From 82bcd2e663b40f0144489a7f1b57a256b0d267b0 Mon Sep 17 00:00:00 2001 From: Marko Budiselic Date: Wed, 24 Sep 2025 16:22:01 +0200 Subject: [PATCH 1/4] Add the integration with LightRAG --- integrations/lightrag-memgraph/README.md | 4 ++++ 1 file changed, 4 insertions(+) create mode 100644 integrations/lightrag-memgraph/README.md diff --git a/integrations/lightrag-memgraph/README.md b/integrations/lightrag-memgraph/README.md new file mode 100644 index 0000000..4218423 --- /dev/null +++ b/integrations/lightrag-memgraph/README.md @@ -0,0 +1,4 @@ +# Why? + +* Connect extracted entities with existing domain-specific entities. +* Cost for your scale (e.g., $ per your document page). From c5ad6152bdb5b5d0fb5185a4ec5f6dab35d3426d Mon Sep 17 00:00:00 2001 From: Marko Budiselic Date: Wed, 24 Sep 2025 16:23:01 +0200 Subject: [PATCH 2/4] Add a why item --- integrations/lightrag-memgraph/README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/integrations/lightrag-memgraph/README.md b/integrations/lightrag-memgraph/README.md index 4218423..0b78e16 100644 --- a/integrations/lightrag-memgraph/README.md +++ b/integrations/lightrag-memgraph/README.md @@ -1,4 +1,5 @@ # Why? +* High-quality, slow and high-cost entity extraction. * Connect extracted entities with existing domain-specific entities. * Cost for your scale (e.g., $ per your document page). From 25f0b68e27886f015ee9051fcea9c8739b82e125 Mon Sep 17 00:00:00 2001 From: Marko Budiselic Date: Fri, 26 Sep 2025 14:59:58 +0200 Subject: [PATCH 3/4] Add dummy parsing --- integrations/lightrag-memgraph/main.py | 117 + integrations/lightrag-memgraph/pyproject.toml | 9 + pyproject.toml | 1 + uv.lock | 2218 +++++++++++++---- 4 files changed, 1859 insertions(+), 486 deletions(-) create mode 100644 integrations/lightrag-memgraph/main.py create mode 100644 integrations/lightrag-memgraph/pyproject.toml diff --git a/integrations/lightrag-memgraph/main.py b/integrations/lightrag-memgraph/main.py new file mode 100644 index 0000000..ac321ec --- /dev/null +++ b/integrations/lightrag-memgraph/main.py @@ -0,0 +1,117 @@ +import os +import asyncio +from lightrag import LightRAG +from lightrag.llm.openai import gpt_4o_mini_complete, gpt_4o_complete, openai_embed +from lightrag.kg.shared_storage import initialize_pipeline_status +from lightrag.utils import setup_logger +import numpy as np +import time + + +setup_logger("lightrag", level="INFO") +SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__)) +WORKING_DIR = "./rag_storage.out" +# # NOTE: Clean everything becasue we are testing. +# if os.path.exists(WORKING_DIR): +# import shutil +# shutil.rmtree(WORKING_DIR) +if not os.path.exists(WORKING_DIR): + os.mkdir(WORKING_DIR) + + +class DummyEmbed: + def __init__(self, dim: int = 1): + self.embedding_dim = dim + + async def __call__(self, texts: list[str]) -> np.ndarray: + return np.ones((len(texts), self.embedding_dim), dtype=float) + + +async def initialize_rag_no_embed(working_dir: str, llm_model_func): + rag = LightRAG( + working_dir=working_dir, + llm_model_func=llm_model_func, + embedding_func=DummyEmbed(dim=1), + vector_storage="NanoVectorDBStorage", + ) + await rag.initialize_storages() + await initialize_pipeline_status() + return rag + + +async def main(): + try: + rag = await initialize_rag_no_embed(WORKING_DIR, gpt_4o_mini_complete) + dummy_texts = [ + """In the heart of the bustling city, a small bookstore stood as a + sanctuary for dreamers and thinkers alike. Its shelves, lined with + stories from every corner of the world, beckoned to those seeking + adventure, solace, or simply a quiet moment away from the noise. + The owner, an elderly gentleman with a gentle smile, greeted each + visitor as if they were an old friend. On rainy afternoons, the + soft patter of drops against the windows created a symphony that + mingled with the rustle of pages. Children gathered in the reading + nook, their imaginations ignited by tales of dragons and distant + lands. College students found refuge among the stacks, their minds + wandering as they prepared for exams. The bookstore was more than a + place to buy books; it was a haven where stories came alive, + friendships blossomed, and the magic of words wove its spell on all + who entered.""", + """Beneath the golden canopy of autumn leaves, a + quiet park unfolded its charm to those who wandered its winding + paths. Joggers traced familiar routes, their breath visible in the + crisp morning air, while elderly couples strolled hand in