Clean up core cognee repo

.data/code/example.txt

@@ -1,28 +0,0 @@
-'''
-	Given a string, find the length of the longest substring without repeating characters.
-
-	Examples:
-
-	Given "abcabcbb", the answer is "abc", which the length is 3.
-
-	Given "bbbbb", the answer is "b", with the length of 1.
-
-	Given "pwwkew", the answer is "wke", with the length of 3. Note that the answer must be a substring, "pwke" is a subsequence and not a substring.
-'''
-
-class Solution(object):
-    def lengthOfLongestSubstring(self, s):
-        """
-        :type s: str
-        :rtype: int
-        """
-        mapSet = {}
-        start, result = 0, 0
-
-        for end in range(len(s)):
-        	if s[end] in mapSet:
-        		start = max(mapSet[s[end]], start)
-        	result = max(result, end-start+1)
-        	mapSet[s[end]] = end+1
-
-        return result

.dlt/config.toml

@@ -1,6 +0,0 @@
-# put your configuration values here
-
-[runtime]
-log_level = "WARNING"  # the system log level of dlt
-# use the dlthub_telemetry setting to enable/disable anonymous usage data reporting, see https://dlthub.com/docs/telemetry
-dlthub_telemetry = false

.dockerignore

@@ -1,4 +1,4 @@
-bin
+tools/bin
 dist
 docs
 evals

.gitignore

@@ -1,4 +1,4 @@
-.data
+examples/.data
 .env
 .local.env
 .prod.env

README.md

@@ -35,9 +35,9 @@ More on [use-cases](https://docs.cognee.ai/use-cases) and [evals](https://github
   <p align="center">
   🌐 Available Languages
   :
-  <a href="community/README.pt.md">🇵🇹 Português</a>
+  <a href="assets/community/README.pt.md">🇵🇹 Português</a>
   ·
-  <a href="community/README.zh.md">🇨🇳 [中文]</a>
+  <a href="assets/community/README.zh.md">🇨🇳 [中文]</a>
   </p>
 
 <div style="text-align: center">

alembic.ini

@@ -1,117 +0,0 @@
-# A generic, single database configuration.
-
-[alembic]
-# path to migration scripts
-# Use forward slashes (/) also on windows to provide an os agnostic path
-script_location = alembic
-
-# template used to generate migration file names; The default value is %%(rev)s_%%(slug)s
-# Uncomment the line below if you want the files to be prepended with date and time
-# see https://alembic.sqlalchemy.org/en/latest/tutorial.html#editing-the-ini-file
-# for all available tokens
-# file_template = %%(year)d_%%(month).2d_%%(day).2d_%%(hour).2d%%(minute).2d-%%(rev)s_%%(slug)s
-
-# sys.path path, will be prepended to sys.path if present.
-# defaults to the current working directory.
-prepend_sys_path = .
-
-# timezone to use when rendering the date within the migration file
-# as well as the filename.
-# If specified, requires the python>=3.9 or backports.zoneinfo library.
-# Any required deps can installed by adding `alembic[tz]` to the pip requirements
-# string value is passed to ZoneInfo()
-# leave blank for localtime
-# timezone =
-
-# max length of characters to apply to the "slug" field
-# truncate_slug_length = 40
-
-# set to 'true' to run the environment during
-# the 'revision' command, regardless of autogenerate
-# revision_environment = false
-
-# set to 'true' to allow .pyc and .pyo files without
-# a source .py file to be detected as revisions in the
-# versions/ directory
-# sourceless = false
-
-# version location specification; This defaults
-# to alembic/versions.  When using multiple version
-# directories, initial revisions must be specified with --version-path.
-# The path separator used here should be the separator specified by "version_path_separator" below.
-# version_locations = %(here)s/bar:%(here)s/bat:alembic/versions
-
-# version path separator; As mentioned above, this is the character used to split
-# version_locations. The default within new alembic.ini files is "os", which uses os.pathsep.
-# If this key is omitted entirely, it falls back to the legacy behavior of splitting on spaces and/or commas.
-# Valid values for version_path_separator are:
-#
-# version_path_separator = :
-# version_path_separator = ;
-# version_path_separator = space
-# version_path_separator = newline
-version_path_separator = os  # Use os.pathsep. Default configuration used for new projects.
-
-# set to 'true' to search source files recursively
-# in each "version_locations" directory
-# new in Alembic version 1.10
-# recursive_version_locations = false
-
-# the output encoding used when revision files
-# are written from script.py.mako
-# output_encoding = utf-8
-
-sqlalchemy.url = %(SQLALCHEMY_DATABASE_URI)s
-
-
-[post_write_hooks]
-# post_write_hooks defines scripts or Python functions that are run
-# on newly generated revision scripts.  See the documentation for further
-# detail and examples
-
-# format using "black" - use the console_scripts runner, against the "black" entrypoint
-# hooks = black
-# black.type = console_scripts
-# black.entrypoint = black
-# black.options = -l 79 REVISION_SCRIPT_FILENAME
-
-# lint with attempts to fix using "ruff" - use the exec runner, execute a binary
-# hooks = ruff
-# ruff.type = exec
-# ruff.executable = %(here)s/.venv/bin/ruff
-# ruff.options = --fix REVISION_SCRIPT_FILENAME
-
-# Logging configuration
-[loggers]
-keys = root,sqlalchemy,alembic
-
-[handlers]
-keys = console
-
-[formatters]
-keys = generic
-
-[logger_root]
-level = WARN
-handlers = console
-qualname =
-
-[logger_sqlalchemy]
-level = WARN
-handlers =
-qualname = sqlalchemy.engine
-
-[logger_alembic]
-level = INFO
-handlers =
-qualname = alembic
-
-[handler_console]
-class = StreamHandler
-args = (sys.stderr,)
-level = NOTSET
-formatter = generic
-
-[formatter_generic]
-format = %(levelname)-5.5s [%(name)s] %(message)s
-datefmt = %H:%M:%S

cognee-gui.py

@@ -1,153 +0,0 @@
-import sys
-import asyncio
-
-try:
-    import cognee
-    from PySide6.QtWidgets import (
-        QApplication,
-        QWidget,
-        QPushButton,
-        QLineEdit,
-        QFileDialog,
-        QVBoxLayout,
-        QHBoxLayout,
-        QLabel,
-        QMessageBox,
-        QTextEdit,
-        QProgressDialog,
-    )
-    from PySide6.QtCore import Qt
-
-    from qasync import QEventLoop  # Import QEventLoop from qasync
-except ImportError as e:
-    print(
-        "\nPlease install Cognee with optional gui dependencies or manually install missing dependencies.\n"
-    )
-    print("\nTo install with poetry use:")
-    print("\npoetry install -E gui\n")
-    print("\nOr to install with poetry and all dependencies use:")
-    print("\npoetry install --all-extras\n")
-    print("\nTo install with pip use: ")
-    print('\npip install ".[gui]"\n')
-    raise e
-
-
-class FileSearchApp(QWidget):
-    def __init__(self):
-        super().__init__()
-        self.selected_file = None
-        self.init_ui()
-
-    def init_ui(self):
-        # Horizontal layout for file upload and visualization buttons
-        button_layout = QHBoxLayout()
-
-        # Button to open file dialog
-        self.file_button = QPushButton("Upload File to Cognee", parent=self)
-        self.file_button.clicked.connect(self.open_file_dialog)
-        button_layout.addWidget(self.file_button)
-
-        # Button to visualize data
-        self.visualize_button = QPushButton("Visualize Data", parent=self)
-        self.visualize_button.clicked.connect(lambda: asyncio.ensure_future(self.visualize_data()))
-        button_layout.addWidget(self.visualize_button)
-
-        # Label to display selected file path
-        self.file_label = QLabel("No file selected", parent=self)
-
-        # Line edit for search input
-        self.search_input = QLineEdit(parent=self)
-        self.search_input.setPlaceholderText("Enter text to search...")
-
-        # Button to perform search; schedule the async search on click
-        self.search_button = QPushButton("Cognee Search", parent=self)
-        self.search_button.clicked.connect(lambda: asyncio.ensure_future(self._cognee_search()))
-
-        # Text output area for search results
-        self.result_output = QTextEdit(parent=self)
-        self.result_output.setReadOnly(True)
-        self.result_output.setPlaceholderText("Search results will appear here...")
-
-        # Progress dialog
-        self.progress_dialog = QProgressDialog("Processing..", None, 0, 0, parent=self)
-        self.progress_dialog.setWindowModality(Qt.WindowModal)
-        self.progress_dialog.setCancelButton(None)  # Remove the cancel button
-        self.progress_dialog.close()
-
-        # Layout setup
-        layout = QVBoxLayout()
-        layout.addLayout(button_layout)
-        layout.addWidget(self.file_label)
-        layout.addWidget(self.search_input)
-        layout.addWidget(self.search_button)
-        layout.addWidget(self.result_output)
-
-        self.setLayout(layout)
-        self.setWindowTitle("Cognee")
-        self.resize(500, 300)
-
-    def open_file_dialog(self):
-        file_path, _ = QFileDialog.getOpenFileName(
