two version of R2R are here HEAD master

1 files changed, 149 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/litellm/llms/vertex_ai/vertex_model_garden/main.py b/.venv/lib/python3.12/site-packages/litellm/llms/vertex_ai/vertex_model_garden/main.py
new file mode 100644
index 00000000..7b54d4e3
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/litellm/llms/vertex_ai/vertex_model_garden/main.py
@@ -0,0 +1,149 @@
+"""
+API Handler for calling Vertex AI Model Garden Models
+
+Most Vertex Model Garden Models are OpenAI compatible - so this handler calls `openai_like_chat_completions`
+
+Usage:
+
+response = litellm.completion(
+    model="vertex_ai/openai/5464397967697903616",
+    messages=[{"role": "user", "content": "Hello, how are you?"}],
+)
+
+Sent to this route when `model` is in the format `vertex_ai/openai/{MODEL_ID}`
+
+
+Vertex Documentation for using the OpenAI /chat/completions endpoint: https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/community/model_garden/model_garden_pytorch_llama3_deployment.ipynb
+"""
+
+from typing import Callable, Optional, Union
+
+import httpx  # type: ignore
+
+from litellm.utils import ModelResponse
+
+from ..common_utils import VertexAIError
+from ..vertex_llm_base import VertexBase
+
+
+def create_vertex_url(
+    vertex_location: str,
+    vertex_project: str,
+    stream: Optional[bool],
+    model: str,
+    api_base: Optional[str] = None,
+) -> str:
+    """Return the base url for the vertex garden models"""
+    #  f"https://{self.endpoint.location}-aiplatform.googleapis.com/v1beta1/projects/{PROJECT_ID}/locations/{self.endpoint.location}"
+    return f"https://{vertex_location}-aiplatform.googleapis.com/v1beta1/projects/{vertex_project}/locations/{vertex_location}/endpoints/{model}"
+
+
+class VertexAIModelGardenModels(VertexBase):
+    def __init__(self) -> None:
+        pass
+
+    def completion(
+        self,
+        model: str,
+        messages: list,
+        model_response: ModelResponse,
+        print_verbose: Callable,
+        encoding,
+        logging_obj,
+        api_base: Optional[str],
+        optional_params: dict,
+        custom_prompt_dict: dict,
+        headers: Optional[dict],
+        timeout: Union[float, httpx.Timeout],
+        litellm_params: dict,
+        vertex_project=None,
+        vertex_location=None,
+        vertex_credentials=None,
+        logger_fn=None,
+        acompletion: bool = False,
+        client=None,
+    ):
+        """
+        Handles calling Vertex AI Model Garden Models in OpenAI compatible format
+
+        Sent to this route when `model` is in the format `vertex_ai/openai/{MODEL_ID}`
+        """
+        try:
+            import vertexai
+
+            from litellm.llms.openai_like.chat.handler import OpenAILikeChatHandler
+            from litellm.llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import (
+                VertexLLM,
+            )
+        except Exception as e:
+
+            raise VertexAIError(
+                status_code=400,
+                message=f"""vertexai import failed please run `pip install -U "google-cloud-aiplatform>=1.38"`. Got error: {e}""",
+            )
+
+        if not (
+            hasattr(vertexai, "preview") or hasattr(vertexai.preview, "language_models")
+        ):
+            raise VertexAIError(
+                status_code=400,
+                message="""Upgrade vertex ai. Run `pip install "google-cloud-aiplatform>=1.38"`""",
+            )
+        try:
+            model = model.replace("openai/", "")
+            vertex_httpx_logic = VertexLLM()
+
+            access_token, project_id = vertex_httpx_logic._ensure_access_token(
+                credentials=vertex_credentials,
+                project_id=vertex_project,
+                custom_llm_provider="vertex_ai",
+            )
+
+            openai_like_chat_completions = OpenAILikeChatHandler()
+
+            ## CONSTRUCT API BASE
+            stream: bool = optional_params.get("stream", False) or False
+            optional_params["stream"] = stream
+            default_api_base = create_vertex_url(
+                vertex_location=vertex_location or "us-central1",
+                vertex_project=vertex_project or project_id,
+                stream=stream,
+                model=model,
+            )
+
+            if len(default_api_base.split(":")) > 1:
+                endpoint = default_api_base.split(":")[-1]
+            else:
+                endpoint = ""
+
+            _, api_base = self._check_custom_proxy(
+                api_base=api_base,
+                custom_llm_provider="vertex_ai",
+                gemini_api_key=None,
+                endpoint=endpoint,
+                stream=stream,
+                auth_header=None,
+                url=default_api_base,
+            )
+            model = ""
+            return openai_like_chat_completions.completion(
+                model=model,
+                messages=messages,
+                api_base=api_base,
+                api_key=access_token,
+                custom_prompt_dict=custom_prompt_dict,
+                model_response=model_response,
+                print_verbose=print_verbose,
+                logging_obj=logging_obj,
+                optional_params=optional_params,
+                acompletion=acompletion,
+                litellm_params=litellm_params,
+                logger_fn=logger_fn,
+                client=client,
+                timeout=timeout,
+                encoding=encoding,
+                custom_llm_provider="vertex_ai",
+            )
+
+        except Exception as e:
+            raise VertexAIError(status_code=500, message=str(e))