Merge branch 'dev' into feature/mistral_llm_provider

.env.template

@@ -176,7 +176,14 @@ ENABLE_BACKEND_ACCESS_CONTROL=False
 
 # Cognee Cloud API settings for syncing data to/from cloud infrastructure
 COGNEE_CLOUD_API_URL="http://localhost:8001"
-COGNEE_CLOUD_AUTH_TOKEN="your-auth-token"
+COGNEE_CLOUD_AUTH_TOKEN="your-api-key"
+
+################################################################################
+# UI Settings
+################################################################################
+
+# URL where the frontend is served, defaults to http://localhost:3000
+UI_APP_URL=http://localhost:3000
 
 ################################################################################
 #  🛠️ DEV Settings
@@ -196,6 +203,16 @@ LITELLM_LOG="ERROR"
 # DEFAULT_USER_EMAIL=""
 # DEFAULT_USER_PASSWORD=""
 
+################################################################################
+#  📂 AWS Settings
+################################################################################
+
+#AWS_REGION=""
+#AWS_ENDPOINT_URL=""
+#AWS_ACCESS_KEY_ID=""
+#AWS_SECRET_ACCESS_KEY=""
+#AWS_SESSION_TOKEN=""
+
 ------------------------------- END OF POSSIBLE SETTINGS -------------------------------
 
 

.github/actions/cognee_setup/action.yml

@@ -24,7 +24,7 @@ runs:
       uses: astral-sh/setup-uv@v4
       with:
         enable-cache: true
-    
+
     - name: Rebuild uv lockfile
       shell: bash
       run: |

.github/workflows/basic_tests.yml

@@ -188,6 +188,7 @@ jobs:
         uses: ./.github/actions/cognee_setup
         with:
           python-version: ${{ inputs.python-version }}
+          extra-dependencies: "baml"
 
       - name: Run Simple Examples
         run: uv run python ./examples/python/simple_example.py

.github/workflows/e2e_tests.yml

@@ -166,9 +166,6 @@ jobs:
             python-version: '3.11.x'
             extra-dependencies: "aws"
 
-        - name: Dependencies already installed
-          run: echo "Dependencies already installed in setup"
-
         - name: Run S3 Bucket Test
           env:
             ENV: 'dev'

.github/workflows/test_s3_file_storage.yml

@@ -18,6 +18,7 @@ jobs:
         uses: ./.github/actions/cognee_setup
         with:
           python-version: '3.11.x'
+          extra-dependencies: "aws"
 
       - name: Run S3 File Storage Test
         env:

cognee-frontend/src/ui/Layout/Header.tsx

@@ -2,10 +2,11 @@
 
 import Link from "next/link";
 import Image from "next/image";
-import { useBoolean } from "@/utils";
+import { useEffect } from "react";
+import { useBoolean, fetch } from "@/utils";
 
 import { CloseIcon, CloudIcon, CogneeIcon } from "../Icons";
-import { CTAButton, GhostButton, IconButton, Modal } from "../elements";
+import { CTAButton, GhostButton, IconButton, Modal, StatusDot } from "../elements";
 import syncData from "@/modules/cloud/syncData";
 
 interface HeaderProps {
@@ -23,6 +24,12 @@ export default function Header({ user }: HeaderProps) {
     setFalse: closeSyncModal,
   } = useBoolean(false);
 
+  const {
+    value: isMCPConnected,
+    setTrue: setMCPConnected,
+    setFalse: setMCPDisconnected,
+  } = useBoolean(false);
+
   const handleDataSyncConfirm = () => {
     syncData()
       .finally(() => {
@@ -30,6 +37,19 @@ export default function Header({ user }: HeaderProps) {
       });
   };
 
+  useEffect(() => {
+    const checkMCPConnection = () => {
+      fetch.checkMCPHealth()
+        .then(() => setMCPConnected())
+        .catch(() => setMCPDisconnected());
+    };
+
+    checkMCPConnection();
+    const interval = setInterval(checkMCPConnection, 30000);
+    
+    return () => clearInterval(interval);
+  }, [setMCPConnected, setMCPDisconnected]);
+
   return (
     <>
       <header className="relative flex flex-row h-14 min-h-14 px-5 items-center justify-between w-full max-w-[1920px] mx-auto">
@@ -39,6 +59,10 @@ export default function Header({ user }: HeaderProps) {
         </div>
 
         <div className="flex flex-row items-center gap-2.5">
+          <Link href="/mcp-status" className="!text-indigo-600 pl-4 pr-4">
+            <StatusDot className="mr-2" isActive={isMCPConnected} />
+            { isMCPConnected ? "MCP connected" : "MCP disconnected" }
+          </Link>
           <GhostButton onClick={openSyncModal} className="text-indigo-600 gap-3 pl-4 pr-4">
             <CloudIcon />
             <div>Sync</div>

cognee-frontend/src/ui/elements/StatusDot.tsx

@@ -0,0 +1,13 @@
+import React from "react";
+
+const StatusDot = ({ isActive, className }: { isActive: boolean, className?: string }) => {
+  return (
+    <span
+      className={`inline-block w-3 h-3 rounded-full ${className} ${
+        isActive ? "bg-green-500" : "bg-red-500"
+      }`}
+    />
+  );
+};
+
+export default StatusDot;

cognee-frontend/src/ui/elements/index.ts

@@ -8,5 +8,6 @@ export { default as IconButton } from "./IconButton";
 export { default as GhostButton } from "./GhostButton";
 export { default as NeutralButton } from "./NeutralButton";
 export { default as StatusIndicator } from "./StatusIndicator";
+export { default as StatusDot } from "./StatusDot";
 export { default as Accordion } from "./Accordion";
 export { default as Notebook } from "./Notebook"; 

cognee-frontend/src/utils/fetch.ts

@@ -9,6 +9,8 @@ const backendApiUrl = process.env.NEXT_PUBLIC_BACKEND_API_URL || "http://localho
 
 const cloudApiUrl = process.env.NEXT_PUBLIC_CLOUD_API_URL || "http://localhost:8001";
 
+const mcpApiUrl = process.env.NEXT_PUBLIC_MCP_API_URL || "http://localhost:8001";
+
 let apiKey: string | null = process.env.NEXT_PUBLIC_COGWIT_API_KEY || null;
 let accessToken: string | null = null;
 
@@ -66,6 +68,10 @@ fetch.checkHealth = () => {
   return global.fetch(`${backendApiUrl.replace("/api", "")}/health`);
 };
 
+fetch.checkMCPHealth = () => {
+  return global.fetch(`${mcpApiUrl.replace("/api", "")}/health`);
+};
+
 fetch.setApiKey = (newApiKey: string) => {
   apiKey = newApiKey;
 };

cognee-mcp/entrypoint.sh

@@ -48,27 +48,27 @@ if [ "$ENVIRONMENT" = "dev" ] || [ "$ENVIRONMENT" = "local" ]; then
     if [ "$DEBUG" = "true" ]; then
         echo "Waiting for the debugger to attach..."
         if [ "$TRANSPORT_MODE" = "sse" ]; then
-            exec python -m debugpy --wait-for-client --listen 0.0.0.0:$DEBUG_PORT -m cognee --transport sse --host 0.0.0.0 --port $HTTP_PORT --no-migration
+            exec python -m debugpy --wait-for-client --listen 0.0.0.0:$DEBUG_PORT -m cognee-mcp --transport sse --host 0.0.0.0 --port $HTTP_PORT --no-migration
         elif [ "$TRANSPORT_MODE" = "http" ]; then
-            exec python -m debugpy --wait-for-client --listen 0.0.0.0:$DEBUG_PORT -m cognee --transport http --host 0.0.0.0 --port $HTTP_PORT --no-migration
+            exec python -m debugpy --wait-for-client --listen 0.0.0.0:$DEBUG_PORT -m cognee-mcp --transport http --host 0.0.0.0 --port $HTTP_PORT --no-migration
         else
-            exec python -m debugpy --wait-for-client --listen 0.0.0.0:$DEBUG_PORT -m cognee --transport stdio --no-migration
+            exec python -m debugpy --wait-for-client --listen 0.0.0.0:$DEBUG_PORT -m cognee-mcp --transport stdio --no-migration
         fi
     else
         if [ "$TRANSPORT_MODE" = "sse" ]; then
-            exec cognee --transport sse --host 0.0.0.0 --port $HTTP_PORT --no-migration
+            exec cognee-mcp --transport sse --host 0.0.0.0 --port $HTTP_PORT --no-migration
         elif [ "$TRANSPORT_MODE" = "http" ]; then
-            exec cognee --transport http --host 0.0.0.0 --port $HTTP_PORT --no-migration
+            exec cognee-mcp --transport http --host 0.0.0.0 --port $HTTP_PORT --no-migration
         else
-            exec cognee --transport stdio --no-migration
+            exec cognee-mcp --transport stdio --no-migration
         fi
     fi
 else
     if [ "$TRANSPORT_MODE" = "sse" ]; then
-        exec cognee --transport sse --host 0.0.0.0 --port $HTTP_PORT --no-migration
+        exec cognee-mcp --transport sse --host 0.0.0.0 --port $HTTP_PORT --no-migration
     elif [ "$TRANSPORT_MODE" = "http" ]; then
-        exec cognee --transport http --host 0.0.0.0 --port $HTTP_PORT --no-migration
+        exec cognee-mcp --transport http --host 0.0.0.0 --port $HTTP_PORT --no-migration
     else
-        exec cognee --transport stdio --no-migration
+        exec cognee-mcp --transport stdio --no-migration
     fi
 fi

cognee-mcp/pyproject.toml

@@ -36,4 +36,4 @@ dev = [
 allow-direct-references = true
 
 [project.scripts]
-cognee = "src:main"
+cognee-mcp = "src:main"

cognee-mcp/src/server.py

@@ -19,6 +19,10 @@ from cognee.api.v1.cognify.code_graph_pipeline import run_code_graph_pipeline
 from cognee.modules.search.types import SearchType
 from cognee.shared.data_models import KnowledgeGraph
 from cognee.modules.storage.utils import JSONEncoder
+from starlette.responses import JSONResponse
+from starlette.middleware import Middleware
+from starlette.middleware.cors import CORSMiddleware
+import uvicorn
 
 
 try:
@@ -38,6 +42,53 @@ mcp = FastMCP("Cognee")
 logger = get_logger()
 
 
+async def run_sse_with_cors():
+    """Custom SSE transport with CORS middleware."""
+    sse_app = mcp.sse_app()
+    sse_app.add_middleware(
+        CORSMiddleware,
+        allow_origins=["http://localhost:3000"],
+        allow_credentials=True,
+        allow_methods=["GET"],
+        allow_headers=["*"],
+    )
+
+    config = uvicorn.Config(
+        sse_app,
+        host=mcp.settings.host,
+        port=mcp.settings.port,
+        log_level=mcp.settings.log_level.lower(),
+    )
+    server = uvicorn.Server(config)
+    await server.serve()
+
+
+async def run_http_with_cors():
+    """Custom HTTP transport with CORS middleware."""
+    http_app = mcp.streamable_http_app()
+    http_app.add_middleware(
+        CORSMiddleware,
+        allow_origins=["http://localhost:3000"],
+        allow_credentials=True,
+        allow_methods=["GET"],
+        allow_headers=["*"],
+    )
+
+    config = uvicorn.Config(
+        http_app,
+        host=mcp.settings.host,
+        port=mcp.settings.port,
+        log_level=mcp.settings.log_level.lower(),
+    )
+    server = uvicorn.Server(config)
+    await server.serve()
+
+
+@mcp.custom_route("/health", methods=["GET"])
+async def health_check(request):
+    return JSONResponse({"status": "ok"})
+
+
 @mcp.tool()
 async def cognee_add_developer_rules(
     base_path: str = ".", graph_model_file: str = None, graph_model_name: str = None
@@ -975,12 +1026,12 @@ async def main():
         await mcp.run_stdio_async()
     elif args.transport == "sse":
         logger.info(f"Running MCP server with SSE transport on {args.host}:{args.port}")
-        await mcp.run_sse_async()
+        await run_sse_with_cors()
     elif args.transport == "http":
         logger.info(
             f"Running MCP server with Streamable HTTP transport on {args.host}:{args.port}{args.path}"
         )
-        await mcp.run_streamable_http_async()
+        await run_http_with_cors()
 
 
 if __name__ == "__main__":

cognee/api/client.py

@@ -3,7 +3,6 @@
 import os
 
 import uvicorn
-import sentry_sdk
 from traceback import format_exc
 from contextlib import asynccontextmanager
 from fastapi import Request
@@ -42,11 +41,18 @@ from cognee.modules.users.methods.get_authenticated_user import REQUIRE_AUTHENTI
 logger = get_logger()
 
 if os.getenv("ENV", "prod") == "prod":
-    sentry_sdk.init(
-        dsn=os.getenv("SENTRY_REPORTING_URL"),
-        traces_sample_rate=1.0,
-        profiles_sample_rate=1.0,
-    )
+    try:
+        import sentry_sdk
+
+        sentry_sdk.init(
+            dsn=os.getenv("SENTRY_REPORTING_URL"),
+            traces_sample_rate=1.0,
+            profiles_sample_rate=1.0,
+        )
+    except ImportError:
+        logger.info(
+            "Sentry SDK not available. Install with 'pip install cognee\"[monitoring]\"' to enable error monitoring."
+        )
 
 
 app_environment = os.getenv("ENV", "prod")
@@ -81,7 +87,7 @@ if CORS_ALLOWED_ORIGINS:
     ]
 else:
     allowed_origins = [
-        "http://localhost:3000",
+        os.getenv("UI_APP_URL", "http://localhost:3000"),
     ]  # Block all except explicitly set origins
 
 app.add_middleware(

cognee/api/v1/ui/__init__.py

@@ -1 +1 @@
-from .ui import start_ui, stop_ui, ui
+from .ui import start_ui

cognee/api/v1/ui/ui.py

@@ -1,5 +1,5 @@
 import os
-import signal
+import socket
 import subprocess
 import threading
 import time
@@ -7,7 +7,7 @@ import webbrowser
 import zipfile
 import requests
 from pathlib import Path
-from typing import Callable, Optional, Tuple
+from typing import Callable, Optional, Tuple, List
 import tempfile
 import shutil
 
@@ -17,6 +17,80 @@ from cognee.version import get_cognee_version
 logger = get_logger()
 
 
+def _stream_process_output(
+    process: subprocess.Popen, stream_name: str, prefix: str, color_code: str = ""
+) -> threading.Thread:
+    """
+    Stream output from a process with a prefix to identify the source.
+
+    Args:
+        process: The subprocess to monitor
+        stream_name: 'stdout' or 'stderr'
+        prefix: Text prefix for each line (e.g., '[BACKEND]', '[FRONTEND]')
+        color_code: ANSI color code for the prefix (optional)
+
+    Returns:
+        Thread that handles the streaming
+    """
+
+    def stream_reader():
+        stream = getattr(process, stream_name)
+        if stream is None:
+            return
+
+        reset_code = "\033[0m" if color_code else ""
+
+        try:
+            for line in iter(stream.readline, b""):
+                if line:
+                    line_text = line.decode("utf-8").rstrip()
+                    if line_text:
+                        print(f"{color_code}{prefix}{reset_code} {line_text}", flush=True)
+        except Exception:
+            pass
+        finally:
+            if stream:
+                stream.close()
+
+    thread = threading.Thread(target=stream_reader, daemon=True)
+    thread.start()
+    return thread
+
+
+def _is_port_available(port: int) -> bool:
+    """
+    Check if a port is available on localhost.
+    Returns True if the port is available, False otherwise.
+    """
+    try:
+        with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock:
+            sock.settimeout(1)  # 1 second timeout
+            result = sock.connect_ex(("localhost", port))
+            return result != 0  # Port is available if connection fails
+    except Exception:
+        return False
+
+
+def _check_required_ports(ports_to_check: List[Tuple[int, str]]) -> Tuple[bool, List[str]]:
+    """
+    Check if all required ports are available on localhost.
+
+    Args:
+        ports_to_check: List of (port, service_name) tuples
+
+    Returns:
+        Tuple of (all_available: bool, unavailable_services: List[str])
+    """
+    unavailable = []
+
+    for port, service_name in ports_to_check:
+        if not _is_port_available(port):
+            unavailable.append(f"{service_name} (port {port})")
+            logger.error(f"Port {port} is already in use for {service_name}")
+
+    return len(unavailable) == 0, unavailable
+
+
 def normalize_version_for_comparison(version: str) -> str:
     """
     Normalize version string for comparison.
@@ -327,55 +401,111 @@ def prompt_user_for_download() -> bool:
 
 def start_ui(
     pid_callback: Callable[[int], None],
-    host: str = "localhost",
     port: int = 3000,
     open_browser: bool = True,
     auto_download: bool = False,
     start_backend: bool = False,
-    backend_host: str = "localhost",
     backend_port: int = 8000,
+    start_mcp: bool = False,
+    mcp_port: int = 8001,
 ) -> Optional[subprocess.Popen]:
     """
-    Start the cognee frontend UI server, optionally with the backend API server.
+    Start the cognee frontend UI server, optionally with the backend API server and MCP server.
 
     This function will:
     1. Optionally start the cognee backend API server
-    2. Find the cognee-frontend directory (development) or download it (pip install)
-    3. Check if Node.js and npm are available (for development mode)
-    4. Install dependencies if needed (development mode)
-    5. Start the frontend server
-    6. Optionally open the browser
+    2. Optionally start the cognee MCP server
+    3. Find the cognee-frontend directory (development) or download it (pip install)
+    4. Check if Node.js and npm are available (for development mode)
+    5. Install dependencies if needed (development mode)
+    6. Start the frontend server
+    7. Optionally open the browser
 
     Args:
         pid_callback: Callback to notify with PID of each spawned process
-        host: Host to bind the frontend server to (default: localhost)
         port: Port to run the frontend server on (default: 3000)
         open_browser: Whether to open the browser automatically (default: True)
         auto_download: If True, download frontend without prompting (default: False)
         start_backend: If True, also start the cognee API backend server (default: False)
-        backend_host: Host to bind the backend server to (default: localhost)
         backend_port: Port to run the backend server on (default: 8000)
+        start_mcp: If True, also start the cognee MCP server (default: False)
+        mcp_port: Port to run the MCP server on (default: 8001)
 
     Returns:
         subprocess.Popen object representing the running frontend server, or None if failed
-        Note: If backend is started, it runs in a separate process that will be cleaned up
-        when the frontend process is terminated.
+        Note: If backend and/or MCP server are started, they run in separate processes
+        that will be cleaned up when the frontend process is terminated.
 
     Example:
         >>> import cognee
+        >>> def dummy_callback(pid): pass
         >>> # Start just the frontend
-        >>> server = cognee.start_ui()
+        >>> server = cognee.start_ui(dummy_callback)
         >>>
         >>> # Start both frontend and backend
-        >>> server = cognee.start_ui(start_backend=True)
+        >>> server = cognee.start_ui(dummy_callback, start_backend=True)
         >>> # UI will be available at http://localhost:3000
         >>> # API will be available at http://localhost:8000
-        >>> # To stop both servers later:
+        >>>
+        >>> # Start frontend with MCP server
+        >>> server = cognee.start_ui(dummy_callback, start_mcp=True)
+        >>> # UI will be available at http://localhost:3000
+        >>> # MCP server will be available at http://127.0.0.1:8001/sse
+        >>> # To stop all servers later:
         >>> server.terminate()
     """
     logger.info("Starting cognee UI...")
+
+    ports_to_check = [(port, "Frontend UI")]
+
+    if start_backend:
+        ports_to_check.append((backend_port, "Backend API"))
+
+    if start_mcp:
+        ports_to_check.append((mcp_port, "MCP Server"))
+
+    logger.info("Checking port availability...")
+    all_ports_available, unavailable_services = _check_required_ports(ports_to_check)
+
+    if not all_ports_available:
+        error_msg = f"Cannot start cognee UI: The following services have ports already in use: {', '.join(unavailable_services)}"
+        logger.error(error_msg)
+        logger.error("Please stop the conflicting services or change the port configuration.")
+        return None
+
+    logger.info("✓ All required ports are available")
     backend_process = None
 
+    if start_mcp:
+        logger.info("Starting Cognee MCP server with Docker...")
+        cwd = os.getcwd()
+        env_file = os.path.join(cwd, ".env")
+        try:
+            mcp_process = subprocess.Popen(
+                [
+                    "docker",
+                    "run",
+                    "-p",
+                    f"{mcp_port}:8000",
+                    "--rm",
+                    "--env-file",
+                    env_file,
+                    "-e",
+                    "TRANSPORT_MODE=sse",
+                    "cognee/cognee-mcp:daulet-dev",
+                ],
+                stdout=subprocess.PIPE,
+                stderr=subprocess.PIPE,
+                preexec_fn=os.setsid if hasattr(os, "setsid") else None,
+            )
+
+            _stream_process_output(mcp_process, "stdout", "[MCP]", "\033[34m")  # Blue
+            _stream_process_output(mcp_process, "stderr", "[MCP]", "\033[34m")  # Blue
+
+            pid_callback(mcp_process.pid)
+            logger.info(f"✓ Cognee MCP server starting on http://127.0.0.1:{mcp_port}/sse")
+        except Exception as e:
+            logger.error(f"Failed to start MCP server with Docker: {str(e)}")
     # Start backend server if requested
     if start_backend:
         logger.info("Starting cognee backend API server...")
@@ -389,16 +519,19 @@ def start_ui(
                     "uvicorn",
                     "cognee.api.client:app",
                     "--host",
-                    backend_host,
+                    "localhost",
                     "--port",
                     str(backend_port),
                 ],
-                # Inherit stdout/stderr from parent process to show logs
-                stdout=None,
-                stderr=None,
+                stdout=subprocess.PIPE,
+                stderr=subprocess.PIPE,
                 preexec_fn=os.setsid if hasattr(os, "setsid") else None,
             )
 
+            # Start threads to stream backend output with prefix
+            _stream_process_output(backend_process, "stdout", "[BACKEND]", "\033[32m")  # Green
+            _stream_process_output(backend_process, "stderr", "[BACKEND]", "\033[32m")  # Green
+
             pid_callback(backend_process.pid)
 
             # Give the backend a moment to start
@@ -408,7 +541,7 @@ def start_ui(
                 logger.error("Backend server failed to start - process exited early")
                 return None
 
-            logger.info(f"✓ Backend API started at http://{backend_host}:{backend_port}")
+            logger.info(f"✓ Backend API started at http://localhost:{backend_port}")
 
         except Exception as e:
             logger.error(f"Failed to start backend server: {str(e)}")
@@ -453,11 +586,11 @@ def start_ui(
 
     # Prepare environment variables
     env = os.environ.copy()
-    env["HOST"] = host
+    env["HOST"] = "localhost"
     env["PORT"] = str(port)
 
     # Start the development server
-    logger.info(f"Starting frontend server at http://{host}:{port}")
+    logger.info(f"Starting frontend server at http://localhost:{port}")
     logger.info("This may take a moment to compile and start...")
 
     try:
@@ -468,10 +601,13 @@ def start_ui(
             env=env,
             stdout=subprocess.PIPE,
             stderr=subprocess.PIPE,
-            text=True,
             preexec_fn=os.setsid if hasattr(os, "setsid") else None,
         )
 
+        # Start threads to stream frontend output with prefix
+        _stream_process_output(process, "stdout", "[FRONTEND]", "\033[33m")  # Yellow
+        _stream_process_output(process, "stderr", "[FRONTEND]", "\033[33m")  # Yellow
+
         pid_callback(process.pid)
 
         # Give it a moment to start up
@@ -479,10 +615,7 @@ def start_ui(
 
         # Check if process is still running
         if process.poll() is not None:
-            stdout, stderr = process.communicate()
-            logger.error("Frontend server failed to start:")
-            logger.error(f"stdout: {stdout}")
-            logger.error(f"stderr: {stderr}")
+            logger.error("Frontend server failed to start - check the logs above for details")
             return None
 
         # Open browser if requested
@@ -491,7 +624,7 @@ def start_ui(
             def open_browser_delayed():
                 time.sleep(5)  # Give Next.js time to fully start
                 try:
-                    webbrowser.open(f"http://{host}:{port}")  # TODO: use dashboard url?
+                    webbrowser.open(f"http://localhost:{port}")
                 except Exception as e:
                     logger.warning(f"Could not open browser automatically: {e}")
 
@@ -499,13 +632,9 @@ def start_ui(
             browser_thread.start()
 
         logger.info("✓ Cognee UI is starting up...")
-        logger.info(f"✓ Open your browser to: http://{host}:{port}")
+        logger.info(f"✓ Open your browser to: http://localhost:{port}")
         logger.info("✓ The UI will be available once Next.js finishes compiling")
 
