(feat) maintain anthropic text completion

docs/my-website/docs/providers/anthropic.md

@@ -56,6 +56,7 @@ for chunk in response:
 | claude-2.1  | `completion('claude-2.1', messages)` | `os.environ['ANTHROPIC_API_KEY']`       |
 | claude-2  | `completion('claude-2', messages)` | `os.environ['ANTHROPIC_API_KEY']`       |
 | claude-instant-1.2  | `completion('claude-instant-1.2', messages)` | `os.environ['ANTHROPIC_API_KEY']`       |
+| claude-instant-1  | `completion('claude-instant-1', messages)` | `os.environ['ANTHROPIC_API_KEY']`       |
 
 ## Advanced
 

litellm/main.py

@@ -39,6 +39,7 @@ from litellm.utils import (
 )
 from .llms import (
     anthropic,
+    anthropic_text,
     together_ai,
     ai21,
     sagemaker,
@@ -1018,13 +1019,40 @@ def completion(
                 or litellm.api_key
                 or os.environ.get("ANTHROPIC_API_KEY")
             )
+            custom_prompt_dict = custom_prompt_dict or litellm.custom_prompt_dict
+
+            if (model == "claude-2") or (model == "claude-instant-1"):
+                # call anthropic /completion, only use this route for claude-2, claude-instant-1
+                api_base = (
+                    api_base
+                    or litellm.api_base
+                    or get_secret("ANTHROPIC_API_BASE")
+                    or "https://api.anthropic.com/v1/complete"
+                )
+                response = anthropic_text.completion(
+                    model=model,
+                    messages=messages,
+                    api_base=api_base,
+                    custom_prompt_dict=litellm.custom_prompt_dict,
+                    model_response=model_response,
+                    print_verbose=print_verbose,
+                    optional_params=optional_params,
+                    litellm_params=litellm_params,
+                    logger_fn=logger_fn,
+                    encoding=encoding,  # for calculating input/output tokens
+                    api_key=api_key,
+                    logging_obj=logging,
+                    headers=headers,
+                )
+            else:
+                # call /messages
+                # default route for all anthropic models
                 api_base = (
                     api_base
                     or litellm.api_base
                     or get_secret("ANTHROPIC_API_BASE")
                     or "https://api.anthropic.com/v1/messages"
                 )
-            custom_prompt_dict = custom_prompt_dict or litellm.custom_prompt_dict
                 response = anthropic.completion(
                     model=model,
                     messages=messages,

litellm/tests/test_completion.py

@@ -56,7 +56,7 @@ def test_completion_custom_provider_model_name():
 def test_completion_claude():
     litellm.set_verbose = True
     litellm.cache = None
-    litellm.AnthropicConfig(max_tokens=200, metadata={"user_id": "1224"})
+    litellm.AnthropicTextConfig(max_tokens_to_sample=200, metadata={"user_id": "1224"})
     messages = [
         {
             "role": "system",
@@ -67,9 +67,10 @@ def test_completion_claude():
     try:
         # test without max tokens
         response = completion(
-            model="claude-instant-1.2",
+            model="claude-instant-1",
             messages=messages,
             request_timeout=10,
+            max_tokens=10,
         )
         # Add any assertions, here to check response args
         print(response)

litellm/utils.py

@@ -4200,6 +4200,10 @@ def get_optional_params(
         if top_p is not None:
             optional_params["top_p"] = top_p
         if max_tokens is not None:
+            if (model == "claude-2") or (model == "claude-instant-1"):
+                # these models use antropic_text.py which only accepts max_tokens_to_sample
+                optional_params["max_tokens_to_sample"] = max_tokens
+            else:
                 optional_params["max_tokens"] = max_tokens
     elif custom_llm_provider == "cohere":
         ## check if unsupported param passed in