Omachoko Tanimu Yakubu commited on
Commit
83b4ffd
·
1 Parent(s): 81917a3

My First Attempt on the Hugging Face Final Assessment

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Files changed (2) hide show
  1. app.py +49 -101
  2. requirements.txt +9 -1
app.py CHANGED
@@ -1,34 +1,43 @@
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.")
@@ -38,38 +47,23 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
38
  questions_url = f"{api_url}/questions"
39
  submit_url = f"{api_url}/submit"
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
47
- # 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)
48
  agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
49
  print(agent_code)
50
 
51
- # 2. Fetch Questions
52
  print(f"Fetching questions from: {questions_url}")
53
  try:
54
  response = requests.get(questions_url, timeout=15)
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
71
 
72
- # 3. Run your Agent
73
  results_log = []
74
  answers_payload = []
75
  print(f"Running agent on {len(questions_data)} questions...")
@@ -77,27 +71,21 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
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
 
99
- # 5. Submit
100
- print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
101
  try:
102
  response = requests.post(submit_url, json=submission_data, timeout=60)
103
  response.raise_for_status()
@@ -109,88 +97,48 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
109
  f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
110
  f"Message: {result_data.get('message', 'No message received.')}"
111
  )
112
- print("Submission successful.")
113
  results_df = pd.DataFrame(results_log)
114
  return final_status, results_df
115
- except requests.exceptions.HTTPError as e:
116
- error_detail = f"Server responded with status {e.response.status_code}."
117
- try:
118
- error_json = e.response.json()
119
- error_detail += f" Detail: {error_json.get('detail', e.response.text)}"
120
- except requests.exceptions.JSONDecodeError:
121
- error_detail += f" Response: {e.response.text[:500]}"
122
- status_message = f"Submission Failed: {error_detail}"
123
- print(status_message)
124
- results_df = pd.DataFrame(results_log)
125
- return status_message, results_df
126
- except requests.exceptions.Timeout:
127
- status_message = "Submission Failed: The request timed out."
128
- print(status_message)
129
- results_df = pd.DataFrame(results_log)
130
- return status_message, results_df
131
- except requests.exceptions.RequestException as e:
132
- status_message = f"Submission Failed: Network error - {e}"
133
- print(status_message)
134
- results_df = pd.DataFrame(results_log)
135
- return status_message, results_df
136
  except Exception as e:
137
- status_message = f"An unexpected error occurred during submission: {e}"
138
- print(status_message)
139
  results_df = pd.DataFrame(results_log)
140
- return status_message, results_df
141
-
142
 
143
  # --- Build Gradio Interface using Blocks ---
144
  with gr.Blocks() as demo:
145
- gr.Markdown("# Basic Agent Evaluation Runner")
146
  gr.Markdown(
147
  """
148
  **Instructions:**
149
-
150
- 1. Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
151
- 2. Log in to your Hugging Face account using the button below. This uses your HF username for submission.
152
- 3. Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
153
-
154
  ---
155
- **Disclaimers:**
156
- 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).
157
- 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.
158
  """
159
  )
160
 
161
  gr.LoginButton()
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}")
182
- print(f" Runtime URL should be: https://{space_host_startup}.hf.space")
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
+ # ---- Constants ----
 
7
  DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
8
 
9
+ # ---- Smolagents imports ----
10
+ from smolagents import WikipediaSearchTool, DuckDuckGoSearchTool
11
+
12
+ # ---- Agent Definition ----
13
+ class SmolAgent:
14
  def __init__(self):
15
+ self.wiki = WikipediaSearchTool()
16
+ self.duck = DuckDuckGoSearchTool()
17
  def __call__(self, question: str) -> str:
18
+ # Try Wikipedia first, fall back to DuckDuckGo if nothing useful.
19
+ wiki_result = ""
20
+ duck_result = ""
21
+ try:
22
+ wiki_result = self.wiki.run(question)
23
+ except Exception as e:
24
+ wiki_result = f"(Wiki error: {e})"
25
+ # If Wikipedia yields nothing or too short, use DuckDuckGo as fallback
26
+ if wiki_result and len(str(wiki_result)) > 40:
27
+ return str(wiki_result)
28
+ try:
29
+ duck_result = self.duck.run(question)
30
+ except Exception as e:
31
+ duck_result = f"(DuckDuckGo error: {e})"
32
+ if duck_result:
33
+ return str(duck_result)
34
+ # If both fail, return error info
35
+ return f"Wikipedia: {wiki_result}\nDuckDuckGo: {duck_result}\n(No answer found.)"
36
+
37
+ def run_and_submit_all(profile: gr.OAuthProfile | None):
38
+ space_id = os.getenv("SPACE_ID")
39
  if profile:
40
+ username = f"{profile.username}"
41
  print(f"User logged in: {username}")
42
  else:
43
  print("User not logged in.")
 
