jjvelezo commited on
Commit
e4f42cb
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1 Parent(s): 4796c94

Update app.py

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Files changed (1) hide show
  1. app.py +21 -55
app.py CHANGED
@@ -3,17 +3,10 @@ import gradio as gr
3
  import requests
4
  import inspect
5
  import pandas as pd
 
6
  from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel
7
- from agent import EnhancedAgent
8
-
9
-
10
-
11
- # (Keep Constants as is)
12
- # --- Constants ---
13
- DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
14
 
15
  # --- Basic Agent Definition ---
16
- # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
17
  class BasicAgent:
18
  def __init__(self):
19
  print("BasicAgent initialized.")
@@ -23,30 +16,26 @@ class BasicAgent:
23
  print(f"Agent returning fixed answer: {fixed_answer}")
24
  return fixed_answer
25
 
26
-
27
-
28
-
29
- agent = CodeAgent(tools=[DuckDuckGoSearchTool()], model=HfApiModel())
30
 
31
  def run_smol_agent():
32
  question = "Search for the best music recommendations for a party at the Wayne's mansion."
33
- response = agent.run(question)
34
  print(f"Smol Agent Response: {response}")
35
  return response
36
 
37
-
38
-
39
-
40
- def run_and_submit_all( profile: gr.OAuthProfile | None):
41
  """
42
- Fetches all questions, runs the BasicAgent on them, submits all answers,
43
  and displays the results.
44
  """
45
  # --- Determine HF Space Runtime URL and Repo URL ---
46
  space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
47
 
48
  if profile:
49
- username= f"jujovele"
50
  print(f"User logged in: {username}")
51
  else:
52
  print("User not logged in.")
@@ -56,13 +45,13 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
56
  questions_url = f"{api_url}/questions"
57
  submit_url = f"{api_url}/submit"
58
 
59
- # 1. Instantiate Agent ( modify this part to create your agent)
60
  try:
61
- agent = SmartDuckDuckGoAgent()
62
  except Exception as e:
63
  print(f"Error instantiating agent: {e}")
64
  return f"Error initializing agent: {e}", None
65
- # In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
66
  agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
67
  print(agent_code)
68
 
@@ -73,16 +62,16 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
73
  response.raise_for_status()
74
  questions_data = response.json()
75
  if not questions_data:
76
- print("Fetched questions list is empty.")
77
- return "Fetched questions list is empty or invalid format.", None
78
  print(f"Fetched {len(questions_data)} questions.")
79
  except requests.exceptions.RequestException as e:
80
  print(f"Error fetching questions: {e}")
81
  return f"Error fetching questions: {e}", None
82
  except requests.exceptions.JSONDecodeError as e:
83
- print(f"Error decoding JSON response from questions endpoint: {e}")
84
- print(f"Response text: {response.text[:500]}")
85
- return f"Error decoding server response for questions: {e}", None
86
  except Exception as e:
87
  print(f"An unexpected error occurred fetching questions: {e}")
88
  return f"An unexpected error occurred fetching questions: {e}", None
@@ -98,12 +87,12 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
98
  print(f"Skipping item with missing task_id or question: {item}")
99
  continue
100
  try:
101
- submitted_answer = agent(question_text)
102
  answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
103
  results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
104
  except Exception as e:
105
- print(f"Error running agent on task {task_id}: {e}")
106
- results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
107
 
108
  if not answers_payload:
109
  print("Agent did not produce any answers to submit.")
@@ -170,7 +159,7 @@ with gr.Blocks() as demo:
170
  ---
171
  **Disclaimers:**
172
  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).
173
- This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a seperate action or even to answer the questions in async.
174
  """
175
  )
176
 
@@ -179,9 +168,7 @@ with gr.Blocks() as demo:
179
  run_button = gr.Button("Run Evaluation & Submit All Answers")
180
  run_smol_agent_button = gr.Button("Run SmolAgent Search")
181
 
182
-
183
  status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
184
- # Removed max_rows=10 from DataFrame constructor
185
  results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
186
 
187
  run_button.click(
@@ -190,25 +177,4 @@ with gr.Blocks() as demo:
190
  )
191
 
