diff --git a/.github/workflows/python-package.yml b/.github/workflows/python-package.yml index ca40123..046353b 100644 --- a/.github/workflows/python-package.yml +++ b/.github/workflows/python-package.yml @@ -37,4 +37,4 @@ jobs: - name: Test Installation run: | pip install -e '.' - python -m log2array --help + python -m log2row --help diff --git a/README.md b/README.md index 8f04476..988bab8 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ -# Log2Array -A command-line tool that automates the detection and extraction of log templates, leveraging regular expressions generated by GPT-4. Say goodbye to the stress of manually writing regex. +# Log2Row +A command-line tool that automates the detection and extraction of log templates, leveraging regular expressions generated by GPT-4. Escape from the stress of manually writing regex. ## What it does? If you have several kinds of logs are mixed together: @@ -33,10 +33,10 @@ I, [2023-09-13T00:00:05.009497 #6] INFO -- : [28aa673a-e6e0-4016-83af-b39619006 I, [2023-09-13T00:00:05.010711 #6] INFO -- : [28aa673a-e6e0-4016-83af-b39619006bc1] Rendered home/index.html.erb within layouts/application (Duration: 0.1ms | Allocations: 16) ``` -Log2Array could detect and extract several log templates, it would take a while, all extracted log would be stored into an embedded in-memory DB [DuckDB](http://duckdb.org/docs/archive/0.9.0/), and opens an IPython REPL: +Log2Row could detect and extract several log templates, it would take a while, all extracted log would be stored into an embedded in-memory DB [DuckDB](http://duckdb.org/docs/archive/0.9.0/), and opens an IPython REPL: ```ipython - ↳ OPENAI_API_KEY="***" python3 log2array run ~/Downloads/hn-*.log --gpt-base https://api.openai-hk.com/v1 --max-lines 1024 --buf-size 1MB --threshold 0.8 + ↳ OPENAI_API_KEY="***" python3 log2row run ~/Downloads/hn-*.log --gpt-base https://api.openai-hk.com/v1 --max-lines 1024 --buf-size 1MB --threshold 0.8 Python 3.11.5 (main, Aug 24 2023, 15:09:45) [Clang 14.0.3 (clang-1403.0.22.14.1)] Type 'copyright', 'credits' or 'license' for more information IPython 8.16.0 -- An enhanced Interactive Python. Type '?' for help. @@ -121,16 +121,16 @@ DuckDB also supports saving results to various output types such as CSV, JSON, a + + > pattern flow ``` -Log2Array processes all logs through a list of regex patterns. If a log matches a pattern successfully, it's grouped and variables are inserted into DuckDB. If a log doesn't match any patterns, it's buffered. These buffered logs are used to detect log communities via a text embedding model. Samples from each community are then sent to GPT-4 to extract their regex patterns. +Log2Row processes all logs through a list of regex patterns. If a log matches a pattern successfully, it's grouped and variables are inserted into DuckDB. If a log doesn't match any patterns, it's buffered. These buffered logs are used to detect log communities via a text embedding model. Samples from each community are then sent to GPT-4 to extract their regex patterns. -The pattern flow isn't part of the main processing, which means that after an initial bootstrap, the processing speed increases significantly. Thus, the longer Log2Array runs, the higher the logs/sec rate it has. +The pattern flow isn't part of the main processing, which means that after an initial bootstrap, the processing speed increases significantly. Thus, the longer Log2Row runs, the higher the logs/sec rate it has. ## How to install it? ``` - ↳pip install git@https://github.com/ethe/log2array.git + ↳pip install git@https://github.com/ethe/log2row.git - ↳ python3 -m log2array -Usage: python -m log2array [OPTIONS] COMMAND [ARGS]... + ↳ python3 -m log2row +Usage: python -m log2row [OPTIONS] COMMAND [ARGS]... Options: --help Show this message and exit. @@ -143,7 +143,7 @@ Commands: *Logs2Array requires Python3.9+* ## How much should I pay? -Log2Array uses GPT-4 to extract the regex of log community, each extraction would costs hundreds to thousands tokens of GPT-4. This means each log community detection would costs 0.01$ to 0.1$. +Log2Row uses GPT-4 to extract the regex of log community, each extraction would costs hundreds to thousands tokens of GPT-4. This means each log community detection would costs 0.01$ to 0.1$. ## What is next? - [ ] auto-detect multiple parts of log templates diff --git a/log2array/__init__.py b/log2array/__init__.py deleted file mode 100644 index a76b932..0000000 --- a/log2array/__init__.py +++ /dev/null @@ -1,102 +0,0 @@ -from __future__ import annotations - -import glob -import logging -import re -import sys -from typing import Generator, List - -import duckdb -from pypika import Column, Query, Schema, Table - -from .util import Log, Memory - - -def sink(path: str, max_size=512) -> Generator[str | None, List[str] | None, None]: - files = glob.glob(path) - logging.info(f"detect log files: {files}") - buffer = [] - - for file in files: - file = open(path, "r") - with file as f: - for line in f: - if buffer is not None: - while len(buffer) != 0: - l = buffer.pop() - yield l - - b = yield line[:-1][:max_size] - if b is not None: - buffer += b - - b = yield None - if b is not None: - buffer += b - while len(buffer) != 0: - l = buffer.pop() - yield l - - -Memory().serialize(re.Pattern, lambda p: p.pattern) - - -@Memory.remember -def match( - memory: Memory, - log_stream: Generator[str | None, List[str] | None, None], -) -> Generator[Log | str | None, re.Pattern | None, None]: - patterns = memory.load("patterns", []) - for offset in range(0, len(patterns)): - patterns[offset] = re.compile(patterns[offset]) - - for line in log_stream: - if line is None: - yield None - continue - - pattern = None - - for regex in patterns: - match = regex.match(line) - if match is None: - continue - pattern = yield Log(regex.pattern, line, match.groups()) - break - else: - pattern = yield line - - if pattern is not None and pattern not in patterns: - patterns.append(pattern) - - -def collect( - logs: Generator[Log, None, None], - max_lines: int, - db_file: str = ":default:", -) -> duckdb.DuckDBPyConnection: - if max_lines <= 0: - max_lines = sys.maxsize - - db = duckdb.connect(db_file) - - for line, _ in zip(logs, range(max_lines)): - schema = Schema("information_schema") - table = db.execute( - Query.from_(schema.tables) - .select("*") - .where(schema.tables.table_name == line.pattern) - .get_sql() - ).fetchone() - if table is None: - columns = [Column(f"c{id}", "string") for id in range(0, len(line.groups))] - db.sql( - Query.create_table(line.pattern.replace('"', '""')) - .columns(*columns) - .get_sql() - ) - - table = Table(line.pattern.replace('"', '""')) - db.sql(Query.into(table).insert(*line.groups).get_sql()) - - return db diff --git a/log2array/cluster.py b/log2array/cluster.py deleted file mode 100644 index 0358ca8..0000000 --- a/log2array/cluster.py +++ /dev/null @@ -1,142 +0,0 @@ -from __future__ import annotations - -import contextlib -import logging -import re -from typing import Generator, List - -import numpy -import torch - -from . import Log - - -@contextlib.contextmanager -def pool(model): - pool = model.start_multi_process_pool() - try: - yield pool - finally: - model.stop_multi_process_pool(pool) - - -class Cluster: - texts: List[str] - embeddings: List[torch.Tensor] - - def __init__(self): - self.texts = [] - self.embeddings = [] - - def append(self, text: str, embedding: torch.Tensor): - self.texts.append(text) - self.embeddings.append(embedding) - - @classmethod - def from_list(cls, texts: List[str], embeddings: List[torch.Tensor]): - self = cls() - self.texts = texts - self.embeddings = embeddings - return self - - def __iter__(self): - for i in zip(self.texts, self.embeddings): - yield i - - -def sample(community: torch.Tensor) -> List[int]: - from sentence_transformers.util import cos_sim - - sims = cos_sim(community, community) - - min = (0, 1) - for offset, sim in enumerate(sims): - mean = sim.mean() - if mean < min[1]: - min = (offset, mean) - - sort = sorted( - [(offset, sim) for offset, sim in enumerate(sims[min[0]].numpy())], - key=lambda i: i[1], - ) - - samples = [community[min[0]], community[sort[0][0]]] - - sims = cos_sim(community, torch.from_numpy(numpy.array(samples))) - - min1 = (0, 1) - for offset, sim in enumerate(sims): - mean = sim.mean() - if mean < min1[1]: - min1 = (offset, mean) - - return [min[0], sort[0][0], min1[0]] - - -def cluster( - log_stream: Generator[str | None, List[str] | None, None], - regex_match: Generator[Log | str | None, re.Pattern | None, None], - model="./all-MiniLM-L6-v2", - buf_size=8 * 1024 * 1024, - threshold=0.7, - min_community_size=3, -) -> Generator[Log | List[str], None, None]: - import torch - from sentence_transformers import SentenceTransformer as Embedder - - from .util import community_detection - - model = Embedder(model) - # sample_clusters: List[Cluster] = [] - buffer: List[str] = [] - size = 0 - - with pool(model) as p: - for line in regex_match: - if line is None: - send, buffer = buffer, [] - log_stream.send(send) - continue - - if isinstance(line, Log): - yield line - continue - - buffer.append(line) - size += len(line) - if size < buf_size: - continue - - logging.info( - f"embedding {format(size / 1024, '.2f')}KB / {len(buffer)} logs, it might take a while." - ) - embeddings = torch.from_numpy(model.encode_multi_process(buffer, p)) - - logging.info("analyze log communities, it might take a while.") - clusters = community_detection( - embeddings, - min_community_size=min_community_size, - threshold=threshold, - ) - logging.info(f"get {len(clusters)} log communities.") - for cluster in clusters: - vecs = [embeddings[i] for i in cluster] - ids = sample(torch.from_numpy(numpy.array(vecs))) - s0, s1, s2 = ( - cluster[ids[0]], - cluster[ids[1]], - cluster[ids[2]], - ) - - samples = Cluster.from_list( - [buffer[s0], buffer[s1], buffer[s2]], - [embeddings[s0], embeddings[s1], embeddings[s2]], - ) - # sample_clusters.append(samples) - - logging.info(f"yield samples {samples.texts}") - yield samples.texts - - send, buffer = buffer, [] - size = 0 - log_stream.send(send) diff --git a/log2array/extract.py b/log2array/extract.py deleted file mode 100644 index a0f4845..0000000 --- a/log2array/extract.py +++ /dev/null @@ -1,97 +0,0 @@ -from __future__ import annotations - -import json -import logging -import re -from typing import Generator, List - -import openai - -from log2array.util import Log - - -def extract( - log_cluster: Generator[Log | List[str], None, None], - regex_match: Generator[Log | str | None, re.Pattern | None, None], - api_base: str = openai.api_base, - model: str = "gpt-4", - top_p: float = 0.1, -) -> Generator[Log, None, None]: - openai.api_base = api_base - - def compile(pattern: str) -> re.Pattern: - return re.compile(pattern) - - kwargs = { - "model": model, - "functions": [ - { - "name": "compile", - "description": "Compile a regular expression pattern into a regular expression object.", - "parameters": { - "type": "object", - "properties": { - "pattern": { - "type": "string", - "description": "regular expression", - }, - }, - "required": ["pattern"], - }, - } - ], - "top_p": top_p, - } - - def get_messages(samples): - samples = "\n".join(samples) - - return [ - { - "role": "system", - "content": "You are a senior regular expression developer." - "Create a regular expression which could match, group and extract the log template of several logs below." - "Take care of character escaping.", - }, - { - "role": "user", - "content": samples, - }, - ] - - for message in log_cluster: - if isinstance(message, Log): - yield message - continue - - kwargs["messages"] = get_messages(message) - - logging.info(f"thinking about the template of log: {message}...") - completion = openai.ChatCompletion.create(**kwargs) - assert isinstance(completion, dict) - logging.info(f"got {completion['choices'][0]['message']}.") - - try: - pattern = compile( - json.loads( - completion["choices"][0]["message"]["function_call"]["arguments"] - )["pattern"] - ) - logging.info( - f"extractd regex: {pattern.pattern}", - ) - regex_match.send(pattern) - continue - except Exception: - logging.warning(f"faild to compile regex: {completion}, guessing...") - - try: - pattern = re.compile( - json.loads(completion["choices"][0]["message"]["content"])["pattern"] - ) - logging.info( - f"guessing success: {pattern.pattern}", - ) - regex_match.send(pattern) - except Exception: - logging.error("failed to compile regex: {}".format(completion)) diff --git a/log2row/__init__.py b/log2row/__init__.py new file mode 100644 index 0000000..01fdbe4 --- /dev/null +++ b/log2row/__init__.py @@ -0,0 +1,108 @@ +from __future__ import annotations + +import glob +import logging +import re +import sys +from typing import Generator + +import duckdb +from pypika import Column, Query, Schema, Table + +from .util import Log, Memory + + +class Sink: + def __init__(self, path: str, max_size: int = 512): + self.path = path + self.max_size = max_size + self.buffer = [] + + def __iter__(self): + files = glob.glob(self.path) + logging.info(f"detect log files: {files}") + + def f(): + for file in files: + with open(file, "r") as f: + for line in f: + yield line[:-1][: self.max_size] + + def b(): + while len(self.buffer) != 0: + line = self.buffer.pop() + yield line + + file = f() + + while True: + buf = b() + yield from buf + yield from file + yield None + if len(self.buffer) == 0: + break + + def send(self, lines): + self.buffer += lines + + +Memory().serialize(re.Pattern, lambda p: p.pattern) + + +class Match: + def __init__(self, memory: Memory, sink: Sink): + self.sink = sink + self.patterns = memory.load("patterns", []) + for offset in range(0, len(self.patterns)): + self.patterns[offset] = re.compile(self.patterns[offset]) + + def __iter__(self): + for line in self.sink: + if line is None: + yield None + continue + + for regex in self.patterns: + match = regex.match(line) + if match is None: + continue + yield Log(regex.pattern, line, match.groups()) + break + else: + yield line + + def send(self, pattern: re.Pattern): + self.patterns.append(pattern) + + +def collect( + logs: Generator[Log, None, None], + max_lines: int, + db_file: str = ":default:", +) -> duckdb.DuckDBPyConnection: + if max_lines <= 0: + max_lines = sys.maxsize + + db = duckdb.connect(db_file) + + for line, _ in zip(logs, range(max_lines)): + schema = Schema("information_schema") + table = db.execute( + Query.from_(schema.tables) + .select("*") + .where(schema.tables.table_name == line.pattern) + .get_sql() + ).fetchone() + if table is None: + columns = [Column(f"c{id}", "string") for id in range(0, len(line.groups))] + db.sql( + Query.create_table(line.pattern.replace('"', '""')) + .columns(*columns) + .get_sql() + ) + + table = Table(line.pattern.replace('"', '""')) + db.sql(Query.into(table).insert(*line.groups).get_sql()) + + return db diff --git a/log2array/__main__.py b/log2row/__main__.py similarity index 71% rename from log2array/__main__.py rename to log2row/__main__.py index ac28d25..1dbfb32 100644 --- a/log2array/__main__.py +++ b/log2row/__main__.py @@ -7,10 +7,10 @@ from IPython import embed from rich.logging import RichHandler -from log2array import match, sink, collect -from log2array.cluster import cluster -from log2array.extract import extract -from log2array.util import Memory, parse_size +from log2row import Match, Sink, collect +from log2row.cluster import Cluster +from log2row.extract import extract +from log2row.util import Memory, parse_size @click.group() @@ -18,7 +18,9 @@ def main(): pass -@main.command() +@main.command( + help="log2row cache all extracted patterns to each files as default, clean the cache as needed." +) def clean(): files = glob(f"{Memory.PATH}/*") for f in files: @@ -28,7 +30,10 @@ def clean(): @main.command() @click.argument("file") @click.option( - "--gpt-base", default=openai.api_base, help="OpenAI API base.", show_default=True + "--gpt-base", + default=openai.api_base, + help="OpenAI API base.", + show_default=True, ) @click.option( "--max-lines", @@ -65,14 +70,17 @@ def run(file, gpt_base, max_lines, buf_size, max_len, threshold): return logging.basicConfig( - level="INFO", format="%(message)s", datefmt="[%X]", handlers=[RichHandler()] + level="INFO", + format="%(message)s", + datefmt="[%X]", + handlers=[RichHandler()], ) buf_size = parse_size(buf_size) with Memory().current(file): - f = sink(file, max_size=max_len) - m = match(f) - c = cluster(f, m, buf_size=buf_size, threshold=threshold) + f = Sink(file, max_size=max_len) + m = Match(Memory(), f) + c = Cluster(f, m, buf_size=buf_size, threshold=threshold) e = extract( c, m, diff --git a/log2row/cluster.py b/log2row/cluster.py new file mode 100644 index 0000000..ef01fac --- /dev/null +++ b/log2row/cluster.py @@ -0,0 +1,165 @@ +from __future__ import annotations + +import os +import contextlib +import logging +from typing import Generator, List + +import numpy +import torch + +from . import Log, Match, Sink + + +@contextlib.contextmanager +def pool(model): + pool = model.start_multi_process_pool() + try: + yield pool + finally: + model.stop_multi_process_pool(pool) + + +class Community: + texts: List[str] + embeddings: List[torch.Tensor] + + def __init__(self): + self.texts = [] + self.embeddings = [] + + def append(self, text: str, embedding: torch.Tensor): + self.texts.append(text) + self.embeddings.append(embedding) + + @classmethod + def from_list(cls, texts: List[str], embeddings: List[torch.Tensor]): + self = cls() + self.texts = texts + self.embeddings = embeddings + return self + + def __iter__(self): + for i in zip(self.texts, self.embeddings): + yield i + + +def sample(community: torch.Tensor) -> List[int]: + from sentence_transformers.util import cos_sim + + sims = cos_sim(community, community) + + min = (0, 1) + for offset, sim in enumerate(sims): + mean = sim.mean() + if mean < min[1]: + min = (offset, mean) + + sort = sorted( + [(offset, sim) for offset, sim in enumerate(sims[min[0]].numpy())], + key=lambda i: i[1], + ) + + samples = [community[min[0]], community[sort[0][0]]] + + sims = cos_sim(community, torch.from_numpy(numpy.array(samples))) + + min1 = (0, 1) + for offset, sim in enumerate(sims): + mean = sim.mean() + if mean < min1[1]: + min1 = (offset, mean) + + return [min[0], sort[0][0], min1[0]] + + +_path = os.path.dirname(__file__) + + +class Cluster: + def __init__( + self, + sink: Sink, + match: Match, + model=os.path.join(_path, "../all-MiniLM-L6-v2"), + buf_size=8 * 1024 * 1024, + threshold=0.7, + min_community_size=3, + ): + from sentence_transformers import SentenceTransformer as Embedder + + self.buf_size = buf_size + self.threshold = threshold + self.min_community_size = min_community_size + self.sink = sink + self.match = match + self.model = Embedder(model) + self.buffer = [] + self.size = 0 + + def __iter__(self): + import torch + from .util import community_detection + + with pool(self.model) as p: + for line in self.match: + if isinstance(line, Log): + yield line + continue + + if line is not None: + self.buffer.append(line) + self.size += len(line) + + if self.size < self.buf_size and line is not None: + continue + + if self.size == 0: + continue + + logging.info( + f"embedding {format(self.size / 1024, '.2f')}KB / {len(self.buffer)} logs, it might take a while." + ) + embeddings = torch.from_numpy( + self.model.encode_multi_process(self.buffer, p) + ) + + logging.info("analyze log communities, it might take a while.") + clusters = community_detection( + embeddings, + min_community_size=self.min_community_size, + threshold=self.threshold, + ) + logging.info(f"get {len(clusters)} log communities.") + + if len(clusters) > 0: + yield from self._sample(clusters, embeddings) + self._recycle() + else: + logging.warning( + f"no cluster is detected, maybe you should decrease the threshold." + ) + + def _sample(self, clusters, embeddings): + for cluster, _ in zip(clusters, range(0, 3)): + vecs = [embeddings[i] for i in cluster] + ids = sample(torch.from_numpy(numpy.array(vecs))) + s0, s1, s2 = ( + cluster[ids[0]], + cluster[ids[1]], + cluster[ids[2]], + ) + + samples = Community.from_list( + [self.buffer[s0], self.buffer[s1], self.buffer[s2]], + [embeddings[s0], embeddings[s1], embeddings[s2]], + ) + # sample_clusters.append(samples) + + logging.info(f"yield samples {samples.texts}") + yield samples.texts + + def _recycle(self): + send, self.buffer = self.buffer, [] + self.size = 0 + self.sink.send(send) diff --git a/log2row/extract.py b/log2row/extract.py new file mode 100644 index 0000000..1d9418f --- /dev/null +++ b/log2row/extract.py @@ -0,0 +1,162 @@ +from __future__ import annotations + +import json +import logging +import re +from typing import Generator + +import openai + +from . import Match +from .cluster import Cluster +from .util import Log + + +PROMPT = r""" +| Characters | Meaning | +| :-------------------------- | :----------------------------------------------------------- | +| `[xyz][a-c]` | A character class. Matches any one of the enclosed characters. You can specify a range of characters by using a hyphen, but if the hyphen appears as the first or last character enclosed in the square brackets, it is taken as a literal hyphen to be included in the character class as a normal character.For example, `[abcd]` is the same as `[a-d]`. They match the "b" in "brisket", and the "a" or the "c" in "arch", but not the "-" (hyphen) in "non-profit".For example, `[abcd-]` and `[-abcd]` match the "b" in "brisket", the "a" or the "c" in "arch", and the "-" (hyphen) in "non-profit".For example, `[\w-]` is the same as `[A-Za-z0-9_-]`. They both match any of the characters in "no_reply@example-server.com" except for the "@" and the ".". | +| `[^xyz][^a-c]` | A negated or complemented character class. That is, it matches anything that is not enclosed in the square brackets. You can specify a range of characters by using a hyphen, but if the hyphen appears as the first or last character enclosed in the square brackets, it is taken as a literal hyphen to be included in the character class as a normal character. For example, `[^abc]` is the same as `[^a-c]`. They initially match "o" in "bacon" and "h" in "chop".**Note:** The ^ character may also indicate the [beginning of input](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_expressions/Assertions). | +| `.` | Has one of the following meanings:Matches any single character *except* line terminators: `\n`, `\r`, `\u2028` or `\u2029`. For example, `/.y/` matches "my" and "ay", but not "yes", in "yes make my day".Inside a character class, the dot loses its special meaning and matches a literal dot.Note that the `m` multiline flag doesn't change the dot behavior. So to match a pattern across multiple lines, the character class `[^]` can be used — it will match any character including newlines.The `s` "dotAll" flag allows the dot to also match line terminators. | +| `\d` | Matches any digit (Arabic numeral). Equivalent to `[0-9]`. For example, `/\d/` or `/[0-9]/` matches "2" in "B2 is the suite number". | +| `\D` | Matches any character that is not a digit (Arabic numeral). Equivalent to `[^0-9]`. For example, `/\D/` or `/[^0-9]/` matches "B" in "B2 is the suite number". | +| `\w` | Matches any alphanumeric character from the basic Latin alphabet, including the underscore. Equivalent to `[A-Za-z0-9_]`. For example, `/\w/` matches "a" in "apple", "5" in "$5.28", and "3" in "3D". | +| `\W` | Matches any character that is not a word character from the basic Latin alphabet. Equivalent to `[^A-Za-z0-9_]`. For example, `/\W/` or `/[^A-Za-z0-9_]/` matches "%" in "50%". | +| `\s` | Matches a single white space character, including space, tab, form feed, line feed, and other Unicode spaces. Equivalent to `[ \f\n\r\t\v\u00a0\u1680\u2000-\u200a\u2028\u2029\u202f\u205f\u3000\ufeff]`. For example, `/\s\w*/` matches " bar" in "foo bar". | +| `\S` | Matches a single character other than white space. Equivalent to `[^ \f\n\r\t\v\u00a0\u1680\u2000-\u200a\u2028\u2029\u202f\u205f\u3000\ufeff]`. For example, `/\S\w*/` matches "foo" in "foo bar". | +| `\t` | Matches a horizontal tab. | +| `\r` | Matches a carriage return. | +| `\n` | Matches a linefeed. | +| `\v` | Matches a vertical tab. | +| `\f` | Matches a form-feed. | +| `[\b]` | Matches a backspace. If you're looking for the word-boundary character (`\b`), see [Boundaries](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_expressions/Assertions). | +| `\0` | Matches a NUL character. Do not follow this with another digit. | +| `\c*X*` | Matches a control character using [caret notation](https://en.wikipedia.org/wiki/Caret_notation), where "X" is a letter from A–Z (corresponding to code points `U+0001`*–*`U+001F`). For example, `/\cM/` matches "\r" in "\r\n". | +| `\x*hh*` | Matches the character with the code `*hh*` (two hexadecimal digits). | +| `\u*hhhh*` | Matches a UTF-16 code-unit with the value `*hhhh*` (four hexadecimal digits). | +| `\u*{hhhh}* or *\u{hhhhh}*` | (Only when the `u` flag is set.) Matches the character with the Unicode value `U+*hhhh*` or `U+*hhhhh*` (hexadecimal digits). | +| `\` | Indicates that the following character should be treated specially, or "escaped". It behaves one of two ways.For characters that are usually treated literally, indicates that the next character is special and not to be interpreted literally. For example, `/b/` matches the character "b". By placing a backslash in front of "b", that is by using `/\b/`, the character becomes special to mean match a word boundary.For characters that are usually treated specially, indicates that the next character is not special and should be interpreted literally. For example, "*" is a special character that means 0 or more occurrences of the preceding character should be matched; for example, `/a*/` means match 0 or more "a"s. To match `*` literally, precede it with a backslash; for example, `/a\*/` matches "a*".Note that some characters like `:`, `-`, `@`, etc. neither have a special meaning when escaped nor when unescaped. Escape sequences like `\:`, `\-`, `\@` will be equivalent to their literal, unescaped character equivalents in regular expressions. However, in regular expressions with the [unicode flag](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_expressions#advanced_searching_with_flags), these will cause an *invalid identity escape* error. This is done to ensure backward compatibility with existing code that uses new escape sequences like `\p` or `\k`.**Note:** To match this character literally, escape it with itself. In other words to search for `\` use `/\\/`. | +| `*x*|*y*` | **Disjunction:** Matches either "x" or "y". Each component, separated by a pipe (`|`), is called an *alternative*. For example, `/green|red/` matches "green" in "green apple" and "red" in "red apple".**Note:** A disjunction is another way to specify "a set of choices", but it's not a character class. Disjunctions are not atoms — you need to use a [group](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_expressions/Groups_and_backreferences) to make it part of a bigger pattern. `[abc]` is functionally equivalent to `(?:a|b|c)`. | + +| Characters | Meaning | +| :--------- | :----------------------------------------------------------- | +| `^` | Matches the beginning of input. If the multiline flag is set to true, also matches immediately after a line break character. For example, `/^A/` does not match the "A" in "an A", but does match the first "A" in "An A".**Note:** This character has a different meaning when it appears at the start of a [character class](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_expressions/Character_classes). | +| `$` | Matches the end of input. If the multiline flag is set to true, also matches immediately before a line break character. For example, `/t$/` does not match the "t" in "eater", but does match it in "eat". | +| `\b` | Matches a word boundary. This is the position where a word character is not followed or preceded by another word-character, such as between a letter and a space. Note that a matched word boundary is not included in the match. In other words, the length of a matched word boundary is zero.Examples:`/\bm/` matches the "m" in "moon".`/oo\b/` does not match the "oo" in "moon", because "oo" is followed by "n" which is a word character.`/oon\b/` matches the "oon" in "moon", because "oon" is the end of the string, thus not followed by a word character.`/\w\b\w/` will never match anything, because a word character can never be followed by both a non-word and a word character.To match a backspace character (`[\b]`), see [Character Classes](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_expressions/Character_classes). | +| `\B` | Matches a non-word boundary. This is a position where the previous and next character are of the same type: Either both must be words, or both must be non-words, for example between two letters or between two spaces. The beginning and end of a string are considered non-words. Same as the matched word boundary, the matched non-word boundary is also not included in the match. For example, `/\Bon/` matches "on" in "at noon", and `/ye\B/` matches "ye" in "possibly yesterday". | + +| Characters | Meaning | +| :--------- | :----------------------------------------------------------- | +| `x(?=y)` | **Lookahead assertion:** Matches "x" only if "x" is followed by "y". For example, /`Jack(?=Sprat)/` matches "Jack" only if it is followed by "Sprat". `/Jack(?=Sprat|Frost)/` matches "Jack" only if it is followed by "Sprat" or "Frost". However, neither "Sprat" nor "Frost" is part of the match results. | +| `x(?!y)` | **Negative lookahead assertion:** Matches "x" only if "x" is not followed by "y". For example, `/\d+(?!\.)/` matches a number only if it is not followed by a decimal point. `/\d+(?!\.)/.exec('3.141')` matches "141" but not "3". | +| `(?<=y)x` | **Lookbehind assertion:** Matches "x" only if "x" is preceded by "y". For example, `/(?<=Jack)Sprat/` matches "Sprat" only if it is preceded by "Jack". `/(?<=Jack|Tom)Sprat/` matches "Sprat" only if it is preceded by "Jack" or "Tom". However, neither "Jack" nor "Tom" is part of the match results. | +| `(?x)` | **Named capturing group:** Matches "x" and stores it on the groups property of the returned matches under the name specified by ``. The angle brackets (`<` and `>`) are required for group name.For example, to extract the United States area code from a phone number, we could use `/\((?\d\d\d)\)/`. The resulting number would appear under `matches.groups.area`. | +| `(?:*x*)` | **Non-capturing group:** Matches "x" but does not remember the match. The matched substring cannot be recalled from the resulting array's elements (`[1], …, [n]`) or from the predefined `RegExp` object's properties (`$1, …, $9`). | +| `\*n*` | Where "n" is a positive integer. A back reference to the last substring matching the n parenthetical in the regular expression (counting left parentheses). For example, `/apple(,)\sorange\1/` matches "apple, orange," in "apple, orange, cherry, peach". | +| \k | A back reference to the last substring matching the **Named capture group** specified by ``.For example, `/(?\w+), yes \k<title>/` matches "Sir, yes Sir" in "Do you copy? Sir, yes Sir!".**Note:** `\k` is used literally here to indicate the beginning of a back reference to a Named capture group. | + +| Characters | Meaning | +| :------------------------------------------------------- | :----------------------------------------------------------- | +| `*x**` | Matches the preceding item "x" 0 or more times. For example, `/bo*/` matches "boooo" in "A ghost booooed" and "b" in "A bird warbled", but nothing in "A goat grunted". | +| `*x*+` | Matches the preceding item "x" 1 or more times. Equivalent to `{1,}`. For example, `/a+/` matches the "a" in "candy" and all the "a"'s in "caaaaaaandy". | +| `*x*?` | Matches the preceding item "x" 0 or 1 times. For example, `/e?le?/` matches the "el" in "angel" and the "le" in "angle."If used immediately after any of the quantifiers `*`, `+`, `?`, or `{}`, makes the quantifier non-greedy (matching the minimum number of times), as opposed to the default, which is greedy (matching the maximum number of times). | +| `*x*{*n*}` | Where "n" is a positive integer, matches exactly "n" occurrences of the preceding item "x". For example, `/a{2}/` doesn't match the "a" in "candy", but it matches all of the "a"'s in "caandy", and the first two "a"'s in "caaandy". | +| `*x*{*n*,}` | Where "n" is a positive integer, matches at least "n" occurrences of the preceding item "x". For example, `/a{2,}/` doesn't match the "a" in "candy", but matches all of the a's in "caandy" and in "caaaaaaandy". | +| `*x*{*n*,*m*}` | Where "n" is 0 or a positive integer, "m" is a positive integer, and `*m* > *n*`, matches at least "n" and at most "m" occurrences of the preceding item "x". For example, `/a{1,3}/` matches nothing in "cndy", the "a" in "candy", the two "a"'s in "caandy", and the first three "a"'s in "caaaaaaandy". Notice that when matching "caaaaaaandy", the match is "aaa", even though the original string had more "a"s in it. | +| `*x**?` `*x*+?` `*x*??` `*x*{n}?` `*x*{n,}?` `*x*{n,m}?` | By default quantifiers like `*` and `+` are "greedy", meaning that they try to match as much of the string as possible. The `?` character after the quantifier makes the quantifier "non-greedy": meaning that it will stop as soon as it finds a match. For example, given a string like "some <foo> <bar> new </bar> </foo> thing":`/<.*>/` will match "<foo> <bar> new </bar> </foo>"`/<.*?>/` will match "<foo>" | +""" + + +def extract( + cluster: Cluster, + match: Match, + api_base: str = openai.api_base, + model: str = "gpt-4", + top_p: float = 0.1, +) -> Generator[Log, None, None]: + openai.api_base = api_base + + def compile(pattern: str) -> re.Pattern: + return re.compile(pattern) + + kwargs = { + "model": model, + "functions": [ + { + "name": "compile", + "description": "Compile a regular expression pattern into a regular expression object.", + "parameters": { + "type": "object", + "properties": { + "pattern": { + "type": "string", + "description": "regular expression", + }, + }, + "required": ["pattern"], + }, + } + ], + "top_p": top_p, + } + + def get_messages(samples): + samples = "\n".join(samples) + + return [ + { + "role": "system", + "content": "You are a senior regular expression developer." + "Create a regular expression which could match, group and extract the log template of several logs below." + "Same, static parts between logs should be the part of template." + "Pattern should start with `^` and end with `$`", + }, + { + "role": "user", + "content": samples, + }, + ] + + for message in cluster: + if isinstance(message, Log): + yield message + continue + + kwargs["messages"] = get_messages(message) + + logging.info(f"thinking about the template of log: {message}...") + completion = openai.ChatCompletion.create(**kwargs) + assert isinstance(completion, dict) + logging.info(f"got {completion['choices'][0]['message']}.") + + try: + pattern = compile( + json.loads( + completion["choices"][0]["message"]["function_call"]["arguments"] + )["pattern"] + ) + logging.info( + f"extractd regex: {pattern.pattern}", + ) + match.send(pattern) + continue + except Exception as e: + logging.warning( + f"faild to compile regex: {completion}, error: {e}, guessing..." + ) + + try: + pattern = re.compile( + json.loads(completion["choices"][0]["message"]["content"])["pattern"] + ) + logging.info( + f"guessing success: {pattern.pattern}", + ) + match.send(pattern) + except Exception as e: + logging.error(f"failed to compile regex: {completion}, error: {e}") diff --git a/log2array/util.py b/log2row/util.py similarity index 96% rename from log2array/util.py rename to log2row/util.py index 870891a..2db2428 100644 --- a/log2array/util.py +++ b/log2row/util.py @@ -43,7 +43,7 @@ def register(self, type, encoder): class Memory(Singleton): home = os.environ["HOME"] - PATH = f"{home}/.log2array" + PATH = f"{home}/.log2row" def __init__( self, @@ -70,15 +70,6 @@ def current(self, file: str): f.truncate() f.write(json.dumps(all, cls=Serializer)) - @classmethod - def remember(cls, func): - memory = cls() - - def inner(*args, **kwargs): - return func(memory, *args, **kwargs) - - return inner - @classmethod def serialize(cls, type, serializer): Serializer().register(type, serializer) @@ -133,6 +124,8 @@ def community_detection( top_val_large, top_idx_large = cos_scores[i].topk( k=sort_max_size, largest=True ) + if min(2 * sort_max_size, len(embeddings)) <= sort_max_size: + break for idx, val in zip(top_idx_large.tolist(), top_val_large): if val < threshold: diff --git a/poetry.lock b/poetry.lock index 0016d0a..b0c1c87 100644 --- a/poetry.lock +++ b/poetry.lock @@ -203,86 +203,101 @@ files = [ [[package]] name = "charset-normalizer" -version = "3.2.0" +version = "3.3.0" description = "The Real First Universal Charset Detector. 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["filelock", "huggingface-hub (>=0.16.4,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.14,<0.15)", "torch (>=1.10,!=1.12.0)", "tqdm (>=4.27)"] video = ["av (==9.2.0)", "decord (==0.6.0)"] vision = ["Pillow (<10.0.0)"] @@ -1880,13 +1956,13 @@ files = [ [[package]] name = "urllib3" -version = "2.0.5" +version = "2.0.6" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=3.7" files = [ - {file = "urllib3-2.0.5-py3-none-any.whl", hash = "sha256:ef16afa8ba34a1f989db38e1dbbe0c302e4289a47856990d0682e374563ce35e"}, - {file = "urllib3-2.0.5.tar.gz", hash = "sha256:13abf37382ea2ce6fb744d4dad67838eec857c9f4f57009891805e0b5e123594"}, + {file = "urllib3-2.0.6-py3-none-any.whl", hash = "sha256:7a7c7003b000adf9e7ca2a377c9688bbc54ed41b985789ed576570342a375cd2"}, + {file = "urllib3-2.0.6.tar.gz", hash = "sha256:b19e1a85d206b56d7df1d5e683df4a7725252a964e3993648dd0fb5a1c157564"}, ] [package.extras] @@ -1897,13 +1973,13 @@ zstd = ["zstandard (>=0.18.0)"] [[package]] name = "wcwidth" -version = "0.2.7" +version = "0.2.8" description = "Measures the displayed width of unicode strings in a terminal" optional = false python-versions = "*" files = [ - {file = "wcwidth-0.2.7-py2.py3-none-any.whl", hash = "sha256:fabf3e32999d9b0dab7d19d845149f326f04fe29bac67709ee071dbd92640a36"}, - {file = "wcwidth-0.2.7.tar.gz", hash = "sha256:1b6d30a98ddd5ce9bbdb33658191fd2423fc9da203fe3ef1855407dcb7ee4e26"}, + {file = "wcwidth-0.2.8-py2.py3-none-any.whl", hash = "sha256:77f719e01648ed600dfa5402c347481c0992263b81a027344f3e1ba25493a704"}, + {file = "wcwidth-0.2.8.tar.gz", hash = "sha256:8705c569999ffbb4f6a87c6d1b80f324bd6db952f5eb0b95bc07517f4c1813d4"}, ] [[package]] diff --git a/pyproject.toml b/pyproject.toml index f4a1d4f..c94ffac 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,9 +1,10 @@ [tool.poetry] -name = "log2array" +name = "log2row" version = "0.1.0" description = "" authors = ["Gwo Tzu-Hsing <gotzehsing@gmail.com>"] readme = "README.md" +include = ["./all-MiniLM-L6-v2"] [tool.poetry.dependencies] python = "^3.9"