update app.py chat format

app.py

@@ -51,14 +51,6 @@ h1 {
 # Load the tokenizer and model
 tokenizer = AutoTokenizer.from_pretrained("FreedomIntelligence/Apollo-7B")
 
-chat = [
-  {"role": "user", "content": "Hello, how are you?"},
-  {"role": "assistant", "content": "I'm doing great. How can I help you today?"},
-  {"role": "user", "content": "I'd like to show off how chat templating works!"},
-]
-
-tokenizer.apply_chat_template(chat, tokenize=False)
-
 model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/Apollo-7B", device_map="auto")  # to("cuda:0") 
 terminators = [
     tokenizer.eos_token_id,
@@ -66,24 +58,38 @@ terminators = [
 ]
 
 @spaces.GPU(duration=120)
-def chat_llama3_8b(message: str, 
-              history: list, 
+def chat_llama3_8b(conversation_data: dict,
               temperature: float, 
               max_new_tokens: int
              ) -> str:
     """
     Generate a streaming response using the llama3-8b model.
     Args:
-        message (str): The input message.
-        history (list): The conversation history used by ChatInterface.
+        conversation_data (dict): A dictionary containing 'text' and 'history'.
         temperature (float): The temperature for generating the response.
         max_new_tokens (int): The maximum number of new tokens to generate.
     Returns:
         str: The generated response.
     """
+    message = conversation_data.get("text", "")
+    history_str = conversation_data.get("history", "")
+    
+    # 处理历史记录
     conversation = []
-    for user, assistant in history:
-        conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}])
+    if history_str:
+        # 假设历史记录是以某种格式存储的字符串，需要根据实际格式进行解析
+        # 这里假设历史记录是以换行符分隔的用户和助手消息，偶数行是用户，奇数行是助手
+        lines = history_str.strip().split('\n')
+        for i in range(0, len(lines), 2):
+            if i+1 < len(lines):
+                user_msg = lines[i]
+                assistant_msg = lines[i+1]
+                conversation.extend([
+                    {"role": "user", "content": user_msg},
+                    {"role": "assistant", "content": assistant_msg}
+                ])
+    
+    # 添加最新的用户消息
     conversation.append({"role": "user", "content": message})
 
     input_ids = tokenizer.apply_chat_template(conversation, return_tensors="pt").to(model.device)
@@ -140,7 +146,7 @@ with gr.Blocks(fill_height=True, css=css) as demo:
             ],
         examples=[
             ['How to setup a human base on Mars? Give short answer.'],
-            ['Explain theory of relativity to me like I’m 8 years old.'],
+            ['Explain theory of relativity to me like I'm 8 years old.'],
             ['What is 9,000 * 9,000?'],
             ['Write a pun-filled happy birthday message to my friend Alex.'],
             ['Justify why a penguin might make a good king of the jungle.']