diepala commited on
Commit
fe1c24a
·
1 Parent(s): 81917a3

Initial formatting and test

Browse files
Files changed (1) hide show
  1. app.py +51 -28
app.py CHANGED
@@ -1,34 +1,36 @@
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.")
@@ -55,16 +57,16 @@ 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
@@ -81,18 +83,36 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
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)
98
 
@@ -162,20 +182,19 @@ with gr.Blocks() as demo:
162
 
163
  run_button = gr.Button("Run Evaluation & Submit All Answers")
164
 
165
- status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
 
 
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 +202,18 @@ 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
  import gradio as gr
3
  import requests
 
4
  import pandas as pd
5
 
6
  # (Keep Constants as is)
7
  # --- Constants ---
8
  DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
9
 
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
+
17
  def __call__(self, question: str) -> str:
18
  print(f"Agent received question (first 50 chars): {question[:50]}...")
19
+ fixed_answer = "This is my custom default answer."
20
  print(f"Agent returning fixed answer: {fixed_answer}")
21
  return fixed_answer
22
 
23
+
24
+ def run_and_submit_all(profile: gr.OAuthProfile | None):
25
  """
26
  Fetches all questions, runs the BasicAgent on them, submits all answers,
27
  and displays the results.
28
  """
29
  # --- Determine HF Space Runtime URL and Repo URL ---
30
+ space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
31
 
32
  if profile:
33
+ username = f"{profile.username}"
34
  print(f"User logged in: {username}")
35
  else:
36
  print("User not logged in.")
 
57
  response.raise_for_status()
58
  questions_data = response.json()
59
  if not questions_data:
60
+ print("Fetched questions list is empty.")
61
+ return "Fetched questions list is empty or invalid format.", None
62
  print(f"Fetched {len(questions_data)} questions.")
63
  except requests.exceptions.RequestException as e:
64
  print(f"Error fetching questions: {e}")
65
  return f"Error fetching questions: {e}", None
66
  except requests.exceptions.JSONDecodeError as e:
67
+ print(f"Error decoding JSON response from questions endpoint: {e}")
68
+ print(f"Response text: {response.text[:500]}")
69
+ return f"Error decoding server response for questions: {e}", None
70
  except Exception as e:
71
  print(f"An unexpected error occurred fetching questions: {e}")
72
  return f"An unexpected error occurred fetching questions: {e}", None
 
83
  continue
84
  try:
85
  submitted_answer = agent(question_text)
86
+ answers_payload.append(
87
+ {"task_id": task_id, "submitted_answer": submitted_answer}
88
+ )
89
+ results_log.append(
90
+ {
91
+ "Task ID": task_id,
92
+ "Question": question_text,
93
+ "Submitted Answer": submitted_answer,
94
+ }
95
+ )
96
  except Exception as e:
97
+ print(f"Error running agent on task {task_id}: {e}")
98
+ results_log.append(
99
+ {
100
+ "Task ID": task_id,
101
+ "Question": question_text,
102
+ "Submitted Answer": f"AGENT ERROR: {e}",
103
+ }
104
+ )
105
 
106
  if not answers_payload:
107
  print("Agent did not produce any answers to submit.")
108
  return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
109
 
110
+ # 4. Prepare Submission
111
+ submission_data = {
112
+ "username": username.strip(),
113
+ "agent_code": agent_code,
114
+ "answers": answers_payload,
115
+ }
116
  status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
117
  print(status_update)
118
 
 
182
 
183
  run_button = gr.Button("Run Evaluation & Submit All Answers")
184
 
185
+ status_output = gr.Textbox(
186
+ label="Run Status / Submission Result", lines=5, interactive=False
187
+ )
188
  # Removed max_rows=10 from DataFrame constructor
189
  results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
190
 
191
+ run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
 
 
192
 
193
  if __name__ == "__main__":
194
+ print("\n" + "-" * 30 + " App Starting " + "-" * 30)
195
  # Check for SPACE_HOST and SPACE_ID at startup for information
196
  space_host_startup = os.getenv("SPACE_HOST")
197
+ space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
198
 
199
  if space_host_startup:
200
  print(f"✅ SPACE_HOST found: {space_host_startup}")
 
202
  else:
203
  print("ℹ️ SPACE_HOST environment variable not found (running locally?).")
204
 
205
+ if space_id_startup: # Print repo URLs if SPACE_ID is found
206
  print(f"✅ SPACE_ID found: {space_id_startup}")
207
  print(f" Repo URL: https://huggingface.co/spaces/{space_id_startup}")
208
+ print(
209
+ f" Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main"
210
+ )
211
  else:
212
+ print(
213
+ "ℹ️ SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined."
214
+ )
215
 
216
+ print("-" * (60 + len(" App Starting ")) + "\n")
217
 
218
  print("Launching Gradio Interface for Basic Agent Evaluation...")
219
+ demo.launch(debug=True, share=False)