fix replicate error

litellm/__init__.py

@@ -308,7 +308,7 @@ from .utils import (
     validate_environment,
     check_valid_key,
     get_llm_provider,
-    completion_with_config
+    completion_with_config,
 )
 from .main import *  # type: ignore
 from .integrations import *

litellm/llms/replicate.py

@@ -24,7 +24,6 @@ def start_prediction(version_id, input_data, api_token, logging_obj):
     initial_prediction_data = {
         "version": version_id,
         "input": input_data,
-        "max_new_tokens": 500,
     }
 
         ## LOGGING
@@ -109,18 +108,33 @@ def completion(
     litellm_params=None,
     logger_fn=None,
 ):
+    # Start a prediction and get the prediction URL
+    version_id = model_to_version_id(model)
+    if "meta/llama-2-13b-chat" in model: 
+        system_prompt = ""
+        prompt = "" 
+        for message in messages: 
+            if message["role"] == "system":
+                system_prompt = message["content"]
+            else: 
+                prompt += message["content"]
+        input_data = {
+            "system_prompt": system_prompt,
+            "prompt": prompt,
+            **optional_params
+        }
+    else:
         # Convert messages to prompt
         prompt = ""
         for message in messages:
             prompt += message["content"]
 
-    # Start a prediction and get the prediction URL
-    version_id = model_to_version_id(model)
         input_data = {
             "prompt": prompt,
             **optional_params
         }
 
+
     ## COMPLETION CALL
     ## Replicate Compeltion calls have 2 steps
     ## Step1: Start Prediction: gets a prediction url

litellm/utils.py

@@ -1016,7 +1016,7 @@ def get_optional_params(  # use the openai defaults
             optional_params["logit_bias"] = logit_bias
     elif custom_llm_provider == "replicate":
         ## check if unsupported param passed in 
-        supported_params = ["stream", "temperature", "max_tokens", "top_p", "stop"]
+        supported_params = ["stream", "temperature", "max_tokens", "top_p", "stop", "seed"]
         _check_valid_arg(supported_params=supported_params)
         
         if stream:
@@ -1025,6 +1025,8 @@ def get_optional_params(  # use the openai defaults
         if max_tokens:
             if "vicuna" in model or "flan" in model:
                 optional_params["max_length"] = max_tokens
+            elif "meta/codellama-13b" in model: 
+                optional_params["max_tokens"] = max_tokens
             else:
                 optional_params["max_new_tokens"] = max_tokens
         if temperature:
@@ -1289,7 +1291,6 @@ def get_llm_provider(model: str, custom_llm_provider: Optional[str] = None):
     except Exception as e: 
         raise e
 
-
 def get_api_key(llm_provider: str, dynamic_api_key: Optional[str]):
     api_key = (dynamic_api_key or litellm.api_key)
     # openai 

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "litellm"
-version = "0.1.813"
+version = "0.1.814"
 description = "Library to easily interface with LLM API providers"
 authors = ["BerriAI"]
 license = "MIT License"