├── .gitignore ├── LICENSE ├── README.md ├── ROADMAP.md ├── aifs ├── __init__.py ├── search.py ├── test.py └── testfuncs │ ├── _.aifs │ ├── bookTicket.py │ ├── browseWeb.py │ ├── cookDish.py │ ├── doLaundry.py │ ├── drinkAlcohol.py │ ├── executiveAssistant.py │ ├── liftWeights.py │ ├── lowerBrightness.py │ ├── playTennis.py │ ├── sendEmail.py │ └── setAlarm.py ├── poetry.lock ├── pyproject.toml └── tests ├── __init__.py └── test_aifs.py /.gitignore: -------------------------------------------------------------------------------- 1 | # .gitignore 2 | 3 | # Directories 4 | /dist/ 5 | 6 | # OS generated files 7 | .DS_Store 8 | 9 | # Python Cache: 10 | __pycache__/ 11 | *.pyc 12 | *.pyo 13 | *.pyd 14 | *~ 15 | 16 | # Pytest cache: 17 | .cache 18 | .pytest_cache -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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We also recommend that a 185 | file or class name and description of purpose be included on the 186 | same "printed page" as the copyright notice for easier 187 | identification within third-party archives. 188 | 189 | Copyright [yyyy] [name of copyright owner] 190 | 191 | Licensed under the Apache License, Version 2.0 (the "License"); 192 | you may not use this file except in compliance with the License. 193 | You may obtain a copy of the License at 194 | 195 | http://www.apache.org/licenses/LICENSE-2.0 196 | 197 | Unless required by applicable law or agreed to in writing, software 198 | distributed under the License is distributed on an "AS IS" BASIS, 199 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 200 | See the License for the specific language governing permissions and 201 | limitations under the License. 202 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # AI Filesystem 2 | 3 | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1QdXPchTDnzW6I_3HTZFpSeak_XoH81v5?usp=sharing) 4 | 5 | Local semantic search over folders. Why didn't this exist? 6 | 7 | ```shell 8 | pip install aifs 9 | pip install "unstructured[all-docs]" # If you want to parse all doc types. Includes large packages! 10 | ``` 11 | 12 | ```python 13 | from aifs import search 14 | 15 | search("How does AI Filesystem work?", path="/path/to/folder") 16 | search("It's not unlike how Spotlight works.") # Path defaults to CWD 17 | ``` 18 | 19 | # How it works 20 | 21 |
22 | 23 | ![aifs](https://github.com/KillianLucas/aifs/assets/63927363/c61599a9-aad8-483d-b6a4-3671629cd5f4) 24 | 25 | Running `aifs.search` will chunk and embed all nested supported files (`.txt`, `.py`, `.sh`, `.docx`, `.pptx`, `.jpg`, `.png`, `.eml`, `.html`, and `.pdf`) in `path`. It will then store these embeddings into an `_.aifs` file in `path`. 26 | 27 | By storing the index, you only have to chunk/embed once. This makes semantic search **very** fast after the first time you search a path. 28 | 29 | If a file has changed or been added, `aifs.search` will update or add those chunks. We still need to handle file deletions (we welcome PRs). 30 | 31 | ### In detail: 32 | 33 | 1. If a folder hasn't been indexed, we first use [`unstructured`](https://github.com/Unstructured-IO/unstructured/tree/main) to parse and chunk every file in the `path`. 34 | 2. Then we use [`chroma`](https://github.com/chroma-core/chroma) to embed the chunks locally and save them to a `_.aifs` file in `path`. 35 | 3. Finally, `chroma` is used again to semantically search the embeddings. 36 | 37 | If an `_.aifs` file _is_ found in a directory, it uses that instead of indexing it again. If some files have been updated, it will re-index those. 38 | 39 | # Goals 40 | 41 | - We should always have SOTA parsing and chunking. The logic for this should be swapped out as new methods arise. 