Upload 2 files

helpers.py

@@ -0,0 +1,45 @@
+from db import DB
+
+def validate_key(key, db: DB):
+    """ Validate the survey key. """
+    generated_keys = db.get_document_ids('surveykeys')
+    survey_done = db.get_document_ids('responses')
+    if (key in generated_keys) and (key not in survey_done):
+        return True
+    return False
+
+def label_speaker(speaker):
+    if speaker == 'You':
+        return '### Human'
+    elif speaker == 'Other Party':
+        return '### Assistant'
+    
+def expand_for(num):
+    if num < 2:
+        return True
+    else:
+        return False
+    
+def check_none_in_dict(dictionary):
+    for key, value in dictionary.items():
+        if value is None:
+            print(f"Found 'None' value for key: {key}")
+            return True
+    print("No 'None' values found in the dictionary.")
+    return False
+
+def check_conversation_input_validity(lst):
+    for i in range(len(lst)):
+        item = lst[i]
+        if item is None:
+            if i < 2:
+                return False
+            last_item = lst[i-1]
+            if last_item[0:9] == '### Human':
+                return True
+            else:
+                return False
+            
+def wrap_conversation(text: str):
+    wrapped_text = '### Human: ' + text + " ### Assistant:"
+    return wrapped_text

huggingface.py

@@ -0,0 +1,38 @@
+from huggingface_hub import InferenceClient
+import requests
+
+from helpers import wrap_conversation
+
+class Model:
+    
+    def __init__(self, model_name: str, API_URL: str):
+        self.model_name = model_name
+        self.API_URL = API_URL
+
+    def _query(self, payload):
+        headers = {
+            # "Authorization": "Bearer XXX",
+            "Content-Type": "application/json"
+        }
+        response = requests.post(self.API_URL, headers=headers, json=payload)
+        return response.json()
+
+    def generate_text(self, text_input: str) -> str:
+        # output = self.client.text_generation(text_input)
+        # return output
+        payload = {
+            "inputs": wrap_conversation(text_input),
+            "parameters": {
+                "temperature": 0.9,
+                "max_new_tokens": 50
+            }
+        }
+
+        output = self._query(payload)
+        return self._get_first_reply(text_input, output['generated_text'])
+    
+    @staticmethod
+    def _get_first_reply(original_text, output_text):
+        new_text = output_text[len(wrap_conversation(original_text)):]
+        final_text = new_text.split('#', 1)[0]
+        return final_text