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Change the opt dictionary to a mappings dictionary with appropriate casts

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This is to bring consistency with apply_model_params_to_body_openai. Both now use a mapping dictionary then call and return apply_model_params_to_body directly.
This commit is contained in:
ferret99gt 2025-02-19 09:30:16 -05:00
parent fa885c3346
commit 5701d6d333
1 changed files with 32 additions and 34 deletions
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66
backend/open_webui/utils/payload.py
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@ -70,47 +70,45 @@ def apply_model_params_to_body_ollama(params: dict, form_data: dict) -> dict:
name_differences = {
"max_tokens": "num_predict",
}
for key, value in name_differences.items():
if (param := params.get(key, None)) is not None:
# Copy the parameter to new name then delete it, to prevent Ollama warning of invalid option provided
params[value] = params[key]
del params[key]
opts = [
"temperature",
"top_p",
"seed",
"mirostat",
"mirostat_eta",
"mirostat_tau",
"num_ctx",
"num_batch",
"num_keep",
"num_predict",
"repeat_last_n",
"top_k",
"min_p",
"typical_p",
"repeat_penalty",
"presence_penalty",
"frequency_penalty",
"penalize_newline",
"stop",
"numa",
"num_gpu",
"main_gpu",
"low_vram",
"vocab_only",
"use_mmap",
"use_mlock",
"num_thread",
# See https://github.com/ollama/ollama/blob/main/docs/api.md#request-8
mappings = {
"temperature": float,
"top_p": float,
"seed": lambda x: x,
"mirostat": int,
"mirostat_eta": float,
"mirostat_tau": float,
"num_ctx": int,
"num_batch": int,
"num_keep": int,
"num_predict": int,
"repeat_last_n": int,
"top_k": int,
"min_p": float,
"typical_p": float,
"repeat_penalty": float,
"presence_penalty": float,
"frequency_penalty": float,
"penalize_newline": bool,
"stop": lambda x: [bytes(s, "utf-8").decode("unicode_escape") for s in x],
"numa": bool,
"num_gpu": int,
"main_gpu": int,
"low_vram": bool,
"vocab_only": bool,
"use_mmap": bool,
"use_mlock": bool,
"num_thread": int,
}
]
mappings = {i: lambda x: x for i in opts}
form_data = apply_model_params_to_body(params, form_data, mappings)
return form_data
return apply_model_params_to_body(params, form_data, mappings)
def convert_messages_openai_to_ollama(messages: list[dict]) -> list[dict]: