from agent.file_safety import get_read_block_error, is_write_denied
from agent.redact import redact_sensitive_text
ACP_MARKER_BASE_URL = "acp://copilot"
_DEFAULT_TIMEOUT_SECONDS = 900.0
_TOOL_CALL_BLOCK_RE = re.compile(r"<tool_call>\s*(\{.*?\})\s*</tool_call>", re.DOTALL)
_TOOL_CALL_JSON_RE = re.compile(
r"\{\s*\"id\"\s*:\s*\"[^\"]+\"\s*,\s*\"type\"\s*:\s*\"function\"\s*,\s*\"function\"\s*:\s*\{.*?\}\s*\}",
re.DOTALL,
)
def _resolve_command() -> str:
return (
os.getenv("HERMES_COPILOT_ACP_COMMAND", "").strip()
or os.getenv("COPILOT_CLI_PATH", "").strip()
or "copilot"
)
def _resolve_args() -> list[str]:
raw = os.getenv("HERMES_COPILOT_ACP_ARGS", "").strip()
if not raw:
return ["--acp", "--stdio"]
return shlex.split(raw)
def _jsonrpc_error(message_id: Any, code: int, message: str) -> dict[str, Any]:
return {
"jsonrpc": "2.0",
"id": message_id,
"error": {
"code": code,
"message": message,
},
}
def _permission_denied(message_id: Any) -> dict[str, Any]:
return {
"jsonrpc": "2.0",
"id": message_id,
"result": {
"outcome": {
"outcome": "cancelled",
}
},
}
def _format_messages_as_prompt(
messages: list[dict[str, Any]],
model: str | None = None,
tools: list[dict[str, Any]] | None = None,
tool_choice: Any = None,
) -> str:
sections: list[str] = [
"You are being used as the active ACP agent backend for Hermes.",
"Use ACP capabilities to complete tasks.",
"IMPORTANT: If you take an action with a tool, you MUST output tool calls using <tool_call>{...}</tool_call> blocks with JSON exactly in OpenAI function-call shape.",
"If no tool is needed, answer normally.",
]
if model:
sections.append(f"Hermes requested model hint: {model}")
if isinstance(tools, list) and tools:
tool_specs: list[dict[str, Any]] = []
for t in tools:
if not isinstance(t, dict):
continue
fn = t.get("function") or {}
if not isinstance(fn, dict):
continue
name = fn.get("name")
if not isinstance(name, str) or not name.strip():
continue
tool_specs.append(
{
"name": name.strip(),
"description": fn.get("description", ""),
"parameters": fn.get("parameters", {}),
}
)
if tool_specs:
sections.append(
"Available tools (OpenAI function schema). "
"When using a tool, emit ONLY <tool_call>{...}</tool_call> with one JSON object "
"containing id/type/function{name,arguments}. arguments must be a JSON string.\n"
+ json.dumps(tool_specs, ensure_ascii=False)
)
if tool_choice is not None:
sections.append(
f"Tool choice hint: {json.dumps(tool_choice, ensure_ascii=False)}"
)
transcript: list[str] = []
for message in messages:
if not isinstance(message, dict):
continue
role = str(message.get("role") or "unknown").strip().lower()
if role == "tool":
role = "tool"
elif role not in {"system", "user", "assistant"}:
role = "context"
content = message.get("content")
rendered = _render_message_content(content)
if not rendered:
continue
label = {
"system": "System",
"user": "User",
"assistant": "Assistant",
"tool": "Tool",
"context": "Context",
}.get(role, role.title())
transcript.append(f"{label}:\n{rendered}")
if transcript:
sections.append("Conversation transcript:\n\n" + "\n\n".join(transcript))
sections.append("Continue the conversation from the latest user request.")
return "\n\n".join(
section.strip() for section in sections if section and section.strip()
)
def _render_message_content(content: Any) -> str:
if content is None:
return ""
if isinstance(content, str):
return content.strip()
if isinstance(content, dict):
if "text" in content:
return str(content.get("text") or "").strip()
if "content" in content and isinstance(content.get("content"), str):
return str(content.get("content") or "").strip()
return json.dumps(content, ensure_ascii=True)
if isinstance(content, list):
parts: list[str] = []
for item in content:
if isinstance(item, str):
parts.append(item)
elif isinstance(item, dict):
text = item.get("text")
if isinstance(text, str) and text.strip():
parts.append(text.strip())
return "\n".join(parts).strip()
return str(content).strip()
def _extract_tool_calls_from_text(text: str) -> tuple[list[SimpleNamespace], str]:
if not isinstance(text, str) or not text.strip():
return [], ""
extracted: list[SimpleNamespace] = []
consumed_spans: list[tuple[int, int]] = []
def _try_add_tool_call(raw_json: str) -> None:
try:
obj = json.loads(raw_json)
except Exception:
return
if not isinstance(obj, dict):
return
fn = obj.get("function")
if not isinstance(fn, dict):
return
fn_name = fn.get("name")
if not isinstance(fn_name, str) or not fn_name.strip():
return
fn_args = fn.get("arguments", "{}")
if not isinstance(fn_args, str):
fn_args = json.dumps(fn_args, ensure_ascii=False)
call_id = obj.get("id")
if not isinstance(call_id, str) or not call_id.strip():
call_id = f"acp_call_{len(extracted) + 1}"
extracted.append(
SimpleNamespace(
id=call_id,
call_id=call_id,
response_item_id=None,
type="function",
function=SimpleNamespace(name=fn_name.strip(), arguments=fn_args),
)
)
for m in _TOOL_CALL_BLOCK_RE.finditer(text):
raw = m.group(1)
_try_add_tool_call(raw)
consumed_spans.append((m.start(), m.end()))
# Only try bare-JSON fallback when no XML blocks were found.
if not extracted:
for m in _TOOL_CALL_JSON_RE.finditer(text):
raw = m.group(0)
_try_add_tool_call(raw)
consumed_spans.append((m.start(), m.end()))
if not consumed_spans:
return extracted, text.strip()
consumed_spans.sort()
merged: list[tuple[int, int]] = []
for start, end in consumed_spans:
if not merged or start > merged[-1][1]:
merged.append((start, end))
else:
merged[-1] = (merged[-1][0], max(merged[-1][1], end))
parts: list[str] = []
cursor = 0
for start, end in merged:
if cursor < start:
parts.append(text[cursor:start])
cursor = max(cursor, end)
if cursor < len(text):
parts.append(text[cursor:])
cleaned = "\n".join(p.strip() for p in parts if p and p.strip()).strip()
return extracted, cleaned
def _ensure_path_within_cwd(path_text: str, cwd: str) -> Path:
candidate = Path(path_text)
if not candidate.is_absolute():
raise PermissionError("ACP file-system paths must be absolute.")
resolved = candidate.resolve()
root = Path(cwd).resolve()
try:
resolved.relative_to(root)
except ValueError as exc:
raise PermissionError(
f"Path '{resolved}' is outside the session cwd '{root}'."
) from exc
return resolved
class _ACPChatCompletions:
def __init__(self, client: CopilotACPClient):
self._client = client
def create(self, **kwargs: Any) -> Any:
return self._client._create_chat_completion(**kwargs)
class _ACPChatNamespace:
def __init__(self, client: CopilotACPClient):
self.completions = _ACPChatCompletions(client)
class CopilotACPClient:
"""Minimal OpenAI-client-compatible facade for Copilot ACP."""
def __init__(
self,
*,
api_key: str | None = None,
base_url: str | None = None,
default_headers: dict[str, str] | None = None,
acp_command: str | None = None,
acp_args: list[str] | None = None,
acp_cwd: str | None = None,
command: str | None = None,
args: list[str] | None = None,
**_: Any,
):
self.api_key = api_key or "copilot-acp"
self.base_url = base_url or ACP_MARKER_BASE_URL
self._default_headers = dict(default_headers or {})
self._acp_command = acp_command or command or _resolve_command()
self._acp_args = list(acp_args or args or _resolve_args())
self._acp_cwd = str(Path(acp_cwd or os.getcwd()).resolve())
self.chat = _ACPChatNamespace(self)
self.is_closed = False
self._active_process: subprocess.Popen[str] | None = None
self._active_process_lock = threading.Lock()
def close(self) -> None:
proc: subprocess.Popen[str] | None
with self._active_process_lock:
proc = self._active_process
self._active_process = None
self.is_closed = True
if proc is None:
return
try:
proc.terminate()
proc.wait(timeout=2)
except Exception:
try:
proc.kill()
except Exception:
pass
def _create_chat_completion(
self,
*,
model: str | None = None,
messages: list[dict[str, Any]] | None = None,
timeout: float | None = None,
tools: list[dict[str, Any]] | None = None,
tool_choice: Any = None,
**_: Any,
) -> Any:
prompt_text = _format_messages_as_prompt(
messages or [],
model=model,
tools=tools,
tool_choice=tool_choice,
)
# Normalise timeout: run_agent.py may pass an httpx.Timeout object
# (used natively by the OpenAI SDK) rather than a plain float.
if timeout is None:
_effective_timeout = _DEFAULT_TIMEOUT_SECONDS
elif isinstance(timeout, (int, float)):
_effective_timeout = float(timeout)
else:
# httpx.Timeout or similar — pick the largest component so the
# subprocess has enough wall-clock time for the full response.
_candidates = [
getattr(timeout, attr, None)
for attr in ("read", "write", "connect", "pool", "timeout")
]
_numeric = [float(v) for v in _candidates if isinstance(v, (int, float))]
_effective_timeout = max(_numeric) if _numeric else _DEFAULT_TIMEOUT_SECONDS
response_text, reasoning_text = self._run_prompt(
prompt_text,
timeout_seconds=_effective_timeout,
)
tool_calls, cleaned_text = _extract_tool_calls_from_text(response_text)
usage = SimpleNamespace(
prompt_tokens=0,
completion_tokens=0,
total_tokens=0,
prompt_tokens_details=SimpleNamespace(cached_tokens=0),
)
assistant_message = SimpleNamespace(
content=cleaned_text,
tool_calls=tool_calls,
reasoning=reasoning_text or None,
reasoning_content=reasoning_text or None,
reasoning_details=None,
)
finish_reason = "tool_calls" if tool_calls else "stop"
choice = SimpleNamespace(message=assistant_message, finish_reason=finish_reason)
return SimpleNamespace(
choices=[choice],
usage=usage,
model=model or "copilot-acp",
)
def _run_prompt(
self, prompt_text: str, *, timeout_seconds: float
) -> tuple[str, str]:
try:
proc = subprocess.Popen(
[self._acp_command] + self._acp_args,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True,
bufsize=1,
cwd=self._acp_cwd,
)
except FileNotFoundError as exc:
raise RuntimeError(
f"Could not start Copilot ACP command '{self._acp_command}'. "
"Install GitHub Copilot CLI or set HERMES_COPILOT_ACP_COMMAND/COPILOT_CLI_PATH."
) from exc
if proc.stdin is None or proc.stdout is None:
proc.kill()
raise RuntimeError("Copilot ACP process did not expose stdin/stdout pipes.")
self.is_closed = False
with self._active_process_lock:
self._active_process = proc
inbox: queue.Queue[dict[str, Any]] = queue.Queue()
stderr_tail: deque[str] = deque(maxlen=40)
def _stdout_reader() -> None:
if proc.stdout is None:
return
for line in proc.stdout:
try:
inbox.put(json.loads(line))
except Exception:
inbox.put({"raw": line.rstrip("\n")})
def _stderr_reader() -> None:
if proc.stderr is None:
return
for line in proc.stderr:
stderr_tail.append(line.rstrip("\n"))
out_thread = threading.Thread(target=_stdout_reader, daemon=True)
err_thread = threading.Thread(target=_stderr_reader, daemon=True)
out_thread.start()
err_thread.start()
next_id = 0
def _request(
method: str,
params: dict[str, Any],
*,
text_parts: list[str] | None = None,
reasoning_parts: list[str] | None = None,
) -> Any:
nonlocal next_id
next_id += 1
request_id = next_id
payload = {
"jsonrpc": "2.0",
"id": request_id,
"method": method,
"params": params,
}
assert proc.stdin is not None # always set: Popen(stdin=PIPE)
proc.stdin.write(json.dumps(payload) + "\n")
proc.stdin.flush()
deadline = time.time() + timeout_seconds
while time.time() < deadline:
if proc.poll() is not None:
break
try:
msg = inbox.get(timeout=0.1)
except queue.Empty:
continue
if self._handle_server_message(
msg,
process=proc,
cwd=self._acp_cwd,
text_parts=text_parts,
reasoning_parts=reasoning_parts,
):
continue
if msg.get("id") != request_id:
continue
if "error" in msg:
err = msg.get("error") or {}
raise RuntimeError(
f"Copilot ACP {method} failed: {err.get('message') or err}"
)
return msg.get("result")
stderr_text = "\n".join(stderr_tail).strip()
if proc.poll() is not None and stderr_text:
raise RuntimeError(f"Copilot ACP process exited early: {stderr_text}")
raise TimeoutError(
f"Timed out waiting for Copilot ACP response to {method}."
)
try:
_request(
"initialize",
{
"protocolVersion": 1,
"clientCapabilities": {
"fs": {
"readTextFile": True,
"writeTextFile": True,
}
},
"clientInfo": {
"name": "hermes-agent",
"title": "Hermes Agent",
"version": "0.0.0",
},
},
)
session = (
_request(
"session/new",
{
"cwd": self._acp_cwd,
"mcpServers": [],
},
)
or {}
)
session_id = str(session.get("sessionId") or "").strip()
if not session_id:
raise RuntimeError("Copilot ACP did not return a sessionId.")
text_parts: list[str] = []
reasoning_parts: list[str] = []
_request(
"session/prompt",
{
"sessionId": session_id,
"prompt": [
{
"type": "text",
"text": prompt_text,
}
],
},
text_parts=text_parts,
reasoning_parts=reasoning_parts,
)
return "".join(text_parts), "".join(reasoning_parts)
finally:
self.close()
def _handle_server_message(
self,
msg: dict[str, Any],
*,
process: subprocess.Popen[str],
cwd: str,
text_parts: list[str] | None,
reasoning_parts: list[str] | None,
) -> bool:
method = msg.get("method")
if not isinstance(method, str):
return False
if method == "session/update":
params = msg.get("params") or {}
update = params.get("update") or {}
kind = str(update.get("sessionUpdate") or "").strip()
content = update.get("content") or {}
chunk_text = ""
if isinstance(content, dict):
chunk_text = str(content.get("text") or "")
if kind == "agent_message_chunk" and chunk_text and text_parts is not None:
text_parts.append(chunk_text)
elif (
kind == "agent_thought_chunk"
and chunk_text
and reasoning_parts is not None
):
reasoning_parts.append(chunk_text)
return True
if process.stdin is None:
return True
message_id = msg.get("id")
params = msg.get("params") or {}
if method == "session/request_permission":
response = _permission_denied(message_id)
elif method == "fs/read_text_file":
try:
path = _ensure_path_within_cwd(str(params.get("path") or ""), cwd)
block_error = get_read_block_error(str(path))
if block_error:
raise PermissionError(block_error)
content = path.read_text() if path.exists() else ""
line = params.get("line")
limit = params.get("limit")
if isinstance(line, int) and line > 1:
lines = content.splitlines(keepends=True)
start = line - 1
end = (
start + limit if isinstance(limit, int) and limit > 0 else None
)
content = "".join(lines[start:end])
if content:
content = redact_sensitive_text(content)
response = {
"jsonrpc": "2.0",
"id": message_id,
"result": {
"content": content,
},
}
except Exception as exc:
response = _jsonrpc_error(message_id, -32602, str(exc))
elif method == "fs/write_text_file":
try:
path = _ensure_path_within_cwd(str(params.get("path") or ""), cwd)
if is_write_denied(str(path)):
raise PermissionError(
f"Write denied: '{path}' is a protected system/credential file."
)
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(str(params.get("content") or ""))
response = {
"jsonrpc": "2.0",
"id": message_id,
"result": None,
}
except Exception as exc:
response = _jsonrpc_error(message_id, -32602, str(exc))
else:
response = _jsonrpc_error(
message_id,
-32601,
f"ACP client method '{method}' is not supported by Hermes yet.",
)
process.stdin.write(json.dumps(response) + "\n")
process.stdin.flush()
return True

View File

@@ -151,23 +151,31 @@ 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] = {
"gemini": "gemini-3-flash-preview",
"zai": "glm-4.5-flash",
"kimi-coding": "kimi-k2-turbo-preview",
"stepfun": "step-3.5-flash",
"kimi-coding-cn": "kimi-k2-turbo-preview",
"gmi": "google/gemini-3.1-flash-lite-preview",
"minimax": "MiniMax-M2.7",
"minimax-cn": "MiniMax-M2.7",
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.
# New providers should set default_aux_model on their profile instead.
_API_KEY_PROVIDER_AUX_MODELS_FALLBACK: Dict[str, str] = {
"anthropic": "claude-haiku-4-5-20251001",
"ai-gateway": "google/gemini-3-flash",
"opencode-zen": "gemini-3-flash",
"opencode-go": "glm-5",
"kilocode": "google/gemini-3-flash-preview",
"ollama-cloud": "nemotron-3-nano:30b",
}
# Legacy alias — callers that haven't been updated yet can still use this.
_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
@@ -868,7 +876,7 @@ def _resolve_api_key_provider() -> Tuple[Optional[OpenAI], Optional[str]]:
base_url = _to_openai_base_url(
_pool_runtime_base_url(entry, pconfig.inference_base_url) or pconfig.inference_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)
@@ -877,14 +885,22 @@ def _resolve_api_key_provider() -> Tuple[Optional[OpenAI], Optional[str]]:
if is_native_gemini_base_url(base_url):
return GeminiNativeClient(api_key=api_key, base_url=base_url), model
extra = {}
if base_url_host_matches(base_url, "api.kimi.com"):
extra["default_headers"] = {"User-Agent": "claude-code/0.1.0"}
elif base_url_host_matches(base_url, "api.githubcopilot.com"):
from hermes_cli.models import copilot_default_headers
extra = {}
if base_url_host_matches(base_url, "api.kimi.com"):
extra["default_headers"] = {"User-Agent": "claude-code/0.1.0"}
elif base_url_host_matches(base_url, "api.githubcopilot.com"):
from hermes_cli.models import copilot_default_headers
extra["default_headers"] = copilot_default_headers()
return OpenAI(api_key=api_key, base_url=base_url, **extra), model
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
return OpenAI(api_key=api_key, base_url=base_url, **extra), model
creds = resolve_api_key_provider_credentials(provider_id)
api_key = str(creds.get("api_key", "")).strip()
@@ -894,7 +910,7 @@ def _resolve_api_key_provider() -> Tuple[Optional[OpenAI], Optional[str]]:
base_url = _to_openai_base_url(
str(creds.get("base_url", "")).strip().rstrip("/") or pconfig.inference_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)
@@ -910,6 +926,14 @@ 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
return OpenAI(api_key=api_key, base_url=base_url, **extra), model
return None, None
@@ -1258,7 +1282,7 @@ def _try_anthropic() -> Tuple[Optional[Any], Optional[str]]:
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)
@@ -1642,7 +1666,7 @@ def _to_async_client(sync_client, model: str, is_vision: bool = False):
except ImportError:
pass
try:
from agent.copilot_acp_client import CopilotACPClient
from acp_adapter.copilot_client import CopilotACPClient
if isinstance(sync_client, CopilotACPClient):
return sync_client, model
except ImportError:
@@ -1986,7 +2010,7 @@ def resolve_provider_client(
str(creds.get("base_url", "")).strip().rstrip("/") or pconfig.inference_base_url
)
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":
@@ -2056,7 +2080,7 @@ def resolve_provider_client(
"process credentials are incomplete"
)
return None, None
from agent.copilot_acp_client import CopilotACPClient
from acp_adapter.copilot_client import CopilotACPClient
client = CopilotACPClient(
api_key=api_key,

