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gpt4all-bindings/python/gpt4all/__init__.py

@@ -1,2 +1,2 @@
-from .gpt4all import GPT4All, Embed4All  # noqa
+from .gpt4all import Embed4All, GPT4All  # noqa
 from .pyllmodel import LLModel  # noqa

gpt4all-bindings/python/gpt4all/gpt4all.py

@@ -5,7 +5,7 @@ import os
 import time
 from contextlib import contextmanager
 from pathlib import Path
-from typing import Any, Dict, Iterable, List, Union, Optional
+from typing import Any, Dict, Iterable, List, Optional, Union
 
 import requests
 from tqdm import tqdm
@@ -13,22 +13,22 @@ from tqdm import tqdm
 from . import pyllmodel
 
 # TODO: move to config
-DEFAULT_MODEL_DIRECTORY = os.path.join(str(Path.home()), ".cache", "gpt4all").replace(
-    "\\", "\\\\"
-)
+DEFAULT_MODEL_DIRECTORY = os.path.join(str(Path.home()), ".cache", "gpt4all").replace("\\", "\\\\")
 
 DEFAULT_MODEL_CONFIG = {
     "systemPrompt": "",
     "promptTemplate": "### Human: \n{0}\n### Assistant:\n",
 }
 
-ConfigType = Dict[str,str]
+ConfigType = Dict[str, str]
 MessageType = Dict[str, str]
 
+
 class Embed4All:
     """
     Python class that handles embeddings for GPT4All.
     """
+
     def __init__(
         self,
         n_threads: Optional[int] = None,
@@ -41,10 +41,7 @@ class Embed4All:
         """
         self.gpt4all = GPT4All(model_name='ggml-all-MiniLM-L6-v2-f16.bin', n_threads=n_threads)
 
-    def embed(
-        self,
-        text: str
-    ) -> List[float]:
+    def embed(self, text: str) -> List[float]:
         """
         Generate an embedding.
 
@@ -56,6 +53,7 @@ class Embed4All:
         """
         return self.gpt4all.model.generate_embedding(text)
 
+
 class GPT4All:
     """
     Python class that handles instantiation, downloading, generation and chat with GPT4All models.
@@ -84,9 +82,7 @@ class GPT4All:
         self.model_type = model_type
         self.model = pyllmodel.LLModel()
         # Retrieve model and download if allowed
-        self.config: ConfigType = self.retrieve_model(
-            model_name, model_path=model_path, allow_download=allow_download
-        )
+        self.config: ConfigType = self.retrieve_model(model_name, model_path=model_path, allow_download=allow_download)
         self.model.load_model(self.config["path"])
         # Set n_threads
         if n_threads is not None:
@@ -170,9 +166,7 @@ class GPT4All:
         elif allow_download:
             url = config.pop("url", None)
 
-            config["path"] = GPT4All.download_model(
-                model_filename, model_path, verbose=verbose, url=url
-            )
+            config["path"] = GPT4All.download_model(model_filename, model_path, verbose=verbose, url=url)
         else:
             raise ValueError("Failed to retrieve model")
 
@@ -281,19 +275,24 @@ class GPT4All:
         )
 
         if self._is_chat_session_activated:
-            generate_kwargs["reset_context"] = len(self.current_chat_session) == 1 # check if there is only one message, i.e. system prompt
+            # check if there is only one message, i.e. system prompt:
+            generate_kwargs["reset_context"] = len(self.current_chat_session) == 1
             self.current_chat_session.append({"role": "user", "content": prompt})
 
             prompt = self._format_chat_prompt_template(
-                messages = self.current_chat_session[-1:],
-                default_prompt_header = self.current_chat_session[0]["content"] if generate_kwargs["reset_context"] else "",
+                messages=self.current_chat_session[-1:],
+                default_prompt_header=self.current_chat_session[0]["content"]
+                if generate_kwargs["reset_context"]
+                else "",
             )
         else:
             generate_kwargs["reset_context"] = True
 
