Files changed (1) hide show
  1. app.py +17 -6
app.py CHANGED
@@ -1,8 +1,13 @@
 
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  import os
 
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  import gradio as gr
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  import requests
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- import inspect
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  import pandas as pd
 
 
 
 
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  # (Keep Constants as is)
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  # --- Constants ---
@@ -10,14 +15,22 @@ 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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  def __call__(self, question: str) -> str:
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  print(f"Agent received question (first 50 chars): {question[:50]}...")
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- fixed_answer = "This is a default answer."
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- print(f"Agent returning fixed answer: {fixed_answer}")
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- return fixed_answer
 
 
 
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  def run_and_submit_all( profile: gr.OAuthProfile | None):
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  """
@@ -146,11 +159,9 @@ with gr.Blocks() as demo:
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  gr.Markdown(
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  """
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  **Instructions:**
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-
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  1. Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
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  2. Log in to your Hugging Face account using the button below. This uses your HF username for submission.
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  3. Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
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-
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  ---
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  **Disclaimers:**
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  Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
 
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+ """ Basic Agent Evaluation Runner"""
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  import os
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+ import inspect
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  import gradio as gr
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  import requests
 
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  import pandas as pd
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+ from langchain_core.messages import HumanMessage
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+ from agent import build_graph
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+
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+
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  # (Keep Constants as is)
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  # --- Constants ---
 
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  # --- Basic Agent Definition ---
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  # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
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+
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+
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  class BasicAgent:
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+ """A langgraph agent."""
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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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+
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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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+
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  def run_and_submit_all( profile: gr.OAuthProfile | None):
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  """
 
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  gr.Markdown(
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  """
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  **Instructions:**
 
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  1. Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
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  2. Log in to your Hugging Face account using the button below. This uses your HF username for submission.
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  3. Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
 
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  ---
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  **Disclaimers:**
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  Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).