Revert "Auxiliary commit to revert individual files from da05525cbbf2510a2cbc37d7eed6bfb8248e448b"

This reverts commit 1564022cae5da71efc060e576672d51b96051758.
This commit is contained in:
Liujian
2025-04-07 11:51:50 +08:00
parent da05525cbb
commit 9598254d18
60 changed files with 0 additions and 606 deletions
@@ -1,7 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"top_k": "",
"max_tokens": "max_tokens",
"response_format": "response_format"
}
@@ -1,7 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"top_k": "int",
"max_tokens": "int",
"response_format": ""
}
@@ -1,10 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"top_k": "",
"max_tokens": "max_tokens",
"with_search_enhance": "",
"presence_penalty": "presence_penalty",
"frequency_penalty": "frequency_penalty",
"res_format": ""
}
@@ -1,10 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"top_k": "int",
"max_tokens": "int",
"with_search_enhance": "boolean",
"presence_penalty": "float",
"frequency_penalty": "float",
"res_format": "string"
}
@@ -1,17 +0,0 @@
{
"max_tokens": "max_tokens",
"temperature": "temperature",
"top_p": "top_p",
"top_k": "top_k",
"response_format": "response_format",
"max_gen_len": "max_tokens",
"max_new_tokens": "max_tokens",
"p": "top_p",
"k": "",
"presence_penalty": "presence_penalty",
"frequency_penalty": "frequency_penalty",
"topP": "top_p",
"maxTokens": "max_tokens",
"count_penalty": "",
"maxTokenCount": "max_tokens"
}
@@ -1,17 +0,0 @@
{
"max_tokens": "int",
"temperature": "float",
"top_p": "float",
"top_k": "int",
"response_format": "",
"max_gen_len": "int",
"max_new_tokens": "int",
"p": "float",
"k": "int",
"presence_penalty": "float",
"frequency_penalty": "float",
"topP": "float",
"maxTokens": "int",
"count_penalty": "float",
"maxTokenCount": "int"
}
@@ -1,5 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens"
}
@@ -1,5 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int"
}
@@ -1,10 +0,0 @@
{
"temperature": "temperature",
"p": "top_p",
"k": "",
"presence_penalty": "presence_penalty",
"frequency_penalty": "frequency_penalty",
"max_tokens": "max_tokens",
"preamble_override": "",
"prompt_truncation": ""
}
@@ -1,10 +0,0 @@
{
"temperature": "float",
"p": "float",
"k": "int",
"presence_penalty": "float",
"frequency_penalty": "float",
"max_tokens": "int",
"preamble_override": "string",
"prompt_truncation": "string"
}
@@ -1,9 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"logprobs": "",
"top_logprobs": "",
"frequency_penalty": "frequency_penalty",
"response_format": ""
}
@@ -1,9 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"logprobs": "boolean",
"top_logprobs": "int",
"frequency_penalty": "float",
"response_format": "string"
}
@@ -1,6 +0,0 @@
{
"max_tokens": "max_tokens",
"temperature": "temperature",
"top_p": "",
"top_k": ""
}
@@ -1,6 +0,0 @@
{
"max_tokens": "int",
"temperature": "float",
"top_p": "float",
"top_k": "int"
}
@@ -1,8 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"top_k": "",
"max_tokens": "max_tokens",
"context_length_exceeded_behavior": "",
"response_format": "response_format"
}
@@ -1,8 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"top_k": "int",
"max_tokens": "int",
"context_length_exceeded_behavior": "string",
"response_format": ""
}
@@ -1,9 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"top_k": "",
"max_output_tokens": "max_tokens",
"json_schema": "json_schema",
"max_tokens_to_sample": "max_tokens",
"response_format": "response_format"
}
@@ -1,9 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"top_k": "int",
"max_output_tokens": "int",
"json_schema": "",
"max_tokens_to_sample": "int",
"response_format": ""
}
@@ -1,6 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"response_format": ""
}
@@ -1,6 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"response_format": "string"
}
@@ -1,6 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"enable_enhance": ""
}
@@ -1,6 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"enable_enhance": "boolean"
}
@@ -1,9 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"mask_sensitive_info": "",
"presence_penalty": "presence_penalty",
"frequency_penalty": "frequency_penalty",
"plugin_web_search": ""
}
@@ -1,9 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"mask_sensitive_info": "boolean",