-        # Store backend process reference in the frontend process for cleanup
-        if backend_process:
-            process._cognee_backend_process = backend_process
-
         return process
 
     except Exception as e:
@@ -523,102 +652,3 @@ def start_ui(
                 except (OSError, ProcessLookupError):
                     pass
         return None
-
-
-def stop_ui(process: subprocess.Popen) -> bool:
-    """
-    Stop a running UI server process and backend process (if started), along with all their children.
-
-    Args:
-        process: The subprocess.Popen object returned by start_ui()
-
-    Returns:
-        bool: True if stopped successfully, False otherwise
-    """
-    if not process:
-        return False
-
-    success = True
-
-    try:
-        # First, stop the backend process if it exists
-        backend_process = getattr(process, "_cognee_backend_process", None)
-        if backend_process:
-            logger.info("Stopping backend server...")
-            try:
-                backend_process.terminate()
-                try:
-                    backend_process.wait(timeout=5)
-                    logger.info("Backend server stopped gracefully")
-                except subprocess.TimeoutExpired:
-                    logger.warning("Backend didn't terminate gracefully, forcing kill")
-                    backend_process.kill()
-                    backend_process.wait()
-                    logger.info("Backend server stopped")
-            except Exception as e:
-                logger.error(f"Error stopping backend server: {str(e)}")
-                success = False
-
-        # Now stop the frontend process
-        logger.info("Stopping frontend server...")
-        # Try to terminate the process group (includes child processes like Next.js)
-        if hasattr(os, "killpg"):
-            try:
-                # Kill the entire process group
-                os.killpg(os.getpgid(process.pid), signal.SIGTERM)
-                logger.debug("Sent SIGTERM to process group")
-            except (OSError, ProcessLookupError):
-                # Fall back to terminating just the main process
-                process.terminate()
-                logger.debug("Terminated main process only")
-        else:
-            process.terminate()
-            logger.debug("Terminated main process (Windows)")
-
-        try:
-            process.wait(timeout=10)
-            logger.info("Frontend server stopped gracefully")
-        except subprocess.TimeoutExpired:
-            logger.warning("Frontend didn't terminate gracefully, forcing kill")
-
-            # Force kill the process group
-            if hasattr(os, "killpg"):
-                try:
-                    os.killpg(os.getpgid(process.pid), signal.SIGKILL)
-                    logger.debug("Sent SIGKILL to process group")
-                except (OSError, ProcessLookupError):
-                    process.kill()
-                    logger.debug("Force killed main process only")
-            else:
-                process.kill()
-                logger.debug("Force killed main process (Windows)")
-
-            process.wait()
-
-        if success:
-            logger.info("UI servers stopped successfully")
-
-        return success
-
-    except Exception as e:
-        logger.error(f"Error stopping UI servers: {str(e)}")
-        return False
-
-
-# Convenience function similar to DuckDB's approach
-def ui() -> Optional[subprocess.Popen]:
-    """
-    Convenient alias for start_ui() with default parameters.
-    Similar to how DuckDB provides simple ui() function.
-    """
-    return start_ui()
-
-
-if __name__ == "__main__":
-    # Test the UI startup
-    server = start_ui()
-    if server:
-        try:
-            input("Press Enter to stop the server...")
-        finally:
-            stop_ui(server)

cognee/cli/_cognee.py

@@ -204,19 +204,27 @@ def main() -> int:
                 nonlocal spawned_pids
                 spawned_pids.append(pid)
 
+            frontend_port = 3000
+            start_backend, backend_port = True, 8000
+            start_mcp, mcp_port = True, 8001
             server_process = start_ui(
-                host="localhost",
-                port=3000,
-                open_browser=True,
-                start_backend=True,
-                auto_download=True,
                 pid_callback=pid_callback,
+                port=frontend_port,
+                open_browser=True,
+                auto_download=True,
+                start_backend=start_backend,
+                backend_port=backend_port,
+                start_mcp=start_mcp,
+                mcp_port=mcp_port,
             )
 
             if server_process:
                 fmt.success("UI server started successfully!")
-                fmt.echo("The interface is available at: http://localhost:3000")
-                fmt.echo("The API backend is available at: http://localhost:8000")
+                fmt.echo(f"The interface is available at: http://localhost:{frontend_port}")
+                if start_backend:
+                    fmt.echo(f"The API backend is available at: http://localhost:{backend_port}")
+                if start_mcp:
+                    fmt.echo(f"The MCP server is available at: http://localhost:{mcp_port}")
                 fmt.note("Press Ctrl+C to stop the server...")
 
                 try:

cognee/eval_framework/modal_eval_dashboard.py

@@ -1,6 +1,6 @@
 import os
 import json
-import pandas as pd
+
 import subprocess
 import modal
 import streamlit as st
@@ -78,6 +78,14 @@ def main():
             }
         )
 
+    try:
+        import pandas as pd
+    except ImportError:
+        st.error(
+            "Pandas is required for the evaluation dashboard. Install with 'pip install cognee\"[evals]\"' to use this feature."
+        )
+        return
+
     df = pd.DataFrame(records)
     if df.empty:
         st.warning("No JSON files found in the volume.")

cognee/infrastructure/data/utils/extract_keywords.py

@@ -1,48 +0,0 @@
-from sklearn.feature_extraction.text import TfidfVectorizer
-
-from cognee.infrastructure.data.exceptions.exceptions import KeywordExtractionError
-from cognee.shared.utils import extract_pos_tags
-
-
-def extract_keywords(text: str) -> list[str]:
-    """
-    Extract keywords from the provided text string.
-
-    This function raises an KeyWordExtractionError if the input text is empty. It processes the
-    text to extract parts of speech, focusing on nouns, and uses TF-IDF to identify the most
-    relevant keywords based on their frequency. The function returns a list of up to 15
-    keywords, each having more than 3 characters.
-
-    Parameters:
-    -----------
-
-        - text (str): The input text from which to extract keywords.
-
-    Returns:
-    --------
-
-        - list[str]: A list of keywords extracted from the text, containing up to 15 nouns
-          with more than 3 characters.
-    """
-    if len(text) == 0:
-        raise KeywordExtractionError()
-
-    tags = extract_pos_tags(text)
-    nouns = [word for (word, tag) in tags if tag == "NN"]
-
-    vectorizer = TfidfVectorizer()
-    tfidf = vectorizer.fit_transform(nouns)
-
-    top_nouns = sorted(
-        vectorizer.vocabulary_, key=lambda x: tfidf[0, vectorizer.vocabulary_[x]], reverse=True
-    )
-
-    keywords = []
-
-    for word in top_nouns:
-        if len(word) > 3:
-            keywords.append(word)
-        if len(keywords) >= 15:
-            break
-
-    return keywords

cognee/infrastructure/databases/relational/create_relational_engine.py

@@ -39,8 +39,16 @@ def create_relational_engine(
         connection_string = f"sqlite+aiosqlite:///{db_path}/{db_name}"
 
     if db_provider == "postgres":
-        connection_string = (
-            f"postgresql+asyncpg://{db_username}:{db_password}@{db_host}:{db_port}/{db_name}"
-        )
+        try:
+            # Test if asyncpg is available
+            import asyncpg
+
+            connection_string = (
+                f"postgresql+asyncpg://{db_username}:{db_password}@{db_host}:{db_port}/{db_name}"
+            )
+        except ImportError:
+            raise ImportError(
+                "PostgreSQL dependencies are not installed. Please install with 'pip install cognee\"[postgres]\"' or 'pip install cognee\"[postgres-binary]\"' to use PostgreSQL functionality."
+            )
 
     return SQLAlchemyAdapter(connection_string)

cognee/infrastructure/databases/vector/create_vector_engine.py

@@ -66,7 +66,12 @@ def create_vector_engine(
             f"postgresql+asyncpg://{db_username}:{db_password}@{db_host}:{db_port}/{db_name}"
         )
 
-        from .pgvector.PGVectorAdapter import PGVectorAdapter
+        try:
+            from .pgvector.PGVectorAdapter import PGVectorAdapter
+        except ImportError:
+            raise ImportError(
+                "PostgreSQL dependencies are not installed. Please install with 'pip install cognee\"[postgres]\"' or 'pip install cognee\"[postgres-binary]\"' to use PGVector functionality."
+            )
 
         return PGVectorAdapter(
             connection_string,

cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py

@@ -205,9 +205,12 @@ class LanceDBAdapter(VectorDBInterface):
         collection = await self.get_collection(collection_name)
 
         if len(data_point_ids) == 1:
-            results = await collection.query().where(f"id = '{data_point_ids[0]}'").to_pandas()
+            results = await collection.query().where(f"id = '{data_point_ids[0]}'")
         else:
-            results = await collection.query().where(f"id IN {tuple(data_point_ids)}").to_pandas()
+            results = await collection.query().where(f"id IN {tuple(data_point_ids)}")
+
+        # Convert query results to list format
+        results_list = results.to_list() if hasattr(results, "to_list") else list(results)
 
         return [
             ScoredResult(
@@ -215,7 +218,7 @@ class LanceDBAdapter(VectorDBInterface):
                 payload=result["payload"],
                 score=0,
             )
-            for result in results.to_dict("index").values()
+            for result in results_list
         ]
 
     async def search(
@@ -242,9 +245,7 @@ class LanceDBAdapter(VectorDBInterface):
         if limit == 0:
             return []
 
-        results = await collection.vector_search(query_vector).limit(limit).to_pandas()
-
-        result_values = list(results.to_dict("index").values())
+        result_values = await collection.vector_search(query_vector).limit(limit).to_list()
 
         if not result_values:
             return []

cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py

@@ -9,7 +9,6 @@ from sqlalchemy.exc import ProgrammingError
 from tenacity import retry, retry_if_exception_type, stop_after_attempt, wait_exponential
 from asyncpg import DeadlockDetectedError, DuplicateTableError, UniqueViolationError
 
-
 from cognee.shared.logging_utils import get_logger
 from cognee.infrastructure.engine import DataPoint
 from cognee.infrastructure.engine.utils import parse_id

cognee/infrastructure/files/storage/S3FileStorage.py

@@ -1,6 +1,5 @@
 import os
-import s3fs
-from typing import BinaryIO, Union
+from typing import BinaryIO, Union, TYPE_CHECKING
 from contextlib import asynccontextmanager
 
 from cognee.infrastructure.files.storage.s3_config import get_s3_config
@@ -8,23 +7,34 @@ from cognee.infrastructure.utils.run_async import run_async
 from cognee.infrastructure.files.storage.FileBufferedReader import FileBufferedReader
 from .storage import Storage
 
+if TYPE_CHECKING:
+    import s3fs
+
 
 class S3FileStorage(Storage):
     """
-    Manage local file storage operations such as storing, retrieving, and managing files on
-    the filesystem.
+    Manage S3 file storage operations such as storing, retrieving, and managing files on
+    S3-compatible storage.
     """
 
     storage_path: str
-    s3: s3fs.S3FileSystem
+    s3: "s3fs.S3FileSystem"
 
     def __init__(self, storage_path: str):
+        try:
+            import s3fs
+        except ImportError:
+            raise ImportError(
+                's3fs is required for S3FileStorage. Install it with: pip install cognee"[aws]"'
+            )
+
         self.storage_path = storage_path
         s3_config = get_s3_config()
         if s3_config.aws_access_key_id is not None and s3_config.aws_secret_access_key is not None:
             self.s3 = s3fs.S3FileSystem(
                 key=s3_config.aws_access_key_id,
                 secret=s3_config.aws_secret_access_key,
+                token=s3_config.aws_session_token,
                 anon=False,
                 endpoint_url=s3_config.aws_endpoint_url,
                 client_kwargs={"region_name": s3_config.aws_region},

cognee/infrastructure/files/storage/s3_config.py

@@ -8,6 +8,7 @@ class S3Config(BaseSettings):
     aws_endpoint_url: Optional[str] = None
     aws_access_key_id: Optional[str] = None
     aws_secret_access_key: Optional[str] = None
+    aws_session_token: Optional[str] = None
     model_config = SettingsConfigDict(env_file=".env", extra="allow")
 
 

cognee/infrastructure/files/utils/open_data_file.py

@@ -4,7 +4,6 @@ from urllib.parse import urlparse
 from contextlib import asynccontextmanager
 
 from cognee.infrastructure.files.utils.get_data_file_path import get_data_file_path
-from cognee.infrastructure.files.storage.S3FileStorage import S3FileStorage
 from cognee.infrastructure.files.storage.LocalFileStorage import LocalFileStorage
 
 
@@ -23,23 +22,17 @@ async def open_data_file(file_path: str, mode: str = "rb", encoding: str = None,
             yield file
 
     elif file_path.startswith("s3://"):
+        try:
+            from cognee.infrastructure.files.storage.S3FileStorage import S3FileStorage
+        except ImportError:
+            raise ImportError(
+                "S3 dependencies are not installed. Please install with 'pip install cognee\"[aws]\"' to use S3 functionality."
+            )
+
         normalized_url = get_data_file_path(file_path)
         s3_dir_path = os.path.dirname(normalized_url)
         s3_filename = os.path.basename(normalized_url)
 
