RDISCROWD-5843 GIGWork GPT Helper Component MVP (v1) - Backend

pybossa/api/__init__.py

@@ -847,3 +847,75 @@ def user_has_partial_answer(short_name=None):
     task_id_map = get_user_saved_partial_tasks(sentinel, project_id, current_user.id, task_repo)
     response = {"has_answer": bool(task_id_map)}
     return Response(json.dumps(response), status=200, mimetype="application/json")
+
+
+@jsonpify
+@csrf.exempt
+@blueprint.route('/llm', defaults={'model_name': None}, methods=['POST'])
+@blueprint.route('/llm/<model_name>', methods=['POST'])
+@ratelimit(limit=ratelimits.get('LIMIT'), per=ratelimits.get('PER'))
+def large_language_model(model_name):
+    """Large language model endpoint
+    The POST data format can be:
+    data = {
+        "instances": [
+            {
+                "context": "Identify the company name: Microsoft will release Windows 20 next year.",
+                "temperature": 1.0,
+                "seed": 12345,
+                "repetition_penalty": 1.05,
+                "num_beams": 1,
+            }
+        ]
+    }
+    or
+    data = {
+        "prompts": "Identify the company name: Microsoft will release Windows 20 next year."
+    }
+    """
+    if model_name is None:
+        model_name = 'flan-ul2'
+    endpoints = current_app.config.get('LLM_ENDPOINTS')
+    model_endpoint = endpoints.get(model_name.lower())
+
+    if not model_endpoint:
+        return abort(403, f'Model with name {model_name} does not exist.')
+
+    proxies = current_app.config.get('PROXIES')
+    cert = current_app.config.get('CA_CERT', False)
+
+    try:
+        data = request.get_json(force=True)
+    except:
+        return abort(400, "Invalid JSON data")
+
+    if "prompts" not in data and "instances" not in data:
+        return abort(400, "The JSON should have either 'prompts' or 'instances'")
+
+    if "prompts" in data:
+        prompts = data.get("prompts")
+        if not prompts:
+            return abort(400, 'prompts should not be empty')
+        if isinstance(prompts, list):
+            prompts = prompts[0]  # Batch request temporarily NOT supported
+        if not isinstance(prompts, str):
+            return abort(400, f'prompts should be a string a list of strings')
+        data = {
+            "instances": [
+                {
+                    "context": prompts + ' ',
+                    "temperature": 1.0,
+                    "seed": 12345,
+                    "repetition_penalty": 1.05,
+                    "num_beams": 1,
+                }
+            ]
+        }
+    data = json.dumps(data)
+
+    r = requests.post(model_endpoint, data=data, proxies=proxies, verify=cert)
+    out = json.loads(r.text)
+    predictions = out["predictions"][0]["output"]
+    response = {"Model: ": model_name, "predictions: ": predictions}
+
+    return Response(json.dumps(response), status=r.status_code, mimetype="application/json")

test/test_api/__init__.py

@@ -15,11 +15,16 @@
 #
 # You should have received a copy of the GNU Affero General Public License
 # along with PYBOSSA.  If not, see <http://www.gnu.org/licenses/>.
+import json
+import unittest
 from datetime import datetime
+from unittest.mock import patch, MagicMock
 
 from dateutil.parser import parse
 from werkzeug.http import parse_cookie
 
+from pybossa.api import large_language_model
+from pybossa.core import create_app
 from test import Test
 
 
@@ -47,3 +52,127 @@ class TestAPI(Test):
 
     endpoints = ['project', 'task', 'taskrun', 'user']
 