42 | - Chunking should be semantic — as in, `python` and `markdown` files should have _different_ chunking algorithms based on the expected content of those filetypes. Who has this solution? 43 | - For parsing, I think Unstructured is the best of the best. Is this true? 44 | - We should always have SOTA embedding. If a better local embedding model is found, we should automatically download and use it. 45 | - I think Chroma will always do this (is this true?) so we depend on Chroma. 46 | - This project should stay **minimally scoped** — we want `aifs` to be the best local semantic search in the universe. 47 | 48 | # Why? 49 | 50 | We built this to let [`open-interpreter`](https://openinterpreter.com/) quickly semantically search files/folders. 51 | -------------------------------------------------------------------------------- /ROADMAP.md: -------------------------------------------------------------------------------- 1 | # Roadmap 2 | 3 | - [ ] Add file source to chunk metadata, including page number if relevant, and ensure this is displayed when running `search`. 4 | - [ ] Handle file deletions (I think we can just more robustly detect indexed files vs present files) 5 | - [ ] Add tqdm to each step 6 | - [ ] Allow you to ignore certain files or paths (I think path should just accept a list, and if it's a list of files, those are the only files it will take. Then you can write your own logic for ignoring stuff) 7 | - [ ] Make it work with just one file, like pointing to a single PDF. 8 | - [ ] Put an `_.aifs` in each subdirectory, so indexing a path will index all subpaths 9 | - [ ] Support multimodal — transcribe videos and audio, describing each scene / sound, describe images 10 | -------------------------------------------------------------------------------- /aifs/__init__.py: -------------------------------------------------------------------------------- 1 | from .search import search -------------------------------------------------------------------------------- /aifs/search.py: -------------------------------------------------------------------------------- 1 | """ 2 | Simple, fast, local semantic search. Uses an _.aifs file to store embeddings in top most directory. 3 | """ 4 | 5 | import sys 6 | 7 | MAX_CHARS_PER_CHUNK = 500 8 | MAX_CHUNKS = None # More than this, and we'll just embed the filename. None to embed any # of chunks. 9 | 10 | try: 11 | from unstructured.chunking.title import chunk_by_title 12 | from unstructured.partition.auto import partition 13 | 14 | def chunk_file(file_path): 15 | elements = partition(filename=file_path) 16 | chunks = chunk_by_title(elements, max_characters=MAX_CHARS_PER_CHUNK) 17 | return [c.text for c in chunks] 18 | 19 | except ImportError: 20 | # print("Please run 'pip install \"unstructured[all-docs]\"' to improve document-reading performance.") 21 | 22 | def chunk_file(file_path): 23 | with open(file_path, 'r', encoding='utf-8') as file: 24 | file_text = file.read() 25 | 26 | # Chunk the text 27 | chunks = [file_text[i:i+MAX_CHARS_PER_CHUNK] for i in range(0, len(file_text), MAX_CHARS_PER_CHUNK)] 28 | return chunks 29 | 30 | 31 | # TODO 32 | # Should use system search, like spotlight, to narrow it down. Then rerank with semantic. 33 | # Should use sub indexes in nested dirs if they exist. 34 | # Better chunking that works per sentence, paragraph, word level rather than by character. 35 | 36 | import ast 37 | import os 38 | from typing import List 39 | import json 40 | 41 | try: 42 | import chromadb 43 | from chromadb.utils.embedding_functions import DefaultEmbeddingFunction as setup_embed 44 | # Set up the embedding function 45 | os.environ[ 46 | "TOKENIZERS_PARALLELISM" 47 | ] = "false" # Otherwise setup_embed displays a warning message 48 | 49 | embed = setup_embed() 50 | except: 51 | pass # shoulda used vlite 52 | 53 | 54 | # Function to extract function arguments and annotations 55 | def format_function_details(func_def, class_name=None): 56 | name = func_def.name 57 | args = [(arg.arg, None if not arg.annotation else ast.unparse(arg.annotation)) for arg in func_def.args.args] 58 | vararg = (func_def.args.vararg.arg, ast.unparse(func_def.args.vararg.annotation)) if func_def.args.vararg and func_def.args.vararg.annotation else None 59 | return_annotation = ast.unparse(func_def.returns) if func_def.returns else None 60 | docstring = ast.get_docstring(func_def) 61 | 62 | # Start with the function name and opening parenthesis 63 | if class_name: 64 | formatted_string = f"{class_name}.{name}(" 65 | else: 66 | formatted_string = f"{name}(" 67 | 68 | # Add each positional argument with its annotation 69 | for arg_name, arg_annotation in args: 70 | formatted_string += f" {arg_name}: {arg_annotation}, " 71 | 72 | # Add varargs if present 73 | if vararg: 74 | formatted_string += f" *{vararg[0]}: {vararg[1]}" 75 | 76 | # Close the parenthesis and add return annotation 77 | formatted_string += f") -> {return_annotation}" 78 | 79 | # Add the docstring if present 80 | if docstring: 81 | formatted_string += f" # {docstring}" 82 | print(formatted_string) 83 | 84 | return formatted_string 85 | 86 | def log(str): 87 | verbose = os.environ['LOG_VERBOSE'] 88 | if verbose and verbose == 'True': print(str) 89 | 90 | def index_file(file_path, python_docstrings_only=False): 91 | if python_docstrings_only and file_path.lower().endswith(".py"): 92 | return minimally_index_python_file(file_path) 93 | 94 | log(f"Indexing {file_path}...") 95 | try: 96 | chunks = chunk_file(file_path) 97 | if chunks == []: 98 | raise Exception("Failed to chunk.") 99 | if MAX_CHUNKS and len(chunks) > MAX_CHUNKS: 100 | raise Exception("Too many chunks. Will just embed filename.") 101 | except Exception as e: 102 | log(f"Couldn't read `{file_path}`. Continuing.") 103 | log(e) 104 | chunks = [f"There is a file at `{file_path}`."] 105 | 106 | embeddings = embed(chunks) 107 | last_modified = os.path.getmtime(file_path) 108 | 109 | return { 110 | "chunks": chunks, 111 | "embeddings": embeddings, 112 | "last_modified": last_modified, 113 | } 114 | 115 | 116 | def minimally_index_python_file(file_path): 117 | """ 118 | This function indexes a Python file in a minimal way. 119 | It only embeds the docstrings for semantic search, which then point to only the function name. 120 | """ 121 | chunks = [] 122 | representations = [] 123 | 124 | try: 125 | with open(file_path, "r") as source: 126 | tree = ast.parse(source.read()) 127 | except Exception as e: 128 | print(f"Couldn't parse {file_path}. Error:", str(e)) 129 | return None 130 | 131 | def traverse(node): 132 | for child in ast.iter_child_nodes(node): 133 | if isinstance(child, ast.FunctionDef): 134 | if child.name.startswith("_"): 135 | # ignore private functions 136 | continue 137 | class_name = node.name if isinstance(node, ast.ClassDef) else None 138 | docstring = ast.get_docstring(child) 139 | formatted_string = format_function_details(child, class_name) 140 | chunks.append(formatted_string) 141 | representations.append(docstring if docstring else child.name) 142 | traverse(child) 143 | 144 | traverse(tree) 145 | 146 | embeddings = embed(representations) if representations else [] 147 | last_modified = os.path.getmtime(file_path) 148 | 149 | return { 150 | "chunks": chunks, 151 | "embeddings": embeddings, 152 | "last_modified": last_modified, 153 | } 154 | 155 | 156 | def index_files(file_paths, existingIndex=None, indexPath="", python_docstrings_only=False): 157 | if existingIndex is None: 158 | existingIndex = {} 159 | index = existingIndex 160 | deletedFiles = handle_deleted_files(index) 161 | modifiedFiles = handle_modified_files(index, python_docstrings_only) 162 | writeToIndex = len(deletedFiles) > 0 or len(modifiedFiles) > 