-            self, "Select a File", "", "All Files (*.*);;Text Files (*.txt)"
-        )
-        if file_path:
-            self.selected_file = file_path
-            self.file_label.setText(f"Selected: {file_path}")
-            asyncio.ensure_future(self.process_file_async())
-
-    async def process_file_async(self):
-        """Asynchronously add and process the selected file."""
-        # Disable the entire window
-        self.progress_dialog.show()
-        self.setEnabled(False)
-        try:
-            await cognee.add(self.selected_file)
-            await cognee.cognify()
-        except Exception as e:
-            QMessageBox.critical(self, "Error", f"File processing failed: {str(e)}")
-        # Once finished, re-enable the window
-        self.setEnabled(True)
-        self.progress_dialog.close()
-
-    async def _cognee_search(self):
-        """Performs an async search and updates the result output."""
-        # Disable the entire window
-        self.setEnabled(False)
-        self.progress_dialog.show()
-
-        try:
-            search_text = self.search_input.text().strip()
-            result = await cognee.search(query_text=search_text)
-            print(result)
-            # Assuming result is a list-like object; adjust if necessary
-            self.result_output.setText(result[0])
-        except Exception as e:
-            QMessageBox.critical(self, "Error", f"Search failed: {str(e)}")
-
-        # Once finished, re-enable the window
-        self.setEnabled(True)
-        self.progress_dialog.close()
-
-    async def visualize_data(self):
-        """Async slot for handling visualize data button press."""
-        import webbrowser
-        from cognee.api.v1.visualize.visualize import visualize_graph
-        import os
-        import pathlib
-
-        html_file = os.path.join(pathlib.Path(__file__).parent, ".data", "graph_visualization.html")
-        await visualize_graph(html_file)
-        webbrowser.open(f"file://{html_file}")
-
-
-if __name__ == "__main__":
-    app = QApplication(sys.argv)
-    # Create a qasync event loop and set it as the current event loop
-    loop = QEventLoop(app)
-    asyncio.set_event_loop(loop)
-
-    window = FileSearchApp()
-    window.show()
-
-    with loop:
-        loop.run_forever()

deployment/Dockerfile_modal

@@ -21,12 +21,12 @@ WORKDIR /app
 
 ENV PYTHONPATH=/app
 WORKDIR /app
-COPY pyproject.toml poetry.lock /app/
+COPY ../pyproject.toml poetry.lock /app/
 
 
 RUN pip install poetry
 
 RUN poetry install --all-extras --no-root --without dev
 
-COPY cognee/ /app/cognee
-COPY README.md /app/README.md
+COPY ../cognee /app/cognee
+COPY ../README.md /app/README.md

deployment/docker-compose.yml

@@ -4,8 +4,8 @@ services:
     networks:
       - cognee-network
     build:
-      context: .
-      dockerfile: Dockerfile
+      context: ..
+      dockerfile: ../Dockerfile
     volumes:
       - ./cognee:/app/cognee
       - .env:/app/.env
@@ -33,8 +33,8 @@ services:
     profiles:
         - ui
     build:
-      context: ./cognee-frontend
-      dockerfile: Dockerfile
+      context: ../cognee-frontend
+      dockerfile: ../cognee-frontend/Dockerfile
     volumes:
       - ./cognee-frontend/src:/app/src
       - ./cognee-frontend/public:/app/public

