feature: Allow specifying the Gemini model in the API URL

This commit introduces the ability to specify the Gemini model to be used when calling the generative language API.  Previously, the model was hardcoded to `gemini-1.5-flash-latest`.  This change modifies the `url` function to accept an optional `model` parameter, allowing users to select different Gemini models (e.g., different versions or specialized models) if needed.  The default remains `gemini-1.5-flash-latest` for backward compatibility.

Author: beachdweller

action.yml

@@ -15,6 +15,11 @@ inputs:
     description: 'API token for AI'
     required: true
     type: string
+  model:  # New input for the model
+    description: 'The Gemini model to use (e.g., gemini-1.5-flash-latest)'
+    required: false
+    default: 'gemini-1.5-flash-latest'
+    type: string
   student-files:
     description: "Comma-separated list of student's Python file paths or a glob pattern"
     required: false

ai_tutor.py

@@ -19,8 +19,8 @@
 
 
 @functools.lru_cache
-def url(api_key:str) -> str:
-    return f'https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent?key={api_key}'
+def url(api_key:str, model:str='gemini-1.5-flash-latest') -> str:
+    return f'https://generativelanguage.googleapis.com/v1beta/models/{model}:generateContent?key={api_key}'
 
 
 @functools.lru_cache
@@ -31,6 +31,7 @@ def header() -> HEADER:
 def ask_gemini(
             question: str,
             api_key:str,
+            model:str='gemini-1.5-flash-latest',
             header:HEADER=header(),
             retry_delay_sec: float = 5.0,
             max_retry_attempt: int = 3,
@@ -60,7 +61,11 @@ def ask_gemini(
             logging.error(f"Timeout exceeded for question: {question}")
             break  # Exit the loop on timeout
 
-        response = requests.post(url(api_key), headers=header, json=data)
+        response = requests.post(
+            url(api_key, model=model),
+            headers=header,
+            json=data
+        )
 
         if response.status_code == 200:
             result = response.json()
@@ -88,6 +93,7 @@ def gemini_qna(
         readme_file:pathlib.Path,
         api_key:str,
         explanation_in:str='Korean',
+        model:str='gemini-1.5-flash-latest',
     ) -> Tuple[int, str]:
     '''
     Queries the Gemini API to provide explanations for failed pytest test cases.
@@ -112,7 +118,7 @@ def gemini_qna(
         explanation_in
     )
 
-    answers = ask_gemini(consolidated_question, api_key)
+    answers = ask_gemini(consolidated_question, api_key, model=model)
 
     return n_failed, answers
 

entrypoint.py

@@ -30,9 +30,12 @@ def main() -> None:
     assert readme_file.exists(), 'No README file'
 
     api_key = os.environ['INPUT_API-KEY'].strip()
-
     assert api_key, "Please check API-KEY"
 
+    model = os.getenv(
+        'INPUT_MODEL',              # Get model from environment
+        'gemini-1.5-flash-latest'   # use default if not provided
+    )
     explanation_in = os.environ['INPUT_EXPLANATION-IN']
 
     b_fail_expected = ('true' == os.getenv('INPUT_FAIL-EXPECTED', 'false').lower())
@@ -42,7 +45,8 @@ def main() -> None:
         student_files,
         readme_file,
         api_key,
-        explanation_in
+        explanation_in,
+        model=model,
     )
 
     print(feedback)

tests/test_ai_tutor.py

@@ -1,6 +1,7 @@
 import json
 import pathlib
 import sys
+import urllib.parse as up
 
 from typing import Callable, Dict, List, Tuple, Union
 
@@ -549,5 +550,55 @@ def test__exclude_common_contents__double_specific(
     assert end_marker.strip() not in result
 
 
+@pytest.fixture
+def test_api_key() -> str:
+    return 'test_api_key'
+
+
+@pytest.fixture
+def expected_default_gemini_model() -> str:
+    return 'gemini-1.5-flash-latest'
+
+
+def test_url__default_model(
+        test_api_key:str,
+        expected_default_gemini_model:str
+    ):
+    result = ai_tutor.url(test_api_key)
+
+    result_parsed = up.urlparse(result)
+
+    path_parts = result_parsed.path.split('/')
+
+    b_found = False
+
+    for part in path_parts:
+        if expected_default_gemini_model in part.split(':'):
+            b_found = True
+            break
+
+    assert b_found, f"Could not find {expected_default_gemini_model} in {path_parts}."
+
+
+def test_url__specific_model(
+        test_api_key:str,
+    ):
+    model = 'gemini-2.0-flash'
+    result = ai_tutor.url(test_api_key, model=model)
+
+    result_parsed = up.urlparse(result)
+
+    path_parts = result_parsed.path.split('/')
+
+    b_found = False
+
+    for part in path_parts:
+        if model in part.split(':'):
+            b_found = True
+            break
+
+    assert b_found, f"Could not find {expected_default_gemini_model} in {path_parts}."
+
+
 if '__main__' == __name__:
     pytest.main([__file__])

tests/test_integration.py

@@ -20,6 +20,7 @@ def test_main_argument_passing__all_exists(mock_gemini_qna, caplog, tmp_path) ->
     # Setup
     os.environ['INPUT_API-KEY'] = 'test_key'
     os.environ['INPUT_EXPLANATION-IN'] = 'Korean'
+    os.environ['INPUT_MODEL'] = 'gemini-2.0-flash-exp'
 
     os.environ['GITHUB_OUTPUT'] = str(tmp_path / 'output.txt')
 
@@ -54,6 +55,7 @@ def test_main_argument_passing__all_exists(mock_gemini_qna, caplog, tmp_path) ->
         tmp_path / 'readme.txt',
         'test_key',
         'Korean',
+         model='gemini-2.0-flash-exp',
     )
 
     assert 'does not exist' not in caplog.text