Merge branch 'dev' of https://github.com/csunny/DB-GPT into dev

pilot/configs/model_config.py

@@ -34,6 +34,7 @@ LLM_MODEL_CONFIG = {
     "chatglm-6b-int4": os.path.join(MODEL_PATH, "chatglm-6b-int4"),
     "chatglm-6b": os.path.join(MODEL_PATH, "chatglm-6b"),
     "text2vec-base": os.path.join(MODEL_PATH, "text2vec-base-chinese"),
+    "guanaco-33b-merged": os.path.join(MODEL_PATH, "guanaco-33b-merged"
     "sentence-transforms": os.path.join(MODEL_PATH, "all-MiniLM-L6-v2"),
     "guanaco-33b-merged": os.path.join(MODEL_PATH, "guanaco-33b-merged"),
     "proxyllm": "proxyllm",

pilot/model/adapter.py

@@ -82,6 +82,21 @@ class ChatGLMAdapater(BaseLLMAdaper):
             )
             return model, tokenizer
 
+        
+class GuanacoAdapter(BaseLLMAdaper):
+    """TODO Support guanaco"""
+
+    def match(self, model_path: str):
+        return "guanaco" in model_path
+
+    def loader(self, model_path: str, from_pretrained_kwargs: dict):
+        tokenizer = LlamaTokenizer.from_pretrained(model_path)
+        model = AutoModelForCausalLM.from_pretrained(
+            model_path, load_in_4bit=True, device_map={"": 0}, **from_pretrained_kwargs
+        )
+        return model, tokenizer
+
+
 
 class GuanacoAdapter(BaseLLMAdaper):
     """TODO Support guanaco"""

pilot/model/guanaco_stream_llm.py

@@ -0,0 +1,55 @@
+import torch
+from threading import Thread
+from transformers import TextIteratorStreamer, StoppingCriteriaList, StoppingCriteria
+
+
+
+def guanaco_stream_generate_output(model, tokenizer, params, device, context_len=2048):
+    """Fork from: https://github.com/KohakuBlueleaf/guanaco-lora/blob/main/generate.py"""
+    tokenizer.bos_token_id = 1
+    print(params)
+    stop = params.get("stop", "###")
+    prompt = params["prompt"]
+    query = prompt
+    print("Query Message: ", query)
+
+    input_ids = tokenizer(query, return_tensors="pt").input_ids
+    input_ids = input_ids.to(model.device)
+
+    streamer = TextIteratorStreamer(
+        tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True
+    )
+    
+    tokenizer.bos_token_id = 1
+    stop_token_ids = [0]
+
+    class StopOnTokens(StoppingCriteria):
+        def __call__(
+            self, input_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs
+        ) -> bool:
+            for stop_id in stop_token_ids:
+                if input_ids[0][-1] == stop_id:
+                    return True
+            return False
+
+    stop = StopOnTokens()
+
+    generate_kwargs = dict(
+        input_ids=input_ids,
+        max_new_tokens=512,
+        temperature=1.0,
+        do_sample=True,
+        top_k=1,
+        streamer=streamer,
+        repetition_penalty=1.7,
+        stopping_criteria=StoppingCriteriaList([stop]),
+    )
+
+    t = Thread(target=model.generate, kwargs=generate_kwargs)
+    t.start()
+
+    out = ""
+    for new_text in streamer:
+        out += new_text
+        yield new_text
+    return out

pilot/server/chat_adapter.py

@@ -59,6 +59,16 @@ class ChatGLMChatAdapter(BaseChatAdpter):
 
         return chatglm_generate_stream
 
+class GuanacoChatAdapter(BaseChatAdpter):
+    """Model chat adapter for Guanaco"""
+
+    def match(self, model_path: str):
+        return "guanaco" in model_path
+
+    def get_generate_stream_func(self):
+        from pilot.model.llm_out.guanaco_stream_llm import guanaco_stream_generate_output
+
+        return guanaco_generate_output
 
 class CodeT5ChatAdapter(BaseChatAdpter):
 
@@ -110,6 +120,7 @@ register_llm_model_chat_adapter(VicunaChatAdapter)
 register_llm_model_chat_adapter(ChatGLMChatAdapter)
 register_llm_model_chat_adapter(GuanacoChatAdapter)
 
+
 # Proxy model for test and develop, it's cheap for us now.
 register_llm_model_chat_adapter(ProxyllmChatAdapter)