deployment/modal_deployment.py

@@ -12,8 +12,8 @@ app = modal.App("cognee-runner")
 
 image = (
     modal.Image.from_dockerfile(path="Dockerfile_modal", force_build=False)
-    .copy_local_file("pyproject.toml", "pyproject.toml")
-    .copy_local_file("poetry.lock", "poetry.lock")
+    .copy_local_file("../pyproject.toml", "pyproject.toml")
+    .copy_local_file("../poetry.lock", "poetry.lock")
     .env({"ENV": os.getenv("ENV"), "LLM_API_KEY": os.getenv("LLM_API_KEY")})
     .poetry_install_from_file(poetry_pyproject_toml="pyproject.toml")
     .pip_install("protobuf", "h2")

licenses/README.md

@@ -1,4 +0,0 @@
-# Third party licenses
-
-This folder contains the licenses of third-party open-source software that has been redistributed in this project.
-Details of included files and modifications can be found in [NOTICE](/NOTICE.md).

profiling/graph_pydantic_conversion/benchmark_function.py

@@ -1,62 +0,0 @@
-import statistics
-import time
-import tracemalloc
-from typing import Any, Callable, Dict
-
-import psutil
-
-
-def benchmark_function(func: Callable, *args, num_runs: int = 5) -> Dict[str, Any]:
-    """
-    Benchmark a function for memory usage and computational performance.
-
-    Args:
-        func: Function to benchmark
-        *args: Arguments to pass to the function
-        num_runs: Number of times to run the benchmark
-
-    Returns:
-        Dictionary containing benchmark metrics
-    """
-    execution_times = []
-    peak_memory_usages = []
-    cpu_percentages = []
-
-    process = psutil.Process()
-
-    for _ in range(num_runs):
-        # Start memory tracking
-        tracemalloc.start()
-
-        # Measure execution time and CPU usage
-        start_time = time.perf_counter()
-        start_cpu_time = process.cpu_times()
-
-        end_cpu_time = process.cpu_times()
-        end_time = time.perf_counter()
-
-        # Calculate metrics
-        execution_time = end_time - start_time
-        cpu_time = (end_cpu_time.user + end_cpu_time.system) - (
-            start_cpu_time.user + start_cpu_time.system
-        )
-        current, peak = tracemalloc.get_traced_memory()
-
-        # Store results
-        execution_times.append(execution_time)
-        peak_memory_usages.append(peak / 1024 / 1024)  # Convert to MB
-        cpu_percentages.append((cpu_time / execution_time) * 100)
-
-        tracemalloc.stop()
-
-    analysis = {
-        "mean_execution_time": statistics.mean(execution_times),
-        "mean_peak_memory_mb": statistics.mean(peak_memory_usages),
-        "mean_cpu_percent": statistics.mean(cpu_percentages),
-        "num_runs": num_runs,
-    }
-
-    if num_runs > 1:
-        analysis["std_execution_time"] = statistics.stdev(execution_times)
-
-    return analysis

