ctransformers?

code/app.py

@@ -1,14 +1,8 @@
 import logging
-from typing import cast
-from threading import Lock
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+#from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+from ctransformers import AutoModelForCausalLM
 
-import torch
-
-from conversation import get_default_conv_template
 import gradio as gr
-from llama_cpp import Llama
-import json
 
 from huggingface_hub import hf_hub_download
 
@@ -16,7 +10,8 @@ model_path = "./starling-lm-7b-alpha.Q6_K.gguf"
 
 mdlpath = hf_hub_download(repo_id="TheBloke/Starling-LM-7B-alpha-GGUF", filename=model_path, local_dir="./")
 
-lcpp_model = Llama(model_path=model_path, n_ctx=8192)
+#lcpp_model = Llama(model_path=model_path, n_ctx=8192)
+llm = AutoModelForCausalLM.from_pretrained(model_path_or_repo_id=model_path, local_files_only=True, model_type="mistral")
 global otxt, txtinput, txtoutput, running, result
 otxt = ""
 running = False
@@ -56,20 +51,33 @@ def printfmt(jsn):
             txt += "# " + msg["content"] + "\n\n"
     return txt
 
+def jsn2prompt(jsn):
+    txt = ""
+    for msg in jsn:
+        if "system" in msg["role"]:
+            txt += "GPT4 Correct User: Here is how I want you to behave throughout our conversation. " + msg["content"] + "\n"
+        elif "user" in msg["role"]:
+            txt += "GPT4 Correct User: " + msg["content"] + "\n"
+        elif "assistant" in msg["role"]:
+            txt += "GPT4 Assistant: " + msg["content"] + "\n"
+    return txt
+
 def talk(txt, jsn):
     global running, result
     if not jsn:
         jsn = txt
     if not running:
-        result = lcpp_model.create_chat_completion(messages=txt,stream=True,stop=["GPT4 Correct User: ", "<|end_of_turn|>", "</s>"], max_tokens=64, )
+        #result = lcpp_model.create_chat_completion(messages=txt,stream=True,stop=["GPT4 Correct User: ", "<|end_of_turn|>", "</s>"], max_tokens=64, )
+        #result = lcpp_model(prompt=jsn2prompt(txt), stream=True, stop=["GPT4 Correct User: ", "<|end_of_turn|>", "</s>"], max_tokens=64, echo=False)
+        result = llm(prompt=jsn2prompt(txt), stream=True, stop=["GPT4 Correct User: ", "<|end_of_turn|>", "</s>"], max_tokens=192, echo=False)
         running = True
     for r in result:
+        print("GOT RESULT:", r)
         txt2 = None
-        if "content" in r["choices"][0]["delta"]:
-            txt2 = r["choices"][0]["delta"]["content"]
-        elif not "content" in r["choices"][0]["delta"] and not "role" in r["choices"][0]["delta"]:
+        if "content" in r["choices"][0]["text"]:
+            txt2 = r["choices"][0]["text"]
+        elif not "text" in r["choices"][0] and not r["choices"][0]["finish_reason"]:
             running = False
-            #txt = stowchunk(txt, "</s>")
             yield txt
         if txt2 is not None:
             txt = stowchunk(txt, txt2)
@@ -102,7 +110,7 @@ def main():
         jsn2.change(lambda x: gr.update(visible=not running), inputs=jsn2, outputs=talk_btn)
         #jsn2.change(lambda x: gr.update(value=x), inputs=jsn2, outputs=jsn)
 
-    demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=True)
+    demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False)
 
 
 if __name__ == "__main__":

