WeizenGitter400 commited on
Commit
a42adb7
·
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1 Parent(s): 81917a3

Update app.py

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Files changed (1) hide show
  1. app.py +61 -28
app.py CHANGED
@@ -3,32 +3,36 @@ 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 +44,14 @@ 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 +66,16 @@ 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
@@ -80,19 +91,37 @@ def run_and_submit_all( profile: gr.OAuthProfile | 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)
98
 
@@ -162,20 +191,19 @@ 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 +211,19 @@ 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)
 
 
3
  import requests
4
  import inspect
5
  import pandas as pd
6
+ from smolagents import CodeAgent, LiteLLMModel
7
 
8
  # (Keep Constants as is)
9
  # --- Constants ---
10
  DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
11
 
12
+
13
  # --- Basic Agent Definition ---
14
  # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
15
  class BasicAgent:
16
  def __init__(self):
17
  print("BasicAgent initialized.")
18
+
19
  def __call__(self, question: str) -> str:
20
  print(f"Agent received question (first 50 chars): {question[:50]}...")
21
  fixed_answer = "This is a default answer."
22
  print(f"Agent returning fixed answer: {fixed_answer}")
23
  return fixed_answer
24
 
25
+
26
+ def run_and_submit_all(profile: gr.OAuthProfile | None):
27
  """
28
  Fetches all questions, runs the BasicAgent on them, submits all answers,
29
  and displays the results.
30
  """
31
  # --- Determine HF Space Runtime URL and Repo URL ---
32
+ space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
33
 
34
  if profile:
35
+ username = f"{profile.username}"
36
  print(f"User logged in: {username}")
37
  else:
38
  print("User not logged in.")
 
44
 
45
  # 1. Instantiate Agent ( modify this part to create your agent)
46
  try:
47
+ agent = CodeAgent(
48
+ tools=[],
49
+ model=LiteLLMModel(
50
+ model_id="gemini/gemini-2.0-flash-lite",
51
+ api_key=os.getenv("GEMINI_API_KEY"),
52
+ ),
53
+ add_base_tools=True,
54
+ )
55
  except Exception as e:
56
  print(f"Error instantiating agent: {e}")
57
  return f"Error initializing agent: {e}", None
 
66
  response.raise_for_status()
67
  questions_data = response.json()
68
  if not questions_data:
69
+ print("Fetched questions list is empty.")
70
+ return "Fetched questions list is empty or invalid format.", None
71
  print(f"Fetched {len(questions_data)} questions.")
72
  except requests.exceptions.RequestException as e:
73
  print(f"Error fetching questions: {e}")
74
  return f"Error fetching questions: {e}", None
75
  except requests.exceptions.JSONDecodeError as e:
76
+ print(f"Error decoding JSON response from questions endpoint: {e}")
77
+ print(f"Response text: {response.text[:500]}")
78
+ return f"Error decoding server response for questions: {e}", None
79
  except Exception as e:
80
  print(f"An unexpected error occurred fetching questions: {e}")
81
  return f"An unexpected error occurred fetching questions: {e}", None
 
91
  print(f"Skipping item with missing task_id or question: {item}")
92
  continue
93
  try:
94
+ submitted_answer = agent.run(question_text)
95
+ answers_payload.append(
96
+ {"task_id": task_id, "submitted_answer": submitted_answer}
97
+ )
98
+ results_log.append(
99
+ {
100
+ "Task ID": task_id,
101
+ "Question": question_text,
102
+ "Submitted Answer": submitted_answer,
103
+ }
104
+ )
105
  except Exception as e:
106
+ print(f"Error running agent on task {task_id}: {e}")
107
+ results_log.append(
108
+ {
109
+ "Task ID": task_id,
110
+ "Question": question_text,
111
+ "Submitted Answer": f"AGENT ERROR: {e}",
112
+ }
113
+ )
114
 
115
  if not answers_payload:
116
  print("Agent did not produce any answers to submit.")
117
  return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
118
 
119
+ # 4. Prepare Submission
120
+ submission_data = {
121
+ "username": username.strip(),
122
+ "agent_code": agent_code,
123
+ "answers": answers_payload,
124
+ }
125
  status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
126
  print(status_update)
127
 
 
191
 
192
  run_button = gr.Button("Run Evaluation & Submit All Answers")
193
 
194
+ status_output = gr.Textbox(
195
+ label="Run Status / Submission Result", lines=5, interactive=False
196
+ )
197
  # Removed max_rows=10 from DataFrame constructor
198
  results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
199
 
200
+ run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
 
 
201
 
202
  if __name__ == "__main__":
203
+ print("\n" + "-" * 30 + " App Starting " + "-" * 30)
204
  # Check for SPACE_HOST and SPACE_ID at startup for information
205
  space_host_startup = os.getenv("SPACE_HOST")
206
+ space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
207
 
208
  if space_host_startup:
209
  print(f"✅ SPACE_HOST found: {space_host_startup}")
 
211
  else:
212
  print("ℹ️ SPACE_HOST environment variable not found (running locally?).")
213
 
214
+ if space_id_startup: # Print repo URLs if SPACE_ID is found
215
  print(f"✅ SPACE_ID found: {space_id_startup}")
216
  print(f" Repo URL: https://huggingface.co/spaces/{space_id_startup}")
217
+ print(
218
+ f" Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main"
219
+ )
220
  else:
221
+ print(
222
+ "ℹ️ SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined."
223
+ )
224
 
225
+ print("-" * (60 + len(" App Starting ")) + "\n")
226
 
227
  print("Launching Gradio Interface for Basic Agent Evaluation...")
228
+ demo.launch(debug=True, share=False)
229
+