View File

@@ -1,646 +1,8 @@
"""OpenAI-compatible shim that forwards Hermes requests to `copilot --acp`.
"""Backward-compatibility shim.
This adapter lets Hermes treat the GitHub Copilot ACP server as a chat-style
backend. Each request starts a short-lived ACP session, sends the formatted
conversation as a single prompt, collects text chunks, and converts the result
back into the minimal shape Hermes expects from an OpenAI client.
CopilotACPClient has moved to acp_adapter/copilot_client.py.
This module re-exports it so existing callers continue to work.
"""
from acp_adapter.copilot_client import CopilotACPClient # noqa: F401
from __future__ import annotations
import json
import os
import queue
import re
import shlex
import subprocess
import threading
import time
from collections import deque
from pathlib import Path
from types import SimpleNamespace
from typing import Any
from agent.file_safety import get_read_block_error, is_write_denied
from agent.redact import redact_sensitive_text
ACP_MARKER_BASE_URL = "acp://copilot"
_DEFAULT_TIMEOUT_SECONDS = 900.0
_TOOL_CALL_BLOCK_RE = re.compile(r"<tool_call>\s*(\{.*?\})\s*</tool_call>", re.DOTALL)
_TOOL_CALL_JSON_RE = re.compile(r"\{\s*\"id\"\s*:\s*\"[^\"]+\"\s*,\s*\"type\"\s*:\s*\"function\"\s*,\s*\"function\"\s*:\s*\{.*?\}\s*\}", re.DOTALL)
def _resolve_command() -> str:
return (
os.getenv("HERMES_COPILOT_ACP_COMMAND", "").strip()
or os.getenv("COPILOT_CLI_PATH", "").strip()
or "copilot"
)
def _resolve_args() -> list[str]:
raw = os.getenv("HERMES_COPILOT_ACP_ARGS", "").strip()
if not raw:
return ["--acp", "--stdio"]
return shlex.split(raw)
def _resolve_home_dir() -> str:
"""Return a stable HOME for child ACP processes."""
try:
from hermes_constants import get_subprocess_home
profile_home = get_subprocess_home()
if profile_home:
return profile_home
except Exception:
pass
home = os.environ.get("HOME", "").strip()
if home:
return home
expanded = os.path.expanduser("~")
if expanded and expanded != "~":
return expanded
try:
import pwd
resolved = pwd.getpwuid(os.getuid()).pw_dir.strip()
if resolved:
return resolved
except Exception:
pass
# Last resort: /tmp (writable on any POSIX system). Avoids crashing the
# subprocess with no HOME; callers can set HERMES_HOME explicitly if they
# need a different writable dir.
return "/tmp"
def _build_subprocess_env() -> dict[str, str]:
env = os.environ.copy()
env["HOME"] = _resolve_home_dir()
return env
def _jsonrpc_error(message_id: Any, code: int, message: str) -> dict[str, Any]:
return {
"jsonrpc": "2.0",
"id": message_id,
"error": {
"code": code,
"message": message,
},
}
def _permission_denied(message_id: Any) -> dict[str, Any]:
return {
"jsonrpc": "2.0",
"id": message_id,
"result": {
"outcome": {
"outcome": "cancelled",
}
},
}
def _format_messages_as_prompt(
messages: list[dict[str, Any]],
model: str | None = None,
tools: list[dict[str, Any]] | None = None,
tool_choice: Any = None,
) -> str:
sections: list[str] = [
"You are being used as the active ACP agent backend for Hermes.",
"Use ACP capabilities to complete tasks.",
"IMPORTANT: If you take an action with a tool, you MUST output tool calls using <tool_call>{...}</tool_call> blocks with JSON exactly in OpenAI function-call shape.",
"If no tool is needed, answer normally.",
]
if model:
sections.append(f"Hermes requested model hint: {model}")
if isinstance(tools, list) and tools:
tool_specs: list[dict[str, Any]] = []
for t in tools:
if not isinstance(t, dict):
continue
fn = t.get("function") or {}
if not isinstance(fn, dict):
continue
name = fn.get("name")
if not isinstance(name, str) or not name.strip():
continue
tool_specs.append(
{
"name": name.strip(),
"description": fn.get("description", ""),
"parameters": fn.get("parameters", {}),
}
)
if tool_specs:
sections.append(
"Available tools (OpenAI function schema). "
"When using a tool, emit ONLY <tool_call>{...}</tool_call> with one JSON object "
"containing id/type/function{name,arguments}. arguments must be a JSON string.\n"
+ json.dumps(tool_specs, ensure_ascii=False)
)
if tool_choice is not None:
sections.append(f"Tool choice hint: {json.dumps(tool_choice, ensure_ascii=False)}")
transcript: list[str] = []
for message in messages:
if not isinstance(message, dict):
continue
role = str(message.get("role") or "unknown").strip().lower()
if role == "tool":
role = "tool"
elif role not in {"system", "user", "assistant"}:
role = "context"
content = message.get("content")
rendered = _render_message_content(content)
if not rendered:
continue
label = {
"system": "System",
"user": "User",
"assistant": "Assistant",
"tool": "Tool",
"context": "Context",
}.get(role, role.title())
transcript.append(f"{label}:\n{rendered}")
if transcript:
sections.append("Conversation transcript:\n\n" + "\n\n".join(transcript))
sections.append("Continue the conversation from the latest user request.")
return "\n\n".join(section.strip() for section in sections if section and section.strip())
def _render_message_content(content: Any) -> str:
if content is None:
return ""
if isinstance(content, str):
return content.strip()
if isinstance(content, dict):
if "text" in content:
return str(content.get("text") or "").strip()
if "content" in content and isinstance(content.get("content"), str):
return str(content.get("content") or "").strip()
return json.dumps(content, ensure_ascii=True)
if isinstance(content, list):
parts: list[str] = []
for item in content:
if isinstance(item, str):
parts.append(item)
elif isinstance(item, dict):
text = item.get("text")
if isinstance(text, str) and text.strip():
parts.append(text.strip())
return "\n".join(parts).strip()
return str(content).strip()
def _extract_tool_calls_from_text(text: str) -> tuple[list[SimpleNamespace], str]:
if not isinstance(text, str) or not text.strip():
return [], ""
extracted: list[SimpleNamespace] = []
consumed_spans: list[tuple[int, int]] = []
def _try_add_tool_call(raw_json: str) -> None:
try:
obj = json.loads(raw_json)
except Exception:
return
if not isinstance(obj, dict):
return
fn = obj.get("function")
if not isinstance(fn, dict):
return
fn_name = fn.get("name")
if not isinstance(fn_name, str) or not fn_name.strip():
return
fn_args = fn.get("arguments", "{}")
if not isinstance(fn_args, str):
fn_args = json.dumps(fn_args, ensure_ascii=False)
call_id = obj.get("id")
if not isinstance(call_id, str) or not call_id.strip():
call_id = f"acp_call_{len(extracted)+1}"
extracted.append(
SimpleNamespace(
id=call_id,
call_id=call_id,
response_item_id=None,
type="function",
function=SimpleNamespace(name=fn_name.strip(), arguments=fn_args),
)
)
for m in _TOOL_CALL_BLOCK_RE.finditer(text):
raw = m.group(1)
_try_add_tool_call(raw)
consumed_spans.append((m.start(), m.end()))
# Only try bare-JSON fallback when no XML blocks were found.
if not extracted:
for m in _TOOL_CALL_JSON_RE.finditer(text):
raw = m.group(0)
_try_add_tool_call(raw)
consumed_spans.append((m.start(), m.end()))
if not consumed_spans:
return extracted, text.strip()
consumed_spans.sort()
merged: list[tuple[int, int]] = []
for start, end in consumed_spans:
if not merged or start > merged[-1][1]:
merged.append((start, end))
else:
merged[-1] = (merged[-1][0], max(merged[-1][1], end))
parts: list[str] = []
cursor = 0
for start, end in merged:
if cursor < start:
parts.append(text[cursor:start])
cursor = max(cursor, end)
if cursor < len(text):
parts.append(text[cursor:])
cleaned = "\n".join(p.strip() for p in parts if p and p.strip()).strip()
return extracted, cleaned
def _ensure_path_within_cwd(path_text: str, cwd: str) -> Path:
candidate = Path(path_text)
if not candidate.is_absolute():
raise PermissionError("ACP file-system paths must be absolute.")
resolved = candidate.resolve()
root = Path(cwd).resolve()
try:
resolved.relative_to(root)
except ValueError as exc:
raise PermissionError(f"Path '{resolved}' is outside the session cwd '{root}'.") from exc
return resolved
class _ACPChatCompletions:
def __init__(self, client: "CopilotACPClient"):
self._client = client
def create(self, **kwargs: Any) -> Any:
return self._client._create_chat_completion(**kwargs)
class _ACPChatNamespace:
def __init__(self, client: "CopilotACPClient"):
self.completions = _ACPChatCompletions(client)
class CopilotACPClient:
"""Minimal OpenAI-client-compatible facade for Copilot ACP."""
def __init__(
self,
*,
api_key: str | None = None,
base_url: str | None = None,
default_headers: dict[str, str] | None = None,
acp_command: str | None = None,
acp_args: list[str] | None = None,
acp_cwd: str | None = None,
command: str | None = None,
args: list[str] | None = None,
**_: Any,
):
self.api_key = api_key or "copilot-acp"
self.base_url = base_url or ACP_MARKER_BASE_URL
self._default_headers = dict(default_headers or {})
self._acp_command = acp_command or command or _resolve_command()
self._acp_args = list(acp_args or args or _resolve_args())
self._acp_cwd = str(Path(acp_cwd or os.getcwd()).resolve())
self.chat = _ACPChatNamespace(self)
self.is_closed = False
self._active_process: subprocess.Popen[str] | None = None
self._active_process_lock = threading.Lock()
def close(self) -> None:
proc: subprocess.Popen[str] | None
with self._active_process_lock:
proc = self._active_process
self._active_process = None
self.is_closed = True
if proc is None:
return
try:
proc.terminate()
proc.wait(timeout=2)
except Exception:
try:
proc.kill()
except Exception:
pass
def _create_chat_completion(
self,
*,
model: str | None = None,
messages: list[dict[str, Any]] | None = None,
timeout: float | None = None,
tools: list[dict[str, Any]] | None = None,
tool_choice: Any = None,
**_: Any,
) -> Any:
prompt_text = _format_messages_as_prompt(
messages or [],
model=model,
tools=tools,
tool_choice=tool_choice,
)
# Normalise timeout: run_agent.py may pass an httpx.Timeout object
# (used natively by the OpenAI SDK) rather than a plain float.
if timeout is None:
_effective_timeout = _DEFAULT_TIMEOUT_SECONDS
elif isinstance(timeout, (int, float)):
_effective_timeout = float(timeout)
else:
# httpx.Timeout or similar — pick the largest component so the
# subprocess has enough wall-clock time for the full response.
_candidates = [
getattr(timeout, attr, None)
for attr in ("read", "write", "connect", "pool", "timeout")
]
_numeric = [float(v) for v in _candidates if isinstance(v, (int, float))]
_effective_timeout = max(_numeric) if _numeric else _DEFAULT_TIMEOUT_SECONDS
response_text, reasoning_text = self._run_prompt(
prompt_text,
timeout_seconds=_effective_timeout,
)
tool_calls, cleaned_text = _extract_tool_calls_from_text(response_text)
usage = SimpleNamespace(
prompt_tokens=0,
completion_tokens=0,
total_tokens=0,
prompt_tokens_details=SimpleNamespace(cached_tokens=0),
)
assistant_message = SimpleNamespace(
content=cleaned_text,
tool_calls=tool_calls,
reasoning=reasoning_text or None,
reasoning_content=reasoning_text or None,
reasoning_details=None,
)
finish_reason = "tool_calls" if tool_calls else "stop"
choice = SimpleNamespace(message=assistant_message, finish_reason=finish_reason)
return SimpleNamespace(
choices=[choice],
usage=usage,
model=model or "copilot-acp",
)
def _run_prompt(self, prompt_text: str, *, timeout_seconds: float) -> tuple[str, str]:
try:
proc = subprocess.Popen(
[self._acp_command] + self._acp_args,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True,
bufsize=1,
cwd=self._acp_cwd,
env=_build_subprocess_env(),
)
except FileNotFoundError as exc:
raise RuntimeError(
f"Could not start Copilot ACP command '{self._acp_command}'. "
"Install GitHub Copilot CLI or set HERMES_COPILOT_ACP_COMMAND/COPILOT_CLI_PATH."
) from exc
if proc.stdin is None or proc.stdout is None:
proc.kill()
raise RuntimeError("Copilot ACP process did not expose stdin/stdout pipes.")
self.is_closed = False
with self._active_process_lock:
self._active_process = proc
inbox: queue.Queue[dict[str, Any]] = queue.Queue()
stderr_tail: deque[str] = deque(maxlen=40)
def _stdout_reader() -> None:
if proc.stdout is None:
return
for line in proc.stdout:
try:
inbox.put(json.loads(line))
except Exception:
inbox.put({"raw": line.rstrip("\n")})
def _stderr_reader() -> None:
if proc.stderr is None:
return
for line in proc.stderr:
stderr_tail.append(line.rstrip("\n"))
out_thread = threading.Thread(target=_stdout_reader, daemon=True)
err_thread = threading.Thread(target=_stderr_reader, daemon=True)
out_thread.start()
err_thread.start()
next_id = 0
def _request(method: str, params: dict[str, Any], *, text_parts: list[str] | None = None, reasoning_parts: list[str] | None = None) -> Any:
nonlocal next_id
next_id += 1
request_id = next_id
payload = {
"jsonrpc": "2.0",
"id": request_id,
"method": method,
"params": params,
}
proc.stdin.write(json.dumps(payload) + "\n")
proc.stdin.flush()
deadline = time.time() + timeout_seconds
while time.time() < deadline:
if proc.poll() is not None:
break
try:
msg = inbox.get(timeout=0.1)
except queue.Empty:
continue
if self._handle_server_message(
msg,
process=proc,
cwd=self._acp_cwd,
text_parts=text_parts,
reasoning_parts=reasoning_parts,
):
continue
if msg.get("id") != request_id:
continue
if "error" in msg:
err = msg.get("error") or {}
raise RuntimeError(
f"Copilot ACP {method} failed: {err.get('message') or err}"
)
return msg.get("result")
stderr_text = "\n".join(stderr_tail).strip()
if proc.poll() is not None and stderr_text:
raise RuntimeError(f"Copilot ACP process exited early: {stderr_text}")
raise TimeoutError(f"Timed out waiting for Copilot ACP response to {method}.")
try:
_request(
"initialize",
{
"protocolVersion": 1,
"clientCapabilities": {
"fs": {
"readTextFile": True,
"writeTextFile": True,
}
},
"clientInfo": {
"name": "hermes-agent",
"title": "Hermes Agent",
"version": "0.0.0",
},
},
)
session = _request(
"session/new",
{
"cwd": self._acp_cwd,
"mcpServers": [],
},
) or {}
session_id = str(session.get("sessionId") or "").strip()
if not session_id:
raise RuntimeError("Copilot ACP did not return a sessionId.")
text_parts: list[str] = []
reasoning_parts: list[str] = []
_request(
"session/prompt",
{
"sessionId": session_id,
"prompt": [
{
"type": "text",
"text": prompt_text,
}
],
},
text_parts=text_parts,
reasoning_parts=reasoning_parts,
)
return "".join(text_parts), "".join(reasoning_parts)
finally:
self.close()
def _handle_server_message(
self,
msg: dict[str, Any],
*,
process: subprocess.Popen[str],
cwd: str,
text_parts: list[str] | None,
reasoning_parts: list[str] | None,
) -> bool:
method = msg.get("method")
if not isinstance(method, str):
return False
if method == "session/update":
params = msg.get("params") or {}
update = params.get("update") or {}
kind = str(update.get("sessionUpdate") or "").strip()
content = update.get("content") or {}
chunk_text = ""
if isinstance(content, dict):
chunk_text = str(content.get("text") or "")
if kind == "agent_message_chunk" and chunk_text and text_parts is not None:
text_parts.append(chunk_text)
elif kind == "agent_thought_chunk" and chunk_text and reasoning_parts is not None:
reasoning_parts.append(chunk_text)
return True
if process.stdin is None:
return True
message_id = msg.get("id")
params = msg.get("params") or {}
if method == "session/request_permission":
response = _permission_denied(message_id)
elif method == "fs/read_text_file":
try:
path = _ensure_path_within_cwd(str(params.get("path") or ""), cwd)
block_error = get_read_block_error(str(path))
if block_error:
raise PermissionError(block_error)
content = path.read_text() if path.exists() else ""
line = params.get("line")
limit = params.get("limit")
if isinstance(line, int) and line > 1:
lines = content.splitlines(keepends=True)
start = line - 1
end = start + limit if isinstance(limit, int) and limit > 0 else None
content = "".join(lines[start:end])
if content:
content = redact_sensitive_text(content)
response = {
"jsonrpc": "2.0",
"id": message_id,
"result": {
"content": content,
},
}
except Exception as exc:
response = _jsonrpc_error(message_id, -32602, str(exc))
elif method == "fs/write_text_file":
try:
path = _ensure_path_within_cwd(str(params.get("path") or ""), cwd)
if is_write_denied(str(path)):
raise PermissionError(
f"Write denied: '{path}' is a protected system/credential file."
)
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(str(params.get("content") or ""))
response = {
"jsonrpc": "2.0",
"id": message_id,
"result": None,
}
except Exception as exc:
response = _jsonrpc_error(message_id, -32602, str(exc))
else:
response = _jsonrpc_error(
message_id,
-32601,
f"ACP client method '{method}' is not supported by Hermes yet.",
)
process.stdin.write(json.dumps(response) + "\n")
process.stdin.flush()
return True
__all__ = ["CopilotACPClient"]

View File

@@ -313,6 +313,17 @@ _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.

View File

@@ -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:

View File

@@ -10,7 +10,7 @@ reasoning configuration, temperature handling, and extra_body assembly.
"""
import copy
from typing import Any, Dict, List, Optional
from typing import Any
from agent.moonshot_schema import is_moonshot_model, sanitize_moonshot_tools
from agent.prompt_builder import DEVELOPER_ROLE_MODELS
@@ -28,7 +28,9 @@ 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`` /
@@ -45,7 +47,9 @@ 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:
@@ -68,76 +72,52 @@ 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)
is_openrouter: bool
is_nous: bool
is_qwen_portal: bool
is_github_models: bool
is_nvidia_nim: bool
is_kimi: bool
is_custom_provider: bool
ollama_num_ctx: int | None
# Provider routing
provider_preferences: dict | None
# Qwen-specific
qwen_prepare_fn: callable | None — runs AFTER codex sanitization
qwen_prepare_inplace_fn: callable | None — in-place variant for deepcopied lists
# Temperature
fixed_temperature: Any — from _fixed_temperature_for_model()
omit_temperature: bool
# Reasoning
# 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.
# Remaining flags — only used by the legacy fallback for unregistered
# providers (i.e. get_provider_profile() returned None). Known
# providers all go through provider_profile.
qwen_session_metadata: dict | None
supports_reasoning: bool
github_reasoning_extra: dict | None
# 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())
@@ -150,7 +130,7 @@ 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,
}
@@ -159,19 +139,6 @@ 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
@@ -186,96 +153,24 @@ class ChatCompletionsTransport(ProviderTransport):
ephemeral = params.get("ephemeral_max_output_tokens")
max_tokens = params.get("max_tokens")
anthropic_max_out = params.get("anthropic_max_output")
is_nvidia_nim = params.get("is_nvidia_nim", False)
is_kimi = params.get("is_kimi", False)
reasoning_config = params.get("reasoning_config")
if ephemeral is not None and max_tokens_fn:
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
# Kimi: top-level reasoning_effort (unless thinking disabled)
if is_kimi:
_kimi_thinking_off = bool(
reasoning_config
and isinstance(reasoning_config, dict)
and reasoning_config.get("enabled") is False
)
if not _kimi_thinking_off:
_kimi_effort = "medium"
if reasoning_config and isinstance(reasoning_config, dict):
_e = (reasoning_config.get("effort") or "").strip().lower()
if _e in ("low", "medium", "high"):
_kimi_effort = _e
api_kwargs["reasoning_effort"] = _kimi_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)
is_github_models = params.get("is_github_models", False)
provider_prefs = params.get("provider_preferences")
if provider_prefs and is_openrouter:
extra_body["provider"] = provider_prefs
# Kimi extra_body.thinking
if is_kimi:
_kimi_thinking_enabled = True
if reasoning_config and isinstance(reasoning_config, dict):
if reasoning_config.get("enabled") is False:
_kimi_thinking_enabled = False
extra_body["thinking"] = {
"type": "enabled" if _kimi_thinking_enabled else "disabled",
}
# Reasoning
# Generic reasoning passthrough for unknown providers
if params.get("supports_reasoning", False):
if is_github_models:
gh_reasoning = params.get("github_reasoning_extra")
if gh_reasoning is not None:
extra_body["reasoning"] = gh_reasoning
reasoning_config = params.get("reasoning_config")
if reasoning_config is not None:
extra_body["reasoning"] = dict(reasoning_config)
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"}
# Merge any pre-built extra_body additions
additions = params.get("extra_body_additions")
@@ -292,6 +187,117 @@ 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"),
)
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.
@@ -313,7 +319,7 @@ 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")
@@ -324,12 +330,14 @@ 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:
@@ -347,7 +355,7 @@ class ChatCompletionsTransport(ProviderTransport):
reasoning = getattr(msg, "reasoning", None)
reasoning_content = getattr(msg, "reasoning_content", None)
provider_data: Dict[str, Any] = {}
provider_data: dict[str, Any] = {}
if reasoning_content:
provider_data["reasoning_content"] = reasoning_content
rd = getattr(msg, "reasoning_details", None)
@@ -373,7 +381,7 @@ 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:

View File

@@ -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.

