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Update app.py
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app.py
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@@ -19,6 +19,16 @@ from langchain.memory import ConversationBufferMemory
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from langchain.chains.question_answering import load_qa_chain
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from langchain.document_loaders import TextLoader
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from langchain.text_splitter import CharacterTextSplitter
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# --- Constants ---
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MODEL_NAME = "bigscience/bloom-1b7"
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@@ -27,10 +37,6 @@ TEMPERATURE = 0.7
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TOP_P = 0.95
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REPETITION_PENALTY = 1.2
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# --- Model & Tokenizer ---
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model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
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# --- Agents ---
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agents = {
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"WEB_DEV": {
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from langchain.chains.question_answering import load_qa_chain
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from langchain.document_loaders import TextLoader
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from langchain.text_splitter import CharacterTextSplitter
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from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM, Seq2SeqLMForCausalGeneration
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def create_causal_lm(model_name: str):
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForSeq2SeqLM.from_pretrained(model_name).causal_decoder
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return model, tokenizer
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AutoModelForCausalLM = lambda model_name: create_causal_lm(model_name)[0]
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AutoTokenizerForCausalLM = lambda model_name: create_causal_lm(model_name)[1]
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# --- Constants ---
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MODEL_NAME = "bigscience/bloom-1b7"
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TOP_P = 0.95
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REPETITION_PENALTY = 1.2
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# --- Agents ---
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agents = {
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"WEB_DEV": {
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