code/conversation.py

@@ -0,0 +1,223 @@
+"""
+Conversation prompt templates.
+"""
+
+import dataclasses
+from enum import auto, Enum
+from typing import List, Tuple, Any
+
+
+class SeparatorStyle(Enum):
+    """Different separator style."""
+
+    ADD_COLON_SINGLE = auto()
+    ADD_COLON_TWO = auto()
+    NO_COLON_SINGLE = auto()
+    BAIZE = auto()
+    PHOENIX = auto()
+    MINICHAT = auto()
+
+
+@dataclasses.dataclass
+class Conversation:
+    """A class that keeps all conversation history."""
+
+    # System prompts
+    system: str
+    # Two roles
+    roles: List[str]
+    # All messages
+    messages: List[List[str]]
+    # Offset of few shot examples
+    offset: int
+    # Separator
+    sep_style: SeparatorStyle
+    sep: str
+    sep2: str = None
+    # Stop criteria (the default one is EOS token)
+    stop_str: str = None
+    # Stops generation if meeting any token in this list
+    stop_token_ids: List[int] = None
+
+    # Used for the state in the gradio servers.
+    # TODO(lmzheng): refactor this
+    conv_id: Any = None
+    skip_next: bool = False
+    model_name: str = None
+
+    def get_prompt(self):
+        if self.sep_style == SeparatorStyle.ADD_COLON_SINGLE:
+            ret = self.system + self.sep
+            for role, message in self.messages:
+                if message:
+                    ret += role + ": " + message + self.sep
+                else:
+                    ret += role + ": "
+            return ret
+        elif self.sep_style == SeparatorStyle.ADD_COLON_TWO:
+            seps = [self.sep, self.sep2]
+            ret = self.system + seps[0]
+            for i, (role, message) in enumerate(self.messages):
+                if message:
+                    ret += role + ": " + message + seps[i % 2]
+                else:
+                    ret += role + ": "
+            return ret
+        elif self.sep_style == SeparatorStyle.NO_COLON_SINGLE:
+            ret = self.system
+            for role, message in self.messages:
+                if message:
+                    ret += role + message + self.sep
+                else:
+                    ret += role
+            return ret
+        elif self.sep_style == SeparatorStyle.BAIZE:
+            ret = self.system + "\n"
+            for role, message in self.messages:
+                if message:
+                    ret += role + message + "\n"
+                else:
+                    ret += role
+            return ret
+        elif self.sep_style == SeparatorStyle.PHOENIX:
+            ret = self.system
+            for role, message in self.messages:
+                if message:
+                    ret += role + ": " + "<s>" + message + "</s>"
+                else:
+                    ret += role + ": " + "<s>"
+            return ret
+        elif self.sep_style == SeparatorStyle.MINICHAT:
+            ret = self.system
+            for role, message in self.messages:
+                if message:
+                    ret += role + " " + message + "</s>"
+                else:
+                    ret += role # No space is needed.
+            return ret
+        else:
+            raise ValueError(f"Invalid style: {self.sep_style}")
+
+    def append_message(self, role, message):
+        self.messages.append([role, message])
+
+    def to_gradio_chatbot(self):
+        ret = []
+        for i, (role, msg) in enumerate(self.messages[self.offset:]):
+            if i % 2 == 0:
+                ret.append([msg, None])
+            else:
+                ret[-1][-1] = msg
+        return ret
+
+    def to_openai_api_messages(self):
+        ret = [{"role": "system", "content": self.system}]
+
+        for i, (_, msg) in enumerate(self.messages[self.offset:]):
+            if i % 2 == 0:
+                ret.append({"role": "user", "content": msg})
+            else:
+                if msg is not None:
+                    ret.append({"role": "assistant", "content": msg})
+        return ret
+
+    def copy(self):
+        return Conversation(
+            system=self.system,
+            roles=self.roles,
+            messages=[[x, y] for x, y in self.messages],
+            offset=self.offset,
+            sep_style=self.sep_style,
+            sep=self.sep,
+            sep2=self.sep2,
+            stop_str=self.stop_str,
+            stop_token_ids=self.stop_token_ids,
+            conv_id=self.conv_id,
+            model_name=self.model_name,
+        )
+
+    def dict(self):
+        return {
+            "system": self.system,
+            "roles": self.roles,
+            "messages": self.messages,
+            "offset": self.offset,
+            "conv_id": self.conv_id,
+            "model_name": self.model_name,
+        }
+
+
+conv_vicuna = Conversation(
+    system="A chat between a curious user and an artificial intelligence assistant. "
+    "The assistant gives helpful, detailed, and polite answers to the user's questions.",
+    roles=("USER", "ASSISTANT"),
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.ADD_COLON_TWO,
+    sep=" ",
+    sep2="</s>",
+)
+
+conv_baize = Conversation(
+    system="The following is a conversation between a human and an AI assistant named Baize (named after a mythical creature in Chinese folklore). Baize is an open-source AI assistant developed by UCSD and Sun Yat-Sen University. The human and the AI assistant take turns chatting. Human statements start with [|Human|] and AI assistant statements start with [|AI|]. The AI assistant always provides responses in as much detail as possible, and in Markdown format. The AI assistant always declines to engage with topics, questions and instructions related to unethical, controversial, or sensitive issues. Complete the transcript in exactly that format.\n",
+    roles=("[|Human|]", "[|AI|]"),
+    messages=(
+        ("[|Human|]", "Hello!"),
+        ("[|AI|]", "Hi!"),
+    ),
+    offset=2,
+    sep_style=SeparatorStyle.BAIZE,
+    sep="\n",
+    stop_str="[|Human|]",
+)
+
+conv_phoenix = Conversation(
+    system="A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.\n\n",
+    roles=("Human", "Assistant"),
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.PHOENIX,
+    sep="</s>",
+)
+
+conv_chatgpt = Conversation(
+    system="You are a helpful assistant.",
+    roles=("user", "assistant"),
+    messages=(),
+    offset=0,
+    sep_style=None,
+    sep=None,
+)
+
+conv_minichat = Conversation(
+    system="‘MiniChat’是一个由‘Beccurio’开发的AI语言模型。下面是人类和MiniChat之间的一段对话。MiniChat的回复应当尽可能详细，并且以Markdown的形式输出。MiniChat应当拒绝参与违背伦理的讨论。</s>",
+    roles=("[|User|]", "[|Assistant|]"),
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.MINICHAT,
+    sep="</s>",
+)
+
+
+conv_templates = {
+    "vicuna": conv_vicuna,
+    "baize": conv_baize,
+    "phoenix": conv_phoenix,
+    "chatgpt": conv_chatgpt,
+    "minichat": conv_minichat,
+}
+
+def get_default_conv_template(model_name):
+    model_name = model_name.lower()
+    try:
+        ret = conv_templates[model_name]
+        return ret.copy()
+    except:
+        raise NotImplementedError(f"No support for model {model_name}.")
+    
+
+if __name__ == "__main__":
+    conv = conv_templates["minichat"].copy()
+    conv.append_message(conv.roles[0], "Write a Python function that checks if a given number is even or odd.")
+    conv.append_message(conv.roles[1], None)
+    print([conv.get_prompt()])

code/requirements.txt

@@ -1,8 +1,9 @@
 --extra-index-url https://pypi.org/simple/
 huggingface_hub
 numpy
-httpx==0.24.1
-git+https://github.com/huggingface/transformers
+httpx[brotli,http2,==0.25.0
+#git+https://github.com/huggingface/transformers
+git+https://github.com/marella/ctransformers
 torch
 sentencepiece
 accelerate