-        # if "/" in s3_path:
-        #     s3_dir = "/".join(s3_path.split("/")[:-1])
-        #     s3_filename = s3_path.split("/")[-1]
-        # else:
-        #     s3_dir = ""
-        #     s3_filename = s3_path
-
-        # Extract filesystem path from S3 URL structure
-        # file_dir_path = (
-        #     f"s3://{parsed_url.netloc}/{s3_dir}" if s3_dir else f"s3://{parsed_url.netloc}"
-        # )
-        # file_name = s3_filename
-
         file_storage = S3FileStorage(s3_dir_path)
 
         async with file_storage.open(s3_filename, mode=mode, **kwargs) as file:

cognee/infrastructure/llm/config.py

@@ -1,9 +1,13 @@
 import os
-from typing import Optional, ClassVar
+from typing import Optional, ClassVar, Any
 from functools import lru_cache
 from pydantic_settings import BaseSettings, SettingsConfigDict
 from pydantic import model_validator
-from baml_py import ClientRegistry
+
+try:
+    from baml_py import ClientRegistry
+except ImportError:
+    ClientRegistry = None
 
 
 class LLMConfig(BaseSettings):
@@ -65,27 +69,36 @@ class LLMConfig(BaseSettings):
     fallback_endpoint: str = ""
     fallback_model: str = ""
 
-    baml_registry: ClassVar[ClientRegistry] = ClientRegistry()
+    baml_registry: Optional[Any] = None
 
     model_config = SettingsConfigDict(env_file=".env", extra="allow")
 
     def model_post_init(self, __context) -> None:
         """Initialize the BAML registry after the model is created."""
-        raw_options = {
-            "model": self.baml_llm_model,
-            "temperature": self.baml_llm_temperature,
-            "api_key": self.baml_llm_api_key,
-            "base_url": self.baml_llm_endpoint,
-            "api_version": self.baml_llm_api_version,
-        }
+        # Check if BAML is selected as structured output framework but not available
+        if self.structured_output_framework.lower() == "baml" and ClientRegistry is None:
+            raise ImportError(
+                "BAML is selected as structured output framework but not available. "
+                "Please install with 'pip install cognee\"[baml]\"' to use BAML extraction features."
+            )
+        elif self.structured_output_framework.lower() == "baml" and ClientRegistry is not None:
+            self.baml_registry = ClientRegistry()
 
-        # Note: keep the item only when the value is not None or an empty string (they would override baml default values)
-        options = {k: v for k, v in raw_options.items() if v not in (None, "")}
-        self.baml_registry.add_llm_client(
-            name=self.baml_llm_provider, provider=self.baml_llm_provider, options=options
-        )
-        # Sets the primary client
-        self.baml_registry.set_primary(self.baml_llm_provider)
+            raw_options = {
+                "model": self.baml_llm_model,
+                "temperature": self.baml_llm_temperature,
+                "api_key": self.baml_llm_api_key,
+                "base_url": self.baml_llm_endpoint,
+                "api_version": self.baml_llm_api_version,
+            }
+
+            # Note: keep the item only when the value is not None or an empty string (they would override baml default values)
+            options = {k: v for k, v in raw_options.items() if v not in (None, "")}
+            self.baml_registry.add_llm_client(
+                name=self.baml_llm_provider, provider=self.baml_llm_provider, options=options
+            )
+            # Sets the primary client
+            self.baml_registry.set_primary(self.baml_llm_provider)
 
     @model_validator(mode="after")
     def ensure_env_vars_for_ollama(self) -> "LLMConfig":

cognee/infrastructure/llm/structured_output_framework/baml/baml_src/extraction/acreate_structured_output.py

@@ -53,7 +53,8 @@ async def acreate_structured_output(
 
     # Transform BAML response to proper pydantic reponse model
     if response_model is str:
-        return str(result)
+        # Note: when a response model is set to string in python, result is stored in text property in the BAML response model
+        return str(result.text)
     return response_model.model_validate(result.dict())
 
 

cognee/modules/ingestion/data_types/TextData.py

@@ -1,7 +1,6 @@
 from typing import BinaryIO
 from contextlib import asynccontextmanager
 import hashlib
-from cognee.infrastructure.data.utils.extract_keywords import extract_keywords
 from .IngestionData import IngestionData
 
 

cognee/modules/retrieval/context_providers/TripletSearchContextProvider.py

@@ -42,14 +42,12 @@ class TripletSearchContextProvider(BaseContextProvider):
         self,
         entities: List[DataPoint],
         query: str,
-        user: User,
         memory_fragment: CogneeGraph,
     ) -> List:
         """Creates search tasks for valid entities."""
         tasks = [
             brute_force_triplet_search(
                 query=f"{entity_text} {query}",
-                user=user,
                 top_k=self.top_k,
                 collections=self.collections,
                 properties_to_project=self.properties_to_project,
@@ -84,9 +82,8 @@ class TripletSearchContextProvider(BaseContextProvider):
         if not entities:
             return "No entities provided for context search."
 
-        user = await get_default_user()
         memory_fragment = await get_memory_fragment(self.properties_to_project)
-        search_tasks = self._get_search_tasks(entities, query, user, memory_fragment)
+        search_tasks = self._get_search_tasks(entities, query, memory_fragment)
 
         if not search_tasks:
             return "No valid entities found for context search."

cognee/modules/retrieval/graph_completion_retriever.py

@@ -93,11 +93,8 @@ class GraphCompletionRetriever(BaseGraphRetriever):
                         for field_name in index_fields:
                             vector_index_collections.append(f"{subclass.__name__}_{field_name}")
 
-        user = await get_default_user()
-
         found_triplets = await brute_force_triplet_search(
             query,
-            user=user,
             top_k=self.top_k,
             collections=vector_index_collections or None,
             node_type=self.node_type,

cognee/modules/retrieval/utils/brute_force_triplet_search.py

@@ -89,7 +89,6 @@ async def get_memory_fragment(
 
 async def brute_force_triplet_search(
     query: str,
-    user: User,
     top_k: int = 5,
     collections: Optional[List[str]] = None,
     properties_to_project: Optional[List[str]] = None,
@@ -102,7 +101,6 @@ async def brute_force_triplet_search(
 
     Args:
         query (str): The search query.
-        user (User): The user performing the search.
         top_k (int): The number of top results to retrieve.
         collections (Optional[List[str]]): List of collections to query.
         properties_to_project (Optional[List[str]]): List of properties to project.
@@ -139,8 +137,6 @@ async def brute_force_triplet_search(
 
     query_vector = (await vector_engine.embedding_engine.embed_text([query]))[0]
 
-    send_telemetry("cognee.brute_force_triplet_search EXECUTION STARTED", user.id)
-
     async def search_in_collection(collection_name: str):
         try:
             return await vector_engine.search(
@@ -176,20 +172,14 @@ async def brute_force_triplet_search(
 
         results = await memory_fragment.calculate_top_triplet_importances(k=top_k)
 
-        send_telemetry("cognee.brute_force_triplet_search EXECUTION COMPLETED", user.id)
-
         return results
 
     except CollectionNotFoundError:
         return []
     except Exception as error:
         logger.error(
-            "Error during brute force search for user: %s, query: %s. Error: %s",
-            user.id,
+            "Error during brute force search for query: %s. Error: %s",
             query,
             error,
         )
-        send_telemetry(
-            "cognee.brute_force_triplet_search EXECUTION FAILED", user.id, {"error": str(error)}
-        )
         raise error

cognee/modules/search/methods/no_access_control_search.py

@@ -35,7 +35,7 @@ async def no_access_control_search(
         [get_completion, get_context] = search_tools
 
         if only_context:
-            return await get_context(query_text)
+            return None, await get_context(query_text), []
 
         context = await get_context(query_text)
         result = await get_completion(query_text, context)

cognee/modules/search/methods/search.py

@@ -143,20 +143,35 @@ async def search(
                 context = prepared_search_results["context"]
                 datasets = prepared_search_results["datasets"]
 
-                return_value.append(
-                    {
-                        "search_result": [result] if result else None,
-                        "dataset_id": datasets[0].id,
-                        "dataset_name": datasets[0].name,
-                        "graphs": graphs,
-                    }
-                )
+                if only_context:
+                    return_value.append(
+                        {
+                            "search_result": [context] if context else None,
+                            "dataset_id": datasets[0].id,
+                            "dataset_name": datasets[0].name,
+                            "graphs": graphs,
+                        }
+                    )
+                else:
+                    return_value.append(
+                        {
+                            "search_result": [result] if result else None,
+                            "dataset_id": datasets[0].id,
+                            "dataset_name": datasets[0].name,
+                            "graphs": graphs,
+                        }
+                    )
             return return_value
         else:
             return_value = []
-            for search_result in search_results:
-                result, context, datasets = search_result
-                return_value.append(result)
+            if only_context:
+                for search_result in search_results:
+                    prepared_search_results = await prepare_search_result(search_result)
+                    return_value.append(prepared_search_results["context"])
+            else:
+                for search_result in search_results:
+                    result, context, datasets = search_result
+                    return_value.append(result)
             # For maintaining backwards compatibility
             if len(return_value) == 1 and isinstance(return_value[0], list):
                 return return_value[0]

cognee/modules/visualization/cognee_network_visualization.py

@@ -1,6 +1,5 @@
 import os
 import json
-import networkx
 
 from cognee.shared.logging_utils import get_logger
 from cognee.infrastructure.files.storage.LocalFileStorage import LocalFileStorage
@@ -9,6 +8,8 @@ logger = get_logger()
 
 
 async def cognee_network_visualization(graph_data, destination_file_path: str = None):
+    import networkx
+
     nodes_data, edges_data = graph_data
 
     G = networkx.DiGraph()
@@ -22,6 +23,9 @@ async def cognee_network_visualization(graph_data, destination_file_path: str =
         "TableRow": "#f47710",
         "TableType": "#6510f4",
         "ColumnValue": "#13613a",
+        "SchemaTable": "#f47710",
+        "DatabaseSchema": "#6510f4",
+        "SchemaRelationship": "#13613a",
         "default": "#D3D3D3",
     }
 
@@ -104,7 +108,7 @@ async def cognee_network_visualization(graph_data, destination_file_path: str =
             .nodes circle { stroke: white; stroke-width: 0.5px; filter: drop-shadow(0 0 5px rgba(255,255,255,0.3)); }
             .node-label { font-size: 5px; font-weight: bold; fill: white; text-anchor: middle; dominant-baseline: middle; font-family: 'Inter', sans-serif; pointer-events: none; }
             .edge-label { font-size: 3px; fill: rgba(255, 255, 255, 0.7); text-anchor: middle; dominant-baseline: middle; font-family: 'Inter', sans-serif; pointer-events: none; }
-            
+
             .tooltip {
                 position: absolute;
                 text-align: left;
@@ -166,7 +170,7 @@ async def cognee_network_visualization(graph_data, destination_file_path: str =
                     // Create tooltip content for edge
                     var content = "<strong>Edge Information</strong><br/>";
                     content += "Relationship: " + d.relation + "<br/>";
-                    
+
                     // Show all weights
                     if (d.all_weights && Object.keys(d.all_weights).length > 0) {
                         content += "<strong>Weights:</strong><br/>";
@@ -176,23 +180,23 @@ async def cognee_network_visualization(graph_data, destination_file_path: str =
                     } else if (d.weight !== null && d.weight !== undefined) {
                         content += "Weight: " + d.weight + "<br/>";
                     }
-                    
+
                     if (d.relationship_type) {
                         content += "Type: " + d.relationship_type + "<br/>";
                     }
-                    
+
                     // Add other edge properties
                     if (d.edge_info) {
                         Object.keys(d.edge_info).forEach(function(key) {
-                            if (key !== 'weight' && key !== 'weights' && key !== 'relationship_type' && 
-                                key !== 'source_node_id' && key !== 'target_node_id' && 
-                                key !== 'relationship_name' && key !== 'updated_at' && 
+                            if (key !== 'weight' && key !== 'weights' && key !== 'relationship_type' &&
+                                key !== 'source_node_id' && key !== 'target_node_id' &&
+                                key !== 'relationship_name' && key !== 'updated_at' &&
                                 !key.startsWith('weight_')) {
                                 content += key + ": " + d.edge_info[key] + "<br/>";
                             }
                         });
                     }
-                    
+
                     tooltip.html(content)
                         .style("left", (d3.event.pageX + 10) + "px")
                         .style("top", (d3.event.pageY - 10) + "px")

cognee/shared/utils.py

@@ -4,7 +4,6 @@ import os
 import ssl
 import requests
 from datetime import datetime, timezone
-import matplotlib.pyplot as plt
 import http.server
 import socketserver
 from threading import Thread
@@ -30,37 +29,6 @@ def create_secure_ssl_context() -> ssl.SSLContext:
     return ssl.create_default_context()
 
 
-def get_entities(tagged_tokens):
-    import nltk
-
-    nltk.download("maxent_ne_chunker", quiet=True)
-
-    from nltk.chunk import ne_chunk
-
-    return ne_chunk(tagged_tokens)
-
-
-def extract_pos_tags(sentence):
-    """Extract Part-of-Speech (POS) tags for words in a sentence."""
-    import nltk
-
-    # Ensure that the necessary NLTK resources are downloaded
-    nltk.download("words", quiet=True)
-    nltk.download("punkt", quiet=True)
-    nltk.download("averaged_perceptron_tagger", quiet=True)
-
-    from nltk.tag import pos_tag
-    from nltk.tokenize import word_tokenize
-
-    # Tokenize the sentence into words
-    tokens = word_tokenize(sentence)
-
-    # Tag each word with its corresponding POS tag
-    pos_tags = pos_tag(tokens)
-
-    return pos_tags
-
-
 def get_anonymous_id():
     """Creates or reads a anonymous user id"""
     tracking_id = os.getenv("TRACKING_ID", None)

cognee/tasks/graph/infer_data_ontology.py

@@ -1,309 +0,0 @@
-# PROPOSED TO BE DEPRECATED
-
-"""This module contains the OntologyEngine class which is responsible for adding graph ontology from a JSON or CSV file."""
-
-import csv
-import json
-from cognee.shared.logging_utils import get_logger
-from datetime import datetime, timezone
-from fastapi import status
-from typing import Any, Dict, List, Optional, Union, Type
-
-import aiofiles
-import pandas as pd
-from pydantic import BaseModel
-
-from cognee.modules.graph.exceptions import EntityNotFoundError
-from cognee.modules.ingestion.exceptions import IngestionError
-
-from cognee.infrastructure.data.chunking.config import get_chunk_config
-from cognee.infrastructure.data.chunking.get_chunking_engine import get_chunk_engine
-from cognee.infrastructure.databases.graph.get_graph_engine import get_graph_engine
-from cognee.infrastructure.files.utils.extract_text_from_file import extract_text_from_file
-from cognee.infrastructure.files.utils.guess_file_type import guess_file_type, FileTypeException
-from cognee.modules.data.methods.add_model_class_to_graph import (
-    add_model_class_to_graph,
-)
-from cognee.tasks.graph.models import NodeModel, GraphOntology
-from cognee.shared.data_models import KnowledgeGraph
-from cognee.modules.engine.utils import generate_node_id, generate_node_name
-from cognee.infrastructure.llm.LLMGateway import LLMGateway
-
-logger = get_logger("task:infer_data_ontology")
-
-
-async def extract_ontology(content: str, response_model: Type[BaseModel]):
-    """
-    Extracts structured ontology from the provided content using a pre-defined LLM client.
-
-    This asynchronous function retrieves a system prompt from a file and utilizes an LLM
-    client to create a structured output based on the input content and specified response
-    model.
-
-    Parameters:
-    -----------
-
-        - content (str): The content from which to extract the ontology.
-        - response_model (Type[BaseModel]): The model that defines the structure of the
-          output ontology.
-
-    Returns:
-    --------
-
-        The structured ontology extracted from the content.
-    """
-
-    system_prompt = LLMGateway.read_query_prompt("extract_ontology.txt")
-
-    ontology = await LLMGateway.acreate_structured_output(content, system_prompt, response_model)
-
-    return ontology
-
-
-class OntologyEngine:
-    """
-    Manage ontology data and operations for graph structures, providing methods for data
-    loading, flattening models, and adding ontological relationships to a graph database.
-
-    Public methods:
-
-    - flatten_model
-    - recursive_flatten
-    - load_data
-    - add_graph_ontology
-    """
-
-    async def flatten_model(
-        self, model: NodeModel, parent_id: Optional[str] = None
-    ) -> Dict[str, Any]:
-        """
-        Flatten the model to a dictionary including optional parent ID and relationship details
-        if available.
-
-        Parameters:
-        -----------
-
-            - model (NodeModel): The NodeModel instance to flatten.
-            - parent_id (Optional[str]): An optional ID of the parent node for hierarchical
-              purposes. (default None)
-
-        Returns:
-        --------
-
-            - Dict[str, Any]: A dictionary representation of the model with flattened
-              attributes.
-        """
-        result = model.dict()
-        result["parent_id"] = parent_id
-        if model.default_relationship:
-            result.update(
-                {
-                    "relationship_type": model.default_relationship.type,
-                    "relationship_source": model.default_relationship.source,
-                    "relationship_target": model.default_relationship.target,
-                }
-            )
-        return result
-
-    async def recursive_flatten(
-        self, items: Union[List[Dict[str, Any]], Dict[str, Any]], parent_id: Optional[str] = None
-    ) -> List[Dict[str, Any]]:
-        """
-        Recursively flatten a hierarchical structure of models into a flat list of dictionaries.
-
-        Parameters:
-        -----------
-
-            - items (Union[List[Dict[str, Any]], Dict[str, Any]]): A list or dictionary
-              containing models to flatten.
-            - parent_id (Optional[str]): An optional ID of the parent node to maintain hierarchy
-              during flattening. (default None)
-
-        Returns:
-        --------
-
-            - List[Dict[str, Any]]: A flat list of dictionaries representing the hierarchical
-              model structure.
-        """
-        flat_list = []
-
-        if isinstance(items, list):
-            for item in items:
-                flat_list.extend(await self.recursive_flatten(item, parent_id))
-        elif isinstance(items, dict):
-            model = NodeModel.model_validate(items)
-            flat_list.append(await self.flatten_model(model, parent_id))
-            for child in model.children:
-                flat_list.extend(await self.recursive_flatten(child, model.node_id))
-        return flat_list
-
-    async def load_data(self, file_path: str) -> Union[List[Dict[str, Any]], Dict[str, Any]]:
-        """
-        Load data from a specified JSON or CSV file and return it in a structured format.
-
-        Parameters:
-        -----------
-
-            - file_path (str): The path to the file to load data from.
-
-        Returns:
-        --------
-
-            - Union[List[Dict[str, Any]], Dict[str, Any]]: Parsed data from the file as either a
-              list of dictionaries or a single dictionary depending on content type.
-        """
-        try:
-            if file_path.endswith(".json"):
-                async with aiofiles.open(file_path, mode="r") as f:
-                    data = await f.read()
-                    return json.loads(data)
-            elif file_path.endswith(".csv"):
-                async with aiofiles.open(file_path, mode="r") as f:
-                    content = await f.read()
-                    reader = csv.DictReader(content.splitlines())
-                    return list(reader)
-            else:
-                raise IngestionError(message="Unsupported file format")
-        except Exception as e:
-            raise IngestionError(
-                message=f"Failed to load data from {file_path}: {e}",
-                status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
-            )
-
-    async def add_graph_ontology(self, file_path: str = None, documents: list = None):
-        """
-        Add graph ontology from a JSON or CSV file, or infer relationships from provided
-        document content. Raise exceptions for invalid file types or missing entities.
-
-        Parameters:
-        -----------
-
-            - file_path (str): Optional path to a file containing data to be loaded. (default
-              None)
-            - documents (list): Optional list of document objects for content extraction if no
-              file path is provided. (default None)
-        """
-        if file_path is None:
-            initial_chunks_and_ids = []
-
-            chunk_config = get_chunk_config()
-            chunk_engine = get_chunk_engine()
-            chunk_strategy = chunk_config.chunk_strategy
-
-            for base_file in documents:
-                with open(base_file.raw_data_location, "rb") as file:
-                    try:
-                        file_type = guess_file_type(file)
-                        text = extract_text_from_file(file, file_type)
-
-                        subchunks, chunks_with_ids = chunk_engine.chunk_data(
-                            chunk_strategy,
-                            text,
-                            chunk_config.chunk_size,
-                            chunk_config.chunk_overlap,
-                        )
-
-                        if chunks_with_ids[0][0] == 1:
-                            initial_chunks_and_ids.append({base_file.id: chunks_with_ids})
-
-                    except FileTypeException:
-                        logger.warning(
-                            "File (%s) has an unknown file type. We are skipping it.", file["id"]
-                        )
-
-            ontology = await extract_ontology(str(initial_chunks_and_ids), GraphOntology)
-            graph_client = await get_graph_engine()
-
-            await graph_client.add_nodes(
-                [
-                    (
-                        node.id,
-                        dict(
-                            uuid=generate_node_id(node.id),
-                            name=generate_node_name(node.name),
-                            type=generate_node_id(node.id),
-                            description=node.description,
-                            updated_at=datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S"),
-                        ),
-                    )
-                    for node in ontology.nodes
-                ]
-            )
-
-            await graph_client.add_edges(
-                (
-                    generate_node_id(edge.source_id),
-                    generate_node_id(edge.target_id),
-                    edge.relationship_type,
-                    dict(
-                        source_node_id=generate_node_id(edge.source_id),
-                        target_node_id=generate_node_id(edge.target_id),
-                        relationship_name=edge.relationship_type,
-                        updated_at=datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S"),
-                    ),
-                )
-                for edge in ontology.edges
-            )
-
-        else:
-            dataset_level_information = documents[0][1]
-
-            # Extract the list of valid IDs from the explanations
-            valid_ids = {item["id"] for item in dataset_level_information}
-            try:
-                data = await self.load_data(file_path)
-                flt_ontology = await self.recursive_flatten(data)
-                df = pd.DataFrame(flt_ontology)
-                graph_client = await get_graph_engine()
-
-                for _, row in df.iterrows():
-                    node_data = row.to_dict()
-                    node_id = node_data.pop("node_id", None)
-                    if node_id in valid_ids:
-                        await graph_client.add_node(node_id, node_data)
-                    if node_id not in valid_ids:
-                        raise EntityNotFoundError(
-                            message=f"Node ID {node_id} not found in the dataset"
-                        )
-                    if pd.notna(row.get("relationship_source")) and pd.notna(
-                        row.get("relationship_target")
-                    ):
-                        await graph_client.add_edge(
-                            row["relationship_source"],
-                            row["relationship_target"],
-                            relationship_name=row["relationship_type"],
-                            edge_properties={
-                                "source_node_id": row["relationship_source"],
-                                "target_node_id": row["relationship_target"],
-                                "relationship_name": row["relationship_type"],
-                                "updated_at": datetime.now(timezone.utc).strftime(
-                                    "%Y-%m-%d %H:%M:%S"
-                                ),
-                            },
-                        )
-
-                return
-            except Exception as e:
-                raise RuntimeError(f"Failed to add graph ontology from {file_path}: {e}") from e
-
-
-async def infer_data_ontology(documents, ontology_model=KnowledgeGraph, root_node_id=None):
-    """
-    Infer data ontology from provided documents and optionally add it to a graph.
-
-    Parameters:
-    -----------
-
-        - documents: The documents from which to infer the ontology.
-        - ontology_model: The ontology model to use for the inference, defaults to
-          KnowledgeGraph. (default KnowledgeGraph)
-        - root_node_id: An optional root node identifier for the ontology. (default None)
-    """
-    if ontology_model == KnowledgeGraph:
-        ontology_engine = OntologyEngine()
-        root_node_id = await ontology_engine.add_graph_ontology(documents=documents)
-    else:
-        graph_engine = await get_graph_engine()
-        await add_model_class_to_graph(ontology_model, graph_engine)
-
-    yield (documents, root_node_id)

cognee/tasks/ingestion/migrate_relational_database.py

@@ -4,16 +4,20 @@ from sqlalchemy import text
 from cognee.infrastructure.databases.relational.get_migration_relational_engine import (
     get_migration_relational_engine,
 )
+from cognee.infrastructure.databases.relational.config import get_migration_config
 
 from cognee.tasks.storage.index_data_points import index_data_points
 from cognee.tasks.storage.index_graph_edges import index_graph_edges
+from cognee.tasks.schema.ingest_database_schema import ingest_database_schema
 
 from cognee.modules.engine.models import TableRow, TableType, ColumnValue
 
 logger = logging.getLogger(__name__)
 
 
-async def migrate_relational_database(graph_db, schema, migrate_column_data=True):
+async def migrate_relational_database(
+    graph_db, schema, migrate_column_data=True, schema_only=False
+):
     """
     Migrates data from a relational database into a graph database.
 
