add beta deep infra support

litellm/__init__.py

@@ -241,6 +241,7 @@ provider_list: List = [
     "petals",
     "oobabooga",
     "ollama",
+    "deepinfra",
     "custom", # custom apis
 ]
 

litellm/main.py

@@ -663,6 +663,48 @@ def completion(
                 response = CustomStreamWrapper(model_response, model, custom_llm_provider="cohere", logging_obj=logging)
                 return response
             response = model_response
+        elif custom_llm_provider == "deepinfra": # for know this NEEDS to be above Hugging Face otherwise all calls to meta-llama/Llama-2-70b-chat-hf go to hf, we need this to go to deep infra if user sets provider to deep infra 
+            # this can be called with the openai python package
+            api_key = (
+                api_key or
+                litellm.api_key or
+                litellm.openai_key or
+                get_secret("DEEPINFRA_API_KEY")
+            )
+            ## LOGGING
+            logging.pre_call(
+                input=messages,
+                api_key=api_key,
+            )
+            ## COMPLETION CALL
+            openai.api_key = api_key # set key for deep infra 
+            try:
+                response = openai.ChatCompletion.create(
+                    model=model,
+                    messages=messages,
+                    api_base="https://api.deepinfra.com/v1/openai", # use the deepinfra api base
+                    api_type="openai",
+                    api_version=api_version, # default None
+                    **optional_params,
+                )
+            except Exception as e:
+                ## LOGGING - log the original exception returned
+                logging.post_call(
+                    input=messages,
+                    api_key=api_key,
+                    original_response=str(e),
+                )
+                raise e
+            if "stream" in optional_params and optional_params["stream"] == True:
+                response = CustomStreamWrapper(response, model, custom_llm_provider="openai", logging_obj=logging)
+                return response
+            ## LOGGING
+            logging.post_call(
+                input=messages,
+                api_key=api_key,
+                original_response=response,
+                additional_args={"headers": litellm.headers},
+            )
         elif (
             (
                 model in litellm.huggingface_models and 

litellm/tests/test_completion.py

@@ -48,7 +48,7 @@ def test_completion_claude():
         print(response.response_ms)
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
-test_completion_claude()
+# test_completion_claude()
 
 def test_completion_claude_max_tokens():
     try:
@@ -67,7 +67,7 @@ def test_completion_claude_max_tokens():
         print(response.response_ms)
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
-test_completion_claude_max_tokens()
+# test_completion_claude_max_tokens()
 
 # def test_completion_oobabooga():
 #     try:
@@ -854,6 +854,19 @@ def test_completion_ai21():
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
 
+
+## test deep infra 
+def test_completion_deep_infra():
+    # litellm.set_verbose = True
+    model_name = "deepinfra/meta-llama/Llama-2-70b-chat-hf"
+    try:
+        response = completion(model=model_name, messages=messages)
+        # Add any assertions here to check the response
+        print(response)
+        print(response.response_ms)
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+# test_completion_deep_infra()
 # test_completion_ai21()
 # test config file with completion #
 # def test_completion_openai_config():