Files
ragflow/api/apps/restful_apis/_generation_params.py
2026-08-04 10:02:14 +08:00

81 lines
2.8 KiB
Python

#
# Copyright 2026 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from copy import deepcopy
GENERATION_CONFIG_KEYS = ("temperature", "top_p", "frequency_penalty", "presence_penalty", "max_tokens")
# Default values for the four LLM generation parameters stored in
# search_config.llm_setting. When the corresponding ``_enabled`` flag is
# ``False`` (or the key is absent), the default is used instead of whatever
# the user may have stored in ``llm_setting``.
LLM_SETTING_DEFAULTS = {
"temperature": 0.1,
"top_p": 0.3,
"frequency_penalty": 0.7,
"presence_penalty": 0.4,
}
def resolve_llm_setting(llm_setting):
"""Resolve *llm_setting* values according to their enable flags.
For each of the four generation parameters the dictionary may carry a
``{key}_enabled`` boolean. When the flag is ``True`` and the value
exists in *llm_setting*, the user-configured value is kept; otherwise
the default from :data:`LLM_SETTING_DEFAULTS` is substituted.
Keys whose name ends with ``_enabled`` are stripped from the result so
they are never forwarded to the downstream LLM call.
"""
if not llm_setting:
return dict(LLM_SETTING_DEFAULTS)
resolved = {}
for key, default_val in LLM_SETTING_DEFAULTS.items():
enabled_key = f"{key}_enabled"
if llm_setting.get(enabled_key, True) and key in llm_setting:
resolved[key] = llm_setting[key]
else:
resolved[key] = default_val
# Carry over any extra keys that are not generation parameters and not
# enable flags (e.g. ``llm_id``, ``model_type``).
for key, val in llm_setting.items():
if key not in resolved and not key.endswith("_enabled"):
resolved[key] = val
return resolved
def extract_generation_config(req):
return {key: req[key] for key in GENERATION_CONFIG_KEYS if key in req and req[key] is not None}
def pop_generation_config(req):
generation_config = extract_generation_config(req)
for key in GENERATION_CONFIG_KEYS:
req.pop(key, None)
return generation_config
def merge_generation_config(dialog, generation_config):
if not generation_config:
return
llm_setting = deepcopy(getattr(dialog, "llm_setting", None) or {})
llm_setting.update(generation_config)
dialog.llm_setting = llm_setting