Applied latest Black

llm_gpt4all.py

@@ -35,10 +35,13 @@ def retrieve_model(
         verbose: bool = False,
     ) -> str:
         try:
-            return _GPT4All.retrieve_model(model_name, model_path, allow_download, verbose)
+            return _GPT4All.retrieve_model(
+                model_name, model_path, allow_download, verbose
+            )
         except requests.exceptions.ConnectionError:
-            return _GPT4All.retrieve_model(model_name, model_path, allow_download=False, verbose=verbose)
-
+            return _GPT4All.retrieve_model(
+                model_name, model_path, allow_download=False, verbose=verbose
+            )
 
 
 def get_gpt4all_models():
@@ -73,22 +76,28 @@ class Options(llm.Options):
             description="The maximum number of tokens to generate.", default=200
         )
         temp: float = Field(
-            description="The model temperature. Larger values increase creativity but decrease factuality.", default=0.7
+            description="The model temperature. Larger values increase creativity but decrease factuality.",
+            default=0.7,
         )
         top_k: int = Field(
-            description="Randomly sample from the top_k most likely tokens at each generation step. Set this to 1 for greedy decoding.", default=40
+            description="Randomly sample from the top_k most likely tokens at each generation step. Set this to 1 for greedy decoding.",
+            default=40,
         )
         top_p: float = Field(
-            description="Randomly sample at each generation step from the top most likely tokens whose probabilities add up to top_p.", default=0.4
+            description="Randomly sample at each generation step from the top most likely tokens whose probabilities add up to top_p.",
+            default=0.4,
         )
         repeat_penalty: float = Field(
-            description="Penalize the model for repetition. Higher values result in less repetition.", default=1.18
+            description="Penalize the model for repetition. Higher values result in less repetition.",
+            default=1.18,
         )
         repeat_last_n: int = Field(
-            description="How far in the models generation history to apply the repeat penalty.", default=64
+            description="How far in the models generation history to apply the repeat penalty.",
+            default=64,
         )
         n_batch: int = Field(
-            description="Number of prompt tokens processed in parallel. Larger values decrease latency but increase resource requirements.", default=8
+            description="Number of prompt tokens processed in parallel. Larger values decrease latency but increase resource requirements.",
+            default=8,
         )
 
     def __init__(self, details):
@@ -158,13 +167,13 @@ def execute(self, prompt, stream, response, conversation):
             output = gpt_model.generate(
                 text_prompt,
                 streaming=True,
-                max_tokens = prompt.options.max_tokens or 400,
-                temp = prompt.options.temp,
-                top_k = prompt.options.top_k,
-                top_p = prompt.options.top_p,
-                repeat_penalty = prompt.options.repeat_penalty,
-                repeat_last_n = prompt.options.repeat_last_n,
-                n_batch = prompt.options.n_batch,
+                max_tokens=prompt.options.max_tokens or 400,
+                temp=prompt.options.temp,
+                top_k=prompt.options.top_k,
+                top_p=prompt.options.top_p,
+                repeat_penalty=prompt.options.repeat_penalty,
+                repeat_last_n=prompt.options.repeat_last_n,
+                n_batch=prompt.options.n_batch,
             )
             yield from output