From ab54766b55f420a60f84f50aeea9ff7db5852ce1 Mon Sep 17 00:00:00 2001 From: urvishp80 Date: Tue, 17 Dec 2024 11:21:23 -0700 Subject: [PATCH] Semantic Chunking Processor --- poetry.lock | 3380 +++++++++++------ pyproject.toml | 5 +- scraper/models/documents.py | 3 + scraper/processors/__init__.py | 2 + .../processors/semantic_chunking_processor.py | 176 + scraper/sources.yaml | 9 + semantic_chunker_params.json | 12 + 7 files changed, 2329 insertions(+), 1258 deletions(-) create mode 100644 scraper/processors/semantic_chunking_processor.py create mode 100644 semantic_chunker_params.json diff --git a/poetry.lock b/poetry.lock index be01a80..6333810 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,114 +1,99 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand. 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process of gathering information from a variety of key Bitcoin-related sources. It leverages GitHub Actions to schedule nightly cron jobs, ensuring that the most up-to-date content is captured from each source according to a defined frequency. The scraped data are then stored in an Elasticsearch index." authors = ["kouloumos ", "urvish patel "] readme = "README.md" -packages = [{include = "scraper"}] +packages = [{include = "./scraper"}] [tool.poetry.dependencies] python = ">=3.11,<3.13" @@ -18,6 +18,9 @@ python-dotenv = "^1.0.1" aiohttp = "^3.10.5" scrapy = "^2.11.2" openai = "^1.52.2" +langchain = "^0.3.11" +langchain-experimental = "^0.3.3" +langchain-openai = "0.2.2" [tool.poetry.group.dev.dependencies] diff --git a/scraper/models/documents.py b/scraper/models/documents.py index 9e0a988..1f2e6c3 100644 --- a/scraper/models/documents.py +++ b/scraper/models/documents.py @@ -46,6 +46,9 @@ class ScrapedDocument(BaseModel): authors: Optional[List[str]] = Field( default=None, description="List of authors of the document" ) + chunks: Optional[List[dict]] = Field( + default=None, description="List of chunks generated after splitting the document" + ) test_document: Optional[bool] = Field( # TODO: remove hardcoded value default=True, diff --git a/scraper/processors/__init__.py b/scraper/processors/__init__.py index 52da144..533951a 100644 --- a/scraper/processors/__init__.py +++ b/scraper/processors/__init__.py @@ -3,6 +3,7 @@ from .summarization_processor import SummarizationProcessor from .topic_extractor_processor import TopicExtractorProcessor from .vector_embeddings_processor import VectorEmbeddingsProcessor +from .semantic_chunking_processor import SemanticChunkingProcessor __all__ = [ "ProcessorManager", @@ -10,4 +11,5 @@ "SummarizationProcessor", "TopicExtractorProcessor", "VectorEmbeddingsProcessor", + "SemanticChunkingProcessor" ] diff --git a/scraper/processors/semantic_chunking_processor.py b/scraper/processors/semantic_chunking_processor.py new file mode 100644 index 0000000..478f5b2 --- /dev/null +++ b/scraper/processors/semantic_chunking_processor.py @@ -0,0 +1,176 @@ +import os +import re +import json +import traceback +import tiktoken +import numpy as np +import inspect +from dotenv import load_dotenv + +# https://api.python.langchain.com/en/latest/text_splitter/langchain_experimental.text_splitter.SemanticChunker.html +from langchain_experimental.text_splitter import SemanticChunker +from langchain_openai.embeddings import OpenAIEmbeddings +from langchain_openai import ChatOpenAI + +from scraper.models import ScrapedDocument +from scraper.processors.base_processor import BaseProcessor +from scraper.registry import processor_registry + + +@processor_registry.register("semantic_chunking") +class SemanticChunkingProcessor(BaseProcessor): + def __init__(self): + super().