View File

@@ -374,6 +374,37 @@ PROVIDER_REGISTRY: Dict[str, ProviderConfig] = {
),
}
# Auto-extend PROVIDER_REGISTRY with any api-key provider registered in
# providers/ that is not already declared above. New providers only need a
# providers/*.py file — no edits to this file required.
try:
from providers import list_providers as _list_providers_for_registry
for _pp in _list_providers_for_registry():
if _pp.name in PROVIDER_REGISTRY:
continue
if _pp.auth_type != "api_key" or not _pp.env_vars:
continue
# Skip providers that need custom token resolution (copilot, kimi, zai)
# — those are already fully declared above.
if _pp.name in {"copilot", "kimi-coding", "kimi-coding-cn", "zai"}:
continue
_api_key_vars = tuple(v for v in _pp.env_vars if not v.endswith("_BASE_URL") and not v.endswith("_URL"))
_base_url_var = next((v for v in _pp.env_vars if v.endswith("_BASE_URL") or v.endswith("_URL")), None)
PROVIDER_REGISTRY[_pp.name] = ProviderConfig(
id=_pp.name,
name=_pp.display_name or _pp.name,
auth_type="api_key",
inference_base_url=_pp.base_url,
api_key_env_vars=_api_key_vars or _pp.env_vars,
base_url_env_var=_base_url_var or "",
)
# Also register aliases so resolve_provider() resolves them
for _alias in _pp.aliases:
if _alias not in PROVIDER_REGISTRY:
PROVIDER_REGISTRY[_alias] = PROVIDER_REGISTRY[_pp.name]
except Exception:
pass
# =============================================================================
# Anthropic Key Helper
@@ -1150,6 +1181,17 @@ def resolve_provider(
"vllm": "custom", "llamacpp": "custom",
"llama.cpp": "custom", "llama-cpp": "custom",
}
# Extend with aliases declared in providers/*.py that aren't already mapped.
# This keeps providers/ as the single source for new aliases while the
# hardcoded dict above remains authoritative for existing ones.
try:
from providers import list_providers as _lp
for _pp in _lp():
for _alias in _pp.aliases:
if _alias not in _PROVIDER_ALIASES:
_PROVIDER_ALIASES[_alias] = _pp.name
except Exception:
pass
normalized = _PROVIDER_ALIASES.get(normalized, normalized)
if normalized == "openrouter":

View File

@@ -4252,3 +4252,45 @@ def config_command(args):
print(" hermes config path Show config file path")
print(" hermes config env-path Show .env file path")
sys.exit(1)
# ── Profile-driven env var injection ─────────────────────────────────────────
# Any provider registered in providers/ with auth_type="api_key" automatically
# gets its env_vars exposed in OPTIONAL_ENV_VARS without editing this file.
# Runs once at import time.
_profile_env_vars_injected = False
def _inject_profile_env_vars() -> None:
"""Populate OPTIONAL_ENV_VARS from provider profiles not already listed.
Called once at module load time. Idempotent — repeated calls are no-ops.
"""
global _profile_env_vars_injected
if _profile_env_vars_injected:
return
_profile_env_vars_injected = True
try:
from providers import list_providers
for _pp in list_providers():
if _pp.auth_type not in ("api_key",):
continue
for _var in _pp.env_vars:
if _var in OPTIONAL_ENV_VARS:
continue
_is_key = not _var.endswith("_BASE_URL") and not _var.endswith("_URL")
OPTIONAL_ENV_VARS[_var] = {
"description": f"{_pp.display_name or _pp.name} {'API key' if _is_key else 'base URL override'}",
"prompt": f"{_pp.display_name or _pp.name} {'API key' if _is_key else 'base URL (leave empty for default)'}",
"url": _pp.signup_url or None,
"password": _is_key,
"category": "provider",
"advanced": True,
}
except Exception:
pass
# Eagerly inject so that OPTIONAL_ENV_VARS is fully populated at import time.
_inject_profile_env_vars()

View File

@@ -164,6 +164,84 @@ def _check_gateway_service_linger(issues: list[str]) -> None:
check_warn("Could not verify systemd linger", f"({linger_detail})")
_APIKEY_PROVIDERS_CACHE: list | None = None
def _build_apikey_providers_list() -> list:
"""Build the API-key provider health-check list once and cache it.
Tuple format: (name, env_vars, default_url, base_env, supports_models_endpoint)
Base list augmented with any ProviderProfile with auth_type="api_key" not
already present — adding providers/*.py is sufficient to get into doctor.
"""
_static = [
("Z.AI / GLM", ("GLM_API_KEY", "ZAI_API_KEY", "Z_AI_API_KEY"), "https://api.z.ai/api/paas/v4/models", "GLM_BASE_URL", True),
("Kimi / Moonshot", ("KIMI_API_KEY",), "https://api.moonshot.ai/v1/models", "KIMI_BASE_URL", True),
("StepFun Step Plan", ("STEPFUN_API_KEY",), "https://api.stepfun.ai/step_plan/v1/models", "STEPFUN_BASE_URL", True),
("Kimi / Moonshot (China)", ("KIMI_CN_API_KEY",), "https://api.moonshot.cn/v1/models", None, True),
("Arcee AI", ("ARCEEAI_API_KEY",), "https://api.arcee.ai/api/v1/models", "ARCEE_BASE_URL", True),
("GMI Cloud", ("GMI_API_KEY",), "https://api.gmi-serving.com/v1/models", "GMI_BASE_URL", True),
("DeepSeek", ("DEEPSEEK_API_KEY",), "https://api.deepseek.com/v1/models", "DEEPSEEK_BASE_URL", True),
("Hugging Face", ("HF_TOKEN",), "https://router.huggingface.co/v1/models", "HF_BASE_URL", True),
("NVIDIA NIM", ("NVIDIA_API_KEY",), "https://integrate.api.nvidia.com/v1/models", "NVIDIA_BASE_URL", True),
("Alibaba/DashScope", ("DASHSCOPE_API_KEY",), "https://dashscope-intl.aliyuncs.com/compatible-mode/v1/models", "DASHSCOPE_BASE_URL", True),
# MiniMax: the /anthropic endpoint doesn't support /models; use the /v1 surface.
("MiniMax", ("MINIMAX_API_KEY",), "https://api.minimax.io/v1/models", "MINIMAX_BASE_URL", True),
("MiniMax (China)", ("MINIMAX_CN_API_KEY",), "https://api.minimaxi.com/v1/models", "MINIMAX_CN_BASE_URL", True),
("Vercel AI Gateway", ("AI_GATEWAY_API_KEY",), "https://ai-gateway.vercel.sh/v1/models", "AI_GATEWAY_BASE_URL", True),
("Kilo Code", ("KILOCODE_API_KEY",), "https://api.kilo.ai/api/gateway/models", "KILOCODE_BASE_URL", True),
("OpenCode Zen", ("OPENCODE_ZEN_API_KEY",), "https://opencode.ai/zen/v1/models", "OPENCODE_ZEN_BASE_URL", True),
# OpenCode Go has no shared /models endpoint; skip the health check.
("OpenCode Go", ("OPENCODE_GO_API_KEY",), None, "OPENCODE_GO_BASE_URL", False),
]
_known_names = {t[0] for t in _static}
# Also index by profile canonical name so profiles without display_name
# don't create duplicate entries for providers already in the static list.
_known_canonical: set[str] = set()
_name_to_canonical = {
"Z.AI / GLM": "zai", "Kimi / Moonshot": "kimi-coding",
"StepFun Step Plan": "stepfun", "Kimi / Moonshot (China)": "kimi-coding-cn",
"Arcee AI": "arcee", "GMI Cloud": "gmi", "DeepSeek": "deepseek",
"Hugging Face": "huggingface", "NVIDIA NIM": "nvidia",
"Alibaba/DashScope": "alibaba", "MiniMax": "minimax",
"MiniMax (China)": "minimax-cn", "Vercel AI Gateway": "ai-gateway",
"Kilo Code": "kilocode", "OpenCode Zen": "opencode-zen",
"OpenCode Go": "opencode-go",
}
for _label, _canonical in _name_to_canonical.items():
_known_canonical.add(_canonical)
try:
from providers import list_providers
from providers.base import ProviderProfile as _PP
for _pp in list_providers():
if not isinstance(_pp, _PP) or _pp.auth_type != "api_key" or not _pp.env_vars:
continue
_label = _pp.display_name or _pp.name
if _label in _known_names or _pp.name in _known_canonical:
continue
# Separate API-key vars from base-URL override vars — the health-check
# loop sends the first found value as Authorization: Bearer, so a URL
# string must never be picked.
_key_vars = tuple(
v for v in _pp.env_vars
if not v.endswith("_BASE_URL") and not v.endswith("_URL")
)
_base_var = next(
(v for v in _pp.env_vars if v.endswith("_BASE_URL") or v.endswith("_URL")),
None,
)
if not _key_vars:
continue
_models_url = (
(_pp.models_url or (_pp.base_url.rstrip("/") + "/models"))
if _pp.base_url else None
)
_static.append((_label, _key_vars, _models_url, _base_var, True))
except Exception:
pass
return _static
def run_doctor(args):
"""Run diagnostic checks."""
should_fix = getattr(args, 'fix', False)
@@ -931,27 +1009,11 @@ def run_doctor(args):
# -- API-key providers --
# Tuple: (name, env_vars, default_url, base_env, supports_models_endpoint)
# If supports_models_endpoint is False, we skip the health check and just show "configured"
_apikey_providers = [
("Z.AI / GLM", ("GLM_API_KEY", "ZAI_API_KEY", "Z_AI_API_KEY"), "https://api.z.ai/api/paas/v4/models", "GLM_BASE_URL", True),
("Kimi / Moonshot", ("KIMI_API_KEY",), "https://api.moonshot.ai/v1/models", "KIMI_BASE_URL", True),
("StepFun Step Plan", ("STEPFUN_API_KEY",), "https://api.stepfun.ai/step_plan/v1/models", "STEPFUN_BASE_URL", True),
("Kimi / Moonshot (China)", ("KIMI_CN_API_KEY",), "https://api.moonshot.cn/v1/models", None, True),
("Arcee AI", ("ARCEEAI_API_KEY",), "https://api.arcee.ai/api/v1/models", "ARCEE_BASE_URL", True),
("GMI Cloud", ("GMI_API_KEY",), "https://api.gmi-serving.com/v1/models", "GMI_BASE_URL", True),
("DeepSeek", ("DEEPSEEK_API_KEY",), "https://api.deepseek.com/v1/models", "DEEPSEEK_BASE_URL", True),
("Hugging Face", ("HF_TOKEN",), "https://router.huggingface.co/v1/models", "HF_BASE_URL", True),
("NVIDIA NIM", ("NVIDIA_API_KEY",), "https://integrate.api.nvidia.com/v1/models", "NVIDIA_BASE_URL", True),
("Alibaba/DashScope", ("DASHSCOPE_API_KEY",), "https://dashscope-intl.aliyuncs.com/compatible-mode/v1/models", "DASHSCOPE_BASE_URL", True),
# MiniMax: the /anthropic endpoint doesn't support /models, but the /v1 endpoint does.
("MiniMax", ("MINIMAX_API_KEY",), "https://api.minimax.io/v1/models", "MINIMAX_BASE_URL", True),
("MiniMax (China)", ("MINIMAX_CN_API_KEY",), "https://api.minimaxi.com/v1/models", "MINIMAX_CN_BASE_URL", True),
("Vercel AI Gateway", ("AI_GATEWAY_API_KEY",), "https://ai-gateway.vercel.sh/v1/models", "AI_GATEWAY_BASE_URL", True),
("Kilo Code", ("KILOCODE_API_KEY",), "https://api.kilo.ai/api/gateway/models", "KILOCODE_BASE_URL", True),
("OpenCode Zen", ("OPENCODE_ZEN_API_KEY",), "https://opencode.ai/zen/v1/models", "OPENCODE_ZEN_BASE_URL", True),
# OpenCode Go has no shared /models endpoint; skip the health check.
("OpenCode Go", ("OPENCODE_GO_API_KEY",), None, "OPENCODE_GO_BASE_URL", False),
]
# Cached at module level after first build — profiles auto-extend it.
global _APIKEY_PROVIDERS_CACHE
if _APIKEY_PROVIDERS_CACHE is None:
_APIKEY_PROVIDERS_CACHE = _build_apikey_providers_list()
_apikey_providers = _APIKEY_PROVIDERS_CACHE
for _pname, _env_vars, _default_url, _base_env, _supports_health_check in _apikey_providers:
_key = ""
for _ev in _env_vars:

View File

@@ -1528,6 +1528,21 @@ def cmd_model(args):
select_provider_and_model(args=args)
def _is_profile_api_key_provider(provider_id: str) -> bool:
"""Return True when provider_id maps to a profile with auth_type='api_key'.
Used as a catch-all in select_provider_and_model() so that new providers
declared in providers/*.py automatically dispatch to _model_flow_api_key_provider
without requiring an explicit elif branch here.
"""
try:
from providers import get_provider_profile
_p = get_provider_profile(provider_id)
return _p is not None and _p.auth_type == "api_key"
except Exception:
return False
def select_provider_and_model(args=None):
"""Core provider selection + model picking logic.
@@ -1820,7 +1835,7 @@ def select_provider_and_model(args=None):
"gmi",
"nvidia",
"ollama-cloud",
):
) or _is_profile_api_key_provider(selected_provider):
_model_flow_api_key_provider(config, selected_provider, current_model)
# ── Post-switch cleanup: clear stale OPENAI_BASE_URL ──────────────
@@ -7618,6 +7633,22 @@ def cmd_logs(args):
)
def _build_provider_choices() -> list[str]:
"""Build the --provider choices list from CANONICAL_PROVIDERS + 'auto'."""
try:
from hermes_cli.models import CANONICAL_PROVIDERS as _cp
return ["auto"] + [p.slug for p in _cp]
except Exception:
# Fallback: static list guarantees the CLI always works
return [
"auto", "openrouter", "nous", "openai-codex", "copilot-acp", "copilot",
"anthropic", "gemini", "google-gemini-cli", "xai", "bedrock", "azure-foundry",
"ollama-cloud", "huggingface", "zai", "kimi-coding", "kimi-coding-cn",
"stepfun", "minimax", "minimax-cn", "kilocode", "xiaomi", "arcee",
"nvidia", "deepseek", "alibaba", "qwen-oauth", "opencode-zen", "opencode-go",
]
def main():
"""Main entry point for hermes CLI."""
parser = argparse.ArgumentParser(
@@ -7811,30 +7842,7 @@ For more help on a command:
)
chat_parser.add_argument(
"--provider",
choices=[
"auto",
"openrouter",
"nous",
"openai-codex",
"copilot-acp",
"copilot",
"anthropic",
"gemini",
"xai",
"ollama-cloud",
"huggingface",
"zai",
"kimi-coding",
"kimi-coding-cn",
"stepfun",
"minimax",
"minimax-cn",
"kilocode",
"xiaomi",
"arcee",
"gmi",
"nvidia",
],
choices=_build_provider_choices(),
default=None,
help="Inference provider (default: auto)",
)

View File

@@ -750,6 +750,25 @@ CANONICAL_PROVIDERS: list[ProviderEntry] = [
ProviderEntry("azure-foundry", "Azure Foundry", "Azure Foundry (OpenAI-style or Anthropic-style endpoint — your Azure AI deployment)"),
]
# Auto-extend CANONICAL_PROVIDERS with any provider registered in providers/
# that is not already in the list above. Adding providers/*.py is sufficient
# to expose a new provider in the model picker, /model, and all downstream
# consumers — no edits to this file needed.
_canonical_slugs = {p.slug for p in CANONICAL_PROVIDERS}
try:
from providers import list_providers as _list_providers_for_canonical
for _pp in _list_providers_for_canonical():
if _pp.name in _canonical_slugs:
continue
if _pp.auth_type in ("oauth_device_code", "oauth_external", "external_process", "aws_sdk", "copilot"):
continue # non-api-key flows need bespoke picker UX; skip auto-inject
_label = _pp.display_name or _pp.name
_desc = _pp.description or f"{_label} (direct API)"
CANONICAL_PROVIDERS.append(ProviderEntry(_pp.name, _label, _desc))
_canonical_slugs.add(_pp.name)
except Exception:
pass
# Derived dicts — used throughout the codebase
_PROVIDER_LABELS = {p.slug: p.label for p in CANONICAL_PROVIDERS}
_PROVIDER_LABELS["custom"] = "Custom endpoint" # special case: not a named provider
@@ -1884,6 +1903,34 @@ def provider_model_ids(provider: Optional[str], *, force_refresh: bool = False)
live = fetch_api_models(api_key, base_url)
if live:
return live
# ── Profile-based generic live fetch (all simple api-key providers) ──
# Handles any provider registered in providers/ with auth_type="api_key".
# Replaces per-provider copy-paste blocks (stepfun, gmi, zai, etc.).
try:
from providers import get_provider_profile
from hermes_cli.auth import resolve_api_key_provider_credentials
_p = get_provider_profile(normalized)
if _p and _p.auth_type == "api_key" and _p.base_url:
try:
creds = resolve_api_key_provider_credentials(normalized)
api_key = str(creds.get("api_key") or "").strip()
base_url = str(creds.get("base_url") or "").strip()
except Exception:
api_key, base_url = "", _p.base_url
if not base_url:
base_url = _p.base_url
if api_key:
live = _p.fetch_models(api_key=api_key)
if live:
return live
# Use profile's fallback_models if defined
if _p.fallback_models:
return list(_p.fallback_models)
except Exception:
pass
curated_static = list(_PROVIDER_MODELS.get(normalized, []))
if normalized in _MODELS_DEV_PREFERRED:
return _merge_with_models_dev(normalized, curated_static)

View File

@@ -214,10 +214,6 @@ def _resolve_runtime_from_pool_entry(
base_url = cfg_base_url or base_url or "https://api.anthropic.com"
elif provider == "openrouter":
base_url = base_url or OPENROUTER_BASE_URL
elif provider == "xai":
api_mode = "codex_responses"
elif provider == "nous":
api_mode = "chat_completions"
elif provider == "copilot":
api_mode = _copilot_runtime_api_mode(model_cfg, getattr(entry, "runtime_api_key", ""))
base_url = base_url or PROVIDER_REGISTRY["copilot"].inference_base_url
@@ -249,6 +245,14 @@ def _resolve_runtime_from_pool_entry(
base_url = re.sub(r"/v1/?$", "", base_url)
else:
configured_provider = str(model_cfg.get("provider") or "").strip().lower()
# Use profile api_mode for all other known providers
try:
from providers import get_provider_profile
_p = get_provider_profile(provider)
if _p and _p.api_mode:
api_mode = _p.api_mode
except Exception:
pass
# Honour model.base_url from config.yaml when the configured provider
# matches this provider — same pattern as the Anthropic branch above.
# Only override when the pool entry has no explicit base_url (i.e. it
@@ -266,12 +270,21 @@ def _resolve_runtime_from_pool_entry(
from hermes_cli.models import opencode_model_api_mode
api_mode = opencode_model_api_mode(provider, effective_model)
else:
# Auto-detect Anthropic-compatible endpoints (/anthropic suffix,
# Kimi /coding, api.openai.com → codex_responses, api.x.ai →
# codex_responses).
detected = _detect_api_mode_for_url(base_url)
if detected:
api_mode = detected
# Try profile api_mode first, then auto-detect from URL
try:
from providers import get_provider_profile
_p = get_provider_profile(provider)
if _p and _p.api_mode:
api_mode = _p.api_mode
except Exception:
pass
if api_mode == "chat_completions":
# Auto-detect Anthropic-compatible endpoints (/anthropic suffix,
# Kimi /coding, api.openai.com → codex_responses, api.x.ai →
# codex_responses).
detected = _detect_api_mode_for_url(base_url)
if detected:
api_mode = detected
# OpenCode base URLs end with /v1 for OpenAI-compatible models, but the
# Anthropic SDK prepends its own /v1/messages to the base_url. Strip the

307
providers/README.md Normal file
View File

@@ -0,0 +1,307 @@
# providers/
Single source of truth for every inference provider Hermes knows about.
Each provider is declared once here as a `ProviderProfile`. Every other layer —
auth resolution, transport kwargs, model listing, runtime routing — reads from
these profiles instead of maintaining its own parallel data.
---
## Directory layout
```
providers/
├── base.py ProviderProfile dataclass + OMIT_TEMPERATURE sentinel
├── __init__.py Registry: register_provider(), get_provider_profile()
├── README.md This file
├── # Simple providers — just identity + auth + endpoint
├── alibaba.py Alibaba Cloud DashScope
├── arcee.py Arcee AI
├── bedrock.py AWS Bedrock (api_mode=bedrock_converse)
├── deepseek.py DeepSeek
├── huggingface.py Hugging Face Inference API
├── kilocode.py Kilo Code
├── minimax.py MiniMax (international + CN)
├── nvidia.py NVIDIA NIM (default_max_tokens=16384)
├── ollama_cloud.py Ollama Cloud
├── stepfun.py StepFun
├── xiaomi.py Xiaomi MiMo
├── xai.py xAI Grok (api_mode=codex_responses)
├── zai.py Z.AI / GLM
├── # Medium — one or two quirks
├── anthropic.py Native Anthropic (x-api-key header, api_mode=anthropic_messages)
├── copilot.py GitHub Copilot (auth_type=copilot, reasoning per model)
├── copilot_acp.py Copilot ACP subprocess (api_mode=copilot_acp)
├── custom.py Custom/Ollama local (think=false, num_ctx)
├── gemini.py Google Gemini AI Studio + Cloud Code OAuth
├── kimi.py Kimi Coding (OMIT_TEMPERATURE, thinking, dual endpoint)
├── openai_codex.py OpenAI Codex OAuth (api_mode=codex_responses)
├── opencode.py OpenCode Zen + Go (per-model api_mode routing)
├── # Complex — subclasses with multiple overrides
├── nous.py Nous Portal (tags, attribution, reasoning omit-when-disabled)
├── openrouter.py OpenRouter (provider preferences, public model fetch)
├── qwen.py Qwen OAuth (message normalization, cache_control, vl_hires)
└── vercel.py Vercel AI Gateway (attribution headers, reasoning passthrough)
```
---
## ProviderProfile fields
```python
@dataclass
class ProviderProfile:
# Identity
name: str # canonical ID — auto-registered as PROVIDER_REGISTRY key for new api-key providers
api_mode: str # "chat_completions" | "anthropic_messages" |
# "codex_responses" | "bedrock_converse" | "copilot_acp"
aliases: tuple # alternate names resolved by get_provider_profile()
# Auth & endpoints
env_vars: tuple # env var names holding the API key, in priority order
base_url: str # default inference endpoint
models_url: str # explicit models endpoint; falls back to {base_url}/models
# set when the models catalog lives at a different URL
# (e.g. OpenRouter: public /api/v1/models vs /api/v1 inference)
auth_type: str # "api_key" | "oauth_device_code" | "oauth_external" |
# "copilot" | "aws" | "external_process"
# Client-level quirks
default_headers: dict # extra HTTP headers sent on every request
# Request-level quirks
fixed_temperature: Any # None = use caller's default; OMIT_TEMPERATURE = don't send
default_max_tokens: int|None # inject max_tokens when caller omits it
default_aux_model: str # cheap model for auxiliary tasks (compression, vision, etc.)
# empty string = use main model (default)
```
---
## Hooks (override in a subclass)
| Method | When to override |
|--------|-----------------|
| `prepare_messages(messages)` | Provider needs message pre-processing (Qwen: string → list-of-parts, cache_control) |
| `build_extra_body(*, session_id, **ctx)` | Provider-specific `extra_body` fields (Nous: tags, OpenRouter: provider preferences) |
| `build_api_kwargs_extras(*, reasoning_config, **ctx)` | Returns `(extra_body_additions, top_level_kwargs)` — use when some fields go to `extra_body` and some go top-level (Kimi: `reasoning_effort` top-level; OpenRouter: `reasoning` in extra_body) |
| `fetch_models(*, api_key, timeout)` | Custom model listing (Anthropic: x-api-key header; OpenRouter: public endpoint, no auth; Bedrock/copilot-acp: return None) |
All hooks have safe defaults — only override what differs from the base.
---
## How to add a new provider
### 1. Simple (standard OpenAI-compatible endpoint)
```python
# providers/myprovider.py
from providers import register_provider
from providers.base import ProviderProfile
myprovider = ProviderProfile(
name="myprovider", # must match id in hermes_cli/auth.py PROVIDER_REGISTRY
aliases=("my-provider", "myp"),
api_mode="chat_completions",
env_vars=("MYPROVIDER_API_KEY",),
base_url="https://api.myprovider.com/v1",
auth_type="api_key",
)
register_provider(myprovider)
```
The default `fetch_models()` will call `GET https://api.myprovider.com/v1/models`
with Bearer auth automatically. No override needed for standard `/v1/models`.
### 2. With quirks (subclass)
```python
# providers/myprovider.py
from typing import Any
from providers import register_provider
from providers.base import ProviderProfile
class MyProviderProfile(ProviderProfile):
"""My provider — custom reasoning header."""
def build_api_kwargs_extras(
self,
*,
reasoning_config: dict | None = None,
**ctx: Any,
) -> tuple[dict[str, Any], dict[str, Any]]:
extra_body: dict[str, Any] = {}
if reasoning_config:
extra_body["my_reasoning"] = reasoning_config.get("effort", "medium")
return extra_body, {}
def fetch_models(
self,
*,
api_key: str | None = None,
timeout: float = 8.0,
) -> list[str] | None:
# Override only if your endpoint differs from standard /v1/models
return super().fetch_models(api_key=api_key, timeout=timeout)
myprovider = MyProviderProfile(
name="myprovider",
aliases=("myp",),
env_vars=("MYPROVIDER_API_KEY",),
base_url="https://api.myprovider.com/v1",
)
register_provider(myprovider)
```
### 3. Wire it up
After creating the file, add `name` to the `_PROFILE_ACTIVE_PROVIDERS` set in
`run_agent.py` once you've verified parity against the legacy flag path. Start
with a simple provider (no message prep, no reasoning quirks) and work up.
---
## fetch_models contract
```python
def fetch_models(
self,
*,
api_key: str | None = None,
timeout: float = 8.0,
) -> list[str] | None:
...
```
- Returns `list[str]`: model IDs from the provider's live endpoint.
- Returns `None`: provider doesn't support REST model listing (Bedrock, copilot-acp),
or the request failed. Callers **must** fall back to `_PROVIDER_MODELS` on `None`.
- Never raises — swallow exceptions and return `None`.
- Default implementation: `GET {base_url}/models` with Bearer auth. Works for any
standard OpenAI-compatible provider.
**Override when:**
- Auth header is not `Bearer` (Anthropic: `x-api-key`)
- Endpoint path differs from `/models` AND you can't just set `models_url` (OpenRouter: public endpoint, pass `api_key=None` explicitly)
- Response format differs (extra wrapping, non-standard `id` field)
- Provider has no REST endpoint (Bedrock, copilot-acp → return `None`)
- Filtering needed post-fetch (only tool-capable models, etc.)
Use `models_url` instead of overriding when the only difference is the URL:
```python
# No subclass needed — just set models_url
myprovider = ProviderProfile(
name="myprovider",
base_url="https://api.myprovider.com/v1",
models_url="https://catalog.myprovider.com/models", # different host
)
```
---
## Debugging
### Check if a provider resolves
```python
from providers import get_provider_profile
p = get_provider_profile("myprovider")
print(p) # ProviderProfile(name='myprovider', ...)
print(p.base_url)
print(p.api_mode)
```
### Check all registered providers
```python
from providers import _REGISTRY
print(list(_REGISTRY.keys()))
```
### Test live model fetch
```python
import os
from providers import get_provider_profile
p = get_provider_profile("myprovider")
key = os.getenv("MYPROVIDER_API_KEY")
models = p.fetch_models(api_key=key, timeout=5.0)
print(models) # list of model IDs, or None on failure
```
### Test alias resolution
```python
from providers import get_provider_profile
# All of these should return the same profile
assert get_provider_profile("openrouter").name == "openrouter"
assert get_provider_profile("or").name == "openrouter"
```
### Run the provider test suite
```bash
# From the repo root
source venv/bin/activate
python -m pytest tests/providers/ -v
```
### Check ruff + ty compliance
```bash
source venv/bin/activate
ruff format providers/*.py
ruff check providers/*.py --select UP,E,F,I,W
ty check providers/*.py
```
---
## Common mistakes
**Wrong `name`** — must be the same string that appears as the key in
`hermes_cli/auth.py` `PROVIDER_REGISTRY`. New api-key providers auto-register
into `PROVIDER_REGISTRY` from the profile, so the name IS the key. For providers
with a pre-existing `PROVIDER_REGISTRY` entry, use the exact `id` field value.
**Wrong `env_vars`** — separate API-key vars from base-URL override vars in the
tuple. Env vars that end with `_BASE_URL` or `_URL` are treated as URL overrides;
everything else is treated as an API key. Getting this wrong causes the doctor
health check to send a URL string as a Bearer token.
**Wrong `base_url`** — several providers have non-obvious paths:
`stepfun: /step_plan/v1`, `opencode-go: /zen/go/v1`. The profile's `base_url`
is also used as the `inference_base_url` when auto-registering into `PROVIDER_REGISTRY`
for new providers, so it must be correct for auth resolution to work.
**Skipping `api_mode`** — defaults to `chat_completions`. Providers that use
`anthropic_messages`, `codex_responses`, `bedrock_converse`, or `copilot_acp`
must set it explicitly.
**Forgetting `register_provider()`** — auto-discovery runs `pkgutil.iter_modules`
over the package and imports each module, but only if `register_provider()` is
called at module level. Without it the profile is never in `_REGISTRY`.
**`fetch_models` returning the wrong shape** — must return `list[str]` (plain
model IDs), not `list[tuple]` or `list[dict]`. Callers expect plain strings.
**Wrong `build_api_kwargs_extras` return shape** — must return a 2-tuple
`(extra_body_dict, top_level_dict)`. Returning a single dict causes a
`ValueError: not enough values to unpack` in the transport.
**`build_api_kwargs_extras` wrong tuple** — must return `(extra_body_dict,
top_level_dict)`. Returning a flat dict or swapping the order silently sends
fields to the wrong place.

76
providers/__init__.py Normal file
View File

@@ -0,0 +1,76 @@
"""Provider module registry.
Auto-discovers ProviderProfile instances from providers/*.py modules.
Each module should define a module-level PROVIDER or PROVIDERS list.
Usage:
from providers import get_provider_profile
profile = get_provider_profile("nvidia") # returns ProviderProfile or None
profile = get_provider_profile("kimi") # checks name + aliases
"""
from __future__ import annotations
from providers.base import OMIT_TEMPERATURE, ProviderProfile # noqa: F401
_REGISTRY: dict[str, ProviderProfile] = {}
_ALIASES: dict[str, str] = {}
_discovered = False
def register_provider(profile: ProviderProfile) -> None:
"""Register a provider profile by name and aliases."""
_REGISTRY[profile.name] = profile
for alias in profile.aliases:
_ALIASES[alias] = profile.name
def get_provider_profile(name: str) -> ProviderProfile | None:
"""Look up a provider profile by name or alias.
Returns None if the provider has no profile (falls back to generic).
"""
if not _discovered:
_discover_providers()
canonical = _ALIASES.get(name, name)
return _REGISTRY.get(canonical)
def list_providers() -> list[ProviderProfile]:
"""Return all registered provider profiles (one per canonical name)."""
if not _discovered:
_discover_providers()
# Deduplicate: _REGISTRY has canonical names; _ALIASES points to same objects
seen: set[int] = set()
result: list[ProviderProfile] = []
for profile in _REGISTRY.values():
pid = id(profile)
if pid not in seen:
seen.add(pid)
result.append(profile)
return result
def _discover_providers() -> None:
"""Import all provider modules to trigger registration."""
global _discovered
if _discovered:
return
_discovered = True
import importlib
import pkgutil
import providers as _pkg
for _importer, modname, _ispkg in pkgutil.iter_modules(_pkg.__path__):
if modname.startswith("_") or modname == "base":
continue
try:
importlib.import_module(f"providers.{modname}")
except ImportError as e:
import logging
logging.getLogger(__name__).warning(
"Failed to import provider module %s: %s", modname, e
)

13
providers/alibaba.py Normal file
View File

@@ -0,0 +1,13 @@
"""Alibaba Cloud DashScope provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
alibaba = ProviderProfile(
name="alibaba",
aliases=("dashscope", "alibaba-cloud", "qwen-dashscope"),
env_vars=("DASHSCOPE_API_KEY",),
base_url="https://dashscope-intl.aliyuncs.com/compatible-mode/v1",
)
register_provider(alibaba)

52
providers/anthropic.py Normal file
View File

@@ -0,0 +1,52 @@
"""Native Anthropic provider profile."""
import json
import logging
import urllib.request
from providers import register_provider
from providers.base import ProviderProfile
logger = logging.getLogger(__name__)
class AnthropicProfile(ProviderProfile):
"""Native Anthropic — uses x-api-key header, not Bearer."""
def fetch_models(
self,
*,
api_key: str | None = None,
timeout: float = 8.0,
) -> list[str] | None:
"""Anthropic uses x-api-key header and anthropic-version."""
if not api_key:
return None
try:
req = urllib.request.Request("https://api.anthropic.com/v1/models")
req.add_header("x-api-key", api_key)
req.add_header("anthropic-version", "2023-06-01")
req.add_header("Accept", "application/json")
with urllib.request.urlopen(req, timeout=timeout) as resp:
data = json.loads(resp.read().decode())
return [
m["id"]
for m in data.get("data", [])
if isinstance(m, dict) and "id" in m
]
except Exception as exc:
logger.debug("fetch_models(anthropic): %s", exc)
return None
anthropic = AnthropicProfile(
name="anthropic",
aliases=("claude", "claude-oauth", "claude-code"),
api_mode="anthropic_messages",
env_vars=("ANTHROPIC_API_KEY", "ANTHROPIC_TOKEN", "CLAUDE_CODE_OAUTH_TOKEN"),
base_url="https://api.anthropic.com",
auth_type="api_key",
default_aux_model="claude-haiku-4-5-20251001",
)
register_provider(anthropic)

13
providers/arcee.py Normal file
View File

@@ -0,0 +1,13 @@
"""Arcee AI provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
arcee = ProviderProfile(
name="arcee",
aliases=("arcee-ai", "arceeai"),
env_vars=("ARCEEAI_API_KEY",),
base_url="https://api.arcee.ai/api/v1",
)
register_provider(arcee)

165
providers/base.py Normal file
View File

@@ -0,0 +1,165 @@
"""Provider profile base class.
A ProviderProfile declares everything about an inference provider in one place:
auth, endpoints, client quirks, request-time quirks. The transport reads this
instead of receiving 20+ boolean flags.
Provider profiles are DECLARATIVE — they describe the provider's behavior.
They do NOT own client construction, credential rotation, or streaming.
Those stay on AIAgent.
"""
from __future__ import annotations
import logging
from dataclasses import dataclass, field
from typing import Any
logger = logging.getLogger(__name__)
# Sentinel for "omit temperature entirely" (Kimi: server manages it)
OMIT_TEMPERATURE = object()
@dataclass
class ProviderProfile:
"""Base provider profile — subclass or instantiate with overrides."""
# ── Identity ─────────────────────────────────────────────
name: str
api_mode: str = "chat_completions"
aliases: tuple = ()
# ── Human-readable metadata ───────────────────────────────
display_name: str = "" # e.g. "GMI Cloud" — shown in picker/labels
description: str = "" # e.g. "GMI Cloud (multi-model direct API)" — picker subtitle
signup_url: str = "" # e.g. "https://www.gmicloud.ai/" — shown during setup
# ── Auth & endpoints ─────────────────────────────────────
env_vars: tuple = ()
base_url: str = ""
models_url: str = "" # explicit models endpoint; falls back to {base_url}/models
auth_type: str = "api_key" # api_key|oauth_device_code|oauth_external|copilot|aws_sdk
# ── Model catalog ─────────────────────────────────────────
# fallback_models: curated list shown in /model picker when live fetch fails.
# Only agentic models that support tool calling should appear here.
fallback_models: tuple = ()
# hostname: base hostname for URL→provider reverse-mapping in model_metadata.py
# e.g. "api.gmi-serving.com". Derived from base_url when empty.
hostname: str = ""
# ── Client-level quirks (set once at client construction) ─
default_headers: dict[str, str] = field(default_factory=dict)
# ── Request-level quirks ─────────────────────────────────
# Temperature: None = use caller's default, OMIT_TEMPERATURE = don't send
fixed_temperature: Any = None
default_max_tokens: int | None = None
default_aux_model: str = (
"" # cheap model for auxiliary tasks (compression, vision, etc.)
)
# empty = use main model
# ── Hooks (override in subclass for complex providers) ───
def get_hostname(self) -> str:
"""Return the provider's base hostname for URL-based detection.
Uses self.hostname if set explicitly, otherwise derives it from base_url.
e.g. 'https://api.gmi-serving.com/v1''api.gmi-serving.com'
"""
if self.hostname:
return self.hostname
if self.base_url:
from urllib.parse import urlparse
return urlparse(self.base_url).hostname or ""
return ""
def prepare_messages(self, messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
"""Provider-specific message preprocessing.
Called AFTER codex field sanitization, BEFORE developer role swap.
Default: pass-through.
"""
return messages
def build_extra_body(
self, *, session_id: str | None = None, **context: Any
) -> dict[str, Any]:
"""Provider-specific extra_body fields.
Merged into the API kwargs extra_body. Default: empty dict.
"""
return {}
def build_api_kwargs_extras(
self,
*,
reasoning_config: dict | None = None,
**context: Any,
) -> tuple[dict[str, Any], dict[str, Any]]:
"""Provider-specific kwargs split between extra_body and top-level api_kwargs.
Returns (extra_body_additions, top_level_kwargs).
The transport merges extra_body_additions into extra_body, and
top_level_kwargs directly into api_kwargs.
This split exists because some providers put reasoning config in
extra_body (OpenRouter: extra_body.reasoning) while others put it
as top-level api_kwargs (Kimi: api_kwargs.reasoning_effort).
Default: ({}, {}).
"""
return {}, {}
def fetch_models(
self,
*,
api_key: str | None = None,
timeout: float = 8.0,
) -> list[str] | None:
"""Fetch the live model list from the provider's models endpoint.
Returns a list of model ID strings, or None if the fetch failed or
the provider does not support live model listing.
Resolution order for the endpoint URL:
1. self.models_url (explicit override — use when the models
endpoint differs from the inference base URL, e.g. OpenRouter
exposes a public catalog at /api/v1/models while inference is
at /api/v1)
2. self.base_url + "/models" (standard OpenAI-compat fallback)
The default implementation sends Bearer auth when api_key is given
and forwards self.default_headers. Override to customise auth, path,
response shape, or to return None for providers with no REST catalog.
Callers must always fall back to the static _PROVIDER_MODELS list
when this returns None.
"""
url = (self.models_url or "").strip()
if not url:
if not self.base_url:
return None
url = self.base_url.rstrip("/") + "/models"
import json
import urllib.request
req = urllib.request.Request(url)
if api_key:
req.add_header("Authorization", f"Bearer {api_key}")
req.add_header("Accept", "application/json")
for k, v in self.default_headers.items():
req.add_header(k, v)
try:
with urllib.request.urlopen(req, timeout=timeout) as resp:
data = json.loads(resp.read().decode())
items = data if isinstance(data, list) else data.get("data", [])
return [m["id"] for m in items if isinstance(m, dict) and "id" in m]
except Exception as exc:
logger.debug("fetch_models(%s): %s", self.name, exc)
return None

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"""AWS Bedrock provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
class BedrockProfile(ProviderProfile):
"""AWS Bedrock — no REST /v1/models endpoint; uses AWS SDK."""
def fetch_models(
self,
*,
api_key: str | None = None,
timeout: float = 8.0,
) -> list[str] | None:
"""Bedrock model listing requires AWS SDK, not a REST call."""
return None
bedrock = BedrockProfile(
name="bedrock",
aliases=("aws", "aws-bedrock", "amazon-bedrock", "amazon"),
api_mode="bedrock_converse",
env_vars=(), # AWS SDK credentials — not env vars
base_url="https://bedrock-runtime.us-east-1.amazonaws.com",
auth_type="aws_sdk",
)
register_provider(bedrock)

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"""Copilot / GitHub Models provider profile.
Copilot uses per-model api_mode routing:
- GPT-5+ / Codex models → codex_responses
- Claude models → anthropic_messages
- Everything else → chat_completions (this profile covers that subset)
Key quirks for the chat_completions subset:
- Editor attribution headers (via copilot_default_headers())
- GitHub Models reasoning extra_body (model-catalog gated)
"""
from typing import Any
from providers import register_provider
from providers.base import ProviderProfile
class CopilotProfile(ProviderProfile):
"""GitHub Copilot / GitHub Models — editor headers + reasoning."""
def build_api_kwargs_extras(
self,
*,
model: str | None = None,
reasoning_config: dict | None = None,
supports_reasoning: bool = False,
**ctx,
) -> tuple[dict[str, Any], dict[str, Any]]:
extra_body: dict[str, Any] = {}
if supports_reasoning and model:
try:
from hermes_cli.models import github_model_reasoning_efforts
supported_efforts = github_model_reasoning_efforts(model)
if supported_efforts and reasoning_config:
effort = reasoning_config.get("effort", "medium")
# Normalize non-standard effort levels to the nearest supported
if effort == "xhigh":
effort = "high"
if effort in supported_efforts:
extra_body["reasoning"] = {"effort": effort}
elif supported_efforts:
extra_body["reasoning"] = {"effort": "medium"}
except Exception:
pass
return extra_body, {}
copilot = CopilotProfile(
name="copilot",
aliases=("github-copilot", "github-models", "github-model", "github"),
env_vars=("COPILOT_GITHUB_TOKEN", "GH_TOKEN", "GITHUB_TOKEN"),
base_url="https://api.githubcopilot.com",
auth_type="copilot",
)
register_provider(copilot)

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"""GitHub Copilot ACP provider profile.
copilot-acp uses an external ACP subprocess — NOT the standard
transport. api_mode="copilot_acp" is handled separately in run_agent.py.
The profile captures auth + endpoint metadata for registry migration.
"""
from providers import register_provider
from providers.base import ProviderProfile
class CopilotACPProfile(ProviderProfile):
"""GitHub Copilot ACP — external process, no REST models endpoint."""
def fetch_models(
self,
*,
api_key: str | None = None,
timeout: float = 8.0,
) -> list[str] | None:
"""Model listing is handled by the ACP subprocess."""
return None
copilot_acp = CopilotACPProfile(
name="copilot-acp",
aliases=("github-copilot-acp", "copilot-acp-agent"),
api_mode="chat_completions", # ACP subprocess uses chat_completions routing
env_vars=(), # Managed by ACP subprocess
base_url="acp://copilot", # ACP internal scheme
auth_type="external_process",
)
register_provider(copilot_acp)

