style(test_completion.py): fix merge conflict

litellm/llms/replicate.py

@@ -1,9 +1,10 @@
-import os
+import os, types
 import json
 import requests
 import time
-from typing import Callable
+from typing import Callable, Optional
 from litellm.utils import ModelResponse
+import litellm 
 
 class ReplicateError(Exception):
     def __init__(self, status_code, message):
@@ -13,6 +14,65 @@ class ReplicateError(Exception):
             self.message
         )  # Call the base class constructor with the parameters it needs
 
+class ReplicateConfig(): 
+    """
+    Reference: https://replicate.com/meta/llama-2-70b-chat/api
+    - `prompt` (string): The prompt to send to the model.
+        
+    - `system_prompt` (string): The system prompt to send to the model. This is prepended to the prompt and helps guide system behavior. Default value: `You are a helpful assistant`.
+        
+    - `max_new_tokens` (integer): Maximum number of tokens to generate. Typically, a word is made up of 2-3 tokens. Default value: `128`.
+        
+    - `min_new_tokens` (integer): Minimum number of tokens to generate. To disable, set to `-1`. A word is usually 2-3 tokens. Default value: `-1`.
+        
+    - `temperature` (number): Adjusts the randomness of outputs. Values greater than 1 increase randomness, 0 is deterministic, and 0.75 is a reasonable starting value. Default value: `0.75`.
+        
+    - `top_p` (number): During text decoding, it samples from the top `p` percentage of most likely tokens. Reduce this to ignore less probable tokens. Default value: `0.9`.
+        
+    - `top_k` (integer): During text decoding, samples from the top `k` most likely tokens. Reduce this to ignore less probable tokens. Default value: `50`.
+    
+    - `stop_sequences` (string): A comma-separated list of sequences to stop generation at. For example, inputting '<end>,<stop>' will cease generation at the first occurrence of either 'end' or '<stop>'.
+        
+    - `seed` (integer): This is the seed for the random generator. Leave it blank to randomize the seed.
+        
+    - `debug` (boolean): If set to `True`, it provides debugging output in logs.
+
+    Please note that Replicate's mapping of these parameters can be inconsistent across different models, indicating that not all of these parameters may be available for use with all models.
+    """
+    system_prompt: Optional[str]=None
+    max_new_tokens: Optional[int]=None
+    min_new_tokens: Optional[int]=None
+    temperature: Optional[int]=None
+    top_p: Optional[int]=None
+    top_k: Optional[int]=None
+    stop_sequences: Optional[str]=None
+    seed: Optional[int]=None
+    debug: Optional[bool]=None
+
+    def __init__(self,
+                 system_prompt: Optional[str]=None,
+                 max_new_tokens: Optional[int]=None,
+                 min_new_tokens: Optional[int]=None,
+                 temperature: Optional[int]=None,
+                 top_p: Optional[int]=None,
+                 top_k: Optional[int]=None,
+                 stop_sequences: Optional[str]=None,
+                 seed: Optional[int]=None,
+                 debug: Optional[bool]=None) -> None:
+        locals_ = locals()
+        for key, value in locals_.items():
+            if key != 'self' and value is not None:
+                setattr(self.__class__, key, value)
+    
+    @classmethod
+    def get_config(cls):
+        return {k: v for k, v in cls.__dict__.items() 
+                if not k.startswith('__') 
+                and not isinstance(v, (types.FunctionType, types.BuiltinFunctionType, classmethod, staticmethod)) 
+                and v is not None}
+
+
+
 # Function to start a prediction and get the prediction URL
 def start_prediction(version_id, input_data, api_token, logging_obj):
     base_url = "https://api.replicate.com/v1"
@@ -110,6 +170,13 @@ def completion(
 ):
     # Start a prediction and get the prediction URL
     version_id = model_to_version_id(model)
+
+    ## Load Config
+    config = litellm.ReplicateConfig.get_config() 
+    for k, v in config.items(): 
+        if k not in optional_params: # completion(top_k=3) > replicate_config(top_k=3) <- allows for dynamic variables to be passed in
+            optional_params[k] = v
+
     if "meta/llama-2-13b-chat" in model: 
         system_prompt = ""
         prompt = ""