wrigleyDan commited on
Commit
3be6804
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1 Parent(s): 525d9b5

Update app.py

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Files changed (1) hide show
  1. app.py +14 -1
app.py CHANGED
@@ -14,6 +14,12 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
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  # --- Basic Agent Definition ---
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  # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
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  class BasicAgent:
 
 
 
 
 
 
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  def __init__(self):
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  print("BasicAgent initialized.")
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  self.graph = build_graph()
@@ -21,7 +27,14 @@ class BasicAgent:
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  def __call__(self, question: str) -> str:
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  print(f"Agent received question (first 50 chars): {question[:50]}...")
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  # Wrap the question in a HumanMessage from langchain_core
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- messages = [HumanMessage(content=question)]
 
 
 
 
 
 
 
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  messages = self.graph.invoke({"messages": messages})
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  answer = messages['messages'][-1].content
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  return answer[14:]
 
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  # --- Basic Agent Definition ---
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  # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
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  class BasicAgent:
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+ system_prompt = """You are a helpful assistant tasked with answering questions using a set of tools.
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+ Now, I will ask you a question. Report your thoughts, and finish your answer with the following template:
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+ FINAL ANSWER: [YOUR FINAL ANSWER].
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+ YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
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+ Your answer should only start with "FINAL ANSWER: ", then follows with the answer.
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+ """
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  def __init__(self):
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  print("BasicAgent initialized.")
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  self.graph = build_graph()
 
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  def __call__(self, question: str) -> str:
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  print(f"Agent received question (first 50 chars): {question[:50]}...")
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  # Wrap the question in a HumanMessage from langchain_core
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+ #messages = [HumanMessage(content=question)]
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+ messages = [
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+ SystemMessage(
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+ content=system_prompt
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+ ),
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+ HumanMessage(
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+ content=question
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+ )]
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  messages = self.graph.invoke({"messages": messages})
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  answer = messages['messages'][-1].content
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  return answer[14:]