Merge branch 'main' into dev

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 +56,55 @@ 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"]
+    max_new_tokens = params.get("max_new_tokens", 512)
+    temerature = params.get("temperature", 1.0)
+
+    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[-1][-1] == stop_id:
+                    return True
+            return False
+
+    stop = StopOnTokens()
+
+    generate_kwargs = dict(
+        input_ids=input_ids,
+        max_new_tokens=max_new_tokens,
+        temperature=temerature,
+        do_sample=True,
+        top_k=1,
+        streamer=streamer,
+        repetition_penalty=1.7,
+        stopping_criteria=StoppingCriteriaList([stop]),
+    )
+
+    model.generate(**generate_kwargs)
+
+    out = ""
+    for new_text in streamer:
+        out += new_text
+        yield out

pilot/model/llm_out/proxy_llm.py

@@ -68,15 +68,11 @@ def proxyllm_generate_stream(model, tokenizer, params, device, context_len=2048)
         "max_tokens": params.get("max_new_tokens"),
     }
 
-    print(payloads)
-    print(headers)
     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")

pilot/model/loader.py

@@ -118,6 +118,8 @@ class ModelLoader(metaclass=Singleton):
                 model.to(self.device)
             except ValueError:
                 pass
+            except AttributeError:
+                pass
 
         if debug:
             print(model)

pilot/out_parser/base.py

@@ -56,8 +56,11 @@ class BaseOutputParser(ABC):
                 # output = data["text"][skip_echo_len + 11:].strip()
                 output = data["text"][skip_echo_len:].strip()
             elif "guanaco" in CFG.LLM_MODEL:
-                # output = data["text"][skip_echo_len + 14:].replace("<s>", "").strip()
+                # NO stream output
-                output = data["text"][skip_echo_len:].replace("<s>", "").strip()
+                # output = data["text"][skip_echo_len + 2:].replace("<s>", "").strip()
+
+                # stream out output
+                output = data["text"][11:].replace("<s>", "").strip()
             else:
                 output = data["text"].strip()
 

pilot/server/chat_adapter.py

@@ -101,9 +101,9 @@ class GuanacoChatAdapter(BaseChatAdpter):
         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.llm_out.guanaco_llm import guanaco_generate_stream
 
-        return guanaco_generate_output
+        return guanaco_generate_stream
 
 
 class ProxyllmChatAdapter(BaseChatAdpter):