192
  if __name__ == "__main__":
193
- print("\n" + "-"*30 + " App Starting " + "-"*30)
194
- # Check for SPACE_HOST and SPACE_ID at startup for information
195
- space_host_startup = os.getenv("SPACE_HOST")
196
- space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
197
-
198
- if space_host_startup:
199
- print(f"✅ SPACE_HOST found: {space_host_startup}")
200
- print(f" Runtime URL should be: https://{space_host_startup}.hf.space")
201
- else:
202
- print("ℹ️ SPACE_HOST environment variable not found (running locally?).")
203
-
204
- if space_id_startup: # Print repo URLs if SPACE_ID is found
205
- print(f"✅ SPACE_ID found: {space_id_startup}")
206
- print(f" Repo URL: https://huggingface.co/spaces/{space_id_startup}")
207
- print(f" Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
208
- else:
209
- print("ℹ️ SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
210
-
211
- print("-"*(60 + len(" App Starting ")) + "\n")
212
-
213
- print("Launching Gradio Interface for Basic Agent Evaluation...")
214
- demo.launch(debug=True, share=True)
 
3
  import requests
4
  import inspect
5
  import pandas as pd
6
+ from agent import EnhancedAgent # Importa el EnhancedAgent
7
  from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel
 
 
 
 
 
 
 
8
 
9
  # --- Basic Agent Definition ---
 
10
  class BasicAgent:
11
  def __init__(self):
12
  print("BasicAgent initialized.")
 
16
  print(f"Agent returning fixed answer: {fixed_answer}")
17
  return fixed_answer
18
 
19
+ # Inicializa el agente mejorado
20
+ api_key = "tu_api_key" # Asegúrate de tener la API Key correcta
21
+ agent = EnhancedAgent(api_key=api_key)
 
22
 
23
  def run_smol_agent():
24
  question = "Search for the best music recommendations for a party at the Wayne's mansion."
25
+ response = agent.run(question) # Usa el agente mejorado aquí
26
  print(f"Smol Agent Response: {response}")
27
  return response
28
 
29
+ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
 
 
30
  """
31
+ Fetches all questions, runs the EnhancedAgent on them, submits all answers,
32
  and displays the results.
33
  """
34
  # --- Determine HF Space Runtime URL and Repo URL ---
35
  space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
36
 
37
  if profile:
38
+ username = f"jujovele"
39
  print(f"User logged in: {username}")
40
  else:
41
  print("User not logged in.")
 
45
  questions_url = f"{api_url}/questions"
46
  submit_url = f"{api_url}/submit"
47
 
48
+ # 1. Instantiate Agent (modify this part to create your agent)
49
  try:
50
+ agent = EnhancedAgent(api_key=api_key) # Crea tu agente mejorado
51
  except Exception as e:
52
  print(f"Error instantiating agent: {e}")
53
  return f"Error initializing agent: {e}", None
54
+
55
  agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
56
  print(agent_code)
57
 
 
62
  response.raise_for_status()
63
  questions_data = response.json()
64
  if not questions_data:
65
+ print("Fetched questions list is empty.")
66
+ return "Fetched questions list is empty or invalid format.", None
67
  print(f"Fetched {len(questions_data)} questions.")
68
  except requests.exceptions.RequestException as e:
69
  print(f"Error fetching questions: {e}")
70
  return f"Error fetching questions: {e}", None
71
  except requests.exceptions.JSONDecodeError as e:
72
+ print(f"Error decoding JSON response from questions endpoint: {e}")
73
+ print(f"Response text: {response.text[:500]}")
74
+ return f"Error decoding server response for questions: {e}", None
75
  except Exception as e:
76
  print(f"An unexpected error occurred fetching questions: {e}")
77
  return f"An unexpected error occurred fetching questions: {e}", None
 
87
  print(f"Skipping item with missing task_id or question: {item}")
88
  continue
89
  try:
90
+ submitted_answer = agent.run(question_text) # Usa el método run del agente mejorado
91
  answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
92
  results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
93
  except Exception as e:
94
+ print(f"Error running agent on task {task_id}: {e}")
95
+ results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
96
 
97
  if not answers_payload:
98
  print("Agent did not produce any answers to submit.")
 
159
  ---
160
  **Disclaimers:**
161
  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).
162
+ This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a separate action or even to answer the questions in async.
163
  """
164
  )
165
 
 
168
  run_button = gr.Button("Run Evaluation & Submit All Answers")
169
  run_smol_agent_button = gr.Button("Run SmolAgent Search")
170
 
 
171
  status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
 
172
  results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
173
 
174
  run_button.click(
 
177
  )
178
 
179
  if __name__ == "__main__":
180
+ demo.launch(debug=True, share=True)