two version of R2R are here HEAD master

1 files changed, 170 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/litellm/llms/custom_llm.py b/.venv/lib/python3.12/site-packages/litellm/llms/custom_llm.py
new file mode 100644
index 00000000..a2d04b18
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/litellm/llms/custom_llm.py
@@ -0,0 +1,170 @@
+# What is this?
+## Handler file for a Custom Chat LLM
+
+"""
+- completion
+- acompletion
+- streaming
+- async_streaming
+"""
+
+from typing import Any, AsyncIterator, Callable, Iterator, Optional, Union
+
+import httpx
+
+from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler
+from litellm.types.utils import GenericStreamingChunk
+from litellm.utils import ImageResponse, ModelResponse
+
+from .base import BaseLLM
+
+
+class CustomLLMError(Exception):  # use this for all your exceptions
+    def __init__(
+        self,
+        status_code,
+        message,
+    ):
+        self.status_code = status_code
+        self.message = message
+        super().__init__(
+            self.message
+        )  # Call the base class constructor with the parameters it needs
+
+
+class CustomLLM(BaseLLM):
+    def __init__(self) -> None:
+        super().__init__()
+
+    def completion(
+        self,
+        model: str,
+        messages: list,
+        api_base: str,
+        custom_prompt_dict: dict,
+        model_response: ModelResponse,
+        print_verbose: Callable,
+        encoding,
+        api_key,
+        logging_obj,
+        optional_params: dict,
+        acompletion=None,
+        litellm_params=None,
+        logger_fn=None,
+        headers={},
+        timeout: Optional[Union[float, httpx.Timeout]] = None,
+        client: Optional[HTTPHandler] = None,
+    ) -> ModelResponse:
+        raise CustomLLMError(status_code=500, message="Not implemented yet!")
+
+    def streaming(
+        self,
+        model: str,
+        messages: list,
+        api_base: str,
+        custom_prompt_dict: dict,
+        model_response: ModelResponse,
+        print_verbose: Callable,
+        encoding,
+        api_key,
+        logging_obj,
+        optional_params: dict,
+        acompletion=None,
+        litellm_params=None,
+        logger_fn=None,
+        headers={},
+        timeout: Optional[Union[float, httpx.Timeout]] = None,
+        client: Optional[HTTPHandler] = None,
+    ) -> Iterator[GenericStreamingChunk]:
+        raise CustomLLMError(status_code=500, message="Not implemented yet!")
+
+    async def acompletion(
+        self,
+        model: str,
+        messages: list,
+        api_base: str,
+        custom_prompt_dict: dict,
+        model_response: ModelResponse,
+        print_verbose: Callable,
+        encoding,
+        api_key,
+        logging_obj,
+        optional_params: dict,
+        acompletion=None,
+        litellm_params=None,
+        logger_fn=None,
+        headers={},
+        timeout: Optional[Union[float, httpx.Timeout]] = None,
+        client: Optional[AsyncHTTPHandler] = None,
+    ) -> ModelResponse:
+        raise CustomLLMError(status_code=500, message="Not implemented yet!")
+
+    async def astreaming(
+        self,
+        model: str,
+        messages: list,
+        api_base: str,
+        custom_prompt_dict: dict,
+        model_response: ModelResponse,
+        print_verbose: Callable,
+        encoding,
+        api_key,
+        logging_obj,
+        optional_params: dict,
+        acompletion=None,
+        litellm_params=None,
+        logger_fn=None,
+        headers={},
+        timeout: Optional[Union[float, httpx.Timeout]] = None,
+        client: Optional[AsyncHTTPHandler] = None,
+    ) -> AsyncIterator[GenericStreamingChunk]:
+        raise CustomLLMError(status_code=500, message="Not implemented yet!")
+
+    def image_generation(
+        self,
+        model: str,
+        prompt: str,
+        api_key: Optional[str],
+        api_base: Optional[str],
+        model_response: ImageResponse,
+        optional_params: dict,
+        logging_obj: Any,
+        timeout: Optional[Union[float, httpx.Timeout]] = None,
+        client: Optional[HTTPHandler] = None,
+    ) -> ImageResponse:
+        raise CustomLLMError(status_code=500, message="Not implemented yet!")
+
+    async def aimage_generation(
+        self,
+        model: str,
+        prompt: str,
+        model_response: ImageResponse,
+        api_key: Optional[
+            str
+        ],  # dynamically set api_key - https://docs.litellm.ai/docs/set_keys#api_key
+        api_base: Optional[
+            str
+        ],  # dynamically set api_base - https://docs.litellm.ai/docs/set_keys#api_base
+        optional_params: dict,
+        logging_obj: Any,
+        timeout: Optional[Union[float, httpx.Timeout]] = None,
+        client: Optional[AsyncHTTPHandler] = None,
+    ) -> ImageResponse:
+        raise CustomLLMError(status_code=500, message="Not implemented yet!")
+
+
+def custom_chat_llm_router(
+    async_fn: bool, stream: Optional[bool], custom_llm: CustomLLM
+):
+    """
+    Routes call to CustomLLM completion/acompletion/streaming/astreaming functions, based on call type
+
+    Validates if response is in expected format
+    """
+    if async_fn:
+        if stream:
+            return custom_llm.astreaming
+        return custom_llm.acompletion
+    if stream:
+        return custom_llm.streaming
+    return custom_llm.completion