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https://github.com/nomic-ai/gpt4all
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adds a simple cli chat repl (#566)
* adds a simple cli chat repl * add n thread support and append assistant response
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gpt4all-bindings/cli/app.py
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118
gpt4all-bindings/cli/app.py
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@ -0,0 +1,118 @@
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import sys
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import typer
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from typing_extensions import Annotated
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from gpt4all import GPT4All
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MESSAGES = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Hello there."},
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{"role": "assistant", "content": "Hi, how can I help you?"},
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]
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SPECIAL_COMMANDS = {
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"/reset": lambda messages: messages.clear(),
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"/exit": lambda _: sys.exit(),
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"/clear": lambda _: print("\n" * 100),
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"/help": lambda _: print("Special commands: /reset, /exit, /help and /clear"),
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}
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VERSION = "0.1.0"
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CLI_START_MESSAGE = f"""
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██████ ██████ ████████ ██ ██ █████ ██ ██
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██ ██ ██ ██ ██ ██ ██ ██ ██ ██
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██ ███ ██████ ██ ███████ ███████ ██ ██
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██ ██ ██ ██ ██ ██ ██ ██ ██
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██████ ██ ██ ██ ██ ██ ███████ ███████
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Welcome to the GPT4All CLI! Version {VERSION}
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Type /help for special commands.
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"""
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def _cli_override_response_callback(token_id, response):
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resp = response.decode("utf-8")
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print(resp, end="", flush=True)
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return True
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# create typer app
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app = typer.Typer()
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@app.command()
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def repl(
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model: Annotated[
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str,
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typer.Option("--model", "-m", help="Model to use for chatbot"),
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] = "ggml-gpt4all-j-v1.3-groovy",
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n_threads: Annotated[
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int,
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typer.Option("--n-threads", "-t", help="Number of threads to use for chatbot"),
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] = 4,
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):
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gpt4all_instance = GPT4All(model)
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# if threads are passed, set them
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if n_threads != 4:
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num_threads = gpt4all_instance.model.thread_count()
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print(f"\nAdjusted: {num_threads} →", end="")
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# set number of threads
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gpt4all_instance.model.set_thread_count(n_threads)
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num_threads = gpt4all_instance.model.thread_count()
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print(f" {num_threads} threads", end="", flush=True)
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# overwrite _response_callback on model
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gpt4all_instance.model._response_callback = _cli_override_response_callback
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print(CLI_START_MESSAGE)
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while True:
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message = input(" ⇢ ")
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# Check if special command and take action
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if message in SPECIAL_COMMANDS:
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SPECIAL_COMMANDS[message](MESSAGES)
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continue
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# if regular message, append to messages
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MESSAGES.append({"role": "user", "content": message})
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# execute chat completion and ignore the full response since
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# we are outputting it incrementally
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full_response = gpt4all_instance.chat_completion(
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MESSAGES,
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# preferential kwargs for chat ux
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logits_size=0,
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tokens_size=0,
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n_past=0,
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n_ctx=0,
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n_predict=200,
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top_k=40,
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top_p=0.9,
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temp=0.9,
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n_batch=9,
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repeat_penalty=1.1,
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repeat_last_n=64,
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context_erase=0.0,
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# required kwargs for cli ux (incremental response)
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verbose=False,
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std_passthrough=True,
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)
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# record assistant's response to messages
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MESSAGES.append(full_response.get("choices")[0].get("message"))
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print() # newline before next prompt
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@app.command()
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def version():
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print("gpt4all-cli v0.1.0")
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if __name__ == "__main__":
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app()
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@ -6,6 +6,21 @@ import platform
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import re
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import sys
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class DualOutput:
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def __init__(self, stdout, string_io):
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self.stdout = stdout
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self.string_io = string_io
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def write(self, text):
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self.stdout.write(text)
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self.string_io.write(text)
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def flush(self):
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# It's a good idea to also define a flush method that flushes both
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# outputs, as sys.stdout is expected to have this method.
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self.stdout.flush()
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self.string_io.flush()
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# TODO: provide a config file to make this more robust
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LLMODEL_PATH = os.path.join("llmodel_DO_NOT_MODIFY", "build").replace("\\", "\\\\")
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@ -81,6 +96,15 @@ llmodel.llmodel_prompt.argtypes = [ctypes.c_void_p,
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RecalculateCallback,
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ctypes.POINTER(LLModelPromptContext)]
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llmodel.llmodel_prompt.restype = None
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llmodel.llmodel_setThreadCount.argtypes = [ctypes.c_void_p, ctypes.c_int32]
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llmodel.llmodel_setThreadCount.restype = None
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llmodel.llmodel_threadCount.argtypes = [ctypes.c_void_p]
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llmodel.llmodel_threadCount.restype = ctypes.c_int32
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class LLModel:
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"""
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Base class and universal wrapper for GPT4All language models
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@ -125,6 +149,18 @@ class LLModel:
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else:
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return False
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def set_thread_count(self, n_threads):
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if not llmodel.llmodel_isModelLoaded(self.model):
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raise Exception("Model not loaded")
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llmodel.llmodel_setThreadCount(self.model, n_threads)
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def thread_count(self):
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if not llmodel.llmodel_isModelLoaded(self.model):
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raise Exception("Model not loaded")
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return llmodel.llmodel_threadCount(self.model)
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def generate(self,
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prompt: str,
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logits_size: int = 0,
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@ -138,7 +174,8 @@ class LLModel:
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n_batch: int = 8,
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repeat_penalty: float = 1.2,
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repeat_last_n: int = 10,
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context_erase: float = .5) -> str:
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context_erase: float = .5,
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std_passthrough: bool = False) -> str:
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"""
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Generate response from model from a prompt.
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@ -164,6 +201,9 @@ class LLModel:
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# Change stdout to StringIO so we can collect response
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old_stdout = sys.stdout
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collect_response = StringIO()
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if std_passthrough:
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sys.stdout = DualOutput(old_stdout, collect_response)
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else:
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sys.stdout = collect_response
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context = LLModelPromptContext(
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@ -222,7 +262,7 @@ class GPTJModel(LLModel):
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self.model = llmodel.llmodel_gptj_create()
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def __del__(self):
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if self.model is not None:
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if self.model is not None and llmodel is not None:
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llmodel.llmodel_gptj_destroy(self.model)
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super().__del__()
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@ -236,7 +276,7 @@ class LlamaModel(LLModel):
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self.model = llmodel.llmodel_llama_create()
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def __del__(self):
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if self.model is not None:
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if self.model is not None and llmodel is not None:
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llmodel.llmodel_llama_destroy(self.model)
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super().__del__()
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@ -250,6 +290,6 @@ class MPTModel(LLModel):
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self.model = llmodel.llmodel_mpt_create()
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def __del__(self):
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if self.model is not None:
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if self.model is not None and llmodel is not None:
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llmodel.llmodel_mpt_destroy(self.model)
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super().__del__()
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