Update app.py
Browse files
app.py
CHANGED
@@ -20,9 +20,9 @@ from langchain_core.runnables import RunnablePassthrough, RunnableParallel
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model_name= 'mistralai/Mistral-7B-Instruct-v0.2'
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-
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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tokenizer.pad_token = tokenizer.unk_token
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@@ -98,7 +98,7 @@ db3 = Chroma(persist_directory="chroma/", embedding_function=instructor_embeddin
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retriever = db3.as_retriever(search_type="similarity_score_threshold",
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search_kwargs={"score_threshold": .
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"k": 20})
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#retriever = db3.as_retriever(search_kwargs={"k":15})
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@@ -154,7 +154,7 @@ def format_result(result):
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def generate_with_filters(message, subject_input, rubric, date_beg, date_end):
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if date_beg == "2010-01-01" and date_end == "2025-01-01":
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rag_chain_with_filters = RunnableParallel(
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{"context": db3.as_retriever(search_type="mmr", search_kwargs={"k":
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"filter": {'$and': [{'subject': {
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'$in': subject_input}}, {
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'rubric': {
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@@ -163,7 +163,7 @@ def generate_with_filters(message, subject_input, rubric, date_beg, date_end):
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).assign(answer=rag_chain_from_docs)
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else:
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rag_chain_with_filters = RunnableParallel(
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{"context": db3.as_retriever(search_type="mmr", search_kwargs={"k":
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"filter": {'$and': [{'subject': {
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'$in': subject_input}}, {
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'rubric': {
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@@ -215,7 +215,7 @@ def generate_answer(message, history, checkbox, subject_input, rubric, date_beg,
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'Галузевий розвиток', 'Економічна політика',
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'Державне будівництво', 'Соціальна політика', 'Правова політика',
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'Безпека і оборона', 'Гуманітарна політика']
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result = generate_with_filters(message)
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result['answer'] =result['answer'].split("[/INST]")[-1].strip()
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#model_name= 'mistralai/Mistral-7B-Instruct-v0.2'
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model_name='SherlockAssistant/Mistral-7B-Instruct-Ukrainian'
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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tokenizer.pad_token = tokenizer.unk_token
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retriever = db3.as_retriever(search_type="similarity_score_threshold",
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search_kwargs={"score_threshold": .8,
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"k": 20})
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#retriever = db3.as_retriever(search_kwargs={"k":15})
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def generate_with_filters(message, subject_input, rubric, date_beg, date_end):
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if date_beg == "2010-01-01" and date_end == "2025-01-01":
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rag_chain_with_filters = RunnableParallel(
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{"context": db3.as_retriever(search_type="mmr", search_kwargs={"k": 15,
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"filter": {'$and': [{'subject': {
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'$in': subject_input}}, {
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'rubric': {
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).assign(answer=rag_chain_from_docs)
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else:
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rag_chain_with_filters = RunnableParallel(
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{"context": db3.as_retriever(search_type="mmr", search_kwargs={"k": 15,
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"filter": {'$and': [{'subject': {
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'$in': subject_input}}, {
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'rubric': {
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'Галузевий розвиток', 'Економічна політика',
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'Державне будівництво', 'Соціальна політика', 'Правова політика',
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'Безпека і оборона', 'Гуманітарна політика']
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result = generate_with_filters(message, subject_input, rubric, date_beg, date_end)
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result['answer'] =result['answer'].split("[/INST]")[-1].strip()
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