         # Prepare the callback, process the model response
         output_collector: List[MessageType]
-        output_collector = [{"content": ""}]  # placeholder for the self.current_chat_session if chat session is not activated
+        output_collector = [
+            {"content": ""}
+        ]  # placeholder for the self.current_chat_session if chat session is not activated
 
         if self._is_chat_session_activated:
             self.current_chat_session.append({"role": "assistant", "content": ""})

gpt4all-bindings/python/gpt4all/pyllmodel.py

@@ -1,4 +1,5 @@
 import ctypes
+import logging
 import os
 import platform
 from queue import Queue
@@ -6,8 +7,7 @@ import re
 import subprocess
 import sys
 import threading
-import logging
-from typing import Iterable, Callable, List
+from typing import Callable, Iterable, List
 
 import pkg_resources
 
@@ -16,9 +16,7 @@ logger: logging.Logger = logging.getLogger(__name__)
 
 # TODO: provide a config file to make this more robust
 LLMODEL_PATH = os.path.join("llmodel_DO_NOT_MODIFY", "build").replace("\\", "\\\\")
-MODEL_LIB_PATH = str(pkg_resources.resource_filename("gpt4all", LLMODEL_PATH)).replace(
-    "\\", "\\\\"
-)
+MODEL_LIB_PATH = str(pkg_resources.resource_filename("gpt4all", LLMODEL_PATH)).replace("\\", "\\\\")
 
 
 def load_llmodel_library():
@@ -113,9 +111,7 @@ llmodel.llmodel_embedding.argtypes = [
 
 llmodel.llmodel_embedding.restype = ctypes.POINTER(ctypes.c_float)
 
-llmodel.llmodel_free_embedding.argtypes = [
-    ctypes.POINTER(ctypes.c_float)
-]
+llmodel.llmodel_free_embedding.argtypes = [ctypes.POINTER(ctypes.c_float)]
 llmodel.llmodel_free_embedding.restype = None
 
 llmodel.llmodel_setThreadCount.argtypes = [ctypes.c_void_p, ctypes.c_int32]
@@ -251,10 +247,7 @@ class LLModel:
         self.context.repeat_last_n = repeat_last_n
         self.context.context_erase = context_erase
 
-    def generate_embedding(
-        self,
-        text: str
-    ) -> List[float]:
+    def generate_embedding(self, text: str) -> List[float]:
         if not text:
             raise ValueError("Text must not be None or empty")
 
@@ -330,10 +323,7 @@ class LLModel:
 
 
     def prompt_model_streaming(
-        self,
-        prompt: str,
-        callback: ResponseCallbackType = empty_response_callback,
-        **kwargs
+        self, prompt: str, callback: ResponseCallbackType = empty_response_callback, **kwargs
     ) -> Iterable[str]:
         # Symbol to terminate from generator
         TERMINATING_SYMBOL = object()
@@ -361,10 +351,7 @@ class LLModel:
         # immediately
         thread = threading.Thread(
             target=run_llmodel_prompt,
-            args=(
-                prompt, 
-                _generator_callback_wrapper(callback)
-            ),
+            args=(prompt, _generator_callback_wrapper(callback)),
             kwargs=kwargs,
         )
         thread.start()

gpt4all-bindings/python/gpt4all/tests/test_embed_timings.py

@@ -1,8 +1,9 @@
 import sys
+import time
 from io import StringIO
 
-from gpt4all import GPT4All, Embed4All
-import time
+from gpt4all import Embed4All, GPT4All
+
 
 def time_embedding(i, embedder):
     text = 'foo bar ' * i
@@ -12,6 +13,7 @@ def time_embedding(i, embedder):
     elapsed_time = end_time - start_time
     print(f"Time report: {2 * i / elapsed_time} tokens/second with {2 * i} tokens taking {elapsed_time} seconds")
 
+
 if __name__ == "__main__":
     embedder = Embed4All(n_threads=8)
     for i in [2**n for n in range(6, 14)]:

gpt4all-bindings/python/gpt4all/tests/test_gpt4all.py

@@ -6,6 +6,7 @@ from gpt4all import GPT4All, Embed4All
 import time
 import pytest
 
+
 def test_inference():
     model = GPT4All(model_name='orca-mini-3b.ggmlv3.q4_0.bin')
     output_1 = model.generate('hello', top_k=1)
@@ -102,6 +103,7 @@ def test_inference_mpt():
     assert isinstance(output, str)
     assert len(output) > 0
 
+
 def test_embedding():
     text = 'The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox jumps over the lazy dog The quick brown fox'
     embedder = Embed4All()
@@ -110,6 +112,7 @@ def test_embedding():
         #print(f'Value at index {i}: {value}')
     assert len(output) == 384
 
+
 def test_empty_embedding():
     text = ''
     embedder = Embed4All()