[Feat] Support for all litellm providers on Responses API (works with Codex) - Anthropic, Bedrock API, VertexAI, Ollama (#10132)

* transform request

* basic handler for LiteLLMCompletionTransformationHandler

* complete transform litellm to responses api

* fixes to test

* fix stream=True

* fix streaming iterator

* fixes for transformation

* fixes for anthropic codex support

* fix pass response_api_optional_params

* test anthropic responses api tools

* update responses types

* working codex with litellm

* add session handler

* fixes streaming iterator

* fix handler

* add litellm codex example

* fix code quality

* test fix

* docs litellm codex

* litellm codexdoc

* docs openai codex with litellm

* docs litellm openai codex

* litellm codex

* linting fixes for transforming responses API

* fix import error

* fix responses api test

* add sync iterator support for responses api

litellm/responses/litellm_completion_transformation/session_handler.py

@@ -0,0 +1,59 @@
+"""
+Responses API has previous_response_id, which is the id of the previous response.
+
+LiteLLM needs to maintain a cache of the previous response input, output, previous_response_id, and model.
+
+This class handles that cache.
+"""
+
+from typing import List, Optional, Tuple, Union
+
+from typing_extensions import TypedDict
+
+from litellm.caching import InMemoryCache
+from litellm.types.llms.openai import ResponseInputParam, ResponsesAPIResponse
+
+RESPONSES_API_PREVIOUS_RESPONSES_CACHE = InMemoryCache()
+MAX_PREV_SESSION_INPUTS = 50
+
+
+class ResponsesAPISessionElement(TypedDict, total=False):
+    input: Union[str, ResponseInputParam]
+    output: ResponsesAPIResponse
+    response_id: str
+    previous_response_id: Optional[str]
+
+
+class SessionHandler:
+
+    def add_completed_response_to_cache(
+        self, response_id: str, session_element: ResponsesAPISessionElement
+    ):
+        RESPONSES_API_PREVIOUS_RESPONSES_CACHE.set_cache(
+            key=response_id, value=session_element
+        )
+
+    def get_chain_of_previous_input_output_pairs(
+        self, previous_response_id: str
+    ) -> List[Tuple[ResponseInputParam, ResponsesAPIResponse]]:
+        response_api_inputs: List[Tuple[ResponseInputParam, ResponsesAPIResponse]] = []
+        current_previous_response_id = previous_response_id
+
+        count_session_elements = 0
+        while current_previous_response_id:
+            if count_session_elements > MAX_PREV_SESSION_INPUTS:
+                break
+            session_element = RESPONSES_API_PREVIOUS_RESPONSES_CACHE.get_cache(
+                key=current_previous_response_id
+            )
+            if session_element:
+                response_api_inputs.append(
+                    (session_element.get("input"), session_element.get("output"))
+                )
+                current_previous_response_id = session_element.get(
+                    "previous_response_id"
+                )
+            else:
+                break
+            count_session_elements += 1
+        return response_api_inputs