+class TestLargeLanguageModel(unittest.TestCase):
+    def setUp(self):
+        self.app = create_app(run_as_server=False)
+        self.app.config['LLM_ENDPOINTS'] = {
+            'flan-ul2': 'http://localhost:5000/llm'
+        }
+        self.client = self.app.test_client()
+
+    @patch('requests.post')
+    def test_valid_request(self, mock_post):
+        response_data = {
+            "predictions": [{
+                "output": "Microsoft"
+            }]
+        }
+        mock_post.return_value = MagicMock(status_code=200, text=json.dumps(response_data))
+        with self.app.test_request_context('/', json={
+            "prompts": "Identify the company name: Microsoft will release Windows 20 next year."
+        }):
+            response = large_language_model('flan-ul2')
+            self.assertEqual(response.status_code, 200)
+            self.assertIn('Model: ', response.json)
+            self.assertIn('predictions: ', response.json)
+
+    @patch('requests.post')
+    def test_valid_request_with_list_of_prompts(self, mock_post):
+        response_data = {
+            "predictions": [{
+                "output": "Microsoft"
+            }]
+        }
+        mock_post.return_value = MagicMock(status_code=200,
+                                           text=json.dumps(response_data))
+        with self.app.test_request_context('/', json={
+            "prompts": ["Identify the company name: Microsoft will release Windows 20 next year.", "test"]
+        }):
+            response = large_language_model('flan-ul2')
+            self.assertEqual(response.status_code, 200)
+            self.assertIn('Model: ', response.json)
+            self.assertIn('predictions: ', response.json)
+
+    @patch('requests.post')
+    def test_valid_request_with_instances_key_in_json(self, mock_post):
+        response_data = {
+            "predictions": [{
+                "output": "Microsoft"
+            }]
+        }
+        mock_post.return_value = MagicMock(status_code=200,
+                                           text=json.dumps(response_data))
+        with self.app.test_request_context('/', json={
+            "instances": [
+                {
+                    "context": "Identify the company name: Microsoft will release Windows 20 next year.",
+                    "temperature": 1.0,
+                    "seed": 12345,
+                    "repetition_penalty": 1.05,
+                    "num_beams": 1,
+                }
+            ]
+        }):
+            response = large_language_model('flan-ul2')
+            self.assertEqual(response.status_code, 200)
+            self.assertIn('Model: ', response.json)
+            self.assertIn('predictions: ', response.json)
+
+    @patch('requests.post')
+    def test_invalid_model_name(self, mock_post):
+        mock_post.return_value = MagicMock(status_code=403, text='{"error": "Model not found"}')
+        with self.app.test_request_context('/', json={
+            "prompts": "Identify the company name: Microsoft will release Windows 20 next year."
+        }):
+            response = large_language_model('invalid-model')
+            self.assertEqual(response.status_code, 403)
+            self.assertIn('Model with name', response.json.get('exception_msg'))
+
+    @patch('requests.post')
+    def test_invalid_json(self, mock_post):
+        with self.app.test_request_context('/', data='invalid-json', content_type='application/json'):
+            response = large_language_model('flan-ul2')
+            self.assertEqual(response.status_code, 400)
+            self.assertIn('Invalid JSON', response.json.get('exception_msg'))
+
+    @patch('requests.post')
+    def test_invalid_post_data(self, mock_post):
+        response_data = {
+            "predictions": [{
+                "output": "Microsoft"
+            }]
+        }
+        mock_post.return_value = MagicMock(status_code=200,
+                                           text=json.dumps(response_data))
+        with self.app.test_request_context('/', json={
+            "invalid": [
+                {
+                    "context": "Identify the company name: Microsoft will release Windows 20 next year.",
+                    "temperature": 1.0,
+                    "seed": 12345,
+                    "repetition_penalty": 1.05,
+                    "num_beams": 1,
+                }
+            ]
+        }):
+            response = large_language_model('flan-ul2')
+            self.assertEqual(response.status_code, 400)
+            self.assertIn('The JSON should have', response.json.get('exception_msg'))
+
+    @patch('requests.post')
+    def test_empty_prompts(self, mock_post):
+        with self.app.test_request_context('/', json={
+            "prompts": ""
+        }):
+            response = large_language_model('flan-ul2')
+            self.assertEqual(response.status_code, 400)
+            self.assertIn('prompts should not be empty', response.json.get('exception_msg'))
+
+    @patch('requests.post')
+    def test_invalid_prompts_type(self, mock_post):
+        with self.app.test_request_context('/', json={
+            "prompts": 123
+        }):
+            response = large_language_model('flan-ul2')
+            self.assertEqual(response.status_code, 400)
+            self.assertIn('prompts should be a string', response.json.get('exception_msg'))