zaldivards commited on
Commit
10c9801
·
1 Parent(s): 98e87f9

Refactor run_and_submit_all to use MainAgent

Browse files
Files changed (1) hide show
  1. app.py +26 -39
app.py CHANGED
@@ -1,34 +1,23 @@
1
  import os
 
2
  import gradio as gr
3
  import requests
4
- import inspect
5
  import pandas as pd
6
 
7
- # (Keep Constants as is)
8
- # --- Constants ---
9
- DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
10
-
11
- # --- Basic Agent Definition ---
12
- # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
13
- class BasicAgent:
14
- def __init__(self):
15
- print("BasicAgent initialized.")
16
- def __call__(self, question: str) -> str:
17
- print(f"Agent received question (first 50 chars): {question[:50]}...")
18
- fixed_answer = "This is a default answer."
19
- print(f"Agent returning fixed answer: {fixed_answer}")
20
- return fixed_answer
21
-
22
- def run_and_submit_all( profile: gr.OAuthProfile | None):
23
  """
24
  Fetches all questions, runs the BasicAgent on them, submits all answers,
25
  and displays the results.
26
  """
27
  # --- Determine HF Space Runtime URL and Repo URL ---
28
- space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
29
 
30
  if profile:
31
- username= f"{profile.username}"
32
  print(f"User logged in: {username}")
33
  else:
34
  print("User not logged in.")
@@ -40,7 +29,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
40
 
41
  # 1. Instantiate Agent ( modify this part to create your agent)
42
  try:
43
- agent = BasicAgent()
44
  except Exception as e:
45
  print(f"Error instantiating agent: {e}")
46
  return f"Error initializing agent: {e}", None
@@ -55,16 +44,16 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
55
  response.raise_for_status()
56
  questions_data = response.json()
57
  if not questions_data:
58
- print("Fetched questions list is empty.")
59
- return "Fetched questions list is empty or invalid format.", None
60
  print(f"Fetched {len(questions_data)} questions.")
 
 
 
 
61
  except requests.exceptions.RequestException as e:
62
  print(f"Error fetching questions: {e}")
63
  return f"Error fetching questions: {e}", None
64
- except requests.exceptions.JSONDecodeError as e:
65
- print(f"Error decoding JSON response from questions endpoint: {e}")
66
- print(f"Response text: {response.text[:500]}")
67
- return f"Error decoding server response for questions: {e}", None
68
  except Exception as e:
69
  print(f"An unexpected error occurred fetching questions: {e}")
70
  return f"An unexpected error occurred fetching questions: {e}", None
@@ -76,22 +65,23 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
76
  for item in questions_data:
77
  task_id = item.get("task_id")
78
  question_text = item.get("question")
 
79
  if not task_id or question_text is None:
80
  print(f"Skipping item with missing task_id or question: {item}")
81
  continue
82
  try:
83
- submitted_answer = agent(question_text)
84
  answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
85
  results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
86
  except Exception as e:
87
- print(f"Error running agent on task {task_id}: {e}")
88
- results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
89
 
90
  if not answers_payload:
91
  print("Agent did not produce any answers to submit.")
92
  return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
93
 
94
- # 4. Prepare Submission
95
  submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
96
  status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
97
  print(status_update)
@@ -166,16 +156,13 @@ with gr.Blocks() as demo:
166
  # Removed max_rows=10 from DataFrame constructor
167
  results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
168
 
169
- run_button.click(
170
- fn=run_and_submit_all,
171
- outputs=[status_output, results_table]
172
- )
173
 
174
  if __name__ == "__main__":
175
- print("\n" + "-"*30 + " App Starting " + "-"*30)
176
  # Check for SPACE_HOST and SPACE_ID at startup for information
177
  space_host_startup = os.getenv("SPACE_HOST")
178
- space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
179
 
180
  if space_host_startup:
181
  print(f"✅ SPACE_HOST found: {space_host_startup}")
@@ -183,14 +170,14 @@ if __name__ == "__main__":
183
  else:
184
  print("ℹ️ SPACE_HOST environment variable not found (running locally?).")
185
 
