prompt formatting for together ai llama2 models

litellm/llms/huggingface_restapi.py

@@ -7,7 +7,7 @@ import time
 from typing import Callable
 from litellm.utils import ModelResponse
 from typing import Optional
-from .huggingface_model_prompt_templates.factory import prompt_factory, custom_prompt
+from .prompt_templates.factory import prompt_factory, custom_prompt
 
 class HuggingfaceError(Exception):
     def __init__(self, status_code, message):

litellm/llms/prompt_templates/factory.py

@@ -13,8 +13,18 @@ def llama_2_chat_pt(messages):
             prompt += message["content"] + "[/INST]"
     return prompt
 
-def llama_2_pt(messages):
-    return " ".join(message["content"] for message in messages)
+# TogetherAI Llama2 prompt template
+def togetherai_llama_2_chat_pt(messages):
+    prompt = "[INST]\n"
+    for message in messages:
+        if message["role"] == "system":
+            prompt += message["content"]
+        elif message["role"] == "assistant":
+            prompt += message["content"]
+        elif message["role"] == "user":
+            prompt += message["content"]
+    prompt += "\n[\INST]\n\n"
+    return prompt
 
 # Falcon prompt template - from https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py#L110
 def falcon_instruct_pt(messages):
@@ -77,21 +87,17 @@ def custom_prompt(role_dict: dict, pre_message_sep: str, post_message_sep: str,
 
 def prompt_factory(model: str, messages: list):
     model = model.lower()
-    if "bloom" in model:
-        return default_pt(messages=messages)
-    elif "flan-t5" in model:
-        return default_pt(messages=messages)
-    elif "meta-llama" in model:
+    if "meta-llama/Llama-2" in model:
         if "chat" in model:
             return llama_2_chat_pt(messages=messages)
         else:
             return default_pt(messages=messages)
-    elif "falcon" in model: # Note: for the instruct models, it's best to use a User: .., Assistant:.. approach in your prompt template.
+    elif "tiiuae/falcon" in model: # Note: for the instruct models, it's best to use a User: .., Assistant:.. approach in your prompt template.
         if "instruct" in model:
             return falcon_instruct_pt(messages=messages)
         else:
             return default_pt(messages=messages)
-    elif "mpt" in model:
+    elif "mosaicml/mpt" in model:
         if "chat" in model:
             return mpt_chat_pt(messages=messages)
         else:
@@ -101,9 +107,11 @@ def prompt_factory(model: str, messages: list):
             return llama_2_chat_pt(messages=messages) # https://huggingface.co/blog/codellama#conversational-instructions
         else:
             return default_pt(messages=messages)
-    elif "wizardcoder" in model:
+    elif "wizardlm/wizardcoder" in model:
         return wizardcoder_pt(messages=messages)
-    elif "phind-codellama" in model:
+    elif "phind/phind-codellama" in model:
         return phind_codellama_pt(messages=messages)
+    elif "togethercomputer/llama-2" in model:
+        return togetherai_llama_2_chat_pt(messages=messages)
     else:
         return default_pt(messages=messages)

litellm/llms/together_ai.py

@@ -5,6 +5,7 @@ import requests
 import time
 from typing import Callable
 from litellm.utils import ModelResponse
+from .prompt_templates.factory import prompt_factory, custom_prompt
 
 class TogetherAIError(Exception):
     def __init__(self, status_code, message):
@@ -34,21 +35,19 @@ def completion(
     encoding,
     api_key,
     logging_obj,
+    custom_prompt_dict={},
     optional_params=None,
     litellm_params=None,
     logger_fn=None,
 ):
     headers = validate_environment(api_key)
     model = model
-    prompt = ""
-    for message in messages:
-        if "role" in message:
-            if message["role"] == "user":
-                prompt += f"{message['content']}"
-            else:
-                prompt += f"{message['content']}"
-        else:
-            prompt += f"{message['content']}"
+    if model in custom_prompt_dict:
+        # check if the model has a registered custom prompt
+        model_prompt_details = custom_prompt_dict[model]
+        prompt = custom_prompt(role_dict=model_prompt_details["roles"], pre_message_sep=model_prompt_details["pre_message_sep"],  post_message_sep=model_prompt_details["post_message_sep"], messages=messages)
+    else:
+        prompt = prompt_factory(model=model, messages=messages)
     data = {
         "model": model,
         "prompt": prompt,

litellm/tests/test_completion.py

@@ -20,7 +20,7 @@ litellm.use_client = True
 # litellm.set_verbose = True
 # litellm.secret_manager_client = InfisicalClient(token=os.environ["INFISICAL_TOKEN"])
 
-user_message = "write me a function to print hello world in python"
+user_message = "Write a short poem about the sky"
 messages = [{"content": user_message, "role": "user"}]
 
 
@@ -390,12 +390,13 @@ def test_completion_replicate_stability():
 def test_completion_together_ai():
     model_name = "togethercomputer/llama-2-70b-chat"
     try:
-        response = completion(model=model_name, messages=messages)
+        response = completion(model=model_name, messages=messages, max_tokens=256, logger_fn=logger_fn)
         # Add any assertions here to check the response
         print(response)
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
 
+test_completion_together_ai()
 
 def test_completion_sagemaker():
     try: