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0975a65347
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55d0dbb62c
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@ -22,7 +22,6 @@ from langchain_openai import ChatOpenAI # pip install -U langchain_openai
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import requests
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# from FlagEmbedding import FlagReranker # deldar-reranker-v2
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import aiofiles
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import oss
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# chatbot = FastAPI()
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# origins = ["*"]
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@ -149,76 +148,6 @@ def llm_base_request2(system_prompt, user_prompt):
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return answer, cost
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async def oss_base_request(sys_prompt, user_prompt):
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base_messages = []
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try:
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if sys_prompt:
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base_messages.append({
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"role": "system",
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"content": sys_prompt
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})
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base_messages.append({
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"role": "user",
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"content": user_prompt
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})
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response = await oss.process_item(base_messages, reasoning_effort='low', temperature=0.1, max_tokens=40)
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if response[0]:
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answer = response[1]
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else:
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answer = ''
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cost = 0
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except Exception as error:
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# برای مدیریت خطاها، میتوانید فایلنویسی را به صورت async انجام دهید (در صورت نیاز)
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async with aiofiles.open('./llm-answer/error-in-llm.txt', mode='a+', encoding='utf-8') as file:
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error_message = f'\n\nquery: {user_prompt.strip()}\nerror:{error} \n------------------------------\n'
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await file.write(error_message) # فایلنویسی async
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return '', 0
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return answer, cost
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async def oss_request(query):
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if query == '':
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return 'لطفا متن سوال را وارد نمائید', 0
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try:
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messages.append({"role": "user", "content": query})
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print(f'final prompt request attmpt')
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response = await oss.process_item(messages= messages) # reasoning_effort='high'
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print(response)
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if response[0]:
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answer = response[1]
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else:
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answer = 'متاسفانه پاسخی دریافت نشد'
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cost_prompt = 0
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# پاسخ را هم به سابقه اضافه میکنیم
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messages.append({"role": "assistant", "content": answer})
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response_dict = {}
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response_dict['output'] = str(response)
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async with aiofiles. open('./llm-answer/messages.json', mode='w', encoding='utf-8') as output:
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await output.write(json.dumps(response_dict, ensure_ascii=False, indent=2))
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print('response created')
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async with aiofiles.open('./llm-answer/chat-objs.txt', mode='a+', encoding='utf-8') as file:
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response_value = '0'
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await file.write(response_value) # estimated_cost
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except Exception as error:
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print(f'error-in-llm.txt writing ...')
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async with aiofiles.open('./llm-answer/error-in-llm.txt', mode='a+', encoding='utf-8') as file:
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error_message = f'\n\nquery: {query.strip()}\nerror:{error} \n-------------------------------\n'
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await file.write(error_message)
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return 'با عرض پوزش؛ متاسفانه خطایی رخ داده است. لطفا لحظاتی دیگر دوباره تلاش نمائید', 0
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print('================')
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print(f'len messages: {len(messages)}')
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print('================')
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return answer, cost_prompt
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async def llm_request(query, model):
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if query == '':
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@ -560,7 +489,7 @@ async def get_title_user_prompt(query: str):
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"""
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get a query and prepare a prompt to generate title based on that
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"""
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title_prompt = f'برای متن {query} یک عنوان با معنا که بین 3 تا 6 کلمه داشته باشد، در قالب یک رشته متن ایجاد کن. سبک و لحن عنوان، حقوقی و کاملا رسمی باشد. عنوان تولید شده کاملا ساده و بدون هیچ مارک داون یا علائم افزوده ای باشد. غیر از عنوان، به هیچ وجه توضیح اضافه ای در قبل یا بعد آن اضافه نکن.'
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title_prompt = f'برای متن {query} زیر، یک موضوع با معنا که بین 3 تا 6 کلمه داشته باشد، در قالب یک رشته متن ایجاد کن. سبک ادبی عنوان، حقوقی و کاملا رسمی باشد. عنوان تولید شده کاملا ساده و بدون هیچ مارک داون یا علائم افزوده ای باشد. غیر از عنوان، به هیچ وجه توضیح اضافه ای در قبل یا بعد آن اضافه نکن.'