0 163 | 164 | for file_path in file_paths: 165 | if file_path.endswith("_index.aifs") and file_path.endswith(".DS_Store") and file_path.endswith("_.aifs"): 166 | continue 167 | # if there are new files not in index, or modified Files, index them 168 | if file_path not in index or file_path in modifiedFiles: 169 | log(f"{file_path} is new file or modified, indexing it") 170 | writeToIndex = True 171 | file_index = index_file(file_path, python_docstrings_only) 172 | if file_index: 173 | index[file_path] = file_index 174 | else: 175 | log(f"{file_path} is in index, skip") 176 | 177 | save_index(writeToIndex, index, indexPath) 178 | 179 | return index 180 | 181 | 182 | def handle_deleted_files(index: dict) -> List[str]: 183 | """updates the index to remove deleted files. returns deleted files""" 184 | deletedFiles = [] 185 | for file_path, _ in index.items(): 186 | if not os.path.isfile(file_path): 187 | log(f"Removing {file_path} since it does not exist.") 188 | deletedFiles.append(file_path) 189 | # remove deleted files 190 | for file_path in deletedFiles: 191 | index.pop(file_path, None) 192 | 193 | return deletedFiles 194 | 195 | 196 | def handle_modified_files(index: dict, python_docstrings_only: bool) -> List[str]: 197 | modifiedFiles = [] 198 | for file_path, file_index in index.items(): 199 | if file_path == None or file_index == None: 200 | continue 201 | if os.path.getmtime(file_path) != file_index["last_modified"]: 202 | log(f"Re-indexing {file_path} due to modification.") 203 | new_file_index = index_file(file_path, python_docstrings_only) 204 | index[file_path] = new_file_index 205 | modifiedFiles.append(file_path) 206 | return modifiedFiles 207 | 208 | 209 | def save_index(writeToIndex, index, indexPath): 210 | if writeToIndex: 211 | log(f"Index has changed, saving again to {indexPath}") 212 | with open(indexPath, "w") as f: 213 | json.dump(index, f) 214 | 215 | 216 | def index_directory(path, existingIndex=None, indexPath="", python_docstrings_only=False): 217 | if existingIndex is None: 218 | existingIndex = {} 219 | index = existingIndex 220 | deletedFiles = handle_deleted_files(index) 221 | modifiedFiles = handle_modified_files(index, python_docstrings_only) 222 | writeToIndex = len(deletedFiles) > 0 or len(modifiedFiles) > 0 223 | 224 | for root, _, files in os.walk(path): 225 | for file in files: 226 | if file != "" and file != "_index.aifs" and file != ".DS_Store" and file != "_.aifs": 227 | file_path = os.path.join(root, file) 228 | # if there are new files not in index, or modified Files, index them 229 | if file_path not in index or file_path in modifiedFiles: 230 | log(f"{file_path} is new file or modified, indexing it") 231 | writeToIndex = True 232 | file_index = index_file(file_path, python_docstrings_only) 233 | index[file_path] = file_index 234 | else: 235 | log(f"{file_path} is in index, skip") 236 | 237 | save_index(writeToIndex, index, indexPath) 238 | 239 | return index 240 | 241 | 242 | def search(query, path=None, file_paths=None, max_results=5, verbose=False, python_docstrings_only=False): 243 | """ 244 | Performs a semantic search of the `query` in `path` and its subdirectories. 245 | 246 | Parameters: 247 | query (str): The search query. 248 | path (str, optional): The path to the directory to search. Defaults to the current working directory. 249 | file_paths (list, optional): A list of file paths to search. Defaults to None. Used only if path isn't provided. 250 | max_results (int, optional): The maximum number of search results to return. Defaults to 5. 251 | 252 | Returns: 253 | list: A list of search results. 