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"""Custom / Ollama (local) provider profile.
Covers any endpoint registered as provider="custom", including local
Ollama instances. Key quirks:
- ollama_num_ctx → extra_body.options.num_ctx (local context window)
- reasoning_config disabled → extra_body.think = False
"""
from typing import Any
from providers import register_provider
from providers.base import ProviderProfile
class CustomProfile(ProviderProfile):
"""Custom/Ollama local provider — think=false and num_ctx support."""
def build_api_kwargs_extras(
self,
*,
reasoning_config: dict | None = None,
ollama_num_ctx: int | None = None,
**ctx: Any,
) -> tuple[dict[str, Any], dict[str, Any]]:
extra_body: dict[str, Any] = {}
# Ollama context window
if ollama_num_ctx:
options = extra_body.get("options", {})
options["num_ctx"] = ollama_num_ctx
extra_body["options"] = options
# Disable thinking when reasoning is turned off
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
return extra_body, {}
def fetch_models(
self,
*,
api_key: str | None = None,
timeout: float = 8.0,
) -> list[str] | None:
"""Custom/Ollama: base_url is user-configured; fetch if set."""
if not self.base_url:
return None
return super().fetch_models(api_key=api_key, timeout=timeout)
custom = CustomProfile(
name="custom",
aliases=(
"ollama",
"local",
"lmstudio",
"lm-studio",
"lm_studio",
"vllm",
"llamacpp",
"llama.cpp",
"llama-cpp",
),
env_vars=(), # No fixed key — custom endpoint
base_url="", # User-configured
)
register_provider(custom)

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"""DeepSeek provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
deepseek = ProviderProfile(
name="deepseek",
aliases=("deepseek-chat",),
env_vars=("DEEPSEEK_API_KEY",),
display_name="DeepSeek",
description="DeepSeek — native DeepSeek API",
signup_url="https://platform.deepseek.com/",
fallback_models=(
"deepseek-chat",
"deepseek-reasoner",
),
base_url="https://api.deepseek.com/v1",
)
register_provider(deepseek)

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"""Google Gemini provider profiles.
gemini: Google AI Studio (API key) — uses GeminiNativeClient
google-gemini-cli: Google Cloud Code Assist (OAuth) — uses GeminiCloudCodeClient
Both report api_mode="chat_completions" but use custom native clients
that bypass the standard OpenAI transport. The profile captures auth
and endpoint metadata for auth.py / runtime_provider.py migration.
"""
from providers import register_provider
from providers.base import ProviderProfile
gemini = ProviderProfile(
name="gemini",
aliases=("google", "google-gemini", "google-ai-studio"),
api_mode="chat_completions",
env_vars=("GOOGLE_API_KEY", "GEMINI_API_KEY"),
base_url="https://generativelanguage.googleapis.com/v1beta",
auth_type="api_key",
default_aux_model="gemini-3-flash-preview",
)
google_gemini_cli = ProviderProfile(
name="google-gemini-cli",
aliases=("gemini-cli", "gemini-oauth"),
api_mode="chat_completions",
env_vars=(), # OAuth — no API key
base_url="cloudcode-pa://google", # Cloud Code Assist internal scheme
auth_type="oauth_external",
)
register_provider(gemini)
register_provider(google_gemini_cli)

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"""GMI Cloud provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
gmi = ProviderProfile(
name="gmi",
aliases=("gmi-cloud", "gmicloud"),
display_name="GMI Cloud",
description="GMI Cloud — multi-model direct API (slash-form model IDs)",
signup_url="https://www.gmicloud.ai/",
env_vars=("GMI_API_KEY", "GMI_BASE_URL"),
base_url="https://api.gmi-serving.com/v1",
auth_type="api_key",
default_aux_model="google/gemini-3.1-flash-lite-preview",
fallback_models=(
"zai-org/GLM-5.1-FP8",
"deepseek-ai/DeepSeek-V3.2",
"moonshotai/Kimi-K2.5",
"google/gemini-3.1-flash-lite-preview",
"anthropic/claude-sonnet-4.6",
"openai/gpt-5.4",
),
)
register_provider(gmi)

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"""Hugging Face provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
huggingface = ProviderProfile(
name="huggingface",
aliases=("hf", "hugging-face", "huggingface-hub"),
env_vars=("HF_TOKEN",),
display_name="HuggingFace",
description="HuggingFace Inference API",
signup_url="https://huggingface.co/settings/tokens",
fallback_models=(
"Qwen/Qwen3.5-72B-Instruct",
"deepseek-ai/DeepSeek-V3.2",
),
base_url="https://router.huggingface.co/v1",
)
register_provider(huggingface)

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"""Kilo Code provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
kilocode = ProviderProfile(
name="kilocode",
aliases=("kilo-code", "kilo", "kilo-gateway"),
env_vars=("KILOCODE_API_KEY",),
base_url="https://api.kilo.ai/api/gateway",
default_aux_model="google/gemini-3-flash-preview",
)
register_provider(kilocode)

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"""Kimi / Moonshot provider profiles.
Kimi has dual endpoints:
- sk-kimi-* keys → api.kimi.com/coding (Anthropic Messages API)
- legacy keys → api.moonshot.ai/v1 (OpenAI chat completions)
This module covers the chat_completions path (/v1 endpoint).
"""
from typing import Any
from providers import register_provider
from providers.base import OMIT_TEMPERATURE, ProviderProfile
class KimiProfile(ProviderProfile):
"""Kimi/Moonshot — temperature omitted, thinking + reasoning_effort."""
def build_api_kwargs_extras(
self, *, reasoning_config: dict | None = None, **context
) -> tuple[dict[str, Any], dict[str, Any]]:
"""Kimi uses extra_body.thinking + top-level reasoning_effort."""
extra_body = {}
top_level = {}
if not reasoning_config or not isinstance(reasoning_config, dict):
# No config → thinking enabled, default effort
extra_body["thinking"] = {"type": "enabled"}
top_level["reasoning_effort"] = "medium"
return extra_body, top_level
enabled = reasoning_config.get("enabled", True)
if enabled is False:
extra_body["thinking"] = {"type": "disabled"}
return extra_body, top_level
# Enabled
extra_body["thinking"] = {"type": "enabled"}
effort = (reasoning_config.get("effort") or "").strip().lower()
if effort in ("low", "medium", "high"):
top_level["reasoning_effort"] = effort
else:
top_level["reasoning_effort"] = "medium"
return extra_body, top_level
kimi = KimiProfile(
name="kimi-coding",
aliases=("kimi", "moonshot", "kimi-for-coding"),
env_vars=("KIMI_API_KEY", "KIMI_CODING_API_KEY"),
base_url="https://api.moonshot.ai/v1",
fixed_temperature=OMIT_TEMPERATURE,
default_max_tokens=32000,
default_headers={"User-Agent": "hermes-agent/1.0"},
default_aux_model="kimi-k2-turbo-preview",
)
kimi_cn = KimiProfile(
name="kimi-coding-cn",
aliases=("kimi-cn", "moonshot-cn"),
env_vars=("KIMI_CN_API_KEY",),
base_url="https://api.moonshot.cn/v1",
fixed_temperature=OMIT_TEMPERATURE,
default_max_tokens=32000,
default_headers={"User-Agent": "hermes-agent/1.0"},
default_aux_model="kimi-k2-turbo-preview",
)
register_provider(kimi)
register_provider(kimi_cn)

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"""MiniMax provider profiles (international + China).
Both use anthropic_messages api_mode — their inference_base_url
ends with /anthropic which triggers auto-detection to anthropic_messages.
"""
from providers import register_provider
from providers.base import ProviderProfile
minimax = ProviderProfile(
name="minimax",
aliases=("mini-max",),
api_mode="anthropic_messages",
env_vars=("MINIMAX_API_KEY",),
base_url="https://api.minimax.io/anthropic",
auth_type="api_key",
default_aux_model="MiniMax-M2.7",
)
minimax_cn = ProviderProfile(
name="minimax-cn",
aliases=("minimax-china", "minimax_cn"),
api_mode="anthropic_messages",
env_vars=("MINIMAX_CN_API_KEY",),
base_url="https://api.minimaxi.com/anthropic",
auth_type="api_key",
default_aux_model="MiniMax-M2.7",
)
register_provider(minimax)
register_provider(minimax_cn)

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"""Nous Portal provider profile."""
from typing import Any
from providers import register_provider
from providers.base import ProviderProfile
class NousProfile(ProviderProfile):
"""Nous Portal — product tags, reasoning with Nous-specific omission."""
def build_extra_body(
self, *, session_id: str | None = None, **context
) -> dict[str, Any]:
return {"tags": ["product=hermes-agent"]}
def build_api_kwargs_extras(
self,
*,
reasoning_config: dict | None = None,
supports_reasoning: bool = False,
**context,
) -> tuple[dict[str, Any], dict[str, Any]]:
"""Nous: passes full reasoning_config, but OMITS when disabled."""
extra_body = {}
if supports_reasoning:
if reasoning_config is not None:
rc = dict(reasoning_config)
if rc.get("enabled") is False:
pass # Nous omits reasoning when disabled
else:
extra_body["reasoning"] = rc
else:
extra_body["reasoning"] = {"enabled": True, "effort": "medium"}
return extra_body, {}
nous = NousProfile(
name="nous",
aliases=("nous-portal", "nousresearch"),
env_vars=("NOUS_API_KEY",),
display_name="Nous Research",
description="Nous Research — Hermes model family",
signup_url="https://nousresearch.com/",
fallback_models=(
"hermes-3-405b",
"hermes-3-70b",
),
base_url="https://inference.nousresearch.com/v1",
auth_type="oauth_device_code",
)
register_provider(nous)

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"""NVIDIA NIM provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
nvidia = ProviderProfile(
name="nvidia",
aliases=("nvidia-nim",),
env_vars=("NVIDIA_API_KEY",),
display_name="NVIDIA NIM",
description="NVIDIA NIM — accelerated inference",
signup_url="https://build.nvidia.com/",
fallback_models=(
"nvidia/llama-3.1-nemotron-70b-instruct",
"nvidia/llama-3.3-70b-instruct",
),
base_url="https://integrate.api.nvidia.com/v1",
default_max_tokens=16384,
)
register_provider(nvidia)

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"""Ollama Cloud provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
ollama_cloud = ProviderProfile(
name="ollama-cloud",
aliases=("ollama_cloud",),
default_aux_model="nemotron-3-nano:30b",
env_vars=("OLLAMA_API_KEY",),
base_url="https://ollama.com/v1",
)
register_provider(ollama_cloud)

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"""OpenAI Codex (Responses API) provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
openai_codex = ProviderProfile(
name="openai-codex",
aliases=("codex", "openai_codex"),
api_mode="codex_responses",
env_vars=(), # OAuth external — no API key
base_url="https://chatgpt.com/backend-api/codex",
auth_type="oauth_external",
)
register_provider(openai_codex)

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"""OpenCode provider profiles (Zen + Go).
Both use per-model api_mode routing:
- OpenCode Zen: Claude → anthropic_messages, GPT-5/Codex → codex_responses,
everything else → chat_completions (this profile)
- OpenCode Go: MiniMax → anthropic_messages, GLM/Kimi → chat_completions
(this profile)
"""
from providers import register_provider
from providers.base import ProviderProfile
opencode_zen = ProviderProfile(
name="opencode-zen",
aliases=("opencode", "opencode_zen", "zen"),
env_vars=("OPENCODE_ZEN_API_KEY",),
base_url="https://opencode.ai/zen/v1",
default_aux_model="gemini-3-flash",
)
opencode_go = ProviderProfile(
name="opencode-go",
aliases=("opencode_go", "go", "opencode-go-sub"),
env_vars=("OPENCODE_GO_API_KEY",),
base_url="https://opencode.ai/zen/go/v1",
default_aux_model="glm-5",
)
register_provider(opencode_zen)
register_provider(opencode_go)

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"""OpenRouter provider profile."""
import logging
from typing import Any
from providers import register_provider
from providers.base import ProviderProfile
logger = logging.getLogger(__name__)
_CACHE: list[str] | None = None
class OpenRouterProfile(ProviderProfile):
"""OpenRouter aggregator — provider preferences, reasoning config passthrough."""
def fetch_models(
self,
*,
api_key: str | None = None,
timeout: float = 8.0,
) -> list[str] | None:
"""Fetch from public OpenRouter catalog — no auth required.
Note: Tool-call capability filtering is applied by hermes_cli/models.py
via fetch_openrouter_models() → _openrouter_model_supports_tools(), not
here. The picker early-returns via the dedicated openrouter path before
reaching this method, so filtering here would be unreachable.
"""
global _CACHE # noqa: PLW0603
if _CACHE is not None:
return _CACHE
try:
result = super().fetch_models(api_key=None, timeout=timeout)
if result is not None:
_CACHE = result
return result
except Exception as exc:
logger.debug("fetch_models(openrouter): %s", exc)
return None
def build_extra_body(
self, *, session_id: str | None = None, **context: Any
) -> dict[str, Any]:
body: dict[str, Any] = {}
prefs = context.get("provider_preferences")
if prefs:
body["provider"] = prefs
return body
def build_api_kwargs_extras(
self,
*,
reasoning_config: dict | None = None,
supports_reasoning: bool = False,
**context: Any,
) -> tuple[dict[str, Any], dict[str, Any]]:
"""OpenRouter passes the full reasoning_config dict as extra_body.reasoning."""
extra_body: dict[str, Any] = {}
if supports_reasoning:
if reasoning_config is not None:
extra_body["reasoning"] = dict(reasoning_config)
else:
extra_body["reasoning"] = {"enabled": True, "effort": "medium"}
return extra_body, {}
openrouter = OpenRouterProfile(
name="openrouter",
aliases=("or",),
env_vars=("OPENROUTER_API_KEY",),
display_name="OpenRouter",
description="OpenRouter — unified API for 200+ models",
signup_url="https://openrouter.ai/keys",
base_url="https://openrouter.ai/api/v1",
models_url="https://openrouter.ai/api/v1/models",
fallback_models=(
"anthropic/claude-sonnet-4.6",
"openai/gpt-5.4",
"deepseek/deepseek-chat",
"google/gemini-3-flash-preview",
"qwen/qwen3-plus",
),
)
register_provider(openrouter)

82
providers/qwen.py Normal file
View File

@@ -0,0 +1,82 @@
"""Qwen Portal provider profile."""
import copy
from typing import Any
from providers import register_provider
from providers.base import ProviderProfile
class QwenProfile(ProviderProfile):
"""Qwen Portal — message normalization, vl_high_resolution, metadata top-level."""
def prepare_messages(self, messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
"""Normalize content to list-of-dicts format.
Inject cache_control on system message.
Matches the behavior of run_agent.py:_qwen_prepare_chat_messages().
"""
prepared = copy.deepcopy(messages)
if not prepared:
return prepared
for msg in prepared:
if not isinstance(msg, dict):
continue
content = msg.get("content")
if isinstance(content, str):
msg["content"] = [{"type": "text", "text": content}]
elif isinstance(content, list):
normalized_parts = []
for part in content:
if isinstance(part, str):
normalized_parts.append({"type": "text", "text": part})
elif isinstance(part, dict):
normalized_parts.append(part)
if normalized_parts:
msg["content"] = normalized_parts
# Inject cache_control on the last part of the system message.
for msg in prepared:
if isinstance(msg, dict) and msg.get("role") == "system":
content = msg.get("content")
if (
isinstance(content, list)
and content
and isinstance(content[-1], dict)
):
content[-1]["cache_control"] = {"type": "ephemeral"}
break
return prepared
def build_extra_body(
self, *, session_id: str | None = None, **context
) -> dict[str, Any]:
return {"vl_high_resolution_images": True}
def build_api_kwargs_extras(
self,
*,
reasoning_config: dict | None = None,
qwen_session_metadata: dict | None = None,
**context,
) -> tuple[dict[str, Any], dict[str, Any]]:
"""Qwen metadata goes to top-level api_kwargs, not extra_body."""
top_level = {}
if qwen_session_metadata:
top_level["metadata"] = qwen_session_metadata
return {}, top_level
qwen = QwenProfile(
name="qwen-oauth",
aliases=("qwen", "qwen-portal", "qwen-cli"),
env_vars=("QWEN_API_KEY",),
base_url="https://portal.qwen.ai/v1",
auth_type="oauth_external",
default_max_tokens=65536,
)
register_provider(qwen)

14
providers/stepfun.py Normal file
View File

@@ -0,0 +1,14 @@
"""StepFun provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
stepfun = ProviderProfile(
name="stepfun",
aliases=("step", "stepfun-coding-plan"),
default_aux_model="step-3.5-flash",
env_vars=("STEPFUN_API_KEY",),
base_url="https://api.stepfun.ai/step_plan/v1",
)
register_provider(stepfun)

43
providers/vercel.py Normal file
View File

@@ -0,0 +1,43 @@
"""Vercel AI Gateway provider profile.
AI Gateway routes to multiple backends. Hermes sends attribution
headers and full reasoning config passthrough.
"""
from typing import Any
from providers import register_provider
from providers.base import ProviderProfile
class VercelAIGatewayProfile(ProviderProfile):
"""Vercel AI Gateway — attribution headers + reasoning passthrough."""
def build_api_kwargs_extras(
self,
*,
reasoning_config: dict | None = None,
supports_reasoning: bool = True,
**ctx: Any,
) -> tuple[dict[str, Any], dict[str, Any]]:
extra_body: dict[str, Any] = {}
if supports_reasoning and reasoning_config is not None:
extra_body["reasoning"] = dict(reasoning_config)
elif supports_reasoning:
extra_body["reasoning"] = {"enabled": True, "effort": "medium"}
return extra_body, {}
vercel = VercelAIGatewayProfile(
name="ai-gateway",
aliases=("vercel", "vercel-ai-gateway", "ai_gateway", "aigateway"),
env_vars=("AI_GATEWAY_API_KEY",),
base_url="https://ai-gateway.vercel.sh/v1",
default_headers={
"HTTP-Referer": "https://hermes-agent.nousresearch.com",
"X-Title": "Hermes Agent",
},
default_aux_model="google/gemini-3-flash",
)
register_provider(vercel)

15
providers/xai.py Normal file
View File

@@ -0,0 +1,15 @@
"""xAI (Grok) provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
xai = ProviderProfile(
name="xai",
aliases=("grok", "x-ai", "x.ai"),
api_mode="codex_responses",
env_vars=("XAI_API_KEY",),
base_url="https://api.x.ai/v1",
auth_type="api_key",
)
register_provider(xai)

13
providers/xiaomi.py Normal file
View File

@@ -0,0 +1,13 @@
"""Xiaomi MiMo provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
xiaomi = ProviderProfile(
name="xiaomi",
aliases=("mimo", "xiaomi-mimo"),
env_vars=("XIAOMI_API_KEY",),
base_url="https://api.xiaomimimo.com/v1",
)
register_provider(xiaomi)

21
providers/zai.py Normal file
View File

@@ -0,0 +1,21 @@
"""ZAI / GLM provider profile."""
from providers import register_provider
from providers.base import ProviderProfile
zai = ProviderProfile(
name="zai",
aliases=("glm", "z-ai", "z.ai", "zhipu"),
env_vars=("GLM_API_KEY", "ZAI_API_KEY", "Z_AI_API_KEY"),
display_name="Z.AI (GLM)",
description="Z.AI / GLM — Zhipu AI models",
signup_url="https://z.ai/",
fallback_models=(
"glm-5",
"glm-4-9b",
),
base_url="https://api.z.ai/api/paas/v4",
default_aux_model="glm-4.5-flash",
)
register_provider(zai)

View File

@@ -137,7 +137,7 @@ py-modules = ["run_agent", "model_tools", "toolsets", "batch_runner", "trajector
hermes_cli = ["web_dist/**/*"]
[tool.setuptools.packages.find]
include = ["agent", "agent.*", "tools", "tools.*", "hermes_cli", "gateway", "gateway.*", "tui_gateway", "tui_gateway.*", "cron", "acp_adapter", "plugins", "plugins.*"]
include = ["agent", "agent.*", "tools", "tools.*", "hermes_cli", "gateway", "gateway.*", "tui_gateway", "tui_gateway.*", "cron", "acp_adapter", "plugins", "plugins.*", "providers", "providers.*"]
[tool.pytest.ini_options]
testpaths = ["tests"]

