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367d42f
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Parent(s):
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progress more 61
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app.py
CHANGED
@@ -18,6 +18,7 @@ import transformers
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from langchain_community.llms import HuggingFacePipeline
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from langchain.prompts import PromptTemplate
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from langchain.chains import LLMChain
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from huggingface_hub import login
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from accelerate import init_empty_weights
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import logging
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@@ -54,7 +55,7 @@ def batch_translate(texts, batch_size=32):
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# Update progress
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progress = (i + len(batch)) / len(texts)
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st.progress(progress)
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st.text(f"
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return translated_texts
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@@ -147,14 +148,14 @@ def estimate_impact(llm, news_text, entity):
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Reasoning: [Your reasoning]
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"""
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prompt = PromptTemplate(template=template, input_variables=["entity", "news"])
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chain =
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response = chain.
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# Parse the response
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impact = "Неопределенный эффект"
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reasoning = "Не удалось получить обоснование"
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if "Estimated Impact:" in response and "Reasoning:" in response:
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impact_part, reasoning_part = response.split("Reasoning:")
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impact = impact_part.split("Estimated Impact:")[1].strip()
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reasoning = reasoning_part.strip()
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@@ -504,7 +505,7 @@ def create_output_file(df, uploaded_file, analysis_df):
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return output
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def main():
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st.title("... приступим к анализу... версия
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# Initialize session state
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if 'processed_df' not in st.session_state:
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from langchain_community.llms import HuggingFacePipeline
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from langchain.prompts import PromptTemplate
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from langchain.chains import LLMChain
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from langchain_core.runnables import RunnablePassthrough
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from huggingface_hub import login
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from accelerate import init_empty_weights
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import logging
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# Update progress
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progress = (i + len(batch)) / len(texts)
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st.progress(progress)
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st.text(f"Предобработано {i + len(batch)} из {len(texts)} текстов")
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return translated_texts
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Reasoning: [Your reasoning]
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"""
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prompt = PromptTemplate(template=template, input_variables=["entity", "news"])
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chain = prompt | llm | RunnablePassthrough()
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response = chain.invoke({"entity": entity, "news": news_text})
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# Parse the response
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impact = "Неопределенный эффект"
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reasoning = "Не удалось получить обоснование"
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if isinstance(response, str) and "Estimated Impact:" in response and "Reasoning:" in response:
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impact_part, reasoning_part = response.split("Reasoning:")
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impact = impact_part.split("Estimated Impact:")[1].strip()
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reasoning = reasoning_part.strip()
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return output
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def main():
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st.title("... приступим к анализу... версия 61")
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# Initialize session state
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if 'processed_df' not in st.session_state:
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