updated prompt wording issue

app.py

@@ -9,6 +9,8 @@ import spacy
 from langchain_openai import ChatOpenAI
 from langchain.schema import AIMessage, HumanMessage
 import pandas as pd
+import uuid
+import json
 
 # Load environment variables from .env file
 load_dotenv()
@@ -16,6 +18,8 @@ load_dotenv()
 # Access the env
 HF_TOKEN = os.getenv('HUGGING_FACE_TOKEN')
 
+GITHUB_TOKEN = "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" # move to env
+
 # openai setup
 # client = OpenAI(
 #   api_key=os.getenv('OPENAI_API_KEY')
@@ -30,6 +34,29 @@ headers = {"Authorization": f"Bearer {HF_TOKEN}"}
 # Global variable to control debug printing
 DEBUG_MODE = True
 
+
+def share_to_gist(content, public=False):
+    url = "https://api.github.com/gists"
+    headers = {
+        "Authorization": f"token {os.getenv(GITHUB_TOKEN)}",
+        "Accept": "application/vnd.github.v3+json",
+    }
+    data = {
+        "public": public,
+        "description": "Chat history",
+        "files": {
+            "chat.txt": {
+                "content": content
+            }
+        }
+    }
+    response = requests.post(url, headers=headers, data=json.dumps(data))
+    gist_url = response.json().get('html_url', '')
+    return gist_url
+
+def generate_unique_id():
+    return str(uuid.uuid4())
+
 def debug_print(*args, **kwargs):
     if DEBUG_MODE:
         print(*args, **kwargs)
@@ -82,7 +109,7 @@ def predict(message, history):
     Encourage the student by specifying the strengths of their writing.
     DO NOT PROVIDE THE CORRECT ENGLISH TRANSLATION until the student gets the correct translation. Let the student work it out.
     Provide your feedback as a list in the format: a, b, c etc.
-    Do not respond in Japanese - always respond in English even if the student uses Japanese to with you.
+    Do not respond in Japanese - always respond in English even if the student uses Japanese with you.
     
     Execute the following tasks step by step:
     1. Ask the student to translate the following sentence from Japanese to English: {japanese_sentence}. Here is the English translation for reference: {english_sentence}
@@ -109,10 +136,16 @@ def predict(message, history):
 
     #debug_print("### Full history: ", history_langchain_format)
     gpt_response = llm(history_langchain_format)
-    return gpt_response.content
+    return  gpt_response.content
 
 welcome_message = "Hi! 👋. Are you ready to practise translation?"
 
+# with gr.Blocks() as app:
+#     chatbot = gr.Chatbot()
+#     message = gr.Textbox()
+#     clear = gr.ClearButton([message, chatbot])
+#     message.submit(predict, [message, chatbot], [message, chatbot])
+
 app = gr.ChatInterface(fn=predict, title="Translation Chatbot", chatbot=gr.Chatbot(value=[(None, welcome_message)],),)#, multimodal=True) # chatbot=gr.Chatbot(value=[["Welcome 👋. I am an assistant",]])