@@ -26,11 +30,133 @@ async def migrate_relational_database(graph_db, schema, migrate_column_data=True
 
     Both TableType and TableRow inherit from DataPoint to maintain consistency with Cognee data model.
     """
+    # Create a mapping of node_id to node objects for referencing in edge creation
+    if schema_only:
+        node_mapping, edge_mapping = await schema_only_ingestion(schema)
+
+    else:
+        node_mapping, edge_mapping = await complete_database_ingestion(schema, migrate_column_data)
+
+    def _remove_duplicate_edges(edge_mapping):
+        seen = set()
+        unique_original_shape = []
+
+        for tup in edge_mapping:
+            # We go through all the tuples in the edge_mapping and we only add unique tuples to the list
+            # To eliminate duplicate edges.
+            source_id, target_id, rel_name, rel_dict = tup
+            # We need to convert the dictionary to a frozenset to be able to compare values for it
+            rel_dict_hashable = frozenset(sorted(rel_dict.items()))
+            hashable_tup = (source_id, target_id, rel_name, rel_dict_hashable)
+
+            # We use the seen set to keep track of unique edges
+            if hashable_tup not in seen:
+                # A list that has frozensets elements instead of dictionaries is needed to be able to compare values
+                seen.add(hashable_tup)
+                # append the original tuple shape (with the dictionary) if it's the first time we see it
+                unique_original_shape.append(tup)
+
+        return unique_original_shape
+
+    # Add all nodes and edges to the graph
+    # NOTE: Nodes and edges have to be added in batch for speed optimization, Especially for NetworkX.
+    #       If we'd create nodes and add them to graph in real time the process would take too long.
+    #       Every node and edge added to NetworkX is saved to file which is very slow when not done in batches.
+    await graph_db.add_nodes(list(node_mapping.values()))
+    await graph_db.add_edges(_remove_duplicate_edges(edge_mapping))
+
+    # In these steps we calculate the vector embeddings of our nodes and edges and save them to vector database
+    # Cognee uses this information to perform searches on the knowledge graph.
+    await index_data_points(list(node_mapping.values()))
+    await index_graph_edges()
+
+    logger.info("Data successfully migrated from relational database to desired graph database.")
+    return await graph_db.get_graph_data()
+
+
+async def schema_only_ingestion(schema):
+    node_mapping = {}
+    edge_mapping = []
+
+    # Calling the ingest_database_schema function to return DataPoint subclasses
+    result = await ingest_database_schema(
+        schema=schema,
+        max_sample_rows=5,
+    )
+    database_schema = result["database_schema"]
+    schema_tables = result["schema_tables"]
+    schema_relationships = result["relationships"]
+    database_node_id = database_schema.id
+    node_mapping[database_node_id] = database_schema
+    for table in schema_tables:
+        table_node_id = table.id
+        # Add TableSchema Datapoint as a node.
+        node_mapping[table_node_id] = table
+        edge_mapping.append(
+            (
+                table_node_id,
+                database_node_id,
+                "is_part_of",
+                dict(
+                    source_node_id=table_node_id,
+                    target_node_id=database_node_id,
+                    relationship_name="is_part_of",
+                ),
+            )
+        )
+    table_name_to_id = {t.name: t.id for t in schema_tables}
+    for rel in schema_relationships:
+        source_table_id = table_name_to_id.get(rel.source_table)
+        target_table_id = table_name_to_id.get(rel.target_table)
+
+        relationship_id = rel.id
+
+        # Add RelationshipTable DataPoint as a node.
+        node_mapping[relationship_id] = rel
+        edge_mapping.append(
+            (
+                source_table_id,
+                relationship_id,
+                "has_relationship",
+                dict(
+                    source_node_id=source_table_id,
+                    target_node_id=relationship_id,
+                    relationship_name=rel.relationship_type,
+                ),
+            )
+        )
+        edge_mapping.append(
+            (
+                relationship_id,
+                target_table_id,
+                "has_relationship",
+                dict(
+                    source_node_id=relationship_id,
+                    target_node_id=target_table_id,
+                    relationship_name=rel.relationship_type,
+                ),
+            )
+        )
+        edge_mapping.append(
+            (
+                source_table_id,
+                target_table_id,
+                rel.relationship_type,
+                dict(
+                    source_node_id=source_table_id,
+                    target_node_id=target_table_id,
+                    relationship_name=rel.relationship_type,
+                ),
+            )
+        )
+    return node_mapping, edge_mapping
+
+
+async def complete_database_ingestion(schema, migrate_column_data):
     engine = get_migration_relational_engine()
     # Create a mapping of node_id to node objects for referencing in edge creation
     node_mapping = {}
     edge_mapping = []
-
     async with engine.engine.begin() as cursor:
         # First, create table type nodes for all tables
         for table_name, details in schema.items():
@@ -38,7 +164,7 @@ async def migrate_relational_database(graph_db, schema, migrate_column_data=True
             table_node = TableType(
                 id=uuid5(NAMESPACE_OID, name=table_name),
                 name=table_name,
-                description=f"Table: {table_name}",
+                description=f'Relational database table with the following name: "{table_name}".',
             )
 
             # Add TableType node to mapping ( node will be added to the graph later based on this mapping )
@@ -75,7 +201,7 @@ async def migrate_relational_database(graph_db, schema, migrate_column_data=True
                     name=node_id,
                     is_a=table_node,
                     properties=str(row_properties),
-                    description=f"Row in {table_name} with {primary_key_col}={primary_key_value}",
+                    description=f'Row in relational database table from the table with the name: "{table_name}" with the following row data {str(row_properties)} where the dictionary key value is the column name and the value is the column value. This row has the id of: {node_id}',
                 )
 
                 # Store the node object in our mapping
@@ -113,7 +239,7 @@ async def migrate_relational_database(graph_db, schema, migrate_column_data=True
                             id=uuid5(NAMESPACE_OID, name=column_node_id),
                             name=column_node_id,
                             properties=f"{key} {value} {table_name}",
-                            description=f"Column name={key} and value={value} from column from table={table_name}",
+                            description=f"column from relational database table={table_name}. Column name={key} and value={value}. The value of the column is related to the following row with this id: {row_node.id}. This column has the following ID: {column_node_id}",
                         )
                         node_mapping[column_node_id] = column_node
 
@@ -180,39 +306,4 @@ async def migrate_relational_database(graph_db, schema, migrate_column_data=True
                             ),
                         )
                     )
-
-    def _remove_duplicate_edges(edge_mapping):
-        seen = set()
-        unique_original_shape = []
-
-        for tup in edge_mapping:
-            # We go through all the tuples in the edge_mapping and we only add unique tuples to the list
-            # To eliminate duplicate edges.
-            source_id, target_id, rel_name, rel_dict = tup
-            # We need to convert the dictionary to a frozenset to be able to compare values for it
-            rel_dict_hashable = frozenset(sorted(rel_dict.items()))
-            hashable_tup = (source_id, target_id, rel_name, rel_dict_hashable)
-
-            # We use the seen set to keep track of unique edges
-            if hashable_tup not in seen:
-                # A list that has frozensets elements instead of dictionaries is needed to be able to compare values
-                seen.add(hashable_tup)
-                # append the original tuple shape (with the dictionary) if it's the first time we see it
-                unique_original_shape.append(tup)
-
-        return unique_original_shape
-
-    # Add all nodes and edges to the graph
-    # NOTE: Nodes and edges have to be added in batch for speed optimization, Especially for NetworkX.
-    #       If we'd create nodes and add them to graph in real time the process would take too long.
-    #       Every node and edge added to NetworkX is saved to file which is very slow when not done in batches.
-    await graph_db.add_nodes(list(node_mapping.values()))
-    await graph_db.add_edges(_remove_duplicate_edges(edge_mapping))
-
-    # In these steps we calculate the vector embeddings of our nodes and edges and save them to vector database
-    # Cognee uses this information to perform searches on the knowledge graph.
-    await index_data_points(list(node_mapping.values()))
-    await index_graph_edges()
-
-    logger.info("Data successfully migrated from relational database to desired graph database.")
-    return await graph_db.get_graph_data()
+        return node_mapping, edge_mapping

cognee/tasks/ingestion/resolve_data_directories.py

@@ -32,7 +32,10 @@ async def resolve_data_directories(
         import s3fs
 
         fs = s3fs.S3FileSystem(
-            key=s3_config.aws_access_key_id, secret=s3_config.aws_secret_access_key, anon=False
+            key=s3_config.aws_access_key_id,
+            secret=s3_config.aws_secret_access_key,
+            token=s3_config.aws_session_token,
+            anon=False,
         )
 
     for item in data:

cognee/tasks/schema/ingest_database_schema.py

@@ -0,0 +1,134 @@
+from typing import List, Dict
+from uuid import uuid5, NAMESPACE_OID
+from cognee.infrastructure.engine.models.DataPoint import DataPoint
+from sqlalchemy import text
+from cognee.tasks.schema.models import DatabaseSchema, SchemaTable, SchemaRelationship
+from cognee.infrastructure.databases.relational.get_migration_relational_engine import (
+    get_migration_relational_engine,
+)
+from cognee.infrastructure.databases.relational.config import get_migration_config
+from datetime import datetime, timezone
+
+
+async def ingest_database_schema(
+    schema,
+    max_sample_rows: int = 0,
+) -> Dict[str, List[DataPoint] | DataPoint]:
+    """
+    Extract database schema metadata (optionally with sample data) and return DataPoint models for graph construction.
+
+    Args:
+        schema: Database schema
+        max_sample_rows: Maximum sample rows per table (0 means no sampling)
+
+    Returns:
+        Dict with keys:
+            "database_schema": DatabaseSchema
+            "schema_tables": List[SchemaTable]
+            "relationships": List[SchemaRelationship]
+    """
+
+    tables = {}
+    sample_data = {}
+    schema_tables = []
+    schema_relationships = []
+
+    migration_config = get_migration_config()
+    engine = get_migration_relational_engine()
+    qi = engine.engine.dialect.identifier_preparer.quote
+    try:
+        max_sample_rows = max(0, int(max_sample_rows))
+    except (TypeError, ValueError):
+        max_sample_rows = 0
+
+    def qname(name: str):
+        split_name = name.split(".")
+        return ".".join(qi(p) for p in split_name)
+
+    async with engine.engine.begin() as cursor:
+        for table_name, details in schema.items():
+            tn = qname(table_name)
+            if max_sample_rows > 0:
+                rows_result = await cursor.execute(
+                    text(f"SELECT * FROM {tn} LIMIT :limit;"),  # noqa: S608 - tn is fully quoted
+                    {"limit": max_sample_rows},
+                )
+                rows = [dict(r) for r in rows_result.mappings().all()]
+            else:
+                rows = []
+
+            if engine.engine.dialect.name == "postgresql":
+                if "." in table_name:
+                    schema_part, table_part = table_name.split(".", 1)
+                else:
+                    schema_part, table_part = "public", table_name
+                estimate = await cursor.execute(
+                    text(
+                        "SELECT reltuples::bigint AS estimate "
+                        "FROM pg_class c "
+                        "JOIN pg_namespace n ON n.oid = c.relnamespace "
+                        "WHERE n.nspname = :schema AND c.relname = :table"
+                    ),
+                    {"schema": schema_part, "table": table_part},
+                )
+                row_count_estimate = estimate.scalar() or 0
+            else:
+                count_result = await cursor.execute(text(f"SELECT COUNT(*) FROM {tn};"))  # noqa: S608 - tn is fully quoted
+                row_count_estimate = count_result.scalar()
+
+            schema_table = SchemaTable(
+                id=uuid5(NAMESPACE_OID, name=f"{table_name}"),
+                name=table_name,
+                columns=details["columns"],
+                primary_key=details.get("primary_key"),
+                foreign_keys=details.get("foreign_keys", []),
+                sample_rows=rows,
+                row_count_estimate=row_count_estimate,
+                description=f"Relational database table with '{table_name}' with {len(details['columns'])} columns and approx. {row_count_estimate} rows."
+                f"Here are the columns this table contains: {details['columns']}"
+                f"Here are a few sample_rows to show the contents of the table: {rows}"
+                f"Table is part of the database: {migration_config.migration_db_name}",
+            )
+            schema_tables.append(schema_table)
+            tables[table_name] = details
+            sample_data[table_name] = rows
+
+            for fk in details.get("foreign_keys", []):
+                ref_table_fq = fk["ref_table"]
+                if "." not in ref_table_fq and "." in table_name:
+                    ref_table_fq = f"{table_name.split('.', 1)[0]}.{ref_table_fq}"
+
+                relationship_name = (
+                    f"{table_name}:{fk['column']}->{ref_table_fq}:{fk['ref_column']}"
+                )
+                relationship = SchemaRelationship(
+                    id=uuid5(NAMESPACE_OID, name=relationship_name),
+                    name=relationship_name,
+                    source_table=table_name,
+                    target_table=ref_table_fq,
+                    relationship_type="foreign_key",
+                    source_column=fk["column"],
+                    target_column=fk["ref_column"],
+                    description=f"Relational database table foreign key relationship between: {table_name}.{fk['column']} → {ref_table_fq}.{fk['ref_column']}"
+                    f"This foreing key relationship between table columns is a part of the following database: {migration_config.migration_db_name}",
+                )
+                schema_relationships.append(relationship)
+
+    id_str = f"{migration_config.migration_db_provider}:{migration_config.migration_db_name}"
+    database_schema = DatabaseSchema(
+        id=uuid5(NAMESPACE_OID, name=id_str),
+        name=migration_config.migration_db_name,
+        database_type=migration_config.migration_db_provider,
+        tables=tables,
+        sample_data=sample_data,
+        extraction_timestamp=datetime.now(timezone.utc),
+        description=f"Database schema containing {len(schema_tables)} tables and {len(schema_relationships)} relationships. "
+        f"The database type is {migration_config.migration_db_provider}."
+        f"The database contains the following tables: {tables}",
+    )
+
+    return {
+        "database_schema": database_schema,
+        "schema_tables": schema_tables,
+        "relationships": schema_relationships,
+    }

