fix: lint

pilot/model/adapter.py

@@ -85,8 +85,10 @@ class ChatGLMAdapater(BaseLLMAdaper):
 
 class GuanacoAdapter(BaseLLMAdaper):
     """TODO Support guanaco"""
+
     pass
 
+
 class CodeGenAdapter(BaseLLMAdaper):
     pass
 
@@ -124,12 +126,14 @@ class GPT4AllAdapter(BaseLLMAdaper):
         return "gpt4all" in model_path
 
     def loader(self, model_path: str, from_pretrained_kwargs: dict):
-        # TODO 
+        # TODO
         pass
 
+
 class ProxyllmAdapter(BaseLLMAdaper):
-    
+
     """The model adapter for local proxy"""
+
     def match(self, model_path: str):
         return "proxyllm" in model_path
 

pilot/model/loader.py

@@ -109,8 +109,10 @@ class ModelLoader(metaclass=Singleton):
                 compress_module(model, self.device)
 
         if (
-            self.device == "cuda" and num_gpus == 1 and not cpu_offloading
+            (self.device == "cuda" and num_gpus == 1 and not cpu_offloading)
-        ) or self.device == "mps" and tokenizer:
+            or self.device == "mps"
+            and tokenizer
+        ):
             model.to(self.device)
 
         if debug:

pilot/model/proxy_llm.py

@@ -8,10 +8,8 @@ from pilot.conversation import ROLE_ASSISTANT, ROLE_USER
 
 CFG = Config()
 
-def proxyllm_generate_stream(
-    model, tokenizer, params, device, context_len=2048
-):
 
+def proxyllm_generate_stream(model, tokenizer, params, device, context_len=2048):
     history = []
 
     prompt = params["prompt"]
@@ -19,9 +17,9 @@ def proxyllm_generate_stream(
 
     headers = {
         "Authorization": "Bearer " + CFG.proxy_api_key,
-        "Token": CFG.proxy_api_key 
+        "Token": CFG.proxy_api_key,
     }
-  
+
     messages = prompt.split(stop)
 
     # Add history conversation
@@ -30,32 +28,35 @@ def proxyllm_generate_stream(
             {"role": "user", "content": messages[i].split(ROLE_USER + ":")[1]},
         )
         history.append(
-            {"role": "system", "content": messages[i + 1].split(ROLE_ASSISTANT + ":")[1]}
+            {
+                "role": "system",
+                "content": messages[i + 1].split(ROLE_ASSISTANT + ":")[1],
+            }
         )
-    
+
-    # Add user query 
+    # Add user query
     query = messages[-2].split(ROLE_USER + ":")[1]
-    history.append(
+    history.append({"role": "user", "content": query})
-        {"role": "user", "content": query}
-    )
     payloads = {
-        "model": "gpt-3.5-turbo",   # just for test, remove this later
+        "model": "gpt-3.5-turbo",  # just for test, remove this later
-        "messages": history, 
+        "messages": history,
         "temperature": params.get("temperature"),
         "max_tokens": params.get("max_new_tokens"),
     }
 
     print(payloads)
     print(headers)
-    res = requests.post(CFG.proxy_server_url, headers=headers, json=payloads, stream=True)
+    res = requests.post(
+        CFG.proxy_server_url, headers=headers, json=payloads, stream=True
+    )
 
     text = ""
     print("====================================res================")
     print(res)
     for line in res.iter_lines():
         if line:
-            decoded_line = line.decode('utf-8')
+            decoded_line = line.decode("utf-8")
             json_line = json.loads(decoded_line)
             print(json_line)
             text += json_line["choices"][0]["message"]["content"]
-            yield text 
+            yield text

pilot/server/chat_adapter.py

@@ -85,13 +85,13 @@ class CodeGenChatAdapter(BaseChatAdpter):
 
 
 class GuanacoChatAdapter(BaseChatAdpter):
-    """Model chat adapter for Guanaco """
+    """Model chat adapter for Guanaco"""
-    
+
     def match(self, model_path: str):
         return "guanaco" in model_path
 
     def get_generate_stream_func(self):
-        # TODO 
+        # TODO
         pass
 
 
@@ -101,7 +101,8 @@ class ProxyllmChatAdapter(BaseChatAdpter):
 
     def get_generate_stream_func(self):
         from pilot.model.proxy_llm import proxyllm_generate_stream
-        return proxyllm_generate_stream 
+
+        return proxyllm_generate_stream
 
 
 register_llm_model_chat_adapter(VicunaChatAdapter)

pilot/server/llmserver.py

@@ -37,7 +37,7 @@ class ModelWorker:
         self.model, self.tokenizer = self.ml.loader(
             num_gpus, load_8bit=ISLOAD_8BIT, debug=ISDEBUG
         )
-        
+
         if not isinstance(self.model, str):
             if hasattr(self.model.config, "max_sequence_length"):
                 self.context_len = self.model.config.max_sequence_length

pilot/server/webserver.py

@@ -434,7 +434,7 @@ def http_bot(
                         """ TODO Multi mode output handler,  rewrite this for multi model, use adapter mode.
                         """
                         if data["error_code"] == 0:
-                            print("****************:",data)
+                            print("****************:", data)
                             if "vicuna" in CFG.LLM_MODEL:
                                 output = data["text"][skip_echo_len:].strip()
                             else: