chore: initial snapshot for gitea/github upload

llm-gateway-competitors/litellm-wheel-src/litellm/router_utils/batch_utils.py

@@ -0,0 +1,150 @@
+import io
+import json
+from os import PathLike
+from typing import List, Optional
+
+from litellm._logging import verbose_logger
+from litellm.types.llms.openai import FileTypes, OpenAIFilesPurpose
+
+
+class InMemoryFile(io.BytesIO):
+    def __init__(
+        self, content: bytes, name: str, content_type: str = "application/jsonl"
+    ):
+        super().__init__(content)
+        self.name = name
+        self.content_type = content_type
+
+
+def parse_jsonl_with_embedded_newlines(content: str) -> List[dict]:
+    """
+    Parse JSONL content that may contain JSON objects with embedded newlines in string values.
+
+    Unlike splitlines(), this function properly handles cases where JSON string values
+    contain literal newline characters, which would otherwise break simple line-based parsing.
+
+    Args:
+        content: The JSONL file content as a string
+
+    Returns:
+        List of parsed JSON objects
+
+    Example:
+        >>> content = '{"id":1,"msg":"Line 1\\nLine 2"}\\n{"id":2,"msg":"test"}'
+        >>> parse_jsonl_with_embedded_newlines(content)
+        [{"id":1,"msg":"Line 1\\nLine 2"}, {"id":2,"msg":"test"}]
+    """
+    json_objects = []
+    buffer = ""
+
+    for char in content:
+        buffer += char
+        if char == "\n":
+            # Try to parse what we have so far
+            try:
+                json_object = json.loads(buffer.strip())
+                json_objects.append(json_object)
+                buffer = ""  # Reset buffer for next JSON object
+            except json.JSONDecodeError:
+                # Not a complete JSON object yet, keep accumulating
+                continue
+
+    # Handle any remaining content in buffer
+    if buffer.strip():
+        try:
+            json_object = json.loads(buffer.strip())
+            json_objects.append(json_object)
+        except json.JSONDecodeError as e:
+            verbose_logger.error(
+                f"error parsing final buffer: {buffer[:100]}..., error: {e}"
+            )
+            raise e
+
+    return json_objects
+
+
+def should_replace_model_in_jsonl(
+    purpose: OpenAIFilesPurpose,
+) -> bool:
+    """
+    Check if the model name should be replaced in the JSONL file for the deployment model name.
+
+    Azure raises an error on create batch if the model name for deployment is not in the .jsonl.
+    """
+    if purpose == "batch":
+        return True
+    return False
+
+
+def replace_model_in_jsonl(file_content: FileTypes, new_model_name: str) -> FileTypes:
+    try:
+        ## if pathlike, return the original file content
+        if isinstance(file_content, PathLike):
+            return file_content
+
+        # Decode the bytes to a string and split into lines
+        # If file_content is a file-like object, read the bytes
+        if hasattr(file_content, "read"):
+            file_content_bytes = file_content.read()  # type: ignore
+        elif isinstance(file_content, tuple):
+            file_content_bytes = file_content[1]
+        else:
+            file_content_bytes = file_content
+
+        # Decode the bytes to a string and split into lines
+        if isinstance(file_content_bytes, bytes):
+            file_content_str = file_content_bytes.decode("utf-8")
+        elif isinstance(file_content_bytes, str):
+            file_content_str = file_content_bytes
+        else:
+            return file_content
+
+        # Parse JSONL properly, handling potential multiline JSON objects
+        json_objects = parse_jsonl_with_embedded_newlines(file_content_str)
+
+        # If no valid JSON objects were found, return the original content
+        if len(json_objects) == 0:
+            return file_content
+
+        modified_lines = []
+        for json_object in json_objects:
+            # Replace the model name if it exists
+            if "body" in json_object:
+                json_object["body"]["model"] = new_model_name
+
+            # Convert the modified JSON object back to a string
+            modified_lines.append(json.dumps(json_object))
+
+        # Reassemble the modified lines and return as bytes
+        modified_file_content = "\n".join(modified_lines).encode("utf-8")
+
+        return InMemoryFile(modified_file_content, name="modified_file.jsonl", content_type="application/jsonl")  # type: ignore
+
+    except (json.JSONDecodeError, UnicodeDecodeError, TypeError):
+        # return the original file content if there is an error replacing the model name
+        return file_content
+
+
+def _get_router_metadata_variable_name(function_name: Optional[str]) -> str:
+    """
+    Helper to return what the "metadata" field should be called in the request data
+
+    For all /thread or /assistant endpoints we need to call this "litellm_metadata"
+
+    For ALL other endpoints we call this "metadata
+    """
+    ROUTER_METHODS_USING_LITELLM_METADATA = set(
+        [
+            "batch",
+            "generic_api_call",
+            "_acreate_batch",
+            "file",
+            "_ageneric_api_call_with_fallbacks",
+        ]
+    )
+    if function_name and any(
+        method in function_name for method in ROUTER_METHODS_USING_LITELLM_METADATA
+    ):
+        return "litellm_metadata"
+    else:
+        return "metadata"