cognee/tasks/schema/models.py

@@ -0,0 +1,41 @@
+from cognee.infrastructure.engine.models.DataPoint import DataPoint
+from typing import List, Dict, Optional
+from datetime import datetime
+
+
+class DatabaseSchema(DataPoint):
+    """Represents a complete database schema with sample data"""
+
+    name: str
+    database_type: str  # sqlite, postgres, etc.
+    tables: Dict[str, Dict]  # Reuse existing schema format from SqlAlchemyAdapter
+    sample_data: Dict[str, List[Dict]]  # Limited examples per table
+    extraction_timestamp: datetime
+    description: str
+    metadata: dict = {"index_fields": ["description", "name"]}
+
+
+class SchemaTable(DataPoint):
+    """Represents an individual table schema with relationships"""
+
+    name: str
+    columns: List[Dict]  # Column definitions with types
+    primary_key: Optional[str]
+    foreign_keys: List[Dict]  # Foreign key relationships
+    sample_rows: List[Dict]  # Max 3-5 example rows
+    row_count_estimate: Optional[int]  # Actual table size
+    description: str
+    metadata: dict = {"index_fields": ["description", "name"]}
+
+
+class SchemaRelationship(DataPoint):
+    """Represents relationships between tables"""
+
+    name: str
+    source_table: str
+    target_table: str
+    relationship_type: str  # "foreign_key", "one_to_many", etc.
+    source_column: str
+    target_column: str
+    description: str
+    metadata: dict = {"index_fields": ["description", "name"]}

cognee/tests/test_relational_db_migration.py

@@ -197,6 +197,80 @@ async def relational_db_migration():
     print(f"All checks passed for {graph_db_provider} provider with '{relationship_label}' edges!")
 
 
+async def test_schema_only_migration():
+    # 1. Setup test DB and extract schema
+    migration_engine = await setup_test_db()
+    schema = await migration_engine.extract_schema()
+
+    # 2. Setup graph engine
+    graph_engine = await get_graph_engine()
+
+    # 4. Migrate schema only
+    await migrate_relational_database(graph_engine, schema=schema, schema_only=True)
+
+    # 5. Verify number of tables through search
+    search_results = await cognee.search(
+        query_text="How many tables are there in this database",
+        query_type=cognee.SearchType.GRAPH_COMPLETION,
+        top_k=30,
+    )
+    assert any("11" in r for r in search_results), (
+        "Number of tables in the database reported in search_results is either None or not equal to 11"
+    )
+
+    graph_db_provider = os.getenv("GRAPH_DATABASE_PROVIDER", "networkx").lower()
+
+    edge_counts = {
+        "is_part_of": 0,
+        "has_relationship": 0,
+        "foreign_key": 0,
+    }
+
+    if graph_db_provider == "neo4j":
+        for rel_type in edge_counts.keys():
+            query_str = f"""
+            MATCH ()-[r:{rel_type}]->()
+            RETURN count(r) as c
+            """
+            rows = await graph_engine.query(query_str)
+            edge_counts[rel_type] = rows[0]["c"]
+
+    elif graph_db_provider == "kuzu":
+        for rel_type in edge_counts.keys():
+            query_str = f"""
+            MATCH ()-[r:EDGE]->()
+            WHERE r.relationship_name = '{rel_type}'
+            RETURN count(r) as c
+            """
+            rows = await graph_engine.query(query_str)
+            edge_counts[rel_type] = rows[0][0]
+
+    elif graph_db_provider == "networkx":
+        nodes, edges = await graph_engine.get_graph_data()
+        for _, _, key, _ in edges:
+            if key in edge_counts:
+                edge_counts[key] += 1
+
+    else:
+        raise ValueError(f"Unsupported graph database provider: {graph_db_provider}")
+
+    # 7. Assert counts match expected values
+    expected_counts = {
+        "is_part_of": 11,
+        "has_relationship": 22,
+        "foreign_key": 11,
+    }
+
+    for rel_type, expected in expected_counts.items():
+        actual = edge_counts[rel_type]
+        assert actual == expected, (
+            f"Expected {expected} edges for relationship '{rel_type}', but found {actual}"
+        )
+
+    print("Schema-only migration edge counts validated successfully!")
+    print(f"Edge counts: {edge_counts}")
+
+
 async def test_migration_sqlite():
     database_to_migrate_path = os.path.join(pathlib.Path(__file__).parent, "test_data/")
 
@@ -209,6 +283,7 @@ async def test_migration_sqlite():
     )
 
     await relational_db_migration()
+    await test_schema_only_migration()
 
 
 async def test_migration_postgres():
@@ -224,6 +299,7 @@ async def test_migration_postgres():
         }
     )
     await relational_db_migration()
+    await test_schema_only_migration()
 
 
 async def main():

cognee/tests/unit/modules/retrieval/graph_completion_retriever_context_extension_test.py

@@ -7,7 +7,6 @@ import cognee
 from cognee.low_level import setup, DataPoint
 from cognee.tasks.storage import add_data_points
 from cognee.modules.graph.utils import resolve_edges_to_text
-from cognee.infrastructure.databases.exceptions import DatabaseNotCreatedError
 from cognee.modules.retrieval.graph_completion_context_extension_retriever import (
     GraphCompletionContextExtensionRetriever,
 )
@@ -165,9 +164,6 @@ class TestGraphCompletionWithContextExtensionRetriever:
 
         retriever = GraphCompletionContextExtensionRetriever()
 
-        with pytest.raises(DatabaseNotCreatedError):
-            await retriever.get_context("Who works at Figma?")
-
         await setup()
 
         context = await retriever.get_context("Who works at Figma?")

cognee/tests/unit/modules/retrieval/graph_completion_retriever_cot_test.py

@@ -7,7 +7,6 @@ import cognee
 from cognee.low_level import setup, DataPoint
 from cognee.modules.graph.utils import resolve_edges_to_text
 from cognee.tasks.storage import add_data_points
-from cognee.infrastructure.databases.exceptions import DatabaseNotCreatedError
 from cognee.modules.retrieval.graph_completion_cot_retriever import GraphCompletionCotRetriever
 
 
@@ -158,9 +157,6 @@ class TestGraphCompletionCoTRetriever:
 
         retriever = GraphCompletionCotRetriever()
 
-        with pytest.raises(DatabaseNotCreatedError):
-            await retriever.get_context("Who works at Figma?")
-
         await setup()
 
         context = await retriever.get_context("Who works at Figma?")

cognee/tests/unit/modules/retrieval/graph_completion_retriever_test.py

@@ -7,7 +7,6 @@ import cognee
 from cognee.low_level import setup, DataPoint
 from cognee.modules.graph.utils import resolve_edges_to_text
 from cognee.tasks.storage import add_data_points
-from cognee.infrastructure.databases.exceptions import DatabaseNotCreatedError
 from cognee.modules.retrieval.graph_completion_retriever import GraphCompletionRetriever
 
 
@@ -218,9 +217,6 @@ class TestGraphCompletionRetriever:
 
         retriever = GraphCompletionRetriever()
 
-        with pytest.raises(DatabaseNotCreatedError):
-            await retriever.get_context("Who works at Figma?")
-
         await setup()
 
         context = await retriever.get_context("Who works at Figma?")

examples/python/graphiti_example.py

@@ -48,7 +48,6 @@ async def main():
     query = "When was Kamala Harris in office?"
     triplets = await brute_force_triplet_search(
         query=query,
-        user=user,
         top_k=3,
         collections=["graphitinode_content", "graphitinode_name", "graphitinode_summary"],
     )

examples/python/relational_database_migration_example.py

@@ -1,16 +1,15 @@
+from pathlib import Path
 import asyncio
-
-import cognee
 import os
 
+import cognee
+from cognee.infrastructure.databases.relational.config import get_migration_config
 from cognee.infrastructure.databases.graph import get_graph_engine
 from cognee.api.v1.visualize.visualize import visualize_graph
 from cognee.infrastructure.databases.relational import (
     get_migration_relational_engine,
 )
-
 from cognee.modules.search.types import SearchType
-
 from cognee.infrastructure.databases.relational import (
     create_db_and_tables as create_relational_db_and_tables,
 )
@@ -32,16 +31,29 @@ from cognee.infrastructure.databases.vector.pgvector import (
 
 
 async def main():
-    engine = get_migration_relational_engine()
-
     # Clean all data stored in Cognee
     await cognee.prune.prune_data()
     await cognee.prune.prune_system(metadata=True)
 
-    # Needed to create appropriate tables only on the Cognee side
+    # Needed to create appropriate database tables only on the Cognee side
     await create_relational_db_and_tables()
     await create_vector_db_and_tables()
 
+    # In case environment variables are not set use the example database from the Cognee repo
+    migration_db_provider = os.environ.get("MIGRATION_DB_PROVIDER", "sqlite")
+    migration_db_path = os.environ.get(
+        "MIGRATION_DB_PATH",
+        os.path.join(Path(__file__).resolve().parent.parent.parent, "cognee/tests/test_data"),
+    )
+    migration_db_name = os.environ.get("MIGRATION_DB_NAME", "migration_database.sqlite")
+
+    migration_config = get_migration_config()
+    migration_config.migration_db_provider = migration_db_provider
+    migration_config.migration_db_path = migration_db_path
+    migration_config.migration_db_name = migration_db_name
+
+    engine = get_migration_relational_engine()
+
     print("\nExtracting schema of database to migrate.")
     schema = await engine.extract_schema()
     print(f"Migrated database schema:\n{schema}")
@@ -53,10 +65,6 @@ async def main():
     await migrate_relational_database(graph, schema=schema)
     print("Relational database migration complete.")
 
