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* Prepare for docker, documentation. * Prepare for docker, documentation. * Prepare for docker, documentation. --------- Co-authored-by: APodoinikov <APodoynikov@detmir.ru>
97 lines
3.7 KiB
Python
97 lines
3.7 KiB
Python
import os
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import lmstudio
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from lmstudio import LLM, LlmPredictionConfig
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from tqdm import tqdm
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from app import params, translate_func
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from app.app_core import AppCore
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from app.dto import TranslatePluginInitInfo, TranslateStruct
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from app.lang_dict import get_lang_by_2_chars_code
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plugin_name = os.path.basename(__file__)[:-3] # calculating modname
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llm_model: LLM | None = None
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def start(core: AppCore):
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manifest = {
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"name": "LM-Studio Translator", # name
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"version": "1.0", # version
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"default_options": {
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"custom_url": "http://localhost:1234", #
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"prompt": "You are professional translator. Translate text from %%from_lang%% to %%to_lang%%. Don't add any notes or any additional info in your answer, write only translate. Text: ",
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"prompt_postfix": "",
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"prompt_no_think_postfix": False,
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"use_library_for_request": True,
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},
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"translate": {
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"lm_studio": (init, translate) # 1 function - init, 2 - translate
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}
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}
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return manifest
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def start_with_options(core: AppCore, manifest: dict):
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params.read_plugin_translate_params(manifest)
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pass
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def init(core: AppCore) -> TranslatePluginInitInfo:
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options = core.plugin_options(plugin_name)
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custom_url: str = options['custom_url']
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use_library_for_request = options["use_library_for_request"]
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if use_library_for_request:
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lmstudio.configure_default_client(custom_url.replace("http://", ""))
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loaded_models = lmstudio.list_loaded_models("llm")
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if len(loaded_models) > 0:
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model_identifier = loaded_models[0].identifier
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global llm_model
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llm_model = lmstudio.llm(model_identifier)
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return TranslatePluginInitInfo(plugin_name=plugin_name, model_name=model_identifier)
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else:
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raise ValueError('List loaded models is empty. Please load model before init this plugin')
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else:
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postfix = translate_func.get_prompt_postfix(options["prompt_postfix"], options['prompt_no_think_postfix'])
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prompt = "You are assistant. " + postfix
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req = translate_func.get_open_ai_request(prompt, "init")
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resp = translate_func.post_request(req, options['custom_url'] + "/v1/chat/completions")
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return TranslatePluginInitInfo(plugin_name=plugin_name, model_name=resp["model"])
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def translate(core: AppCore, ts: TranslateStruct) -> TranslateStruct:
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options = core.plugin_options(plugin_name)
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from_lang_name = get_lang_by_2_chars_code(ts.req.from_lang)
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to_lang_name = get_lang_by_2_chars_code(ts.req.to_lang)
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prompt = translate_func.generate_prompt(options["prompt"], from_lang_name, to_lang_name,
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options["prompt_postfix"], options['prompt_no_think_postfix'])
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use_library_for_request = options["use_library_for_request"]
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for part in tqdm(ts.parts, unit=params.tp.unit, ascii=params.tp.ascii, desc=params.tp.desc):
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if part.need_to_translate():
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content: str
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if use_library_for_request:
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content = library_request(llm_model, prompt, part.text)
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else:
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req = translate_func.get_open_ai_request(prompt, part.text)
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resp = translate_func.post_request(req, options['custom_url'] + "/v1/chat/completions")
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content = resp["choices"][0]['message']['content']
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part.translate = translate_func.remove_think_text(content)
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return ts
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def library_request(model: LLM, prompt: str, text: str) -> str:
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chat = lmstudio.Chat(prompt)
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chat.add_user_message(text)
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result = model.respond(chat, config=LlmPredictionConfig(temperature=0.0))
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return result.content
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