254 | """ 255 | os.environ['LOG_VERBOSE'] = str(verbose) 256 | 257 | if path is None: 258 | common_prefix = os.path.commonprefix(file_paths) 259 | if not common_prefix.endswith("/"): 260 | common_prefix = os.path.dirname(common_prefix) 261 | path_to_index = os.path.join(common_prefix, "_.aifs") 262 | else: 263 | path_to_index = os.path.join(path, "_.aifs") 264 | 265 | index = {} 266 | if not os.path.exists(path_to_index): 267 | # No index. We're embedding everything. 268 | log(f"Indexing for AI search. This will take time, but only happens once.") 269 | else: 270 | log(f"Using existing index at `{path_to_index}`") 271 | with open(path_to_index, 'r') as f: 272 | index = json.load(f) 273 | 274 | if path or file_paths is None: 275 | if path is None: 276 | path = os.getcwd() 277 | index = index_directory(path, existingIndex=index, indexPath=path_to_index, python_docstrings_only=python_docstrings_only) 278 | else: 279 | index = index_files(file_paths, existingIndex=index, indexPath=path_to_index, python_docstrings_only=python_docstrings_only) 280 | 281 | chroma_client = chromadb.Client() 282 | collection = chroma_client.get_or_create_collection(name="temp") 283 | id_counter = 0 284 | for file_path, file_index in index.items(): 285 | if "__pycache__" in file_path: 286 | continue 287 | if file_index and "chunks" in file_index: 288 | ids = [str(id) for id in range(id_counter, id_counter + len(file_index["chunks"]))] 289 | id_counter += len(file_index["chunks"]) 290 | else: 291 | ids = [] 292 | if ids: 293 | collection.add( 294 | ids=ids, 295 | embeddings=file_index["embeddings"], 296 | documents=file_index["chunks"], 297 | metadatas=[{"source": file_path}] * len(file_index["chunks"]), 298 | ) 299 | 300 | results = collection.query( 301 | query_texts=[query], 302 | n_results=max_results 303 | ) 304 | log(results) 305 | 306 | chroma_client.delete_collection("temp") 307 | 308 | return results["documents"][0] 309 | -------------------------------------------------------------------------------- /aifs/test.py: -------------------------------------------------------------------------------- 1 | from aifs import search 2 | import os 3 | 4 | def test_search_index(): 5 | files_path = os.getcwd() + "/testfuncs" 6 | query = "Lift those weights" 7 | results = search(query, path=files_path, python_docstrings_only=True) 8 | print(results) 9 | assert results 10 | 11 | test_search_index() -------------------------------------------------------------------------------- /aifs/testfuncs/_.aifs: -------------------------------------------------------------------------------- 1 | {"/Users/shivenmian/aifs/aifs/testfuncs/doLaundry.py": {"chunks": ["(function) def doLaundry(\n) -> None\n\nThis function does the laundry.\n"], "embeddings": [[-0.0988963171839714, 0.04116939380764961, 0.02906455658376217, 0.0392119400203228, 0.025212986394762993, -0.046314388513565063, -0.0007770400843583047, -0.007474598474800587, -0.02402442693710327, -0.011705213226377964, -0.013186413794755936, 0.011443096213042736, -0.009201028384268284, 0.035191912204027176, -0.010434378869831562, 0.031104490160942078, -0.0261059682816267, 0.09331779181957245, -0.06483171880245209, -0.09063030034303665, 0.06466110050678253, -0.020332537591457367, 0.04183199256658554, -0.02488894760608673, -0.005857236683368683, -0.013792751356959343, -0.037373192608356476, -0.03430858999490738, 0.006552353501319885, -0.06758981198072433, 0.03660040348768234, 0.04338007792830467, 0.04692201688885689, 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-------------------------------------------------------------------------------- /aifs/testfuncs/doLaundry.py: -------------------------------------------------------------------------------- 1 | def doLaundry(): 2 | """ 3 | This function does the laundry. 