"presence_penalty": "float",
"frequency_penalty": "float",
"plugin_web_search": "boolean"
}
@@ -1,7 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"safe_prompt": "",
"random_seed": ""
}
@@ -1,7 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"safe_prompt": "boolean",
"random_seed": "int"
}
@@ -1,6 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"response_format": ""
}
@@ -1,6 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"response_format": "string"
}
@@ -1,7 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"frequency_penalty": "frequency_penalty",
"presence_penalty": "presence_penalty"
}
@@ -1,7 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"frequency_penalty": "float",
"presence_penalty": "float"
}
@@ -1,9 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"frequency_penalty": "frequency_penalty",
"presence_penalty": "presence_penalty",
"random_seed": "",
"frequency_penalt": "frequency_penalty"
}
@@ -1,9 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"frequency_penalty": "float",
"presence_penalty": "float",
"random_seed": "int",
"frequency_penalt": "float"
}
@@ -1,11 +0,0 @@
{
"max_tokens": "max_tokens",
"reasoning_effort": "",
"response_format": "response_format",
"temperature": "temperature",
"top_p": "top_p",
"presence_penalty": "presence_penalty",
"frequency_penalty": "frequency_penalty",
"seed": "",
"json_schema": "json_schema"
}
@@ -1,11 +0,0 @@
{
"max_tokens": "int",
"reasoning_effort": "string",
"response_format": "string",
"temperature": "float",
"top_p": "float",
"presence_penalty": "float",
"frequency_penalty": "float",
"seed": "int",
"json_schema": ""
}
@@ -1,11 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"top_k": "",
"context_length_exceeded_behavior": "",
"response_format": "response_format",
"presence_penalty": "presence_penalty",
"frequency_penalty": "frequency_penalty",
"seed": ""
}
@@ -1,11 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"top_k": "int",
"context_length_exceeded_behavior": "string",
"response_format": "string",
"presence_penalty": "float",
"frequency_penalty": "float",
"seed": "int"
}
@@ -1,7 +0,0 @@
{
"temperature": "temperature",
"max_tokens": "max_tokens",
"top_p": "top_p",
"top_k": "",
"repetition_penalty": ""
}
@@ -1,7 +0,0 @@
{
"temperature": "float",
"max_tokens": "int",
"top_p": "float",
"top_k": "int",
"repetition_penalty": "float"
}
@@ -1,10 +0,0 @@
{
"max_tokens": "max_tokens",
"temperature": "temperature",
"top_p": "top_p",
"frequency_penalty": "frequency_penalty",
"top_k": "",
"response_format": "",
"seed": "",
"repetition_penalty": ""
}
@@ -1,10 +0,0 @@
{
"max_tokens": "int",
"temperature": "float",
"top_p": "float",
"frequency_penalty": "float",
"top_k": "int",
"response_format": "string",
"seed": "int",
"repetition_penalty": "float"
}
@@ -1,6 +0,0 @@
{
"temperature": "temperature",
"max_tokens": "max_tokens",
"top_k": "",
"show_ref_label": ""
}
@@ -1,6 +0,0 @@
{
"temperature": "float",
"max_tokens": "int",
"top_k": "int",
"show_ref_label": "boolean"
}
@@ -1,5 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens"
}
@@ -1,5 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int"
}
@@ -1,11 +0,0 @@
{
"temperature": "temperature",
"max_tokens": "max_tokens",
"top_p": "top_p",
"top_k": "",
"seed": "",
"repetition_penalty": "",
"response_format": "response_format",
"enable_search": "",
"frequency_penalty": "frequency_penalty"
}
@@ -1,11 +0,0 @@
{
"temperature": "float",
"max_tokens": "int",
"top_p": "float",
"top_k": "int",
"seed": "int",
"repetition_penalty": "float",
"response_format": "string",
"enable_search": "boolean",
"frequency_penalty": "float"
}
@@ -1,6 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"seed": ""
}
@@ -1,6 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"seed": "int"
}
@@ -1,10 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"top_k": "",
"max_output_tokens": "max_tokens",
"json_schema": "json_schema",
"presence_penalty": "presence_penalty",
"frequency_penalty": "frequency_penalty",
"max_tokens": "max_tokens"
}
@@ -1,10 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"top_k": "int",
"max_output_tokens": "int",
"json_schema": "",
"presence_penalty": "float",
"frequency_penalty": "float",
"max_tokens": "int"
}
@@ -1,11 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"presence_penalty": "presence_penalty",
"frequency_penalty": "frequency_penalty",
"response_format": "response_format",
"disable_search": "",
"min_output_tokens": "max_tokens",
"max_output_tokens": "max_tokens"
}
@@ -1,11 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"presence_penalty": "float",
"frequency_penalty": "float",
"response_format": "",
"disable_search": "boolean",
"min_output_tokens": "int",
"max_output_tokens": "int"
}
@@ -1,5 +0,0 @@
{
"temperature": "temperature",
"max_tokens": "max_tokens",
"top_p": "top_p"
}
@@ -1,5 +0,0 @@
{
"temperature": "float",
"max_tokens": "int",
"top_p": "float"
}
@@ -1,7 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"max_tokens": "max_tokens",
"frequency_penalty": "frequency_penalty",
"presence_penalty": "presence_penalty"
}
@@ -1,7 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"max_tokens": "int",
"frequency_penalty": "float",
"presence_penalty": "float"
}
@@ -1,10 +0,0 @@
{
"temperature": "temperature",
"top_p": "top_p",
"do_sample": "",
"max_tokens": "max_tokens",
"web_search": "",
"response_format": "",
"stream": "",
"return_type": ""
}
@@ -1,10 +0,0 @@
{
"temperature": "float",
"top_p": "float",
"do_sample": "boolean",
"max_tokens": "int",
"web_search": "boolean",
"response_format": "string",
"stream": "boolean",
"return_type": "string"
}
-44
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@@ -1,44 +0,0 @@
{
"context_length_exceeded_behavior": "",
"count_penalty": "",
"disable_search": "",
"do_sample": "",
"enable_enhance": "",
"enable_search": "",
"frequency_penalt": "frequency_penalty",
"frequency_penalty": "frequency_penalty",
"json_schema": "json_schema",
"k": "",
"logprobs": "",
"mask_sensitive_info": "",
"maxTokenCount": "max_tokens",
"maxTokens": "max_tokens",
"max_gen_len": "max_tokens",
"max_new_tokens": "max_tokens",
"max_output_tokens": "max_tokens",
"max_tokens": "max_tokens",
"max_tokens_to_sample": "max_tokens",
"min_output_tokens": "max_tokens",
"p": "top_p",
"plugin_web_search": "",
"preamble_override": "",
"presence_penalty": "presence_penalty",
"prompt_truncation": "",
"random_seed": "",
"reasoning_effort": "",
"repetition_penalty": "",
"res_format": "",
"response_format": "",
"return_type": "",
"safe_prompt": "",
"seed": "",
"show_ref_label": "",
"stream": "",
"temperature": "temperature",
"topP": "top_p",
"top_k": "",
"top_logprobs": "",
"top_p": "top_p",
"web_search": "",
"with_search_enhance": ""
}
-80
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@@ -1,80 +0,0 @@
#!/usr/bin/env python3
import os
import json
from pathlib import Path
# 基础路径
base_path = "/Users/liujian/work/golang/src/github.com/APIParkLab/APIPark/ai-provider/model-runtime/model-providers"
# OpenAI 参数列表
openai_params = [
"max_tokens",
"max_completion_tokens",
"temperature",
"top_p",
"n",
"stream",
"stop",
"presence_penalty",
"response_format",
"seed",
"frequency_penalty"
]
# 参数映射关系
param_mapping = {
"temperature": "temperature",
"top_p": "top_p",
"top_k": "",
"max_tokens": "max_tokens",
"presence_penalty": "presence_penalty",
"frequency_penalty": "frequency_penalty",
"response_format": "response_format",
"res_format": "response_format",
"p": "top_p",
"k": "",
"repetition_penalty": "frequency_penalty",
"reasoning_effort": "",
"enable_enhance": "",
"with_search_enhance": "",
"vision_support": "",
"function_call_support": "",
"context_size": "",
"mode": "",
"max_completion_tokens": "max_completion_tokens",
"seed": "seed",
"n": "n",
"stream": "stream",
"stop": "stop"
}
# 遍历所有供应商目录
for provider_dir in os.listdir(base_path):
provider_path = os.path.join(base_path, provider_dir)
# 检查是否是目录
if not os.path.isdir(provider_path):
continue
# 检查parameter_names.json文件是否存在
param_file = os.path.join(provider_path, "parameter_names.json")
if not os.path.isfile(param_file):
continue
try:
# 读取parameter_names.json文件
with open(param_file, 'r', encoding='utf-8') as f:
params = json.load(f)
# 更新映射关系
for param in params:
if param in param_mapping:
params[param] = param_mapping[param]
# 保存更新后的文件
with open(param_file, 'w', encoding='utf-8') as f:
json.dump(params, f, indent=2, ensure_ascii=False)
print(f"Updated parameter mappings for {provider_dir}")
except Exception as e:
print(f"Error processing {param_file}: {e}")