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https://github.com/BerriAI/litellm.git
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d57be47b0f
* ci(config.yml): add a 'check_code_quality' step Addresses https://github.com/BerriAI/litellm/issues/5991 * ci(config.yml): check why circle ci doesn't pick up this test * ci(config.yml): fix to run 'check_code_quality' tests * fix(__init__.py): fix unprotected import * fix(__init__.py): don't remove unused imports * build(ruff.toml): update ruff.toml to ignore unused imports * fix: fix: ruff + pyright - fix linting + type-checking errors * fix: fix linting errors * fix(lago.py): fix module init error * fix: fix linting errors * ci(config.yml): cd into correct dir for checks * fix(proxy_server.py): fix linting error * fix(utils.py): fix bare except causes ruff linting errors * fix: ruff - fix remaining linting errors * fix(clickhouse.py): use standard logging object * fix(__init__.py): fix unprotected import * fix: ruff - fix linting errors * fix: fix linting errors * ci(config.yml): cleanup code qa step (formatting handled in local_testing) * fix(_health_endpoints.py): fix ruff linting errors * ci(config.yml): just use ruff in check_code_quality pipeline for now * build(custom_guardrail.py): include missing file * style(embedding_handler.py): fix ruff check
62 lines
2.1 KiB
Python
62 lines
2.1 KiB
Python
import io
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import json
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from typing import IO, Optional, Tuple, Union
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class InMemoryFile(io.BytesIO):
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def __init__(self, content: bytes, name: str):
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super().__init__(content)
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self.name = name
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def replace_model_in_jsonl(
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file_content: Union[bytes, Tuple[str, bytes, str]], new_model_name: str
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) -> Optional[InMemoryFile]:
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try:
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# Decode the bytes to a string and split into lines
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# If file_content is a file-like object, read the bytes
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if hasattr(file_content, "read"):
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file_content_bytes = file_content.read() # type: ignore
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elif isinstance(file_content, tuple):
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file_content_bytes = file_content[1]
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else:
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file_content_bytes = file_content
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# Decode the bytes to a string and split into lines
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if isinstance(file_content_bytes, bytes):
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file_content_str = file_content_bytes.decode("utf-8")
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else:
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file_content_str = file_content_bytes
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lines = file_content_str.splitlines()
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modified_lines = []
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for line in lines:
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# Parse each line as a JSON object
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json_object = json.loads(line.strip())
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# Replace the model name if it exists
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if "body" in json_object:
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json_object["body"]["model"] = new_model_name
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# Convert the modified JSON object back to a string
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modified_lines.append(json.dumps(json_object))
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# Reassemble the modified lines and return as bytes
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modified_file_content = "\n".join(modified_lines).encode("utf-8")
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return InMemoryFile(modified_file_content, name="modified_file.jsonl") # type: ignore
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except (json.JSONDecodeError, UnicodeDecodeError, TypeError):
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return None
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def _get_router_metadata_variable_name(function_name) -> str:
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"""
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Helper to return what the "metadata" field should be called in the request data
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For all /thread or /assistant endpoints we need to call this "litellm_metadata"
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For ALL other endpoints we call this "metadata
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"""
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if "batch" in function_name:
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return "litellm_metadata"
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else:
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return "metadata"
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