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

pilot/model/llm_out/guanaco_llm.py

@@ -1,5 +1,4 @@
 import torch
-import copy
 from threading import Thread
 from transformers import TextIteratorStreamer, StoppingCriteriaList, StoppingCriteria
 from pilot.conversation import ROLE_ASSISTANT, ROLE_USER
@@ -57,3 +56,53 @@ def guanaco_generate_output(model, tokenizer, params, device, context_len=2048):
         out = decoded_output.split("### Response:")[-1].strip()
 
         yield out
+
+
+def guanaco_generate_stream(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]),
+    )
+
+
+    generator = model.generate(**generate_kwargs)
+    out = ""
+    for new_text in streamer:
+        out += new_text
+        yield new_text
+    return out

pilot/server/chat_adapter.py

@@ -4,7 +4,7 @@
 from functools import cache
 from typing import List
 
-from pilot.model.llm_out.vicuna_base_llm import generate_stream
+from pilot.model.inference import generate_stream
 
 
 class BaseChatAdpter:
@@ -55,7 +55,7 @@ class ChatGLMChatAdapter(BaseChatAdpter):
         return "chatglm" in model_path
 
     def get_generate_stream_func(self):
-        from pilot.model.llm_out.chatglm_llm import chatglm_generate_stream
+        from pilot.model.chatglm_llm import chatglm_generate_stream
 
         return chatglm_generate_stream
 
@@ -85,15 +85,15 @@ 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):
-        from pilot.model.llm_out.guanaco_llm import guanaco_generate_output
+        from pilot.model.guanaco_llm import guanaco_generate_stream 
         
-        return guanaco_generate_output
+        return guanaco_generate_stream
 
 
 class ProxyllmChatAdapter(BaseChatAdpter):
@@ -101,7 +101,7 @@ class ProxyllmChatAdapter(BaseChatAdpter):
         return "proxyllm" in model_path
 
     def get_generate_stream_func(self):
-        from pilot.model.llm_out.proxy_llm import proxyllm_generate_stream
+        from pilot.model.proxy_llm import proxyllm_generate_stream
 
         return proxyllm_generate_stream