__init__() + self.params = self.load_processor_params() + + def load_processor_params(self): + """Load parameters for chunker, llm model names and other params""" + # Default params + params = { + # Semantic chunking params (for SemanticChunker, from documentation) + "breakpoint_threshold_type": "standard_deviation", + "buffer_size": 4, + "breakpoint_threshold_amount": 3, + "sentence_split_regex": r'(?<=[\.\!\?\n])(\n?)\s+', + # Openai models + "oai_embedding_model": "text-embedding-3-small", # Model for embedding + "oai_gen_model": "gpt-4o-mini", # Model used for generating titles + # Other params + "chunk_threshold": 6000, # Chunk only if number of tokens larger than this + "use_markdown_headers": True, # Use markdown headers for splitting + "max_chunk_size": 6000, # Max number of tokens in a chunk + "generate_titles": False, # Use LLM to generate titles for a chunk + } + param_file = os.getenv("SEMANTIC_CHUNKING_PARAMS", None) # A Json file + if param_file: + params_ = json.load(open(param_file)) + for k,v in params_: + params[k] = v + if "sentence_split_regex" in params: + params["sentence_split_regex"] = re.compile(params["sentence_split_regex"]) + return params + + def check_regex_parsable(self, full_body): + found = re.findall(r'\n# .+\n\n', full_body) # H1 headers + found_h2 = re.findall(r'\n## .+\n\n', full_body) # H2 headers + if len(found) > 2 or len(found_h2) > 2: + return True + return False + + def chunk_text_by_markdown(self, text, found): + """Chunk text based on markdown headers found in the text""" + encoding = tiktoken.encoding_for_model( + self.params.get("oai_embedding_model", "text-embedding-3-small")) + delimiters = [] + found = [i.strip("\n") for i in found] + delimiters.extend(found) + text_chunks = re.split(r"(" + "|".join([re.escape(i) for i in found]) + ")", + text) + text_chunks = [i for i in text_chunks if len(i)>0] + regex_text_chunks = [] + for chunk in text_chunks: + num_tokens = len(encoding.encode(chunk)) + if num_tokens > self.params.get("max_chunk_size", 6000): + sub_chunk_delim = re.findall(r'\n## .+\n\n', chunk) + sub_chunk_delim = [i.strip("\n") for i in sub_chunk_delim] + delimiters.extend(sub_chunk_delim) + if len(sub_chunk_delim) > 0: + regex_text_chunks.extend( + re.split(r"(" + "|".join([re.escape(i) for i in sub_chunk_delim]) + ")", + chunk)) + else: + regex_text_chunks.append(chunk) + else: + regex_text_chunks.append(chunk) + # Combine delimiter string with next chunk + text_chunks = [] + running_str = regex_text_chunks[0] + for chunk in regex_text_chunks[1:]: + if chunk in delimiters: + text_chunks.append(running_str) + running_str = chunk + else: + running_str += chunk + text_chunks.append(running_str) + text_chunks = [(i, "regex") for i in text_chunks] + return text_chunks + + def chunk_text_semantically(self, text): + """Chunk text based on markdown headers""" + found = re.findall(r'\n# .+\n\n', text) # H1 headers + found_h2 = re.findall(r'\n## .+\n\n', text) # H2 headers + found_h3 = re.findall(r'\n### .+\n\n', text) # H3 headers + + chunker_possible_params = dict(inspect.signature(SemanticChunker).parameters) + chunker_params = {k:v for k,v in self.params.items() if k in chunker_possible_params} + text_splitter = SemanticChunker( + OpenAIEmbeddings(model=self.params.get("oai_embedding_model", "text-embedding-3-small")), + **chunker_params) + encoding = tiktoken.encoding_for_model( + self.params.get("oai_embedding_model", "text-embedding-3-small")) + + # found = found + found_h2 + found_h3 # all become a new chunk + if len(found) < 2 and len(found_h2) > 2: + found = found_h2 + + if self.params.get("use_markdown_headers", True) and