186
- if space_id_startup: # Print repo URLs if SPACE_ID is found
187
  print(f"✅ SPACE_ID found: {space_id_startup}")
188
  print(f" Repo URL: https://huggingface.co/spaces/{space_id_startup}")
189
  print(f" Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
190
  else:
191
  print("ℹ️ SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
192
 
193
- print("-"*(60 + len(" App Starting ")) + "\n")
194
 
195
  print("Launching Gradio Interface for Basic Agent Evaluation...")
196
- demo.launch(debug=True, share=False)
 
1
  import os
2
+
3
  import gradio as gr
4
  import requests
 
5
  import pandas as pd
6
 
7
+ from agent import MainAgent
8
+ from utils import DEFAULT_API_URL
9
+
10
+
11
+ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
 
 
 
 
 
 
 
 
 
 
12
  """
13
  Fetches all questions, runs the BasicAgent on them, submits all answers,
14
  and displays the results.
15
  """
16
  # --- Determine HF Space Runtime URL and Repo URL ---
17
+ space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
18
 
19
  if profile:
20
+ username = f"{profile.username}"
21
  print(f"User logged in: {username}")
22
  else:
23
  print("User not logged in.")
 
29
 
30
  # 1. Instantiate Agent ( modify this part to create your agent)
31
  try:
32
+ agent = MainAgent()
33
  except Exception as e:
34
  print(f"Error instantiating agent: {e}")
35
  return f"Error initializing agent: {e}", None
 
44
  response.raise_for_status()
45
  questions_data = response.json()
46
  if not questions_data:
47
+ print("Fetched questions list is empty.")
48
+ return "Fetched questions list is empty or invalid format.", None
49
  print(f"Fetched {len(questions_data)} questions.")
50
+ except requests.exceptions.JSONDecodeError as e:
51
+ print(f"Error decoding JSON response from questions endpoint: {e}")
52
+ print(f"Response text: {response.text[:500]}")
53
+ return f"Error decoding server response for questions: {e}", None
54
  except requests.exceptions.RequestException as e:
55
  print(f"Error fetching questions: {e}")
56
  return f"Error fetching questions: {e}", None
 
 
 
 
57
  except Exception as e:
58
  print(f"An unexpected error occurred fetching questions: {e}")
59
  return f"An unexpected error occurred fetching questions: {e}", None
 
65
  for item in questions_data:
66
  task_id = item.get("task_id")
67
  question_text = item.get("question")
68
+ file_name = item.get("file_name")
69
  if not task_id or question_text is None:
70
  print(f"Skipping item with missing task_id or question: {item}")
71
  continue
72
  try:
73
+ submitted_answer = agent.run(question_text, task_id, file_name)
74
  answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
75
  results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
76
  except Exception as e:
77
+ print(f"Error running agent on task {task_id}: {e}")
78
+ results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
79
 
80
  if not answers_payload:
81
  print("Agent did not produce any answers to submit.")
82
  return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
83
 
84
+ # 4. Prepare Submission
85
  submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
86
  status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
87
  print(status_update)
 
156
  # Removed max_rows=10 from DataFrame constructor
157
  results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
158
 
159
+ run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
 
 
160
 
161
  if __name__ == "__main__":
162
+ print("\n" + "-" * 30 + " App Starting " + "-" * 30)
163
  # Check for SPACE_HOST and SPACE_ID at startup for information
164
  space_host_startup = os.getenv("SPACE_HOST")
165
+ space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
166
 
167
  if space_host_startup:
168
  print(f"✅ SPACE_HOST found: {space_host_startup}")
 
170
  else:
171
  print("ℹ️ SPACE_HOST environment variable not found (running locally?).")
172
 
173
+ if space_id_startup: # Print repo URLs if SPACE_ID is found
174
  print(f"✅ SPACE_ID found: {space_id_startup}")
175
  print(f" Repo URL: https://huggingface.co/spaces/{space_id_startup}")
176
  print(f" Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
177
  else:
178
  print("ℹ️ SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
179
 
180
+ print("-" * (60 + len(" App Starting ")) + "\n")
181
 
182
  print("Launching Gradio Interface for Basic Agent Evaluation...")
183
+ demo.launch(debug=True, share=False)