profiling/graph_pydantic_conversion/profile_graph_pydantic_conversion.py

@@ -1,63 +0,0 @@
-import argparse
-import asyncio
-
-from .benchmark_function import benchmark_function
-
-from cognee.modules.graph.utils import get_graph_from_model
-from cognee.tests.unit.interfaces.graph.util import (
-    PERSON_NAMES,
-    create_organization_recursive,
-)
-
-# Example usage:
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description="Benchmark graph model with configurable recursive depth"
-    )
-    parser.add_argument(
-        "--recursive-depth",
-        type=int,
-        default=3,
-        help="Recursive depth for graph generation (default: 3)",
-    )
-    parser.add_argument("--runs", type=int, default=5, help="Number of benchmark runs (default: 5)")
-    args = parser.parse_args()
-
-    society = create_organization_recursive(
-        "society", "Society", PERSON_NAMES, args.recursive_depth
-    )
-    added_nodes = {}
-    added_edges = {}
-    visited_properties = {}
-    nodes, edges = asyncio.run(
-        get_graph_from_model(
-            society,
-            added_nodes=added_nodes,
-            added_edges=added_edges,
-            visited_properties=visited_properties,
-        )
-    )
-
-    def get_graph_from_model_sync(model):
-        added_nodes = {}
-        added_edges = {}
-        visited_properties = {}
-
-        return asyncio.run(
-            get_graph_from_model(
-                model,
-                added_nodes=added_nodes,
-                added_edges=added_edges,
-                visited_properties=visited_properties,
-            )
-        )
-
-    results = benchmark_function(get_graph_from_model_sync, society, num_runs=args.runs)
-    print("\nBenchmark Results:")
-    print(f"N nodes: {len(nodes)}, N edges: {len(edges)}, Recursion depth: {args.recursive_depth}")
-    print(f"Mean Peak Memory: {results['mean_peak_memory_mb']:.2f} MB")
-    print(f"Mean CPU Usage: {results['mean_cpu_percent']:.2f}%")
-    print(f"Mean Execution Time: {results['mean_execution_time']:.4f} seconds")
-
-    if "std_execution_time" in results:
-        print(f"Execution Time Std: {results['std_execution_time']:.4f} seconds")

profiling/util/DummyEmbeddingEngine.py

@@ -1,10 +0,0 @@
-import numpy as np
-from cognee.infrastructure.databases.vector.embeddings.EmbeddingEngine import EmbeddingEngine
-
-
-class DummyEmbeddingEngine(EmbeddingEngine):
-    async def embed_text(self, text: list[str]) -> list[list[float]]:
-        return list(list(np.random.randn(3072)))
-
-    def get_vector_size(self) -> int:
-        return 3072

profiling/util/DummyLLMAdapter.py

@@ -1,59 +0,0 @@
-from typing import Type
-from uuid import uuid4
-
-import spacy
-import textacy
-from pydantic import BaseModel
-
-from cognee.infrastructure.llm.llm_interface import LLMInterface
-from cognee.shared.data_models import Edge, KnowledgeGraph, Node, SummarizedContent
-
-
-class DummyLLMAdapter(LLMInterface):
-    nlp = spacy.load("en_core_web_sm")
-
-    async def acreate_structured_output(
-        self, text_input: str, system_prompt: str, response_model: Type[BaseModel]
-    ) -> BaseModel:
-        if str(response_model) == "<class 'cognee.shared.data_models.SummarizedContent'>":
-            return dummy_summarize_content(text_input)
-        elif str(response_model) == "<class 'cognee.shared.data_models.KnowledgeGraph'>":
-            return dummy_extract_knowledge_graph(text_input, self.nlp)
-        else:
-            raise Exception(
-                "Currently dummy acreate_structured_input is only implemented for SummarizedContent and KnowledgeGraph"
-            )
-
-
-def dummy_extract_knowledge_graph(text, nlp):
-    doc = nlp(text)
-    triples = list(textacy.extract.subject_verb_object_triples(doc))
-
-    nodes = {}
-    edges = []
-    for triple in triples:
-        source = "_".join([str(e) for e in triple.subject])
-        target = "_".join([str(e) for e in triple.object])
-        nodes[source] = nodes.get(
-            source, Node(id=str(uuid4()), name=source, type="object", description="")
-        )
-        nodes[target] = nodes.get(
-            target, Node(id=str(uuid4()), name=target, type="object", description="")
-        )
-        edge_type = "_".join([str(e) for e in triple.verb])
-        edges.append(
-            Edge(
-                source_node_id=nodes[source].id,
-                target_node_id=nodes[target].id,
-                relationship_name=edge_type,
-            )
-        )
-    return KnowledgeGraph(nodes=list(nodes.values()), edges=edges)
-
-
-def dummy_summarize_content(text):
-    words = [(word, len(word)) for word in set(text.split(" "))]
-    words = sorted(words, key=lambda x: x[1], reverse=True)
-    summary = " ".join([word for word, _ in words[:50]])
-    description = " ".join([word for word, _ in words[:10]])
-    return SummarizedContent(summary=summary, description=description)