philmui commited on
Commit
e0753bf
โ€ข
1 Parent(s): f57b8d4

fixed salesAgent bug

Browse files
Files changed (2) hide show
  1. agents.py +3 -0
  2. models.py +1 -1
agents.py CHANGED
@@ -127,16 +127,19 @@ def bookAgent(query):
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  def agentController(question_text, model_name):
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  output = ""
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  if is_magic(question_text, LOCAL_MAGIC_TOKENS):
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  output = salesAgent(question_text)
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  print(f"๐Ÿ”น salesAgent: {output}")
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  elif is_magic(question_text, DIGITAL_MAGIC_TOKENS):
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  output = chinookAgent(question_text, model_name)
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  print(f"๐Ÿ”น chinookAgent: {output}")
 
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  elif semantically_similar(question_text, "fight a war"):
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  output = bookAgent(question_text)
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  print(f"๐Ÿ”น bookAgent: {output}")
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  elif semantically_similar(question_text, "how to govern"):
 
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  output = bookAgent(question_text)
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  print(f"๐Ÿ”น bookAgent: {output}")
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  else: # reasoning agents
 
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  def agentController(question_text, model_name):
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  output = ""
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+ # deterministic
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  if is_magic(question_text, LOCAL_MAGIC_TOKENS):
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  output = salesAgent(question_text)
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  print(f"๐Ÿ”น salesAgent: {output}")
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  elif is_magic(question_text, DIGITAL_MAGIC_TOKENS):
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  output = chinookAgent(question_text, model_name)
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  print(f"๐Ÿ”น chinookAgent: {output}")
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+ # semantic similarity search
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  elif semantically_similar(question_text, "fight a war"):
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  output = bookAgent(question_text)
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  print(f"๐Ÿ”น bookAgent: {output}")
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  elif semantically_similar(question_text, "how to govern"):
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+ # for illustration: use same bookAgent -- should/could be something else
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  output = bookAgent(question_text)
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  print(f"๐Ÿ”น bookAgent: {output}")
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  else: # reasoning agents
models.py CHANGED
@@ -86,7 +86,7 @@ def load_sales_agent(verbose=True):
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  '''
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  Hard-coded agent that gates an internal sales CSV file for demo
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  '''
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- chat = createLLM(OPENAI_CHAT_LLMS[0], temperature=0.5)
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  df = pd.read_csv("data/sales_data.csv")
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  agent = create_pandas_dataframe_agent(chat, df, verbose=verbose)
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  return agent
 
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  '''
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  Hard-coded agent that gates an internal sales CSV file for demo
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  '''
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+ chat = createLLM(model_name='text-davinci-003')
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  df = pd.read_csv("data/sales_data.csv")
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  agent = create_pandas_dataframe_agent(chat, df, verbose=verbose)
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  return agent