frankai98 commited on
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33248ee
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1 Parent(s): cc58a52

Update app.py

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Files changed (1) hide show
  1. app.py +11 -6
app.py CHANGED
@@ -88,7 +88,7 @@ def build_prompt(query_input, sampled_docs):
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  sentiment_word = doc['sentiment'].lower() if doc.get('sentiment') else "unknown"
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  docs_text += f"Tweet {idx+1} (Sentiment: {sentiment_word}): {doc['comment']}\n"
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- system_message = """You are an intelligent assistant. Read the Tweets with their sentiment score (Negative, Neutral, Positive) provided and produce a well-structured report that answers the query question.
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  Your task:
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  - Summarize both positive and negative aspects, highlighting any trends in user sentiment.
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  - Include an introduction, key insights, and a conclusion, reaching about 300 words.
@@ -103,11 +103,16 @@ Now produce the final report only, without reiterating these instructions or the
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  messages = [
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  [
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- {"role": "system", "content": [{"type": "text", "text": system_message},]},
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- {"role": "user", "content": [{"type": "text", "text": user_content},]},
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- ],
 
 
 
 
 
 
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  ]
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-
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  return messages
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  # A helper to extract the assistant's response
@@ -275,7 +280,7 @@ def main():
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  device="cuda" if torch.cuda.is_available() else -1,
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  torch_dtype=torch.bfloat16,
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  )
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- result = pipe(prompt, max_new_tokens=256, repetition_penalty=1.2, do_sample=True, temperature=0.5, return_full_text=False)
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  return result, None
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  except Exception as e:
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  return None, str(e)
 
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  sentiment_word = doc['sentiment'].lower() if doc.get('sentiment') else "unknown"
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  docs_text += f"Tweet {idx+1} (Sentiment: {sentiment_word}): {doc['comment']}\n"
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+ system_message = """You are an helpful assistant. Read the Tweets with their sentiment (Negative, Neutral, Positive) provided and produce a well-structured report that answers the query question.
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  Your task:
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  - Summarize both positive and negative aspects, highlighting any trends in user sentiment.
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  - Include an introduction, key insights, and a conclusion, reaching about 300 words.
 
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  messages = [
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  [
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+ {
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+ "role": "system",
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+ "content": [{"type": "text", "text": system_message}]
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+ },
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+ {
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+ "role": "user",
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+ "content": [{"type": "text", "text": user_prompt}]
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+ }
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+ ]
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  ]
 
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  return messages
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  # A helper to extract the assistant's response
 
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  device="cuda" if torch.cuda.is_available() else -1,
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  torch_dtype=torch.bfloat16,
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  )
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+ result = pipe(prompt, max_new_tokens=256, return_full_text=False)
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  return result, None
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  except Exception as e:
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  return None, str(e)