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import os |
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import numpy as np |
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from langchain_groq import ChatGroq |
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from langchain_openai import ChatOpenAI |
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from langchain_google_genai import ChatGoogleGenerativeAI |
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from langchain_anthropic import ChatAnthropic |
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from langchain_openai import OpenAIEmbeddings |
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from huggingface_hub import login |
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from dotenv import load_dotenv |
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import tiktoken |
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load_dotenv() |
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os.environ['HUGGINGFACEHUB_ACCESS_TOKEN']=os.getenv('HUGGINGFACEHUB_ACCESS_TOKEN') |
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login(os.environ['HUGGINGFACEHUB_ACCESS_TOKEN']) |
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embedding_model = OpenAIEmbeddings(model="text-embedding-3-small", dimensions=1536) |
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llm_anthropic = ChatAnthropic(model='claude-3-7-sonnet-latest', temperature=1) |
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llm_gemini = ChatGoogleGenerativeAI(model="gemini-1.5-flash") |
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llm_groq_openai = ChatGroq(model="openai/gpt-oss-120b",temperature=0.7) |
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llm_groq = ChatGroq(model="llama-3.3-70b-versatile",temperature=0) |
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llm_gpt_small = ChatOpenAI(model="gpt-3.5-turbo",temperature=0.3) |
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llm_gpt = ChatOpenAI(model="gpt-3.5-turbo",temperature=0.3) |
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llm_gpt_high = ChatOpenAI(model="gpt-5-nano",temperature=0.5) |
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encoding_model = 'encoding_model' |
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captioning_model = "meta-llama/llama-4-scout-17b-16e-instruct" |
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image_generation_model = "black-forest-labs/FLUX.1-schnell" |
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ideator_llm = llm_gpt_high |
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moderator_llm = llm_gpt |
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critic_llm = llm_gpt |
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simplifier_llm = llm_gpt |
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normalizer_llm = llm_gpt |
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validator_llm = llm_gpt_small |
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judge1_llm = llm_gpt |
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judge2_llm = llm_gpt |
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