47
  questions_url = f"{api_url}/questions"
48
  submit_url = f"{api_url}/submit"
49
 
 
50
  try:
51
+ agent = SmolAgent()
52
  except Exception as e:
 
53
  return f"Error initializing agent: {e}", None
 
54
  agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
55
  print(agent_code)
56
 
 
57
  print(f"Fetching questions from: {questions_url}")
58
  try:
59
  response = requests.get(questions_url, timeout=15)
60
  response.raise_for_status()
61
  questions_data = response.json()
62
  if not questions_data:
63
+ return "Fetched questions list is empty or invalid format.", None
 
 
 
 
 
 
 
 
 
64
  except Exception as e:
65
+ return f"Error fetching questions: {e}", None
 
66
 
 
67
  results_log = []
68
  answers_payload = []
69
  print(f"Running agent on {len(questions_data)} questions...")
 
71
  task_id = item.get("task_id")
72
  question_text = item.get("question")
73
  if not task_id or question_text is None:
 
74
  continue
75
  try:
76
  submitted_answer = agent(question_text)
77
  answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
78
  results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
79
  except Exception as e:
80
+ results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
 
81
 
82
  if not answers_payload:
 
83
  return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
84
 
 
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)
88
 
 
 
89
  try:
90
  response = requests.post(submit_url, json=submission_data, timeout=60)
91
  response.raise_for_status()
 
97
  f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
98
  f"Message: {result_data.get('message', 'No message received.')}"
99
  )
 
100
  results_df = pd.DataFrame(results_log)
101
  return final_status, results_df
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
102
  except Exception as e:
 
 
103
  results_df = pd.DataFrame(results_log)
104
+ return f"Submission Failed: {e}", results_df
 
105
 
106
  # --- Build Gradio Interface using Blocks ---
107
  with gr.Blocks() as demo:
108
+ gr.Markdown("# SmolAgent Evaluation Runner")
109
  gr.Markdown(
110
  """
111
  **Instructions:**
112
+ 1. Clone and modify this space to improve your agent logic as you see fit.
113
+ 2. Log in to your Hugging Face account with the button below.
114
+ 3. Click 'Run Evaluation & Submit All Answers' to begin.
 
 
115
  ---
116
+ **Disclaimer:** Submission may take a while depending on the number of questions and agent speed.
 
 
117
  """
118
  )
119
 
120
  gr.LoginButton()
 
121
  run_button = gr.Button("Run Evaluation & Submit All Answers")
 
122
  status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
 
123
  results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
 
124
  run_button.click(
125
  fn=run_and_submit_all,
126
  outputs=[status_output, results_table]
127
  )
128
 
129
  if __name__ == "__main__":
130
+ print("\n--- App Starting ---\n")
 
131
  space_host_startup = os.getenv("SPACE_HOST")
132
+ space_id_startup = os.getenv("SPACE_ID")
 
133
  if space_host_startup:
134
  print(f"✅ SPACE_HOST found: {space_host_startup}")
135
+ print(f" Runtime URL: https://{space_host_startup}.hf.space")
136
  else:
137
+ print("ℹ️ SPACE_HOST not found (running locally?)")
138
+ if space_id_startup:
 
139
  print(f"✅ SPACE_ID found: {space_id_startup}")
140
+ print(f" Repo URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
 
141
  else:
142
+ print("ℹ️ SPACE_ID not found")
143
+ print("--- App Starting ---\n")
144
+ demo.launch(debug=True, share=False)
 
 
 
requirements.txt CHANGED
@@ -1,2 +1,10 @@
1
  gradio
2
- requests
 
 
 
 
 
 
 
 
 
1
  gradio
2
+ requests
3
+ huggingface-hub
4
+ pandas
5
+ duckduckgo-search
6
+ datasets
7
+ llama-index
8
+ llama-index-llms-huggingface
9
+ smolagents
10
+ langgraph