hand, + reminiscing about days gone by. Children’s laughter echoed from the + playground, where swings soared and slides became mountains to + conquer. A painter sat on a weathered bench, capturing the fiery + hues of the season on her canvas, her brush dancing with + inspiration. Nearby, a group of friends gathered for a picnic, + sharing stories and homemade treats as squirrels darted hopefully + around their feet. The gentle breeze carried the scent of earth and + fallen leaves, inviting all to pause and savor the moment. In this + tranquil oasis, time seemed to slow, offering a gentle reminder of + nature’s beauty and the simple joys that color everyday life.""", + """On the edge of a sleepy coastal village, a lighthouse stood + sentinel against the relentless waves. Its beacon, steadfast and + bright, guided fishermen safely home through fog and storm. The + keeper, a solitary figure with weathered hands, tended the light + with unwavering dedication, his days marked by the rhythm of tides + and the cries of gulls. Each evening, as the sun dipped below the + horizon, the village gathered on the shore to watch the sky ignite + in shades of orange and violet. Children chased the surf, their + laughter mingling with the roar of the sea. Local artisans + displayed their crafts at the market, their wares shaped by the + stories and traditions of generations. The lighthouse, a symbol of + hope and resilience, reminded all who saw it that even in the + darkest nights, a guiding light could be found, illuminating the + path home.""", + ] + + total_time = 0.0 + for idx, text in enumerate(dummy_texts): + start_time = time.perf_counter() + await rag.ainsert(text) + end_time = time.perf_counter() + elapsed = end_time - start_time + total_time += elapsed + print(f"Text {idx+1} inserted in {elapsed:.4f} seconds.") + print( + f"Total time for inserting {len(dummy_texts)} texts: {total_time:.4f} seconds." + ) + if len(dummy_texts) > 0: + print(f"Average time per text: {total_time/len(dummy_texts):.4f} seconds.") + + print(await rag.get_graph_labels()) + kg_data = await rag.get_knowledge_graph(node_label="City", max_depth=3) + print("KNOWLEDGE GRAPH DATA:") + print(kg_data) + + except Exception as e: + print(f"An error occurred: {e}") + finally: + if rag: + await rag.finalize_storages() + + +if __name__ == "__main__": + asyncio.run(main()) diff --git 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17:27:01 +0200 Subject: [PATCH 4/4] Add WIP (making lightrag work with gpt-oss-20b) --- integrations/lightrag-memgraph/main.py | 196 ++++++++++++++++++------- 1 file changed, 146 insertions(+), 50 deletions(-) diff --git a/integrations/lightrag-memgraph/main.py b/integrations/lightrag-memgraph/main.py index ac321ec..09f3d9b 100644 --- a/integrations/lightrag-memgraph/main.py +++ b/integrations/lightrag-memgraph/main.py @@ -4,12 +4,14 @@ from lightrag.llm.openai import gpt_4o_mini_complete, gpt_4o_complete, openai_embed from lightrag.kg.shared_storage import initialize_pipeline_status from lightrag.utils import setup_logger +from openai import AsyncOpenAI import numpy as np import time -setup_logger("lightrag", level="INFO") SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__)) +# Set LightRAG working directory. +setup_logger("lightrag", level="DEBUG") WORKING_DIR = "./rag_storage.out" # # NOTE: Clean everything becasue we are testing. # if os.path.exists(WORKING_DIR): @@ -18,6 +20,118 @@ if not os.path.exists(WORKING_DIR): os.mkdir(WORKING_DIR) +DUMMY_TEXTS = [ + """In the heart of the bustling city, a small bookstore stood as a + sanctuary for dreamers and thinkers alike. Its shelves, lined with + stories from every corner of the world, beckoned to those seeking + adventure, solace, or simply a quiet moment away from the noise. + The owner, an elderly gentleman with a gentle smile, greeted each + visitor as if they were an old friend. On rainy afternoons, the + soft patter of drops against the windows created a symphony that + mingled with the rustle of pages. Children gathered in the reading + nook, their imaginations ignited by tales of dragons and distant + lands. College students found refuge among the stacks, their minds + wandering as they prepared for exams. The bookstore was more than a + place to buy books; it was a haven where stories came alive, + friendships blossomed, and the magic of words wove its spell on all + who entered.""", + """Beneath the golden canopy of autumn leaves, a + quiet park unfolded its charm to those