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refactor: Refactor proxy LLM (#1064)

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Fangyin Cheng
2024-01-14 21:01:37 +08:00
committed by GitHub
parent a035433170
commit 22bfd01c4b
95 changed files with 2049 additions and 1294 deletions
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50
dbgpt/model/llm_out/proxy_llm.py
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@@ -13,28 +13,28 @@ from dbgpt.model.proxy.llms.tongyi import tongyi_generate_stream
from dbgpt.model.proxy.llms.wenxin import wenxin_generate_stream
from dbgpt.model.proxy.llms.zhipu import zhipu_generate_stream
def proxyllm_generate_stream(
model: ProxyModel, tokenizer, params, device, context_len=2048
):
generator_mapping = {
"proxyllm": chatgpt_generate_stream,
"chatgpt_proxyllm": chatgpt_generate_stream,
"bard_proxyllm": bard_generate_stream,
"claude_proxyllm": claude_generate_stream,
# "gpt4_proxyllm": gpt4_generate_stream, move to chatgpt_generate_stream
"wenxin_proxyllm": wenxin_generate_stream,
"tongyi_proxyllm": tongyi_generate_stream,
"zhipu_proxyllm": zhipu_generate_stream,
"gemini_proxyllm": gemini_generate_stream,
"bc_proxyllm": baichuan_generate_stream,
"spark_proxyllm": spark_generate_stream,
}
model_params = model.get_params()
model_name = model_params.model_name
default_error_message = f"{model_name} LLM is not supported"
generator_function = generator_mapping.get(
model_name, lambda *args: [default_error_message]
)
yield from generator_function(model, tokenizer, params, device, context_len)
# This has been moved to dbgpt/model/adapter/proxy_adapter.py
# def proxyllm_generate_stream(
# model: ProxyModel, tokenizer, params, device, context_len=2048
# ):
# generator_mapping = {
# "proxyllm": chatgpt_generate_stream,
# "chatgpt_proxyllm": chatgpt_generate_stream,
# "bard_proxyllm": bard_generate_stream,
# "claude_proxyllm": claude_generate_stream,
# # "gpt4_proxyllm": gpt4_generate_stream, move to chatgpt_generate_stream
# "wenxin_proxyllm": wenxin_generate_stream,
# "tongyi_proxyllm": tongyi_generate_stream,
# "zhipu_proxyllm": zhipu_generate_stream,
# "gemini_proxyllm": gemini_generate_stream,
# "bc_proxyllm": baichuan_generate_stream,
# "spark_proxyllm": spark_generate_stream,
# }
# model_params = model.get_params()
# model_name = model_params.model_name
# default_error_message = f"{model_name} LLM is not supported"
# generator_function = generator_mapping.get(
# model_name, lambda *args: [default_error_message]
# )
#
# yield from generator_function(model, tokenizer, params, device, context_len)