Separated llms from the main llm.py file and fixed some deprication bugs

2025-01-25 00:11:00 +01:00
parent 7e1638525c
commit 34018cb1e0
55 changed files with 2144 additions and 1301 deletions
--- a/lightrag/llm/nvidia_openai.py
+++ b/lightrag/llm/nvidia_openai.py
@@ -0,0 +1,112 @@
+"""
+OpenAI LLM Interface Module
+==========================
+
+This module provides interfaces for interacting with openai's language models,
+including text generation and embedding capabilities.
+
+Author: Lightrag team
+Created: 2024-01-24
+License: MIT License
+
+Copyright (c) 2024 Lightrag
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+Version: 1.0.0
+
+Change Log:
+- 1.0.0 (2024-01-24): Initial release
+    * Added async chat completion support
+    * Added embedding generation
+    * Added stream response capability
+
+Dependencies:
+    - openai
+    - numpy
+    - pipmaster
+    - Python >= 3.10
+
+Usage:
+    from llm_interfaces.nvidia_openai import nvidia_openai_model_complete, nvidia_openai_embed
+"""
+
+__version__ = "1.0.0"
+__author__ = "lightrag Team"
+__status__ = "Production"
+
+
+
+import sys
+import os
+
+if sys.version_info < (3, 9):
+    from typing import AsyncIterator
+else:
+    from collections.abc import AsyncIterator
+import pipmaster as pm # Pipmaster for dynamic library install
+
+# install specific modules
+if not pm.is_installed("openai"):
+    pm.install("openai")
+
+from openai import (
+    AsyncOpenAI,
+    APIConnectionError,
+    RateLimitError,
+    APITimeoutError,
+)
+from tenacity import (
+    retry,
+    stop_after_attempt,
+    wait_exponential,
+    retry_if_exception_type,
+)
+
+from lightrag.utils import (
+    wrap_embedding_func_with_attrs,
+    locate_json_string_body_from_string,
+    safe_unicode_decode,
+    logger,
+)
+
+from lightrag.types import GPTKeywordExtractionFormat
+
+import numpy as np
+
+@wrap_embedding_func_with_attrs(embedding_dim=2048, max_token_size=512)
+@retry(
+    stop=stop_after_attempt(3),
+    wait=wait_exponential(multiplier=1, min=4, max=60),
+    retry=retry_if_exception_type(
+        (RateLimitError, APIConnectionError, APITimeoutError)
+    ),
+)
+async def nvidia_openai_embed(
+    texts: list[str],
+    model: str = "nvidia/llama-3.2-nv-embedqa-1b-v1",
+    # refer to https://build.nvidia.com/nim?filters=usecase%3Ausecase_text_to_embedding
+    base_url: str = "https://integrate.api.nvidia.com/v1",
+    api_key: str = None,
+    input_type: str = "passage",  # query for retrieval, passage for embedding
+    trunc: str = "NONE",  # NONE or START or END
+    encode: str = "float",  # float or base64
+) -> np.ndarray:
+    if api_key:
+        os.environ["OPENAI_API_KEY"] = api_key
+
+    openai_async_client = (
+        AsyncOpenAI() if base_url is None else AsyncOpenAI(base_url=base_url)
+    )
+    response = await openai_async_client.embeddings.create(
+        model=model,
+        input=texts,
+        encoding_format=encode,
+        extra_body={"input_type": input_type, "truncate": trunc},
+    )
+    return np.array([dp.embedding for dp in response.data])