Fix bugs: name of client, languages saved and missing standalone prompt

app.py

@@ -97,12 +97,24 @@ with gr.Blocks() as app:
             "=========\n"
             "\n"
             "----------------------- Standalone -----------------------\n"
+            "You are a standalone question-maker. Given the following chat history and follow-up message, rephrase "
+            "the follow-up phrase to be a standalone question (sometimes the follow-up is not a question, so create "
+            "a standalone phrase), in spanish. In the standalone message you must include all the information at the "
+            "moment that is known about the customer, all the important nouns and what they are looking for. In cases "
+            "where you think is usefully, include what is the best recommendation for the customer. To give you "
+            "context, the conversation is about (INGRESE INFORMACIÓN DE LA MARCA, EL NOMBRE Y DE MANERA MUY GENERAL "
+            "QUE ES LO QUE VENDE).\n"
+            "There might be moments when there isn't a question in those cases return a standalone phrase: for example "
+            "if the user says 'hola' (or something similar) then the output would be 'el usuario está saludando', or "
+            "if the user says 'gracias' or 'es muy util' (or something similar) then the output would be a phrase "
+            "showing that the user is grateful and what they are grateful for, or if the user say 'si' then it would "
+            "be a phrase encapsulating the relationship to its previous question or phrase.\n"
+            "Your response cannot be more than 50 words.\n"
             "Chat History:\n"
             "\n"
             "HISTORY\n"
             "Follow-up message: QUESTION\n"
-            "Standalone message:\n"
-            "```", line_breaks=True
+            "Standalone message:\n", line_breaks=True
         )
 
     with gr.Tab('Test'):

services/chatbot.py

@@ -13,12 +13,13 @@ pinecone.init(api_key=os.getenv("PINECONE_API_KEY"), environment=os.getenv("PINE
 INDEX = pinecone.Index(os.getenv("PINECONE_INDEX"))
 
 
-def start_chat(client_name: str) -> tuple[list[list[str | None]], gr.helpers, gr.helpers]:
+def start_chat(client: str) -> tuple[list[list[str | None]], gr.helpers, gr.helpers]:
     """
     Initialize chat with greeting text and audio in spanish
-    :param client_name: name of the client
+    :param client: name of the client
     :return: (chat history with greeting, audio with updated file and gradio update with visible=True)
     """
+    client_name = client.lower().replace(' ', '-')
     # Get greeting text and audio, the first one available in spanish
     with open(f'assets/{client_name}/greetings/es.csv', mode='r', encoding='utf-8') as infile:
         reader = csv.reader(infile)
@@ -31,12 +32,13 @@ def start_chat(client_name: str) -> tuple[list[list[str | None]], gr.helpers, gr
     return chat_history, gr.update(value=f'{audio_name}'), gr.update(visible=True)
 
 
-def get_random_data(client_name: str) -> gr.helpers:
+def get_random_data(client: str) -> gr.helpers:
     """
     Returns an audio with a random data in spanish
-    :param client_name: name of the client for this chatbot
+    :param client: name of the client for this chatbot
     :return: gradio audio updated with a random data from the client
     """
+    client_name = client.lower().replace(' ', '-')
     random_options = []
     path_audios = f'assets/{client_name}/media/audio'
     for random_audio in os.listdir(path_audios):
@@ -49,17 +51,19 @@ def get_random_data(client_name: str) -> gr.helpers:
 
 
 def get_answer(
-        chat_history: list[tuple[str, str]], user_input: str, client_name: str, general_prompt: str, context_prompt: str
+        chat_history: list[tuple[str, str]], user_input: str, client: str, general_prompt: str, context_prompt: str
 ) -> tuple[list[tuple[str, str]], str, gr.helpers]:
     """
     Gets the answer from the chatbot and returns it as an audio and text
     :param chat_history: previous chat history
     :param user_input: user question
-    :param client_name: name of the client
+    :param client: name of the client
     :param general_prompt: prompt used for answering the questions
     :param context_prompt: prompt used for finding the context in the vectorstore
     :return:
     """
+    client_name = client.lower().replace(' ', '-')
+
     # Format chat history to OpenAI format msg history
     msg_history = [{'role': 'system', 'content': general_prompt}]
     for i, (user, bot) in enumerate(chat_history):

services/utils.py

@@ -196,14 +196,16 @@ def create_chatbot(
     return gr.update(value='Chatbot created!!!', interactive=False)
 
 
-def save_prompts(client_name: str, context_prompt: str, prompts_table: list[list[str]]) -> None:
+def save_prompts(client: str, context_prompt: str, prompts_table: list[list[str]]) -> None:
     """
     Saves all the prompts (standalone and one for each language) and uploads them to Google Cloud Storage
-    :param client_name: name of the client
+    :param client: name of the client
     :param context_prompt: standalone prompt used to search into the vectorstore
     :param prompts_table: table with the prompt of each language
     :return: None
     """
+    client_name = client.lower().replace(' ', '-')
+
     path_prompts = f'assets/{client_name}/prompts'
     os.makedirs(path_prompts, exist_ok=True)
 
@@ -221,20 +223,26 @@ def save_prompts(client_name: str, context_prompt: str, prompts_table: list[list
     return
 
 
-def generate_json(client_name: str, languages: list[str], max_num_questions: int, chatbot_name: str) -> gr.helpers:
+def generate_json(client: str, languages: list[str], max_num_questions: int, chatbot_name: str) -> gr.helpers:
     """
     Creates a json file with the environment variables used in the API
-    :param client_name:
+    :param client:
     :param languages:
     :param max_num_questions:
     :param chatbot_name:
     :return: gradio file with the value as the path of the json file
     """
+    # Format the name and the languages
+    short_languages = ''.join(f'{TRANSLATE_LANGUAGES[language]},' for language in languages)
+    short_languages = short_languages[:-1]
+    client_name = client.lower().replace(' ', '-')
+
     json_object = json.dumps(
         {
-            'CLIENT_NAME': client_name, 'MODEL_OPENAI': os.getenv('OPENAI_MODEL'), 'LANGUAGES': languages,
+            'CLIENT_NAME': client_name, 'MODEL_OPENAI': os.getenv('OPENAI_MODEL'), 'LANGUAGES': short_languages,
             'MAX_NUM_QUESTIONS': max_num_questions, 'NUM_VECTORS_CONTEXT': 10, 'THRESHOLD_RECYCLE': 0.97,
-            'OPENAI_API_KEY': 'Check OpenAI for this', 'CHATBOT_NAME': chatbot_name
+            'OPENAI_API_KEY': 'Check OpenAI for this', 'CHATBOT_NAME': chatbot_name, 'HAS_ROADMAP': 0,
+            'SAVE_ANSWERS': 0, 'USE_RECYCLED_DATA': 1
         },
         indent=4
     )