vianmixt commited on
Commit
23d10a4
·
1 Parent(s): 31810ee

Integrate Azrock agent

Browse files
Files changed (1) hide show
  1. app.py +57 -33
app.py CHANGED
@@ -1,34 +1,37 @@
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 +43,7 @@ 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 +58,16 @@ 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
@@ -73,26 +76,44 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
73
  results_log = []
74
  answers_payload = []
75
  print(f"Running agent on {len(questions_data)} questions...")
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)
98
 
@@ -162,20 +183,19 @@ 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 +203,18 @@ 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
+ from azrock.agent import create_agent
6
 
7
  # (Keep Constants as is)
8
  # --- Constants ---
9
  DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
10
 
11
+
12
  # --- Basic Agent Definition ---
13
  # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
14
  class BasicAgent:
15
  def __init__(self):
16
  print("BasicAgent initialized.")
17
+
18
  def __call__(self, question: str) -> str:
19
  print(f"Agent received question (first 50 chars): {question[:50]}...")
20
  fixed_answer = "This is a default answer."
21
  print(f"Agent returning fixed answer: {fixed_answer}")
22
  return fixed_answer
23
 
24
+
25
+ def run_and_submit_all(profile: gr.OAuthProfile | None):
26
  """
27
  Fetches all questions, runs the BasicAgent on them, submits all answers,
28
  and displays the results.
29
  """
30
  # --- Determine HF Space Runtime URL and Repo URL ---
31
+ space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
32
 
33
  if profile:
34
+ username = f"{profile.username}"
35
  print(f"User logged in: {username}")
36
  else:
37
  print("User not logged in.")
 
43
 
44
  # 1. Instantiate Agent ( modify this part to create your agent)
45
  try:
46
+ agent = create_agent()
47
  except Exception as e:
48
  print(f"Error instantiating agent: {e}")
49
  return f"Error initializing agent: {e}", None
 
58
  response.raise_for_status()
59
  questions_data = response.json()
60
  if not questions_data:
61
+ print("Fetched questions list is empty.")
62
+ return "Fetched questions list is empty or invalid format.", None
63
  print(f"Fetched {len(questions_data)} questions.")
64
  except requests.exceptions.RequestException as e:
65
  print(f"Error fetching questions: {e}")
66
  return f"Error fetching questions: {e}", None
67
  except requests.exceptions.JSONDecodeError as e:
68
+ print(f"Error decoding JSON response from questions endpoint: {e}")
69
+ print(f"Response text: {response.text[:500]}")
70
+ return f"Error decoding server response for questions: {e}", None
71
  except Exception as e:
72
  print(f"An unexpected error occurred fetching questions: {e}")
73
  return f"An unexpected error occurred fetching questions: {e}", None
 
76
  results_log = []
77
  answers_payload = []
78
  print(f"Running agent on {len(questions_data)} questions...")
79
+ for question in questions_data:
80
+ task_id = question.get("task_id")
81
+ question_text = question.get("question")
82
  if not task_id or question_text is None:
83
+ print(f"Skipping item with missing task_id or question: {question}")
84
  continue
85
  try:
86
+ submitted_answer = agent.run(str(question))
87
+ answers_payload.append(
88
+ {"task_id": task_id, "submitted_answer": submitted_answer}
89
+ )
90
+ results_log.append(
91
+ {
92
+ "Task ID": task_id,
93
+ "Question": question_text,
94
+ "Submitted Answer": submitted_answer,
95
+ }
96
+ )
97
  except Exception as e:
98
+ print(f"Error running agent on task {task_id}: {e}")
99
+ results_log.append(
100
+ {
101
+ "Task ID": task_id,
102
+ "Question": question_text,
103
+ "Submitted Answer": f"AGENT ERROR: {e}",
104
+ }
105
+ )
106
 
107
  if not answers_payload:
108
  print("Agent did not produce any answers to submit.")
109
  return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
110
 
111
+ # 4. Prepare Submission
112
+ submission_data = {
113
+ "username": username.strip(),
114
+ "agent_code": agent_code,
115
+ "answers": answers_payload,
116
+ }
117
  status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
118
  print(status_update)
119
 
 
183
 
184
  run_button = gr.Button("Run Evaluation & Submit All Answers")
185
 
186
+ status_output = gr.Textbox(
187
+ label="Run Status / Submission Result", lines=5, interactive=False
188
+ )
189
  # Removed max_rows=10 from DataFrame constructor
190
  results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
191
 
192
+ run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
 
 
193
 
194
  if __name__ == "__main__":
195
+ print("\n" + "-" * 30 + " App Starting " + "-" * 30)
196
  # Check for SPACE_HOST and SPACE_ID at startup for information
197
  space_host_startup = os.getenv("SPACE_HOST")
198
+ space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
199
 
200
  if space_host_startup:
201
  print(f"✅ SPACE_HOST found: {space_host_startup}")
 
203
  else:
204
  print("ℹ️ SPACE_HOST environment variable not found (running locally?).")
205
 
206
+ if space_id_startup: # Print repo URLs if SPACE_ID is found
207
  print(f"✅ SPACE_ID found: {space_id_startup}")
208
  print(f" Repo URL: https://huggingface.co/spaces/{space_id_startup}")
209
+ print(
210
+ f" Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main"
211
+ )
212
  else:
213
+ print(
214
+ "ℹ️ SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined."
215
+ )
216
 
217
+ print("-" * (60 + len(" App Starting ")) + "\n")
218
 
219
  print("Launching Gradio Interface for Basic Agent Evaluation...")
220
+ demo.launch(debug=True, share=False)