len(found) > 2: + text_chunks = self.chunk_text_by_markdown(text, found) + else: + text_chunks = text_splitter.split_text(text) + text_chunks = [(re.sub(' +', ' ', re.sub(r'\n\s', '\n', i)), "semantic") for i in text_chunks] + + final_chunks = [] + for chunk, chunk_type in text_chunks: + num_tokens = len(encoding.encode(chunk)) + if num_tokens > self.params.get("max_chunk_size", 6000): + num_chunks = num_tokens // self.params.get("max_chunk_size", 6000) + bool(num_tokens % self.params.get("max_chunk_size", 6000)) + text_splitter_temp = SemanticChunker( + OpenAIEmbeddings(model=self.params.get("oai_embedding_model", "text-embedding-3-small")), + number_of_chunks=num_chunks) + + sub_chunks = text_splitter_temp.split_text(chunk) + sub_chunks = [[i, "semantic_size"] for i in sub_chunks] + final_chunks.extend(sub_chunks) + else: + final_chunks.append([chunk, chunk_type]) + return final_chunks + + def get_chunk_title(self, chunk): + """Get chunk title using llm""" + try: + llm = ChatOpenAI(model_name=self.params.get("oai_gen_model", "gpt-4o-mini")) + response = llm.invoke( + f'Respond only with a suitable title for the following text: "{chunk}"') + return response.content + except Exception as e: + traceback.print_exc() + return None + + async def process(self, document: ScrapedDocument, chunker_params: dict = None) -> ScrapedDocument: + body = document.body + body_chunks = self.chunk_text_semantically(body) + document.chunks = [] + prev_title = None + prev_count = 1 + for idx, (chunk, chunk_type) in enumerate(body_chunks): + chunk_title = None + if chunk_type == "regex": + chunk_title = chunk.strip("\n").split("\n")[0].strip("# ") + prev_title = chunk_title + elif chunk_type == "semantic_size" and prev_title is not None: + chunk_title = prev_title + '-' + str(prev_count) + prev_count += 1 + else: + prev_title = None + prev_count = 1 + chunk_title = None + if self.params.get("generate_titles", False): + chunk_title = self.get_chunk_title(chunk) + # Add chuks to input object + document.chunks.append({ + "title": chunk_title, + "id": f"{document.id}-chunk{idx}", + "body": chunk + }) + + return document \ No newline at end of file diff --git a/scraper/sources.yaml b/scraper/sources.yaml index 4d0355b..385a2f5 100644 --- a/scraper/sources.yaml +++ b/scraper/sources.yaml @@ -2,18 +2,27 @@ github: - name: BIPs domain: https://github.com/bitcoin/bips url: https://github.com/bitcoin/bips.git + processors: + - semantic_chunking - name: BOLTs domain: https://github.com/lightning/bolts url: https://github.com/lightning/bolts.git + processors: + - semantic_chunking - name: BLIPs domain: https://github.com/lightning/blips url: https://github.com/lightning/blips.git + processors: + - semantic_chunking - name: BitcoinOps domain: https://bitcoinops.org url: https://github.com/bitcoinops/bitcoinops.github.io.git directories: _posts/en: post _topics/en: topic + processors: + - summarization + - semantic_chunking - name: BitcoinTranscripts domain: https://btctranscripts.com url: https://github.com/bitcointranscripts/bitcointranscripts.git diff --git a/semantic_chunker_params.json b/semantic_chunker_params.json new file mode 100644 index 0000000..202baad --- /dev/null +++ b/semantic_chunker_params.json @@ -0,0 +1,12 @@ +{ + "breakpoint_threshold_type": "standard_deviation", + "buffer_size": 4, + "breakpoint_threshold_amount": 3, + "sentence_split_regex": "(?<=[\\.\\!\\?\n])(\n?)\\s+", + "oai_embedding_model": "text-embedding-3-small", + "oai_gen_model": "gpt-4o-mini", + "chunk_threshold": 6000, + "use_markdown_headers": false, + "max_chunk_size": 6000, + "generate_titles": false +} \ No newline at end of file