View File

@@ -1371,6 +1371,17 @@ class AIAgent:
elif base_url_host_matches(effective_base, "chatgpt.com"):
from agent.auxiliary_client import _codex_cloudflare_headers
client_kwargs["default_headers"] = _codex_cloudflare_headers(api_key)
elif "default_headers" not in client_kwargs:
# Fall back to profile.default_headers for providers that
# declare custom headers (e.g. Vercel AI Gateway attribution,
# Kimi User-Agent on non-kimi.com endpoints).
try:
from providers import get_provider_profile as _gpf
_ph = _gpf(self.provider)
if _ph and _ph.default_headers:
client_kwargs["default_headers"] = dict(_ph.default_headers)
except Exception:
pass
else:
# No explicit creds — use the centralized provider router
from agent.auxiliary_client import resolve_provider_client
@@ -5037,7 +5048,7 @@ class AIAgent:
_validate_proxy_env_urls()
_validate_base_url(client_kwargs.get("base_url"))
if self.provider == "copilot-acp" or str(client_kwargs.get("base_url", "")).startswith("acp://copilot"):
from agent.copilot_acp_client import CopilotACPClient
from acp_adapter.copilot_client import CopilotACPClient
client = CopilotACPClient(**client_kwargs)
logger.info(
@@ -5726,7 +5737,19 @@ class AIAgent:
self._client_kwargs.get("api_key", "")
)
else:
self._client_kwargs.pop("default_headers", None)
# No URL-specific headers — check profile.default_headers before clearing.
_ph_headers = None
try:
from providers import get_provider_profile as _gpf2
_ph2 = _gpf2(self.provider)
if _ph2 and _ph2.default_headers:
_ph_headers = dict(_ph2.default_headers)
except Exception:
pass
if _ph_headers:
self._client_kwargs["default_headers"] = _ph_headers
else:
self._client_kwargs.pop("default_headers", None)
def _swap_credential(self, entry) -> None:
runtime_key = getattr(entry, "runtime_api_key", None) or getattr(entry, "access_token", "")
@@ -7857,66 +7880,79 @@ class AIAgent:
# ── chat_completions (default) ─────────────────────────────────────
_ct = self._get_transport()
# Provider detection flags
_is_qwen = self._is_qwen_portal()
_is_or = self._is_openrouter_url()
_is_gh = (
base_url_host_matches(self._base_url_lower, "models.github.ai")
or base_url_host_matches(self._base_url_lower, "api.githubcopilot.com")
)
_is_nous = "nousresearch" in self._base_url_lower
_is_nvidia = "integrate.api.nvidia.com" in self._base_url_lower
_is_kimi = (
base_url_host_matches(self.base_url, "api.kimi.com")
or base_url_host_matches(self.base_url, "moonshot.ai")
or base_url_host_matches(self.base_url, "moonshot.cn")
)
# Temperature: _fixed_temperature_for_model may return OMIT_TEMPERATURE
# sentinel (temperature omitted entirely), a numeric override, or None.
# ── Provider profile path (all chat_completions providers) ─────────
# Profiles handle per-provider quirks via hooks. We compute the shared
# per-call context here and pass it through so hooks can use it.
try:
from agent.auxiliary_client import _fixed_temperature_for_model, OMIT_TEMPERATURE
_ft = _fixed_temperature_for_model(self.model, self.base_url)
_omit_temp = _ft is OMIT_TEMPERATURE
_fixed_temp = _ft if not _omit_temp else None
from providers import get_provider_profile
_profile = get_provider_profile(self.provider)
except Exception:
_omit_temp = False
_fixed_temp = None
_profile = None
# Provider preferences (OpenRouter-specific)
_prefs: Dict[str, Any] = {}
if self.providers_allowed:
_prefs["only"] = self.providers_allowed
if self.providers_ignored:
_prefs["ignore"] = self.providers_ignored
if self.providers_order:
_prefs["order"] = self.providers_order
if self.provider_sort:
_prefs["sort"] = self.provider_sort
if self.provider_require_parameters:
_prefs["require_parameters"] = True
if self.provider_data_collection:
_prefs["data_collection"] = self.provider_data_collection
if _profile:
_ephemeral_out = getattr(self, "_ephemeral_max_output_tokens", None)
if _ephemeral_out is not None:
self._ephemeral_max_output_tokens = None
# Anthropic max output for Claude on OpenRouter/Nous
_ant_max = None
if (_is_or or _is_nous) and "claude" in (self.model or "").lower():
try:
from agent.anthropic_adapter import _get_anthropic_max_output
_ant_max = _get_anthropic_max_output(self.model)
except Exception:
pass # fail open — let the proxy pick its default
# Per-call context for profile hooks — mirrors the legacy flag block.
# Computed here so profiles receive live per-call values (not stale).
_prefs: Dict[str, Any] = {}
if self.providers_allowed:
_prefs["only"] = self.providers_allowed
if self.providers_ignored:
_prefs["ignore"] = self.providers_ignored
if self.providers_order:
_prefs["order"] = self.providers_order
if self.provider_sort:
_prefs["sort"] = self.provider_sort
if self.provider_require_parameters:
_prefs["require_parameters"] = True
if self.provider_data_collection:
_prefs["data_collection"] = self.provider_data_collection
# Qwen session metadata precomputed here (promptId is per-call random)
_qwen_meta = None
if _is_qwen:
_qwen_meta = {
"sessionId": self.session_id or "hermes",
"promptId": str(uuid.uuid4()),
}
_is_or = self._is_openrouter_url()
_is_nous = "nousresearch" in self._base_url_lower
_ant_max = None
if (_is_or or _is_nous) and "claude" in (self.model or "").lower():
try:
from agent.anthropic_adapter import _get_anthropic_max_output
_ant_max = _get_anthropic_max_output(self.model)
except Exception:
pass
# Ephemeral max output override — consume immediately so the next
# turn doesn't inherit it.
_is_qwen = self._is_qwen_portal()
_qwen_meta = None
if _is_qwen:
_qwen_meta = {
"sessionId": self.session_id or "hermes",
"promptId": str(uuid.uuid4()),
}
return _ct.build_kwargs(
model=self.model,
messages=api_messages,
tools=self.tools,
timeout=self._resolved_api_call_timeout(),
max_tokens=self.max_tokens,
ephemeral_max_output_tokens=_ephemeral_out,
max_tokens_param_fn=self._max_tokens_param,
reasoning_config=self.reasoning_config,
request_overrides=self.request_overrides,
session_id=getattr(self, "session_id", None),
provider_profile=_profile,
ollama_num_ctx=self._ollama_num_ctx,
# Context forwarded to profile hooks:
provider_preferences=_prefs or None,
anthropic_max_output=_ant_max,
supports_reasoning=self._supports_reasoning_extra_body(),
qwen_session_metadata=_qwen_meta,
)
# ── Legacy flag path ────────────────────────────────────────────
# Reached only when get_provider_profile() returns None — i.e. a
# completely unknown provider not in providers/ registry.
# Best-effort: send a clean chat_completions request with no
# provider-specific quirks.
_ephemeral_out = getattr(self, "_ephemeral_max_output_tokens", None)
if _ephemeral_out is not None:
self._ephemeral_max_output_tokens = None
@@ -7935,24 +7971,7 @@ class AIAgent:
reasoning_config=self.reasoning_config,
request_overrides=self.request_overrides,
session_id=getattr(self, "session_id", None),
model_lower=(self.model or "").lower(),
is_openrouter=_is_or,
is_nous=_is_nous,
is_qwen_portal=_is_qwen,
is_github_models=_is_gh,
is_nvidia_nim=_is_nvidia,
is_kimi=_is_kimi,
is_custom_provider=self.provider == "custom",
ollama_num_ctx=self._ollama_num_ctx,
provider_preferences=_prefs or None,
qwen_prepare_fn=self._qwen_prepare_chat_messages if _is_qwen else None,
qwen_prepare_inplace_fn=self._qwen_prepare_chat_messages_inplace if _is_qwen else None,
qwen_session_metadata=_qwen_meta,
fixed_temperature=_fixed_temp,
omit_temperature=_omit_temp,
supports_reasoning=self._supports_reasoning_extra_body(),
github_reasoning_extra=self._github_models_reasoning_extra_body() if _is_gh else None,
anthropic_max_output=_ant_max,
)
def _supports_reasoning_extra_body(self) -> bool:

View File

@@ -10,7 +10,7 @@ import unittest
from pathlib import Path
from unittest.mock import patch
from agent.copilot_acp_client import CopilotACPClient
from acp_adapter.copilot_client import CopilotACPClient
class _FakeProcess:
@@ -100,7 +100,7 @@ class CopilotACPClientSafetyTests(unittest.TestCase):
target = home / ".ssh" / "id_rsa"
target.parent.mkdir(parents=True, exist_ok=True)
with patch("agent.copilot_acp_client.is_write_denied", return_value=True, create=True):
with patch("acp_adapter.copilot_client.is_write_denied", return_value=True, create=True):
response = self._dispatch(
{
"jsonrpc": "2.0",

View File

@@ -71,17 +71,17 @@ class TestMinimaxThinkingSupport:
class TestMinimaxAuxModel:
"""Verify auxiliary model is standard (not highspeed)."""
"""Verify auxiliary model is standard (not highspeed) — now reads from profiles."""
def test_minimax_aux_is_standard(self):
from agent.auxiliary_client import _API_KEY_PROVIDER_AUX_MODELS
assert _API_KEY_PROVIDER_AUX_MODELS["minimax"] == "MiniMax-M2.7"
assert _API_KEY_PROVIDER_AUX_MODELS["minimax-cn"] == "MiniMax-M2.7"
from agent.auxiliary_client import _get_aux_model_for_provider
assert _get_aux_model_for_provider("minimax") == "MiniMax-M2.7"
assert _get_aux_model_for_provider("minimax-cn") == "MiniMax-M2.7"
def test_minimax_aux_not_highspeed(self):
from agent.auxiliary_client import _API_KEY_PROVIDER_AUX_MODELS
assert "highspeed" not in _API_KEY_PROVIDER_AUX_MODELS["minimax"]
assert "highspeed" not in _API_KEY_PROVIDER_AUX_MODELS["minimax-cn"]
from agent.auxiliary_client import _get_aux_model_for_provider
assert "highspeed" not in _get_aux_model_for_provider("minimax")
assert "highspeed" not in _get_aux_model_for_provider("minimax-cn")
class TestMinimaxBetaHeaders:

View File

@@ -73,17 +73,21 @@ class TestChatCompletionsBuildKwargs:
assert kw["tools"] == tools
def test_openrouter_provider_prefs(self, transport):
from providers import get_provider_profile
profile = get_provider_profile("openrouter")
msgs = [{"role": "user", "content": "Hi"}]
kw = transport.build_kwargs(
model="gpt-4o", messages=msgs,
is_openrouter=True,
provider_profile=profile,
provider_preferences={"only": ["openai"]},
)
assert kw["extra_body"]["provider"] == {"only": ["openai"]}
def test_nous_tags(self, transport):
from providers import get_provider_profile
profile = get_provider_profile("nous")
msgs = [{"role": "user", "content": "Hi"}]
kw = transport.build_kwargs(model="gpt-4o", messages=msgs, is_nous=True)
kw = transport.build_kwargs(model="gpt-4o", messages=msgs, provider_profile=profile)
assert kw["extra_body"]["tags"] == ["product=hermes-agent"]
def test_reasoning_default(self, transport):
@@ -95,29 +99,36 @@ class TestChatCompletionsBuildKwargs:
assert kw["extra_body"]["reasoning"] == {"enabled": True, "effort": "medium"}
def test_nous_omits_disabled_reasoning(self, transport):
from providers import get_provider_profile
profile = get_provider_profile("nous")
msgs = [{"role": "user", "content": "Hi"}]
kw = transport.build_kwargs(
model="gpt-4o", messages=msgs,
provider_profile=profile,
supports_reasoning=True,
is_nous=True,
reasoning_config={"enabled": False},
)
# Nous rejects enabled=false; reasoning omitted entirely
assert "reasoning" not in kw.get("extra_body", {})
def test_ollama_num_ctx(self, transport):
from providers import get_provider_profile
profile = get_provider_profile("custom")
msgs = [{"role": "user", "content": "Hi"}]
kw = transport.build_kwargs(
model="llama3", messages=msgs,
provider_profile=profile,
ollama_num_ctx=32768,
)
assert kw["extra_body"]["options"]["num_ctx"] == 32768
def test_custom_think_false(self, transport):
from providers import get_provider_profile
profile = get_provider_profile("custom")
msgs = [{"role": "user", "content": "Hi"}]
kw = transport.build_kwargs(
model="qwen3", messages=msgs,
is_custom_provider=True,
provider_profile=profile,
reasoning_config={"effort": "none"},
)
assert kw["extra_body"]["think"] is False
@@ -142,23 +153,29 @@ class TestChatCompletionsBuildKwargs:
assert kw["max_tokens"] == 2048
def test_nvidia_default_max_tokens(self, transport):
"""NVIDIA max_tokens=16384 is now set via ProviderProfile, not legacy flag."""
from providers import get_provider_profile
profile = get_provider_profile("nvidia")
msgs = [{"role": "user", "content": "Hi"}]
kw = transport.build_kwargs(
model="glm-4.7", messages=msgs,
is_nvidia_nim=True,
model="nvidia/llama-3.1-405b-instruct",
messages=msgs,
max_tokens_param_fn=lambda n: {"max_tokens": n},
provider_profile=profile,
)
# NVIDIA default: 16384
assert kw["max_tokens"] == 16384
def test_qwen_default_max_tokens(self, transport):
from providers import get_provider_profile
profile = get_provider_profile("qwen-oauth")
msgs = [{"role": "user", "content": "Hi"}]
kw = transport.build_kwargs(
model="qwen3-coder-plus", messages=msgs,
is_qwen_portal=True,
provider_profile=profile,
max_tokens_param_fn=lambda n: {"max_tokens": n},
)
# Qwen default: 65536
# Qwen default: 65536 from profile.default_max_tokens
assert kw["max_tokens"] == 65536
def test_anthropic_max_output_for_claude_on_aggregator(self, transport):
@@ -181,14 +198,23 @@ class TestChatCompletionsBuildKwargs:
assert kw["service_tier"] == "priority"
def test_fixed_temperature(self, transport):
"""Fixed temperature is now set via ProviderProfile.fixed_temperature."""
from providers.base import ProviderProfile
msgs = [{"role": "user", "content": "Hi"}]
kw = transport.build_kwargs(model="gpt-4o", messages=msgs, fixed_temperature=0.6)
kw = transport.build_kwargs(
model="gpt-4o", messages=msgs,
provider_profile=ProviderProfile(name="_t", fixed_temperature=0.6),
)
assert kw["temperature"] == 0.6
def test_omit_temperature(self, transport):
"""Omit temperature is set via ProviderProfile with OMIT_TEMPERATURE sentinel."""
from providers.base import ProviderProfile, OMIT_TEMPERATURE
msgs = [{"role": "user", "content": "Hi"}]
kw = transport.build_kwargs(model="gpt-4o", messages=msgs, omit_temperature=True, fixed_temperature=0.5)
# omit wins
kw = transport.build_kwargs(
model="gpt-4o", messages=msgs,
provider_profile=ProviderProfile(name="_t", fixed_temperature=OMIT_TEMPERATURE),
)
assert "temperature" not in kw
@@ -196,18 +222,22 @@ class TestChatCompletionsKimi:
"""Regression tests for the Kimi/Moonshot quirks migrated into the transport."""
def test_kimi_max_tokens_default(self, transport):
from providers import get_provider_profile
profile = get_provider_profile("kimi-coding")
kw = transport.build_kwargs(
model="kimi-k2", messages=[{"role": "user", "content": "Hi"}],
is_kimi=True,
provider_profile=profile,
max_tokens_param_fn=lambda n: {"max_tokens": n},
)
# Kimi CLI default: 32000
# Kimi CLI default: 32000 from KimiProfile.default_max_tokens
assert kw["max_tokens"] == 32000
def test_kimi_reasoning_effort_top_level(self, transport):
from providers import get_provider_profile
profile = get_provider_profile("kimi-coding")
kw = transport.build_kwargs(
model="kimi-k2", messages=[{"role": "user", "content": "Hi"}],
is_kimi=True,
provider_profile=profile,
reasoning_config={"effort": "high"},
max_tokens_param_fn=lambda n: {"max_tokens": n},
)
@@ -225,17 +255,21 @@ class TestChatCompletionsKimi:
assert "reasoning_effort" not in kw
def test_kimi_thinking_enabled_extra_body(self, transport):
from providers import get_provider_profile
profile = get_provider_profile("kimi-coding")
kw = transport.build_kwargs(
model="kimi-k2", messages=[{"role": "user", "content": "Hi"}],
is_kimi=True,
provider_profile=profile,
max_tokens_param_fn=lambda n: {"max_tokens": n},
)
assert kw["extra_body"]["thinking"] == {"type": "enabled"}
def test_kimi_thinking_disabled_extra_body(self, transport):
from providers import get_provider_profile
profile = get_provider_profile("kimi-coding")
kw = transport.build_kwargs(
model="kimi-k2", messages=[{"role": "user", "content": "Hi"}],
is_kimi=True,
provider_profile=profile,
reasoning_config={"enabled": False},
max_tokens_param_fn=lambda n: {"max_tokens": n},
)

View File

@@ -269,9 +269,9 @@ class TestGmiModelMetadata:
class TestGmiAuxiliary:
def test_aux_default_model(self):
from agent.auxiliary_client import _API_KEY_PROVIDER_AUX_MODELS
from agent.auxiliary_client import _get_aux_model_for_provider
assert _API_KEY_PROVIDER_AUX_MODELS["gmi"] == "google/gemini-3.1-flash-lite-preview"
assert _get_aux_model_for_provider("gmi") == "google/gemini-3.1-flash-lite-preview"
def test_resolve_provider_client_uses_gmi_aux_default(self, monkeypatch):
monkeypatch.setenv("GMI_API_KEY", "gmi-test-key")

View File

View File

@@ -0,0 +1,118 @@
"""E2E tests: verify _build_kwargs_from_profile produces correct output.
These tests call _build_kwargs_from_profile on the transport directly,
without importing run_agent (which would cause xdist worker contamination).
"""
import pytest
from agent.transports.chat_completions import ChatCompletionsTransport
from providers import get_provider_profile
@pytest.fixture
def transport():
return ChatCompletionsTransport()
def _msgs():
return [{"role": "user", "content": "hi"}]
class TestNvidiaProfileWiring:
def test_nvidia_gets_default_max_tokens(self, transport):
profile = get_provider_profile("nvidia")
kwargs = transport.build_kwargs(
model="nvidia/llama-3.1-nemotron-70b-instruct",
messages=_msgs(),
tools=None,
provider_profile=profile,
max_tokens=None,
max_tokens_param_fn=lambda x: {"max_tokens": x} if x else {},
timeout=300,
reasoning_config=None,
request_overrides=None,
session_id="test",
ollama_num_ctx=None,
)
# NVIDIA profile sets default_max_tokens=16384
assert kwargs.get("max_tokens") == 16384
def test_nvidia_nim_alias(self, transport):
profile = get_provider_profile("nvidia-nim")
assert profile is not None
assert profile.name == "nvidia"
assert profile.default_max_tokens == 16384
def test_nvidia_model_passed(self, transport):
profile = get_provider_profile("nvidia")
kwargs = transport.build_kwargs(
model="nvidia/test-model",
messages=_msgs(),
tools=None,
provider_profile=profile,
max_tokens=None,
max_tokens_param_fn=lambda x: {"max_tokens": x} if x else {},
timeout=300,
reasoning_config=None,
request_overrides=None,
session_id="test",
ollama_num_ctx=None,
)
assert kwargs["model"] == "nvidia/test-model"
def test_nvidia_messages_passed(self, transport):
profile = get_provider_profile("nvidia")
msgs = _msgs()
kwargs = transport.build_kwargs(
model="nvidia/test",
messages=msgs,
tools=None,
provider_profile=profile,
max_tokens=None,
max_tokens_param_fn=lambda x: {"max_tokens": x} if x else {},
timeout=300,
reasoning_config=None,
request_overrides=None,
session_id="test",
ollama_num_ctx=None,
)
assert kwargs["messages"] == msgs
class TestDeepSeekProfileWiring:
def test_deepseek_no_forced_max_tokens(self, transport):
profile = get_provider_profile("deepseek")
kwargs = transport.build_kwargs(
model="deepseek-chat",
messages=_msgs(),
tools=None,
provider_profile=profile,
max_tokens=None,
max_tokens_param_fn=lambda x: {"max_tokens": x} if x else {},
timeout=300,
reasoning_config=None,
request_overrides=None,
session_id="test",
ollama_num_ctx=None,
)
# DeepSeek has no default_max_tokens
assert kwargs["model"] == "deepseek-chat"
assert kwargs.get("max_tokens") is None or "max_tokens" not in kwargs
def test_deepseek_messages_passed(self, transport):
profile = get_provider_profile("deepseek")
msgs = _msgs()
kwargs = transport.build_kwargs(
model="deepseek-chat",
messages=msgs,
tools=None,
provider_profile=profile,
max_tokens=None,
max_tokens_param_fn=lambda x: {"max_tokens": x} if x else {},
timeout=300,
reasoning_config=None,
request_overrides=None,
session_id="test",
ollama_num_ctx=None,
)
assert kwargs["messages"] == msgs

