remove gitignore

.venv/lib/python3.10/site-packages/litellm/llms/anthropic/batches/transformation.py

@@ -0,0 +1,76 @@
+import json
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, cast
+
+from httpx import Response
+
+from litellm.types.llms.openai import AllMessageValues
+from litellm.types.utils import ModelResponse
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+
+    LoggingClass = LiteLLMLoggingObj
+else:
+    LoggingClass = Any
+
+
+class AnthropicBatchesConfig:
+    def __init__(self):
+        from ..chat.transformation import AnthropicConfig
+
+        self.anthropic_chat_config = AnthropicConfig()  # initialize once
+
+    def transform_response(
+        self,
+        model: str,
+        raw_response: Response,
+        model_response: ModelResponse,
+        logging_obj: LoggingClass,
+        request_data: Dict,
+        messages: List[AllMessageValues],
+        optional_params: Dict,
+        litellm_params: dict,
+        encoding: Any,
+        api_key: Optional[str] = None,
+        json_mode: Optional[bool] = None,
+    ) -> ModelResponse:
+        from litellm.cost_calculator import BaseTokenUsageProcessor
+        from litellm.types.utils import Usage
+
+        response_text = raw_response.text.strip()
+        all_usage: List[Usage] = []
+
+        try:
+            # Split by newlines and try to parse each line as JSON
+            lines = response_text.split("\n")
+            for line in lines:
+                line = line.strip()
+                if not line:
+                    continue
+                try:
+                    response_json = json.loads(line)
+                    # Update model_response with the parsed JSON
+                    completion_response = response_json["result"]["message"]
+                    transformed_response = (
+                        self.anthropic_chat_config.transform_parsed_response(
+                            completion_response=completion_response,
+                            raw_response=raw_response,
+                            model_response=model_response,
+                        )
+                    )
+
+                    transformed_response_usage = getattr(
+                        transformed_response, "usage", None
+                    )
+                    if transformed_response_usage:
+                        all_usage.append(cast(Usage, transformed_response_usage))
+                except json.JSONDecodeError:
+                    continue
+
+            ## SUM ALL USAGE
+            combined_usage = BaseTokenUsageProcessor.combine_usage_objects(all_usage)
+            setattr(model_response, "usage", combined_usage)
+
+            return model_response
+        except Exception as e:
+            raise e