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reasoning effort as models support

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Game_Time
2025-08-24 23:53:37 +05:00
parent e58500d824
commit 7d944548cd
6 changed files with 111 additions and 31 deletions
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3
chatmock/app.py
View File

@@ -14,6 +14,7 @@ def create_app(
reasoning_summary: str = "auto",
reasoning_compat: str = "think-tags",
debug_model: str | None = None,
expose_reasoning_models: bool = False,
) -> Flask:
app = Flask(__name__)
@@ -24,6 +25,7 @@ def create_app(
REASONING_COMPAT=reasoning_compat,
DEBUG_MODEL=debug_model,
BASE_INSTRUCTIONS=BASE_INSTRUCTIONS,
EXPOSE_REASONING_MODELS=bool(expose_reasoning_models),
)
@app.get("/")
@@ -41,4 +43,3 @@ def create_app(
app.register_blueprint(ollama_bp)
return app

12
chatmock/cli.py
View File

@@ -54,6 +54,7 @@ def cmd_serve(
reasoning_summary: str,
reasoning_compat: str,
debug_model: str | None,
expose_reasoning_models: bool,
) -> int:
app = create_app(
verbose=verbose,
@@ -61,6 +62,7 @@ def cmd_serve(
reasoning_summary=reasoning_summary,
reasoning_compat=reasoning_compat,
debug_model=debug_model,
expose_reasoning_models=expose_reasoning_models,
)
app.run(host=host, debug=False, use_reloader=False, port=port, threaded=True)
@@ -106,6 +108,15 @@ def main() -> None:
"'current' is accepted as an alias for 'legacy'"
),
)
p_serve.add_argument(
"--expose-reasoning-models",
action="store_true",
default=os.getenv("CHATGPT_LOCAL_EXPOSE_REASONING_MODELS", "").strip().lower() in ("1", "true", "yes", "on"),
help=(
"Expose gpt-5 reasoning effort variants (minimal|low|medium|high) as separate models from /v1/models. "
"This allows choosing effort via model selection in compatible UIs."
),
)
p_info = sub.add_parser("info", help="Print current stored tokens and derived account id")
p_info.add_argument("--json", action="store_true", help="Output raw auth.json contents")
@@ -124,6 +135,7 @@ def main() -> None:
reasoning_summary=args.reasoning_summary,
reasoning_compat=args.reasoning_compat,
debug_model=args.debug_model,
expose_reasoning_models=args.expose_reasoning_models,
)
)
elif args.command == "info":

26
chatmock/reasoning.py
View File

@@ -72,3 +72,29 @@ def apply_reasoning_to_message(
message["content"] = think_block + (content_text or "")
return message
def extract_reasoning_from_model_name(model: str | None) -> Dict[str, Any] | None:
"""Infer reasoning overrides from a model."""
if not isinstance(model, str) or not model:
return None
s = model.strip().lower()
if not s:
return None
efforts = {"minimal", "low", "medium", "high"}
if ":" in s:
maybe = s.rsplit(":", 1)[-1].strip()
if maybe in efforts:
return {"effort": maybe}
for sep in ("-", "_"):
if s.endswith(sep + "minimal"):
return {"effort": "minimal"}
if s.endswith(sep + "low"):
return {"effort": "low"}
if s.endswith(sep + "medium"):
return {"effort": "medium"}
if s.endswith(sep + "high"):
return {"effort": "high"}
return None