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return title_prompt
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async def get_title_system_prompt():
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@ -588,11 +517,7 @@ async def run_chatbot(query:str, chat_id:str):
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before_title_time = datetime.datetime.now()
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title_system_prompt = await get_title_system_prompt()
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title_user_prompt = await get_title_user_prompt(query)
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# title, cost_title = await llm_base_request(title_system_prompt, title_user_prompt)
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title, cost_title = await oss_base_request(title_system_prompt, title_user_prompt)
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if not title:
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title = query
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title, cost_title = await llm_base_request(title_system_prompt, title_user_prompt)
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title_prompt_duration = (datetime.datetime.now() - before_title_time).total_seconds()
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if title == '':
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@ -608,18 +533,18 @@ async def run_chatbot(query:str, chat_id:str):
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prompt = f'برای پرسش "{query}" از میان مواد قانونی "{result_passages_text}" .پاسخ مناسب و دقیق را استخراج کن. درصورتی که مطلبی مرتبط با پرسش در متن پیدا نشد، فقط پاسخ بده: "متاسفانه در منابع، پاسخی پیدا نشد!"'
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# for model in models:
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for model in models:
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# before_prompt_credit = credit_refresh()
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try:
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# llm_model = model
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# print(f'using model: {llm_model}')
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# llm_answer, cost_prompt = await llm_request(prompt, model)
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llm_answer, cost_prompt = await oss_request(prompt)
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llm_model = model
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print(f'using model: {llm_model}')
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llm_answer, cost_prompt = await llm_request(prompt, model)
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break
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except Exception as error:
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# after_prompt_credit = credit_refresh()
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# prompt_cost = int(before_prompt_credit) - int(after_prompt_credit)
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error = f'model: gpt.oss.120b \n{error}\n\n'
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error = f'model: {model} \n{error}\n\n'
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print('+++++++++++++++++')
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print(f'llm-error.txt writing error: {error}')
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print('+++++++++++++++++')
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@ -2,4 +2,3 @@ FROM docker.tavasi.ir/tavasi/qachat_base:1.0.0
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RUN pip install uvicorn[standard]
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RUN pip install FlagEmbedding
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RUN pip install aiofiles
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RUN pip install openai
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File diff suppressed because one or more lines are too long
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@ -539,40 +539,3 @@ Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessa
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31.68
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-------------------------------
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45.93
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-------------------------------
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74.96
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-------------------------------
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100.02
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-------------------------------
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129.08
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-------------------------------
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123.44
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-------------------------------
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236.05
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-------------------------------
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259.93
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-------------------------------
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291.77
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-------------------------------
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319.9
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-------------------------------
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348.04
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-------------------------------
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383.19
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-------------------------------
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235.45
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-------------------------------
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0000000000000000000000000000
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@ -372,46 +372,3 @@
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File diff suppressed because one or more lines are too long
63
oss.py
63
oss.py
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@ -1,63 +0,0 @@
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from openai import AsyncOpenAI
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LLM_URL = "http://172.16.29.102:8001/v1/"
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# item structure:
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# item = {
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# 'id' : '',
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# 'system_prompt' : '',
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# 'user_prompt' : '',
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# 'assistant_prompt' : '',
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# }
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async def process_item(messages, reasoning_effort= 'medium', temperature= 0.4, top_p= 0.9, max_tokens= 2048):
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"""
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generates answer with gpt-oss-120b model
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**Args:
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reasoning_effort = 'medium' # -> low / high / medium
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temperature = 0.4 # 0-1 -> creativity
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top_p = 0.9 # 0-1 -> logic
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max_tokens = 2048 # -> ... 128K
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** Returns(tuple):
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returns True, generated answer / False, failed message
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"""
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try:
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async with AsyncOpenAI(base_url= LLM_URL, api_key="EMPTY") as client:
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model_name = 'gpt-oss-120b'
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# messages = [
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# {"role": "system", "content": prompt_params.get("system_prompt", "")},
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# {"role": "user", "content": prompt_params.get("user_prompt", "")},
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# ]
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# if prompt_params.get("assistant_prompt"):
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# messages.append(
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# {"role": "assistant", "content": prompt_params["assistant_prompt"]}
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# )
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# print(f'==== max_token {max_token}')
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response = await client.chat.completions.parse(
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model= model_name,
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messages= messages,
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temperature= temperature, # 0-1
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top_p=top_p, # 0-1
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reasoning_effort= reasoning_effort, # low , high , medium
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# max_tokens= max_tokens, # ... 128K
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stop= None,
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)
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# print('666666666666666666666666666666666')
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# print(f"response.choices[0].message.parsed: {response.choices[0].message.parsed}")
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# print('666666666666666666666666666666666')
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if response and response.choices : # and response.choices[0].message.parsed:
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response_message = response.choices[0].message.content
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return True, response_message
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except Exception as e:
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response_message = 'error in llm response generation!'
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print('!!!!!!!!!!!!!!!!!!!!!!!!!')
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print(e)
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print('!!!!!!!!!!!!!!!!!!!!!!!!!')
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return False, response_message
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