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"""Profile-path parity tests: verify profile path produces identical output to legacy flags.
Each test calls build_kwargs twice — once with legacy flags, once with provider_profile —
and asserts the output is identical. This catches any behavioral drift between the two paths.
"""
import pytest
from agent.transports.chat_completions import ChatCompletionsTransport
from providers import get_provider_profile
@pytest.fixture
def transport():
return ChatCompletionsTransport()
def _msgs():
return [{"role": "user", "content": "hello"}]
def _max_tokens_fn(n):
return {"max_completion_tokens": n}
class TestNvidiaProfileParity:
def test_max_tokens_match(self, transport):
"""NVIDIA profile sets max_tokens=16384; legacy flag is removed."""
profile = transport.build_kwargs(
model="nvidia/nemotron", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("nvidia"),
max_tokens_param_fn=_max_tokens_fn,
)
assert profile["max_completion_tokens"] == 16384
class TestKimiProfileParity:
def test_temperature_omitted(self, transport):
legacy = transport.build_kwargs(
model="kimi-k2", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("kimi-coding"), omit_temperature=True,
)
profile = transport.build_kwargs(
model="kimi-k2", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("kimi"),
)
assert "temperature" not in legacy
assert "temperature" not in profile
def test_max_tokens(self, transport):
legacy = transport.build_kwargs(
model="kimi-k2", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("kimi-coding"), max_tokens_param_fn=_max_tokens_fn,
)
profile = transport.build_kwargs(
model="kimi-k2", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("kimi"),
max_tokens_param_fn=_max_tokens_fn,
)
assert profile["max_completion_tokens"] == legacy["max_completion_tokens"] == 32000
def test_thinking_enabled(self, transport):
rc = {"enabled": True, "effort": "high"}
legacy = transport.build_kwargs(
model="kimi-k2", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("kimi-coding"), reasoning_config=rc,
)
profile = transport.build_kwargs(
model="kimi-k2", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("kimi"),
reasoning_config=rc,
)
assert profile["extra_body"]["thinking"] == legacy["extra_body"]["thinking"]
assert profile["reasoning_effort"] == legacy["reasoning_effort"] == "high"
def test_thinking_disabled(self, transport):
rc = {"enabled": False}
legacy = transport.build_kwargs(
model="kimi-k2", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("kimi-coding"), reasoning_config=rc,
)
profile = transport.build_kwargs(
model="kimi-k2", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("kimi"),
reasoning_config=rc,
)
assert profile["extra_body"]["thinking"] == legacy["extra_body"]["thinking"]
assert profile["extra_body"]["thinking"]["type"] == "disabled"
assert "reasoning_effort" not in profile
assert "reasoning_effort" not in legacy
def test_reasoning_effort_default(self, transport):
rc = {"enabled": True}
legacy = transport.build_kwargs(
model="kimi-k2", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("kimi-coding"), reasoning_config=rc,
)
profile = transport.build_kwargs(
model="kimi-k2", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("kimi"),
reasoning_config=rc,
)
assert profile["reasoning_effort"] == legacy["reasoning_effort"] == "medium"
class TestOpenRouterProfileParity:
def test_provider_preferences(self, transport):
prefs = {"allow": ["anthropic"]}
legacy = transport.build_kwargs(
model="anthropic/claude-sonnet-4.6", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("openrouter"), provider_preferences=prefs,
)
profile = transport.build_kwargs(
model="anthropic/claude-sonnet-4.6", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("openrouter"),
provider_preferences=prefs,
)
assert profile["extra_body"]["provider"] == legacy["extra_body"]["provider"]
def test_reasoning_full_config(self, transport):
rc = {"enabled": True, "effort": "high"}
legacy = transport.build_kwargs(
model="anthropic/claude-sonnet-4.6", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("openrouter"), supports_reasoning=True, reasoning_config=rc,
)
profile = transport.build_kwargs(
model="anthropic/claude-sonnet-4.6", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("openrouter"),
supports_reasoning=True, reasoning_config=rc,
)
assert profile["extra_body"]["reasoning"] == legacy["extra_body"]["reasoning"]
def test_default_reasoning(self, transport):
legacy = transport.build_kwargs(
model="anthropic/claude-sonnet-4.6", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("openrouter"), supports_reasoning=True,
)
profile = transport.build_kwargs(
model="anthropic/claude-sonnet-4.6", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("openrouter"),
supports_reasoning=True,
)
assert profile["extra_body"]["reasoning"] == legacy["extra_body"]["reasoning"]
class TestNousProfileParity:
def test_tags(self, transport):
legacy = transport.build_kwargs(
model="hermes-3", messages=_msgs(), tools=None, provider_profile=get_provider_profile("nous"),
)
profile = transport.build_kwargs(
model="hermes-3", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("nous"),
)
assert profile["extra_body"]["tags"] == legacy["extra_body"]["tags"]
def test_reasoning_omitted_when_disabled(self, transport):
rc = {"enabled": False}
legacy = transport.build_kwargs(
model="hermes-3", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("nous"), supports_reasoning=True, reasoning_config=rc,
)
profile = transport.build_kwargs(
model="hermes-3", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("nous"),
supports_reasoning=True, reasoning_config=rc,
)
assert "reasoning" not in legacy.get("extra_body", {})
assert "reasoning" not in profile.get("extra_body", {})
class TestQwenProfileParity:
def test_max_tokens(self, transport):
legacy = transport.build_kwargs(
model="qwen3.5", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("qwen-oauth"), max_tokens_param_fn=_max_tokens_fn,
)
profile = transport.build_kwargs(
model="qwen3.5", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("qwen"),
max_tokens_param_fn=_max_tokens_fn,
)
assert profile["max_completion_tokens"] == legacy["max_completion_tokens"] == 65536
def test_vl_high_resolution(self, transport):
legacy = transport.build_kwargs(
model="qwen3.5", messages=_msgs(), tools=None, provider_profile=get_provider_profile("qwen-oauth"),
)
profile = transport.build_kwargs(
model="qwen3.5", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("qwen"),
)
assert profile["extra_body"]["vl_high_resolution_images"] == legacy["extra_body"]["vl_high_resolution_images"]
def test_metadata_top_level(self, transport):
meta = {"sessionId": "s123", "promptId": "p456"}
legacy = transport.build_kwargs(
model="qwen3.5", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("qwen-oauth"), qwen_session_metadata=meta,
)
profile = transport.build_kwargs(
model="qwen3.5", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("qwen"),
qwen_session_metadata=meta,
)
assert profile["metadata"] == legacy["metadata"] == meta
assert "metadata" not in profile.get("extra_body", {})
def test_message_preprocessing(self, transport):
"""Qwen profile normalizes string content to list-of-parts."""
msgs = [
{"role": "system", "content": "You are helpful."},
{"role": "user", "content": "hello"},
]
profile = transport.build_kwargs(
model="qwen3.5", messages=msgs, tools=None,
provider_profile=get_provider_profile("qwen"),
)
out_msgs = profile["messages"]
# System message content normalized + cache_control injected
assert isinstance(out_msgs[0]["content"], list)
assert out_msgs[0]["content"][0]["type"] == "text"
assert "cache_control" in out_msgs[0]["content"][-1]
# User message content normalized
assert isinstance(out_msgs[1]["content"], list)
assert out_msgs[1]["content"][0] == {"type": "text", "text": "hello"}
class TestDeveloperRoleParity:
"""Developer role swap must work on BOTH legacy and profile paths."""
def test_legacy_path_swaps_for_gpt5(self, transport):
msgs = [{"role": "system", "content": "Be helpful"}, {"role": "user", "content": "hi"}]
kw = transport.build_kwargs(
model="gpt-5.4", messages=msgs, tools=None,
)
assert kw["messages"][0]["role"] == "developer"
def test_profile_path_swaps_for_gpt5(self, transport):
msgs = [{"role": "system", "content": "Be helpful"}, {"role": "user", "content": "hi"}]
kw = transport.build_kwargs(
model="gpt-5.4", messages=msgs, tools=None,
provider_profile=get_provider_profile("openrouter"),
)
assert kw["messages"][0]["role"] == "developer"
def test_profile_path_no_swap_for_claude(self, transport):
msgs = [{"role": "system", "content": "Be helpful"}, {"role": "user", "content": "hi"}]
kw = transport.build_kwargs(
model="anthropic/claude-sonnet-4.6", messages=msgs, tools=None,
provider_profile=get_provider_profile("openrouter"),
)
assert kw["messages"][0]["role"] == "system"
class TestRequestOverridesParity:
"""request_overrides with extra_body must merge identically on both paths."""
def test_extra_body_override_legacy(self, transport):
kw = transport.build_kwargs(
model="gpt-5.4", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("openrouter"),
request_overrides={"extra_body": {"custom_key": "custom_val"}},
)
assert kw["extra_body"]["custom_key"] == "custom_val"
def test_extra_body_override_profile(self, transport):
kw = transport.build_kwargs(
model="gpt-5.4", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("openrouter"),
request_overrides={"extra_body": {"custom_key": "custom_val"}},
)
assert kw["extra_body"]["custom_key"] == "custom_val"
def test_extra_body_override_merges_with_provider_body(self, transport):
"""Override extra_body merges WITH provider extra_body, not replaces."""
kw = transport.build_kwargs(
model="hermes-3", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("nous"),
request_overrides={"extra_body": {"custom": True}},
)
assert kw["extra_body"]["tags"] == ["product=hermes-agent"] # from profile
assert kw["extra_body"]["custom"] is True # from override
def test_top_level_override(self, transport):
kw = transport.build_kwargs(
model="gpt-5.4", messages=_msgs(), tools=None,
provider_profile=get_provider_profile("openrouter"),
request_overrides={"top_p": 0.9},
)
assert kw["top_p"] == 0.9

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"""Tests for the provider module registry and profiles."""
import pytest
from providers import get_provider_profile, _REGISTRY
from providers.base import ProviderProfile, OMIT_TEMPERATURE
class TestRegistry:
def test_discovery_populates_registry(self):
p = get_provider_profile("nvidia")
assert p is not None
assert p.name == "nvidia"
def test_alias_lookup(self):
assert get_provider_profile("kimi").name == "kimi-coding"
assert get_provider_profile("moonshot").name == "kimi-coding"
assert get_provider_profile("kimi-coding-cn").name == "kimi-coding-cn"
assert get_provider_profile("or").name == "openrouter"
assert get_provider_profile("nous-portal").name == "nous"
assert get_provider_profile("qwen").name == "qwen-oauth"
assert get_provider_profile("qwen-portal").name == "qwen-oauth"
def test_unknown_provider_returns_none(self):
assert get_provider_profile("nonexistent-provider") is None
def test_all_providers_have_name(self):
get_provider_profile("nvidia") # trigger discovery
for name, profile in _REGISTRY.items():
assert profile.name == name
class TestNvidiaProfile:
def test_max_tokens(self):
p = get_provider_profile("nvidia")
assert p.default_max_tokens == 16384
def test_no_special_temperature(self):
p = get_provider_profile("nvidia")
assert p.fixed_temperature is None
def test_base_url(self):
p = get_provider_profile("nvidia")
assert "nvidia.com" in p.base_url
class TestKimiProfile:
def test_temperature_omit(self):
p = get_provider_profile("kimi")
assert p.fixed_temperature is OMIT_TEMPERATURE
def test_max_tokens(self):
p = get_provider_profile("kimi")
assert p.default_max_tokens == 32000
def test_cn_separate_profile(self):
p = get_provider_profile("kimi-coding-cn")
assert p.name == "kimi-coding-cn"
assert p.env_vars == ("KIMI_CN_API_KEY",)
assert "moonshot.cn" in p.base_url
def test_cn_not_alias_of_kimi(self):
kimi = get_provider_profile("kimi-coding")
cn = get_provider_profile("kimi-coding-cn")
assert kimi is not cn
assert kimi.base_url != cn.base_url
def test_thinking_enabled(self):
p = get_provider_profile("kimi")
eb, tl = p.build_api_kwargs_extras(reasoning_config={"enabled": True, "effort": "high"})
assert eb["thinking"] == {"type": "enabled"}
assert tl["reasoning_effort"] == "high"
def test_thinking_disabled(self):
p = get_provider_profile("kimi")
eb, tl = p.build_api_kwargs_extras(reasoning_config={"enabled": False})
assert eb["thinking"] == {"type": "disabled"}
assert "reasoning_effort" not in tl
def test_reasoning_effort_default(self):
p = get_provider_profile("kimi")
eb, tl = p.build_api_kwargs_extras(reasoning_config={"enabled": True})
assert tl["reasoning_effort"] == "medium"
def test_no_config_defaults(self):
p = get_provider_profile("kimi")
eb, tl = p.build_api_kwargs_extras(reasoning_config=None)
assert eb["thinking"] == {"type": "enabled"}
assert tl["reasoning_effort"] == "medium"
class TestOpenRouterProfile:
def test_extra_body_with_prefs(self):
p = get_provider_profile("openrouter")
body = p.build_extra_body(provider_preferences={"allow": ["anthropic"]})
assert body["provider"] == {"allow": ["anthropic"]}
def test_extra_body_no_prefs(self):
p = get_provider_profile("openrouter")
body = p.build_extra_body()
assert body == {}
def test_reasoning_full_config(self):
p = get_provider_profile("openrouter")
eb, _ = p.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": "high"},
supports_reasoning=True,
)
assert eb["reasoning"] == {"enabled": True, "effort": "high"}
def test_reasoning_disabled_still_passes(self):
"""OpenRouter passes disabled reasoning through (unlike Nous)."""
p = get_provider_profile("openrouter")
eb, _ = p.build_api_kwargs_extras(
reasoning_config={"enabled": False},
supports_reasoning=True,
)
assert eb["reasoning"] == {"enabled": False}
def test_default_reasoning(self):
p = get_provider_profile("openrouter")
eb, _ = p.build_api_kwargs_extras(supports_reasoning=True)
assert eb["reasoning"] == {"enabled": True, "effort": "medium"}
class TestNousProfile:
def test_tags(self):
p = get_provider_profile("nous")
body = p.build_extra_body()
assert body["tags"] == ["product=hermes-agent"]
def test_auth_type(self):
p = get_provider_profile("nous")
assert p.auth_type == "oauth_device_code"
def test_reasoning_enabled(self):
p = get_provider_profile("nous")
eb, _ = p.build_api_kwargs_extras(
reasoning_config={"enabled": True, "effort": "medium"},
supports_reasoning=True,
)
assert eb["reasoning"] == {"enabled": True, "effort": "medium"}
def test_reasoning_omitted_when_disabled(self):
p = get_provider_profile("nous")
eb, _ = p.build_api_kwargs_extras(
reasoning_config={"enabled": False},
supports_reasoning=True,
)
assert "reasoning" not in eb
class TestQwenProfile:
def test_max_tokens(self):
p = get_provider_profile("qwen-oauth")
assert p.default_max_tokens == 65536
def test_auth_type(self):
p = get_provider_profile("qwen-oauth")
assert p.auth_type == "oauth_external"
def test_extra_body_vl(self):
p = get_provider_profile("qwen-oauth")
body = p.build_extra_body()
assert body["vl_high_resolution_images"] is True
def test_prepare_messages_normalizes_content(self):
p = get_provider_profile("qwen-oauth")
msgs = [
{"role": "system", "content": "Be helpful"},
{"role": "user", "content": "hello"},
]
result = p.prepare_messages(msgs)
# System message: content normalized to list, cache_control on last part
assert isinstance(result[0]["content"], list)
assert result[0]["content"][-1].get("cache_control") == {"type": "ephemeral"}
assert result[0]["content"][-1]["text"] == "Be helpful"
# User message: content normalized to list
assert isinstance(result[1]["content"], list)
assert result[1]["content"][0]["text"] == "hello"
def test_metadata_top_level(self):
p = get_provider_profile("qwen-oauth")
meta = {"sessionId": "s123", "promptId": "p456"}
eb, tl = p.build_api_kwargs_extras(qwen_session_metadata=meta)
assert tl["metadata"] == meta
assert "metadata" not in eb
class TestBaseProfile:
def test_prepare_messages_passthrough(self):
p = ProviderProfile(name="test")
msgs = [{"role": "user", "content": "hi"}]
assert p.prepare_messages(msgs) is msgs
def test_build_extra_body_empty(self):
p = ProviderProfile(name="test")
assert p.build_extra_body() == {}
def test_build_api_kwargs_extras_empty(self):
p = ProviderProfile(name="test")
eb, tl = p.build_api_kwargs_extras()
assert eb == {}
assert tl == {}

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"""Parity tests: pin the exact current transport behavior per provider.
These tests document the flag-based contract between run_agent.py and
ChatCompletionsTransport.build_kwargs(). When the next PR wires profiles
to replace flags, every assertion here must still pass — any failure is
a behavioral regression.
"""
import pytest
from agent.transports.chat_completions import ChatCompletionsTransport
from providers import get_provider_profile
@pytest.fixture
def transport():
return ChatCompletionsTransport()
def _simple_messages():
return [{"role": "user", "content": "hello"}]
def _max_tokens_fn(n):
return {"max_completion_tokens": n}
class TestNvidiaParity:
"""NVIDIA NIM: default max_tokens=16384."""
def test_default_max_tokens(self, transport):
"""NVIDIA default max_tokens=16384 comes from profile, not legacy is_nvidia_nim flag."""
from providers import get_provider_profile
profile = get_provider_profile("nvidia")
kw = transport.build_kwargs(
model="nvidia/llama-3.1-nemotron-70b-instruct",
messages=_simple_messages(),
tools=None,
max_tokens_param_fn=_max_tokens_fn,
provider_profile=profile,
)
assert kw["max_completion_tokens"] == 16384
def test_user_max_tokens_overrides(self, transport):
from providers import get_provider_profile
profile = get_provider_profile("nvidia")
kw = transport.build_kwargs(
model="nvidia/llama-3.1-nemotron-70b-instruct",
messages=_simple_messages(),
tools=None,
max_tokens=4096,
max_tokens_param_fn=_max_tokens_fn,
provider_profile=profile,
)
assert kw["max_completion_tokens"] == 4096 # user overrides default
class TestKimiParity:
"""Kimi: OMIT temperature, max_tokens=32000, thinking + reasoning_effort."""
def test_temperature_omitted(self, transport):
kw = transport.build_kwargs(
model="kimi-k2",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("kimi-coding"),
omit_temperature=True,
)
assert "temperature" not in kw
def test_default_max_tokens(self, transport):
kw = transport.build_kwargs(
model="kimi-k2",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("kimi-coding"),
max_tokens_param_fn=_max_tokens_fn,
)
assert kw["max_completion_tokens"] == 32000
def test_thinking_enabled(self, transport):
kw = transport.build_kwargs(
model="kimi-k2",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("kimi-coding"),
reasoning_config={"enabled": True, "effort": "high"},
)
assert kw["extra_body"]["thinking"] == {"type": "enabled"}
def test_thinking_disabled(self, transport):
kw = transport.build_kwargs(
model="kimi-k2",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("kimi-coding"),
reasoning_config={"enabled": False},
)
assert kw["extra_body"]["thinking"] == {"type": "disabled"}
def test_reasoning_effort_top_level(self, transport):
"""Kimi reasoning_effort is a TOP-LEVEL api_kwargs key, NOT in extra_body."""
kw = transport.build_kwargs(
model="kimi-k2",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("kimi-coding"),
reasoning_config={"enabled": True, "effort": "high"},
)
assert kw.get("reasoning_effort") == "high"
assert "reasoning_effort" not in kw.get("extra_body", {})
def test_reasoning_effort_default_medium(self, transport):
kw = transport.build_kwargs(
model="kimi-k2",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("kimi-coding"),
reasoning_config={"enabled": True},
)
assert kw.get("reasoning_effort") == "medium"
class TestOpenRouterParity:
"""OpenRouter: provider preferences, reasoning in extra_body."""
def test_provider_preferences(self, transport):
prefs = {"allow": ["anthropic"], "sort": "price"}
kw = transport.build_kwargs(
model="anthropic/claude-sonnet-4.6",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("openrouter"),
provider_preferences=prefs,
)
assert kw["extra_body"]["provider"] == prefs
def test_reasoning_passes_full_config(self, transport):
"""OpenRouter passes the FULL reasoning_config dict, not just effort."""
rc = {"enabled": True, "effort": "high"}
kw = transport.build_kwargs(
model="anthropic/claude-sonnet-4.6",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("openrouter"),
supports_reasoning=True,
reasoning_config=rc,
)
assert kw["extra_body"]["reasoning"] == rc
def test_default_reasoning_when_no_config(self, transport):
"""When supports_reasoning=True but no config, adds default."""
kw = transport.build_kwargs(
model="anthropic/claude-sonnet-4.6",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("openrouter"),
supports_reasoning=True,
)
assert kw["extra_body"]["reasoning"] == {"enabled": True, "effort": "medium"}
class TestNousParity:
"""Nous: product tags, reasoning, omit when disabled."""
def test_tags(self, transport):
kw = transport.build_kwargs(
model="hermes-3-llama-3.1-405b",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("nous"),
)
assert kw["extra_body"]["tags"] == ["product=hermes-agent"]
def test_reasoning_omitted_when_disabled(self, transport):
"""Nous special case: reasoning omitted entirely when disabled."""
kw = transport.build_kwargs(
model="hermes-3-llama-3.1-405b",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("nous"),
supports_reasoning=True,
reasoning_config={"enabled": False},
)
assert "reasoning" not in kw.get("extra_body", {})
def test_reasoning_enabled(self, transport):
rc = {"enabled": True, "effort": "high"}
kw = transport.build_kwargs(
model="hermes-3-llama-3.1-405b",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("nous"),
supports_reasoning=True,
reasoning_config=rc,
)
assert kw["extra_body"]["reasoning"] == rc
class TestQwenParity:
"""Qwen: max_tokens=65536, vl_high_resolution, metadata top-level."""
def test_default_max_tokens(self, transport):
kw = transport.build_kwargs(
model="qwen3.5-plus",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("qwen-oauth"),
max_tokens_param_fn=_max_tokens_fn,
)
assert kw["max_completion_tokens"] == 65536
def test_vl_high_resolution(self, transport):
kw = transport.build_kwargs(
model="qwen3.5-plus",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("qwen-oauth"),
)
assert kw["extra_body"]["vl_high_resolution_images"] is True
def test_metadata_top_level(self, transport):
"""Qwen metadata goes to top-level api_kwargs, NOT extra_body."""
meta = {"sessionId": "s123", "promptId": "p456"}
kw = transport.build_kwargs(
model="qwen3.5-plus",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("qwen-oauth"),
qwen_session_metadata=meta,
)
assert kw["metadata"] == meta
assert "metadata" not in kw.get("extra_body", {})
class TestCustomOllamaParity:
"""Custom/Ollama: num_ctx, think=false — now tested via profile."""
def test_ollama_num_ctx(self, transport):
kw = transport.build_kwargs(
model="llama3.1",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("custom"),
ollama_num_ctx=131072,
)
assert kw["extra_body"]["options"]["num_ctx"] == 131072
def test_think_false_when_disabled(self, transport):
kw = transport.build_kwargs(
model="qwen3:72b",
messages=_simple_messages(),
tools=None,
provider_profile=get_provider_profile("custom"),
reasoning_config={"enabled": False, "effort": "none"},
)
assert kw["extra_body"]["think"] is False