57
chatmock/routes_ollama.py
View File

@@ -9,7 +9,7 @@ from flask import Blueprint, Response, current_app, jsonify, make_response, requ
from .config import BASE_INSTRUCTIONS
from .http import build_cors_headers
from .reasoning import build_reasoning_param
from .reasoning import build_reasoning_param, extract_reasoning_from_model_name
from .transform import convert_ollama_messages, normalize_ollama_tools
from .upstream import normalize_model_name, start_upstream_request
from .utils import convert_chat_messages_to_responses_input, convert_tools_chat_to_responses
@@ -32,24 +32,39 @@ _OLLAMA_FAKE_EVAL = {
def ollama_tags() -> Response:
if bool(current_app.config.get("VERBOSE")):
print("IN GET /api/tags")
model_id = "gpt-5"
models = [
{
"name": model_id,
"model": model_id,
"modified_at": "2023-10-01T00:00:00Z",
"size": 815319791,
"digest": "8648f39daa8fbf5b18c7b4e6a8fb4990c692751d49917417b8842ca5758e7ffc",
"details": {
"parent_model": "",
"format": "gguf",
"family": "llama",
"families": ["llama"],
"parameter_size": "8.0B",
"quantization_level": "Q4_0",
},
}
expose_variants = bool(current_app.config.get("EXPOSE_REASONING_MODELS"))
model_ids = [
"gpt-5",
*(
[
"gpt-5-high",
"gpt-5-medium",
"gpt-5-low",
"gpt-5-minimal",
]
if expose_variants
else []
),
]
models = []
for model_id in model_ids:
models.append(
{
"name": model_id,
"model": model_id,
"modified_at": "2023-10-01T00:00:00Z",
"size": 815319791,
"digest": "8648f39daa8fbf5b18c7b4e6a8fb4990c692751d49917417b8842ca5758e7ffc",
"details": {
"parent_model": "",
"format": "gguf",
"family": "llama",
"families": ["llama"],
"parameter_size": "8.0B",
"quantization_level": "Q4_0",
},
}
)
resp = make_response(jsonify({"models": models}), 200)
for k, v in build_cors_headers().items():
resp.headers.setdefault(k, v)
@@ -137,6 +152,8 @@ def ollama_chat() -> Response:
input_items = convert_chat_messages_to_responses_input(messages)
# Infer effort from model variant (gpt-5-high, etc.) but send base model upstream
model_reasoning = extract_reasoning_from_model_name(model)
upstream, error_resp = start_upstream_request(
normalize_model_name(model),
input_items,
@@ -144,7 +161,7 @@ def ollama_chat() -> Response:
tools=tools_responses,
tool_choice=tool_choice,
parallel_tool_calls=parallel_tool_calls,
reasoning_param=build_reasoning_param(reasoning_effort, reasoning_summary, None),
reasoning_param=build_reasoning_param(reasoning_effort, reasoning_summary, model_reasoning),
)
if error_resp is not None:
return error_resp
@@ -162,7 +179,7 @@ def ollama_chat() -> Response:
)
created_at = datetime.datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%SZ")
model_out = normalize_model_name(model)
model_out = model if isinstance(model, str) and model.strip() else normalize_model_name(model)
if stream_req:
def _gen():