4 | """ 5 | print("Did laundry") -------------------------------------------------------------------------------- /aifs/testfuncs/drinkAlcohol.py: -------------------------------------------------------------------------------- 1 | def drinkAlcohol(): 2 | """ 3 | This function drinks alcohol 4 | """ 5 | print("Alcohol drunk") -------------------------------------------------------------------------------- /aifs/testfuncs/executiveAssistant.py: -------------------------------------------------------------------------------- 1 | def executiveAssistant(): 2 | """ 3 | This function executes a task 4 | """ 5 | print("Executed task") -------------------------------------------------------------------------------- /aifs/testfuncs/liftWeights.py: -------------------------------------------------------------------------------- 1 | def liftWeights(): 2 | """ 3 | This function lifts Weights 4 | """ 5 | print("Weights lifted") 6 | -------------------------------------------------------------------------------- /aifs/testfuncs/lowerBrightness.py: -------------------------------------------------------------------------------- 1 | def lowerBrightness(): 2 | """ 3 | This function lowers the screen brightness. 4 | """ 5 | print("Screen brightness lowered") -------------------------------------------------------------------------------- /aifs/testfuncs/playTennis.py: -------------------------------------------------------------------------------- 1 | def playTennis(): 2 | """ 3 | This function plays tennis. 4 | """ 5 | print("Tennis played") -------------------------------------------------------------------------------- /aifs/testfuncs/sendEmail.py: 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pluggy = ">=0.12,<2.0" 82 | tomli = {version = ">=1.0.0", markers = "python_version < \"3.11\""} 83 | 84 | [package.extras] 85 | testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "nose", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"] 86 | 87 | [[package]] 88 | name = "tomli" 89 | version = "2.0.1" 90 | description = "A lil' TOML parser" 91 | optional = false 92 | python-versions = ">=3.7" 93 | files = [ 94 | {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"}, 95 | {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"}, 96 | ] 97 | 98 | [metadata] 99 | lock-version = "2.0" 100 | python-versions = ">=3.9,<4" 101 | content-hash = "7063c0e2812bd0dc9e6a3f31ed04d9a3b0629ae5ce2faaa875b36a4ea1f82238" 102 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [tool.poetry] 2 | name = "aifs" 3 | version = "0.0.15" 4 | description = "Local semantic search. Stupidly simple." 5 | authors = ["Killian Lucas "] 6 | license = "MIT" 7 | readme = "README.md" 8 | 9 | [tool.poetry.dependencies] 10 | python = ">=3.9,<4" 11 | #chromadb = "^0.4.22" 12 | #numpy = "^1.26.4" 13 | 14 | [tool.poetry.group.dev.dependencies] 15 | pytest = "^7.4.4" 16 | 17 | [build-system] 18 | requires = ["poetry-core"] 19 | build-backend = "poetry.core.masonry.api" -------------------------------------------------------------------------------- /tests/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/OpenInterpreter/aifs/3f74c6aaf6b1a190d99e7ab16d78163afbf1b1ca/tests/__init__.py -------------------------------------------------------------------------------- /tests/test_aifs.py: -------------------------------------------------------------------------------- 1 | from aifs import search 2 | import os 3 | 4 | def test_search_this(): 5 | os.environ['AIFS_MINIMAL_PYTHON_INDEXING'] = 'false' 6 | current_dir_path = os.path.dirname(os.path.realpath(__file__)) 7 | query = "test search" 8 | results = search(query, path=current_dir_path) 9 | print(results) 10 | assert results 11 | 12 | def test_search_desktop(): 13 | os.environ['AIFS_MINIMAL_PYTHON_INDEXING'] = 'false' 14 | desktop_path = os.path.expanduser("~/Desktop") 15 | query = "forest gump" 16 | results = search(query, path=desktop_path) 17 | print(results) 18 | assert results 19 | --------------------------------------------------------------------------------