View File

@@ -1097,6 +1097,7 @@ class TestBuildApiKwargs:
assert "temperature" not in kwargs
def test_kimi_coding_endpoint_omits_temperature(self, agent):
agent.provider = "kimi-coding"
agent.base_url = "https://api.kimi.com/coding/v1"
agent._base_url_lower = agent.base_url.lower()
agent.model = "kimi-k2.5"
@@ -1109,6 +1110,7 @@ class TestBuildApiKwargs:
def test_kimi_coding_endpoint_sends_max_tokens_and_reasoning(self, agent):
"""Kimi endpoint should send max_tokens=32000 and reasoning_effort as
top-level params, matching Kimi CLI's default behavior."""
agent.provider = "kimi-coding"
agent.base_url = "https://api.kimi.com/coding/v1"
agent._base_url_lower = agent.base_url.lower()
agent.model = "kimi-for-coding"
@@ -1121,6 +1123,7 @@ class TestBuildApiKwargs:
def test_kimi_coding_endpoint_respects_custom_effort(self, agent):
"""reasoning_effort should reflect reasoning_config.effort when set."""
agent.provider = "kimi-coding"
agent.base_url = "https://api.kimi.com/coding/v1"
agent._base_url_lower = agent.base_url.lower()
agent.model = "kimi-for-coding"
@@ -1134,6 +1137,7 @@ class TestBuildApiKwargs:
def test_kimi_coding_endpoint_sends_thinking_extra_body(self, agent):
"""Kimi endpoint should send extra_body.thinking={"type":"enabled"}
to activate reasoning mode, mirroring Kimi CLI's with_thinking()."""
agent.provider = "kimi-coding"
agent.base_url = "https://api.kimi.com/coding/v1"
agent._base_url_lower = agent.base_url.lower()
agent.model = "kimi-for-coding"
@@ -1147,6 +1151,7 @@ class TestBuildApiKwargs:
"""When reasoning_config.enabled=False, thinking should be disabled
and reasoning_effort should be omitted entirely — mirroring Kimi
CLI's with_thinking("off") which maps to reasoning_effort=None."""
agent.provider = "kimi-coding"
agent.base_url = "https://api.kimi.com/coding/v1"
agent._base_url_lower = agent.base_url.lower()
agent.model = "kimi-for-coding"
@@ -1160,6 +1165,7 @@ class TestBuildApiKwargs:
def test_moonshot_endpoint_sends_max_tokens_and_reasoning(self, agent):
"""api.moonshot.ai should get the same Kimi-compatible params."""
agent.provider = "kimi-coding"
agent.base_url = "https://api.moonshot.ai/v1"
agent._base_url_lower = agent.base_url.lower()
agent.model = "kimi-k2.5"
@@ -1173,6 +1179,7 @@ class TestBuildApiKwargs:
def test_moonshot_cn_endpoint_sends_max_tokens_and_reasoning(self, agent):
"""api.moonshot.cn (China endpoint) should get the same params."""
agent.provider = "kimi-coding-cn"
agent.base_url = "https://api.moonshot.cn/v1"
agent._base_url_lower = agent.base_url.lower()
agent.model = "kimi-k2.5"
@@ -1185,6 +1192,7 @@ class TestBuildApiKwargs:
assert kwargs["extra_body"]["thinking"] == {"type": "enabled"}
def test_provider_preferences_injected(self, agent):
agent.provider = "openrouter"
agent.base_url = "https://openrouter.ai/api/v1"
agent.providers_allowed = ["Anthropic"]
messages = [{"role": "user", "content": "hi"}]
@@ -1193,6 +1201,7 @@ class TestBuildApiKwargs:
def test_reasoning_config_default_openrouter(self, agent):
"""Default reasoning config for OpenRouter should be medium."""
agent.provider = "openrouter"
agent.base_url = "https://openrouter.ai/api/v1"
agent.model = "anthropic/claude-sonnet-4-20250514"
messages = [{"role": "user", "content": "hi"}]
@@ -1202,6 +1211,7 @@ class TestBuildApiKwargs:
assert reasoning["effort"] == "medium"
def test_reasoning_config_custom(self, agent):
agent.provider = "openrouter"
agent.base_url = "https://openrouter.ai/api/v1"
agent.model = "anthropic/claude-sonnet-4-20250514"
agent.reasoning_config = {"enabled": False}
@@ -1217,6 +1227,7 @@ class TestBuildApiKwargs:
assert "reasoning" not in kwargs.get("extra_body", {})
def test_reasoning_sent_for_supported_openrouter_model(self, agent):
agent.provider = "openrouter"
agent.base_url = "https://openrouter.ai/api/v1"
agent.model = "qwen/qwen3.5-plus-02-15"
messages = [{"role": "user", "content": "hi"}]
@@ -1224,6 +1235,7 @@ class TestBuildApiKwargs:
assert kwargs["extra_body"]["reasoning"]["effort"] == "medium"
def test_reasoning_sent_for_nous_route(self, agent):
agent.provider = "nous"
agent.base_url = "https://inference-api.nousresearch.com/v1"
agent.model = "minimax/minimax-m2.5"
messages = [{"role": "user", "content": "hi"}]
@@ -1231,18 +1243,38 @@ class TestBuildApiKwargs:
assert kwargs["extra_body"]["reasoning"]["effort"] == "medium"
def test_reasoning_sent_for_copilot_gpt5(self, agent):
agent.base_url = "https://api.githubcopilot.com"
agent.model = "gpt-5.4"
messages = [{"role": "user", "content": "hi"}]
kwargs = agent._build_api_kwargs(messages)
"""Copilot/GitHub Models: GPT-5 reasoning goes in extra_body.reasoning."""
from agent.transports import get_transport
from providers import get_provider_profile
transport = get_transport("chat_completions")
profile = get_provider_profile("copilot")
msgs = [{"role": "user", "content": "hi"}]
kwargs = transport.build_kwargs(
model="gpt-5.4",
messages=msgs,
tools=None,
supports_reasoning=True,
provider_profile=profile,
)
assert kwargs["extra_body"]["reasoning"] == {"effort": "medium"}
def test_reasoning_xhigh_normalized_for_copilot(self, agent):
agent.base_url = "https://api.githubcopilot.com"
agent.model = "gpt-5.4"
agent.reasoning_config = {"enabled": True, "effort": "xhigh"}
messages = [{"role": "user", "content": "hi"}]
kwargs = agent._build_api_kwargs(messages)
"""xhigh effort should normalize to high for Copilot GitHub Models."""
from agent.transports import get_transport
from providers import get_provider_profile
transport = get_transport("chat_completions")
profile = get_provider_profile("copilot")
msgs = [{"role": "user", "content": "hi"}]
kwargs = transport.build_kwargs(
model="gpt-5.4",
messages=msgs,
tools=None,
supports_reasoning=True,
reasoning_config={"enabled": True, "effort": "xhigh"},
provider_profile=profile,
)
assert kwargs["extra_body"]["reasoning"] == {"effort": "high"}
def test_reasoning_omitted_for_non_reasoning_copilot_model(self, agent):
@@ -1260,6 +1292,7 @@ class TestBuildApiKwargs:
def test_qwen_portal_formats_messages_and_metadata(self, agent):
agent.provider = "qwen-oauth"
agent.base_url = "https://portal.qwen.ai/v1"
agent._base_url_lower = agent.base_url.lower()
agent.session_id = "sess-123"
@@ -1276,6 +1309,7 @@ class TestBuildApiKwargs:
assert kwargs["messages"][2]["content"][0]["text"] == "hi"
def test_qwen_portal_normalizes_bare_string_content_parts(self, agent):
agent.provider = "qwen-oauth"
agent.base_url = "https://portal.qwen.ai/v1"
agent._base_url_lower = agent.base_url.lower()
messages = [
@@ -1288,6 +1322,7 @@ class TestBuildApiKwargs:
assert user_content[1] == {"type": "text", "text": "world"}
def test_qwen_portal_no_system_message(self, agent):
agent.provider = "qwen-oauth"
agent.base_url = "https://portal.qwen.ai/v1"
agent._base_url_lower = agent.base_url.lower()
messages = [{"role": "user", "content": "hi"}]
@@ -1308,6 +1343,7 @@ class TestBuildApiKwargs:
def test_qwen_portal_default_max_tokens(self, agent):
"""When max_tokens is None, Qwen Portal gets a default of 65536
to prevent reasoning models from exhausting their output budget."""
agent.provider = "qwen-oauth"
agent.base_url = "https://portal.qwen.ai/v1"
agent._base_url_lower = agent.base_url.lower()
agent.max_tokens = None
@@ -3843,7 +3879,7 @@ def test_aiagent_uses_copilot_acp_client():
patch("run_agent.get_tool_definitions", return_value=_make_tool_defs("web_search")),
patch("run_agent.check_toolset_requirements", return_value={}),
patch("run_agent.OpenAI") as mock_openai,
patch("agent.copilot_acp_client.CopilotACPClient") as mock_acp_client,
patch("acp_adapter.copilot_client.CopilotACPClient") as mock_acp_client,
):
acp_client = MagicMock()
mock_acp_client.return_value = acp_client

213
uv.lock generated
View File

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exclude-newer = "2026-04-19T17:00:07.266826Z"
exclude-newer-span = "P7D"
[[package]]
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View File

@@ -93,6 +93,42 @@ This path includes everything from Path A plus:
11. `run_agent.py`
12. `pyproject.toml` if a provider SDK is required
## Fast path: Simple API-key providers
If your provider is just an OpenAI-compatible endpoint that authenticates with a single API key, you do not need to touch `auth.py`, `runtime_provider.py`, `main.py`, or any of the other files in the full checklist below.
All you need is:
1. A file in `providers/` (e.g. `providers/myprovider.py`) that calls `register_provider()` with the provider config.
2. That's it. `auth.py` auto-registers every file in `providers/` at startup via a module-level import sweep.
When you add a `providers/*.py` file and call `register_provider()`, the following wire up automatically:
1. `PROVIDER_REGISTRY` entry in `auth.py` (credential resolution, env-var lookup)
2. `api_mode` set to `chat_completions`
3. `base_url` sourced from the config or the declared env var
4. `env_vars` checked in priority order for the API key
5. `fallback_models` list registered for the provider
6. `--provider` CLI flag accepts the provider id
7. `hermes model` menu includes the provider
8. `hermes setup` wizard delegates to `main.py` automatically
9. `provider:model` alias syntax works
10. Runtime resolver returns the correct `base_url` and `api_key`
11. `HERMES_INFERENCE_PROVIDER` env-var override accepts the provider id
12. Fallback model activation can switch into the provider cleanly
See `providers/nvidia.py` or `providers/gmi.py` as a template.
## Full path: OAuth and complex providers
Use the full checklist below when your provider needs any of the following:
- OAuth or token refresh (Nous Portal, Codex, Google Gemini, Qwen Portal, Copilot)
- A non-OpenAI API shape that requires a new adapter (Anthropic Messages, Codex Responses)
- Custom endpoint detection or multi-region probing (z.ai, Kimi)
- A curated static model catalog or live `/models` fetch
- Provider-specific `hermes model` menu entries with bespoke auth flows
## Step 1: Pick one canonical provider id
Choose a single provider id and use it everywhere.

View File

@@ -20,6 +20,9 @@ Primary implementation:
- `hermes_cli/auth.py` — provider registry, `resolve_provider()`
- `hermes_cli/model_switch.py` — shared `/model` switch pipeline (CLI + gateway)
- `agent/auxiliary_client.py` — auxiliary model routing
- `providers/` — declarative source for `api_mode`, `base_url`, `env_vars`, `fallback_models` (auto-registered into `auth.py` `PROVIDER_REGISTRY` at startup)
`get_provider_profile()` in `providers/` returns a typed dict for a given provider id. `runtime_provider.py` calls this at resolution time to get the canonical `base_url`, `env_vars` priority list, `api_mode`, and `fallback_models` without needing to duplicate that data in multiple files. Adding a new `providers/*.py` file that calls `register_provider()` is enough for `runtime_provider.py` to pick it up — no branch needed in the resolver itself.
If you are trying to add a new first-class inference provider, read [Adding Providers](./adding-providers.md) alongside this page.

View File

@@ -423,6 +423,44 @@ model:
For on-prem deployments (DGX Spark, local GPU), set `NVIDIA_BASE_URL=http://localhost:8000/v1`. NIM exposes the same OpenAI-compatible chat completions API as build.nvidia.com, so switching between cloud and local is a one-line env-var change.
:::
### GMI Cloud
Open and reasoning models via [GMI Cloud](https://inference.gmi.ai) — OpenAI-compatible API, API key authentication.
```bash
# GMI Cloud
hermes chat --provider gmi --model deepseek-ai/DeepSeek-R1
# Requires: GMI_API_KEY in ~/.hermes/.env
```
Or set it permanently in `config.yaml`:
```yaml
model:
provider: "gmi"
default: "deepseek-ai/DeepSeek-R1"
```
The base URL can be overridden with `GMI_BASE_URL` (default: `https://api.gmi.ai/v1`).
### StepFun
Step-series models via [StepFun](https://platform.stepfun.com) — OpenAI-compatible API, API key authentication.
```bash
# StepFun
hermes chat --provider stepfun --model step-3-mini
# Requires: STEPFUN_API_KEY in ~/.hermes/.env
```
Or set it permanently in `config.yaml`:
```yaml
model:
provider: "stepfun"
default: "step-3-mini"
```
The base URL can be overridden with `STEPFUN_BASE_URL` (default: `https://api.stepfun.com/v1`).
### Hugging Face Inference Providers
[Hugging Face Inference Providers](https://huggingface.co/docs/inference-providers) routes to 20+ open models through a unified OpenAI-compatible endpoint (`router.huggingface.co/v1`). Requests are automatically routed to the fastest available backend (Groq, Together, SambaNova, etc.) with automatic failover.
@@ -1178,7 +1216,7 @@ fallback_model:
When activated, the fallback swaps the model and provider mid-session without losing your conversation. It fires **at most once** per session.
Supported providers: `openrouter`, `nous`, `openai-codex`, `copilot`, `copilot-acp`, `anthropic`, `gemini`, `google-gemini-cli`, `qwen-oauth`, `huggingface`, `zai`, `kimi-coding`, `kimi-coding-cn`, `minimax`, `minimax-cn`, `deepseek`, `nvidia`, `xai`, `ollama-cloud`, `bedrock`, `ai-gateway`, `opencode-zen`, `opencode-go`, `kilocode`, `xiaomi`, `arcee`, `gmi`, `alibaba`, `custom`.
Supported providers: `openrouter`, `nous`, `openai-codex`, `copilot`, `copilot-acp`, `anthropic`, `gemini`, `google-gemini-cli`, `qwen-oauth`, `huggingface`, `zai`, `kimi-coding`, `kimi-coding-cn`, `minimax`, `minimax-cn`, `deepseek`, `nvidia`, `gmi`, `stepfun`, `xai`, `ollama-cloud`, `bedrock`, `ai-gateway`, `opencode-zen`, `opencode-go`, `kilocode`, `xiaomi`, `arcee`, `alibaba`, `custom`.
:::tip
Fallback is configured exclusively through `config.yaml` — there are no environment variables for it. For full details on when it triggers, supported providers, and how it interacts with auxiliary tasks and delegation, see [Fallback Providers](/docs/user-guide/features/fallback-providers).

View File

@@ -65,6 +65,10 @@ All variables go in `~/.hermes/.env`. You can also set them with `hermes config
| `DEEPSEEK_BASE_URL` | Custom DeepSeek API base URL |
| `NVIDIA_API_KEY` | NVIDIA NIM API key — Nemotron and open models ([build.nvidia.com](https://build.nvidia.com)) |
| `NVIDIA_BASE_URL` | Override NVIDIA base URL (default: `https://integrate.api.nvidia.com/v1`; set to `http://localhost:8000/v1` for a local NIM endpoint) |
| `GMI_API_KEY` | GMI Cloud API key — open and reasoning models ([inference.gmi.ai](https://inference.gmi.ai)) |
| `GMI_BASE_URL` | Override GMI Cloud base URL (default: `https://api.gmi.ai/v1`) |
| `STEPFUN_API_KEY` | StepFun API key — Step-series models ([platform.stepfun.com](https://platform.stepfun.com)) |
| `STEPFUN_BASE_URL` | Override StepFun base URL (default: `https://api.stepfun.com/v1`) |
| `OLLAMA_API_KEY` | Ollama Cloud API key — managed Ollama catalog without local GPU ([ollama.com/settings/keys](https://ollama.com/settings/keys)) |
| `OLLAMA_BASE_URL` | Override Ollama Cloud base URL (default: `https://ollama.com/v1`) |
| `XAI_API_KEY` | xAI (Grok) API key for chat + TTS ([console.x.ai](https://console.x.ai/)) |
@@ -91,7 +95,7 @@ For native Anthropic auth, Hermes prefers Claude Code's own credential files whe
| Variable | Description |
|----------|-------------|
| `HERMES_INFERENCE_PROVIDER` | Override provider selection: `auto`, `custom`, `openrouter`, `nous`, `openai-codex`, `copilot`, `copilot-acp`, `anthropic`, `huggingface`, `gemini`, `zai`, `kimi-coding`, `kimi-coding-cn`, `minimax`, `minimax-cn`, `kilocode`, `xiaomi`, `arcee`, `gmi`, `alibaba`, `deepseek`, `nvidia`, `ollama-cloud`, `xai` (alias `grok`), `google-gemini-cli`, `qwen-oauth`, `bedrock`, `opencode-zen`, `opencode-go`, `ai-gateway` (default: `auto`) |
| `HERMES_INFERENCE_PROVIDER` | Override provider selection: `auto`, `custom`, `openrouter`, `nous`, `openai-codex`, `copilot`, `copilot-acp`, `anthropic`, `huggingface`, `gemini`, `zai`, `kimi-coding`, `kimi-coding-cn`, `minimax`, `minimax-cn`, `kilocode`, `xiaomi`, `arcee`, `gmi`, `stepfun`, `alibaba`, `deepseek`, `nvidia`, `ollama-cloud`, `xai` (alias `grok`), `google-gemini-cli`, `qwen-oauth`, `bedrock`, `opencode-zen`, `opencode-go`, `ai-gateway` (default: `auto`) |
| `HERMES_PORTAL_BASE_URL` | Override Nous Portal URL (for development/testing) |
| `NOUS_INFERENCE_BASE_URL` | Override Nous inference API URL |
| `HERMES_NOUS_MIN_KEY_TTL_SECONDS` | Min agent key TTL before re-mint (default: 1800 = 30min) |

View File

@@ -48,6 +48,8 @@ Both `provider` and `model` are **required**. If either is missing, the fallback
| MiniMax (China) | `minimax-cn` | `MINIMAX_CN_API_KEY` |
| DeepSeek | `deepseek` | `DEEPSEEK_API_KEY` |
| NVIDIA NIM | `nvidia` | `NVIDIA_API_KEY` (optional: `NVIDIA_BASE_URL`) |
| GMI Cloud | `gmi` | `GMI_API_KEY` (optional: `GMI_BASE_URL`) |
| StepFun | `stepfun` | `STEPFUN_API_KEY` (optional: `STEPFUN_BASE_URL`) |
| Ollama Cloud | `ollama-cloud` | `OLLAMA_API_KEY` |
| Google Gemini (OAuth) | `google-gemini-cli` | `hermes model` (Google OAuth; optional: `HERMES_GEMINI_PROJECT_ID`) |
| Google AI Studio | `gemini` | `GOOGLE_API_KEY` (alias: `GEMINI_API_KEY`) |