37
chatmock/routes_openai.py
View File

@@ -8,7 +8,7 @@ from flask import Blueprint, Response, current_app, jsonify, make_response, requ
from .config import BASE_INSTRUCTIONS
from .http import build_cors_headers
from .reasoning import apply_reasoning_to_message, build_reasoning_param
from .reasoning import apply_reasoning_to_message, build_reasoning_param, extract_reasoning_from_model_name
from .upstream import normalize_model_name, start_upstream_request
from .utils import (
convert_chat_messages_to_responses_input,
@@ -45,7 +45,8 @@ def chat_completions() -> Response:
except Exception:
return jsonify({"error": {"message": "Invalid JSON body"}}), 400
model = normalize_model_name(payload.get("model"), debug_model)
requested_model = payload.get("model")
model = normalize_model_name(requested_model, debug_model)
messages = payload.get("messages")
if messages is None and isinstance(payload.get("prompt"), str):
messages = [{"role": "user", "content": payload.get("prompt") or ""}]
@@ -76,7 +77,8 @@ def chat_completions() -> Response:
{"type": "message", "role": "user", "content": [{"type": "input_text", "text": payload.get("prompt")}]}
]
reasoning_overrides = payload.get("reasoning") if isinstance(payload.get("reasoning"), dict) else None
model_reasoning = extract_reasoning_from_model_name(requested_model)
reasoning_overrides = payload.get("reasoning") if isinstance(payload.get("reasoning"), dict) else model_reasoning
reasoning_param = build_reasoning_param(reasoning_effort, reasoning_summary, reasoning_overrides)
upstream, error_resp = start_upstream_request(
@@ -109,7 +111,7 @@ def chat_completions() -> Response:
resp = Response(
sse_translate_chat(
upstream,
model,
requested_model or model,
created,
verbose=verbose,
vlog=print if verbose else None,
@@ -206,7 +208,7 @@ def chat_completions() -> Response:
"id": response_id or "chatcmpl",
"object": "chat.completion",
"created": created,
"model": model,
"model": requested_model or model,
"choices": [
{
"index": 0,
@@ -235,7 +237,8 @@ def completions() -> Response:
except Exception:
return jsonify({"error": {"message": "Invalid JSON body"}}), 400
model = normalize_model_name(payload.get("model"), debug_model)
requested_model = payload.get("model")
model = normalize_model_name(requested_model, debug_model)
prompt = payload.get("prompt")
if isinstance(prompt, list):
prompt = "".join([p if isinstance(p, str) else "" for p in prompt])
@@ -248,7 +251,8 @@ def completions() -> Response:
messages = [{"role": "user", "content": prompt or ""}]
input_items = convert_chat_messages_to_responses_input(messages)
reasoning_overrides = payload.get("reasoning") if isinstance(payload.get("reasoning"), dict) else None
model_reasoning = extract_reasoning_from_model_name(requested_model)
reasoning_overrides = payload.get("reasoning") if isinstance(payload.get("reasoning"), dict) else model_reasoning
reasoning_param = build_reasoning_param(reasoning_effort, reasoning_summary, reasoning_overrides)
upstream, error_resp = start_upstream_request(
model,
@@ -274,7 +278,7 @@ def completions() -> Response:
resp = Response(
sse_translate_text(
upstream,
model,
requested_model or model,
created,
verbose=verbose,
vlog=(print if verbose else None),
@@ -335,7 +339,7 @@ def completions() -> Response:
"id": response_id or "cmpl",
"object": "text_completion",
"created": created,
"model": model,
"model": requested_model or model,
"choices": [
{"index": 0, "text": full_text, "finish_reason": "stop", "logprobs": None}
],
@@ -349,7 +353,20 @@ def completions() -> Response:
@openai_bp.route("/v1/models", methods=["GET"])
def list_models() -> Response:
models = {"object": "list", "data": [{"id": "gpt-5", "object": "model", "owned_by": "owner"}]}
expose_variants = bool(current_app.config.get("EXPOSE_REASONING_MODELS"))
data = []
if expose_variants:
variant_ids = [
"gpt-5",
"gpt-5-high",
"gpt-5-medium",
"gpt-5-low",
"gpt-5-minimal",
]
data = [{"id": mid, "object": "model", "owned_by": "owner"} for mid in variant_ids]
else:
data = [{"id": "gpt-5", "object": "model", "owned_by": "owner"}]
models = {"object": "list", "data": data}
resp = make_response(jsonify(models), 200)
for k, v in build_cors_headers().items():
resp.headers.setdefault(k, v)

7
chatmock/upstream.py
View File

@@ -20,6 +20,13 @@ def normalize_model_name(name: str | None, debug_model: str | None = None) -> st
if not isinstance(name, str) or not name.strip():
return "gpt-5"
base = name.split(":", 1)[0].strip()
for sep in ("-", "_"):
lowered = base.lower()
for effort in ("minimal", "low", "medium", "high"):
suffix = f"{sep}{effort}"
if lowered.endswith(suffix):
base = base[: -len(suffix)]
break
mapping = {
"gpt5": "gpt-5",
"gpt-5-latest": "gpt-5",