who wandered its winding + paths. Joggers traced familiar routes, their breath visible in the + crisp morning air, while elderly couples strolled hand in hand, + reminiscing about days gone by. Children’s laughter echoed from the + playground, where swings soared and slides became mountains to + conquer. A painter sat on a weathered bench, capturing the fiery + hues of the season on her canvas, her brush dancing with + inspiration. Nearby, a group of friends gathered for a picnic, + sharing stories and homemade treats as squirrels darted hopefully + around their feet. The gentle breeze carried the scent of earth and + fallen leaves, inviting all to pause and savor the moment. In this + tranquil oasis, time seemed to slow, offering a gentle reminder of + nature’s beauty and the simple joys that color everyday life.""", + """On the edge of a sleepy coastal village, a lighthouse stood + sentinel against the relentless waves. Its beacon, steadfast and + bright, guided fishermen safely home through fog and storm. The + keeper, a solitary figure with weathered hands, tended the light + with unwavering dedication, his days marked by the rhythm of tides + and the cries of gulls. Each evening, as the sun dipped below the + horizon, the village gathered on the shore to watch the sky ignite + in shades of orange and violet. Children chased the surf, their + laughter mingling with the roar of the sea. Local artisans + displayed their crafts at the market, their wares shaped by the + stories and traditions of generations. The lighthouse, a symbol of + hope and resilience, reminded all who saw it that even in the + darkest nights, a guiding light could be found, illuminating the + path home.""", +] + + +# Configure the LLM client. +client = AsyncOpenAI( + api_key=os.getenv("OPENAI_API_KEY", "sk-local"), + base_url=os.getenv("OPENAI_API_BASE", "http://127.0.0.1:8000/v1"), +) + + +async def vllm_gpt_oss_20b_v0(prompt: str, system_prompt: str = "", **kwargs) -> str: + resp = await client.chat.completions.create( + model="gpt-oss-20b", # must match --served-model-name from vLLM + messages=[ + {"role": "system", "content": system_prompt}, + {"role": "user", "content": prompt}, + ], + temperature=kwargs.get("temperature", 0.0), + # max_tokens is the output lenght + max_tokens=min( + kwargs.get("max_tokens", 512), 1024 + ), # NOTE: gpt-oss-20b was configured with 16kB of context window -> min ~15kB for the input. + response_format={"type": "json_object"}, + ) + return resp.choices[0].message.content or "" + + +async def vllm_gpt_oss_20b_v1(prompt: str, **kwargs) -> str: + resp = await client.chat.completions.create( + model="gpt-oss-20b", # must match --served-model-name from vLLM + messages=[{"role": "user", "content": prompt}], + temperature=kwargs.get("temperature", 0.0), + # max_tokens is the output lenght + max_tokens=min( + kwargs.get("max_tokens", 512), 2048 + ), # NOTE: gpt-oss-20b was configured with 16kB of context window -> min ~15kB for the input. + ) + return resp.choices[0].message.content or "" + + +async def vllm_gpt_oss_20b_v2( + prompt, + system_prompt=None, + history_messages=None, + enable_cot: bool = False, + keyword_extraction: bool = False, + **kwargs, +) -> str: + if history_messages is None: + history_messages = [] + response_format = None + if keyword_extraction: + from lightrag.utils import GPTKeywordExtractionFormat + + response_format = GPTKeywordExtractionFormat + messages = [] + if system_prompt: + messages.append({"role": "system", "content": system_prompt}) + messages.extend(history_messages) + messages.append({"role": "user", "content": prompt}) + resp = await client.chat.completions.create( + model="gpt-oss-20b", # must match your vLLM --served-model-name + messages=messages, + temperature=kwargs.get("temperature", 0.0), + max_tokens=kwargs.get("max_tokens", 1024), + response_format=response_format, # may be None + ) + return resp.choices[0].message.content or "" + class DummyEmbed: def __init__(self, dim: int = 1): @@ -30,6 +144,7 @@ async def __call__(self, texts: list[str]) -> np.ndarray: async def initialize_rag_no_embed(working_dir: str, llm_model_func): rag = LightRAG( working_dir=working_dir, + # llm_model_name="gpt-oss-20b", # BUG -> LightRAG has hardcoded stuff..., whatever you put here the gpt-4o-mini is going to be used llm_model_func=llm_model_func, embedding_func=DummyEmbed(dim=1), vector_storage="NanoVectorDBStorage", @@ -39,56 +154,17 @@ async def initialize_rag_no_embed(working_dir: str, llm_model_func): return rag +async def test_vllm_dummy(): + text = "Apple acquired Beats in 2014." + out = await vllm_gpt_oss_20b_v1(f"Extract entities and relations from: '{text}'") + print(out) + + async def main(): try: rag = await initialize_rag_no_embed(WORKING_DIR, gpt_4o_mini_complete) - dummy_texts = [ - """In the heart of the bustling city, a small bookstore stood as a - sanctuary for dreamers and thinkers alike. Its shelves, lined with - stories from every corner of the world, beckoned to those seeking - adventure, solace, or simply a quiet moment away from the noise. - The owner, an elderly gentleman with a gentle smile, greeted each - visitor as if they were an old friend. On rainy afternoons, the - soft patter of drops against the windows created a symphony that - mingled with the rustle of pages. Children gathered in the reading - nook, their imaginations ignited by tales of dragons and distant - lands. College students found refuge among the stacks, their minds - wandering as they prepared for exams. The bookstore was more than a - place to buy books; it was a haven where stories came alive, - friendships blossomed, and the magic of words wove its spell on all - who entered.""", - """Beneath the golden canopy of autumn leaves, a - quiet park unfolded its charm to those who wandered its winding - paths. Joggers traced familiar routes, their breath visible in the - crisp morning air, while elderly couples strolled hand in hand, - reminiscing about days gone by. Children’s laughter echoed from the - playground, where swings soared and slides became mountains to - conquer. A painter sat on a weathered bench, capturing the fiery - hues of the season on her canvas, her brush dancing with - inspiration. Nearby, a group of friends gathered for a picnic, - sharing stories and homemade treats as squirrels darted hopefully - around their feet. The gentle breeze carried the scent of earth and - fallen leaves, inviting all to pause and savor the moment. In this - tranquil oasis, time seemed to slow, offering a gentle reminder of - nature’s beauty and the simple joys that color everyday life.""", - """On the edge of a sleepy coastal village, a lighthouse stood - sentinel against the relentless waves. Its beacon, steadfast and - bright, guided fishermen safely home through fog and storm. The - keeper, a solitary figure with weathered hands, tended the light - with unwavering dedication, his days marked by the rhythm of tides - and the cries of gulls. Each evening, as the sun dipped below the - horizon, the village gathered on the shore to watch the sky ignite - in shades of orange and violet. Children chased the surf, their - laughter mingling with the roar of the sea. Local artisans - displayed their crafts at the market, their wares shaped by the - stories and traditions of generations. The lighthouse, a symbol of - hope and resilience, reminded all who saw it that even in the - darkest nights, a guiding light could be found, illuminating the - path home.""", - ] - total_time = 0.0 - for idx, text in enumerate(dummy_texts): + for idx, text in enumerate(DUMMY_TEXTS): start_time = time.perf_counter() await rag.ainsert(text) end_time = time.perf_counter() @@ -96,10 +172,10 @@ async def main(): total_time += elapsed print(f"Text {idx+1} inserted in {elapsed:.4f} seconds.") print( - f"Total time for inserting {len(dummy_texts)} texts: {total_time:.4f} seconds." + f"Total time for inserting {len(DUMMY_TEXTS)} texts: {total_time:.4f} seconds." ) - if len(dummy_texts) > 0: - print(f"Average time per text: {total_time/len(dummy_texts):.4f} seconds.") + if len(DUMMY_TEXTS) > 0: + print(f"Average time per text: {total_time/len(DUMMY_TEXTS):.4f} seconds.") print(await rag.get_graph_labels()) kg_data = await rag.get_knowledge_graph(node_label="City", max_depth=3) @@ -113,5 +189,25 @@ async def main(): await rag.finalize_storages() +async def manual_extraction(): + system_prompt = """You are an information extraction model. +Always respond **only** with valid JSON in the format: +{ + "entities": ["Entity1", "Entity2"], + "relations": [ + {"subject": "Entity1", "predicate": "relation", "object": "Entity2"} + ] +} +Do not include explanations or text outside JSON. +""" + for text in DUMMY_TEXTS: + out = await vllm_gpt_oss_20b_v0( + f"Extract entities and relations from: '{text}'", system_prompt + ) + print(out) + + if __name__ == "__main__": asyncio.run(main()) + # asyncio.run(test_vllm_dummy()) + # asyncio.run(manual_extraction())