-    # Define location where to store html visualization of graph of the migrated database
-    home_dir = os.path.expanduser("~")
-    destination_file_path = os.path.join(home_dir, "graph_visualization.html")
-
     # Make sure to set top_k at a high value for a broader search, the default value is only 10!
     # top_k represent the number of graph tripplets to supply to the LLM to answer your question
     search_results = await cognee.search(
@@ -69,13 +77,25 @@ async def main():
     # Having a top_k value set to too high might overwhelm the LLM context when specific questions need to be answered.
     # For this kind of question we've set the top_k to 30
     search_results = await cognee.search(
-        query_type=SearchType.GRAPH_COMPLETION_COT,
+        query_type=SearchType.GRAPH_COMPLETION,
         query_text="What invoices are related to Leonie Köhler?",
         top_k=30,
     )
     print(f"Search results: {search_results}")
 
-    # test.html is a file with visualized data migration
+    search_results = await cognee.search(
+        query_type=SearchType.GRAPH_COMPLETION,
+        query_text="What invoices are related to Luís Gonçalves?",
+        top_k=30,
+    )
+    print(f"Search results: {search_results}")
+
+    # If you check the relational database for this example you can see that the search results successfully found all
+    # the invoices related to the two customers, without any hallucinations or additional information
+
+    # Define location where to store html visualization of graph of the migrated database
+    home_dir = os.path.expanduser("~")
+    destination_file_path = os.path.join(home_dir, "graph_visualization.html")
     print("Adding html visualization of graph database after migration.")
     await visualize_graph(destination_file_path)
     print(f"Visualization can be found at: {destination_file_path}")

examples/start_ui_example.py

@@ -29,8 +29,11 @@ async def main():
     print("=" * 60)
 
     # Start the UI server
+    def dummy_callback(pid):
+        pass
+
     server = cognee.start_ui(
-        host="localhost",
+        pid_callback=dummy_callback,
         port=3000,
         open_browser=True,  # This will automatically open your browser
     )

poetry.lock

@@ -4,9 +4,10 @@
 name = "aiobotocore"
 version = "2.24.2"
 description = "Async client for aws services using botocore and aiohttp"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"aws\""
 files = [
     {file = "aiobotocore-2.24.2-py3-none-any.whl", hash = "sha256:808c63b2bd344b91e2f2acb874831118a9f53342d248acd16a68455a226e283a"},
     {file = "aiobotocore-2.24.2.tar.gz", hash = "sha256:dfb21bdb2610e8de4d22f401e91a24d50f1330a302d03c62c485757becd439a9"},
@@ -164,9 +165,10 @@ speedups = ["Brotli ; platform_python_implementation == \"CPython\"", "aiodns (>
 name = "aioitertools"
 version = "0.12.0"
 description = "itertools and builtins for AsyncIO and mixed iterables"
-optional = false
+optional = true
 python-versions = ">=3.8"
 groups = ["main"]
+markers = "extra == \"aws\""
 files = [
     {file = "aioitertools-0.12.0-py3-none-any.whl", hash = "sha256:fc1f5fac3d737354de8831cbba3eb04f79dd649d8f3afb4c5b114925e662a796"},
     {file = "aioitertools-0.12.0.tar.gz", hash = "sha256:c2a9055b4fbb7705f561b9d86053e8af5d10cc845d22c32008c43490b2d8dd6b"},
@@ -576,9 +578,10 @@ dev = ["backports.zoneinfo ; python_version < \"3.9\"", "freezegun (>=1.0,<2.0)"
 name = "backoff"
 version = "2.2.1"
 description = "Function decoration for backoff and retry"
-optional = false
+optional = true
 python-versions = ">=3.7,<4.0"
 groups = ["main"]
+markers = "extra == \"deepeval\" or extra == \"posthog\" or extra == \"chromadb\" or extra == \"docs\" or extra == \"monitoring\""
 files = [
     {file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
     {file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
@@ -609,9 +612,10 @@ extras = ["regex"]
 name = "baml-py"
 version = "0.206.0"
 description = "BAML python bindings (pyproject.toml)"
-optional = false
+optional = true
 python-versions = "*"
 groups = ["main"]
+markers = "extra == \"baml\""
 files = [
     {file = "baml_py-0.206.0-cp38-abi3-macosx_10_12_x86_64.whl", hash = "sha256:d9e95f0b481a18ae6936d720b8fc609baec4ea1eabbdde48f1536ffc94ebf39f"},
     {file = "baml_py-0.206.0-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:0f698127da030b728c7aa2641c3164a3ab19779594019234361dd48f0784f195"},
@@ -759,9 +763,10 @@ css = ["tinycss2 (>=1.1.0,<1.5)"]
 name = "boto3"
 version = "1.40.18"
 description = "The AWS SDK for Python"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"neptune\" or extra == \"aws\""
 files = [
     {file = "boto3-1.40.18-py3-none-any.whl", hash = "sha256:daa776ba1251a7458c9d6c7627873d0c2460c8e8272d35759065580e9193700a"},
     {file = "boto3-1.40.18.tar.gz", hash = "sha256:64301d39adecc154e3e595eaf0d4f28998ef0a5551f1d033aeac51a9e1a688e5"},
@@ -779,9 +784,10 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 name = "botocore"
 version = "1.40.18"
 description = "Low-level, data-driven core of boto 3."
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"neptune\" or extra == \"aws\""
 files = [
     {file = "botocore-1.40.18-py3-none-any.whl", hash = "sha256:57025c46ca00cf8cec25de07a759521bfbfb3036a0f69b272654a354615dc45f"},
     {file = "botocore-1.40.18.tar.gz", hash = "sha256:afd69bdadd8c55cc89d69de0799829e555193a352d87867f746e19020271cc0f"},
@@ -945,9 +951,10 @@ pycparser = {version = "*", markers = "implementation_name != \"PyPy\""}
 name = "cfgv"
 version = "3.4.0"
 description = "Validate configuration and produce human readable error messages."
-optional = false
+optional = true
 python-versions = ">=3.8"
 groups = ["main"]
+markers = "extra == \"dev\""
 files = [
     {file = "cfgv-3.4.0-py2.py3-none-any.whl", hash = "sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9"},
     {file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"},
@@ -1150,7 +1157,7 @@ description = "Cross-platform colored terminal text."
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 groups = ["main"]
-markers = "(platform_system == \"Windows\" or sys_platform == \"win32\" or os_name == \"nt\" or extra == \"llama-index\" or extra == \"dev\") and (platform_system == \"Windows\" or sys_platform == \"win32\" or extra == \"llama-index\" or extra == \"dev\" or extra == \"chromadb\") and (platform_system == \"Windows\" or python_version <= \"3.12\" or extra == \"notebook\" or extra == \"dev\" or extra == \"llama-index\" or extra == \"deepeval\" or extra == \"chromadb\") and (platform_system == \"Windows\" or extra == \"notebook\" or extra == \"dev\" or extra == \"llama-index\" or extra == \"deepeval\" or extra == \"chromadb\" or extra == \"codegraph\")"
+markers = "(platform_system == \"Windows\" or sys_platform == \"win32\" or extra == \"llama-index\" or extra == \"dev\" or os_name == \"nt\") and (platform_system == \"Windows\" or sys_platform == \"win32\" or extra == \"llama-index\" or extra == \"dev\" or extra == \"chromadb\")"
 files = [
     {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
@@ -1194,10 +1201,10 @@ test = ["pytest"]
 name = "contourpy"
 version = "1.3.2"
 description = "Python library for calculating contours of 2D quadrilateral grids"
-optional = false
+optional = true
 python-versions = ">=3.10"
 groups = ["main"]
-markers = "python_version == \"3.10\""
+markers = "python_version == \"3.10\" and extra == \"evals\""
 files = [
     {file = "contourpy-1.3.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ba38e3f9f330af820c4b27ceb4b9c7feee5fe0493ea53a8720f4792667465934"},
     {file = "contourpy-1.3.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:dc41ba0714aa2968d1f8674ec97504a8f7e334f48eeacebcaa6256213acb0989"},
@@ -1272,10 +1279,10 @@ test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist"
 name = "contourpy"
 version = "1.3.3"
 description = "Python library for calculating contours of 2D quadrilateral grids"
-optional = false
+optional = true
 python-versions = ">=3.11"
 groups = ["main"]
-markers = "python_version >= \"3.11\""
+markers = "python_version >= \"3.11\" and extra == \"evals\""
 files = [
     {file = "contourpy-1.3.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:709a48ef9a690e1343202916450bc48b9e51c049b089c7f79a267b46cffcdaa1"},
     {file = "contourpy-1.3.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:23416f38bfd74d5d28ab8429cc4d63fa67d5068bd711a85edb1c3fb0c3e2f381"},
@@ -1576,9 +1583,10 @@ files = [
 name = "cycler"
 version = "0.12.1"
 description = "Composable style cycles"
-optional = false
+optional = true
 python-versions = ">=3.8"
 groups = ["main"]
+markers = "extra == \"evals\""
 files = [
     {file = "cycler-0.12.1-py3-none-any.whl", hash = "sha256:85cef7cff222d8644161529808465972e51340599459b8ac3ccbac5a854e0d30"},
     {file = "cycler-0.12.1.tar.gz", hash = "sha256:88bb128f02ba341da8ef447245a9e138fae777f6a23943da4540077d3601eb1c"},
@@ -1847,9 +1855,10 @@ files = [
 name = "distlib"
 version = "0.4.0"
 description = "Distribution utilities"
-optional = false
+optional = true
 python-versions = "*"
 groups = ["main"]
+markers = "extra == \"dev\""
 files = [
     {file = "distlib-0.4.0-py2.py3-none-any.whl", hash = "sha256:9659f7d87e46584a30b5780e43ac7a2143098441670ff0a49d5f9034c54a6c16"},
     {file = "distlib-0.4.0.tar.gz", hash = "sha256:feec40075be03a04501a973d81f633735b4b69f98b05450592310c0f401a4e0d"},
@@ -1871,9 +1880,10 @@ files = [
 name = "dlt"
 version = "1.16.0"
 description = "dlt is an open-source python-first scalable data loading library that does not require any backend to run."
-optional = false
+optional = true
 python-versions = "<3.15,>=3.9.2"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "dlt-1.16.0-py3-none-any.whl", hash = "sha256:882ef281bbdc32eaba3b5ced984a8ed7014d8978fd7ab4a58b198023c8938c9f"},
     {file = "dlt-1.16.0.tar.gz", hash = "sha256:113d17a3f27aa4f41c3438b0b032a68d30db195d8415a471ba43a9502e971a21"},
@@ -2178,10 +2188,9 @@ sqlalchemy = {version = ">=2.0.0,<2.1.0", extras = ["asyncio"]}
 name = "fastembed"
 version = "0.6.0"
 description = "Fast, light, accurate library built for retrieval embedding generation"
-optional = true
+optional = false
 python-versions = ">=3.9.0"
 groups = ["main"]
-markers = "extra == \"codegraph\" and python_version <= \"3.12\""
 files = [
     {file = "fastembed-0.6.0-py3-none-any.whl", hash = "sha256:a08385e9388adea0529a586004f2d588c9787880a510e4e5d167127a11e75328"},
     {file = "fastembed-0.6.0.tar.gz", hash = "sha256:5c9ead25f23449535b07243bbe1f370b820dcc77ec2931e61674e3fe7ff24733"},
@@ -2194,8 +2203,12 @@ mmh3 = ">=4.1.0,<6.0.0"
 numpy = [
     {version = ">=1.21", markers = "python_version >= \"3.10\" and python_version < \"3.12\""},
     {version = ">=1.26", markers = "python_version == \"3.12\""},
+    {version = ">=2.1.0", markers = "python_version >= \"3.13\""},
+]
+onnxruntime = [
+    {version = ">=1.17.0,<1.20.0 || >1.20.0", markers = "python_version >= \"3.10\" and python_version < \"3.13\""},
+    {version = ">1.20.0", markers = "python_version >= \"3.13\""},
 ]
-onnxruntime = {version = ">=1.17.0,<1.20.0 || >1.20.0", markers = "python_version >= \"3.10\" and python_version < \"3.13\""}
 pillow = ">=10.3.0,<12.0.0"
 py-rust-stemmers = ">=0.1.0,<0.2.0"
 requests = ">=2.31,<3.0"
@@ -2241,6 +2254,7 @@ files = [
     {file = "fastuuid-0.12.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b9b31dd488d0778c36f8279b306dc92a42f16904cba54acca71e107d65b60b0c"},
     {file = "fastuuid-0.12.0-cp313-cp313-manylinux_2_34_x86_64.whl", hash = "sha256:b19361ee649365eefc717ec08005972d3d1eb9ee39908022d98e3bfa9da59e37"},
     {file = "fastuuid-0.12.0-cp313-cp313-win_amd64.whl", hash = "sha256:8fc66b11423e6f3e1937385f655bedd67aebe56a3dcec0cb835351cfe7d358c9"},
+    {file = "fastuuid-0.12.0-cp38-cp38-macosx_10_12_x86_64.whl", hash = "sha256:2925f67b88d47cb16aa3eb1ab20fdcf21b94d74490e0818c91ea41434b987493"},
     {file = "fastuuid-0.12.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:7b15c54d300279ab20a9cc0579ada9c9f80d1bc92997fc61fb7bf3103d7cb26b"},
     {file = "fastuuid-0.12.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:458f1bc3ebbd76fdb89ad83e6b81ccd3b2a99fa6707cd3650b27606745cfb170"},
     {file = "fastuuid-0.12.0-cp38-cp38-manylinux_2_34_x86_64.whl", hash = "sha256:a8f0f83fbba6dc44271a11b22e15838641b8c45612cdf541b4822a5930f6893c"},
@@ -2292,9 +2306,10 @@ files = [
 name = "fonttools"
 version = "4.60.0"
 description = "Tools to manipulate font files"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"evals\""
 files = [
     {file = "fonttools-4.60.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:151282a235c36024168c21c02193e939e8b28c73d5fa0b36ae1072671d8fa134"},
     {file = "fonttools-4.60.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:3f32cc42d485d9b1546463b9a7a92bdbde8aef90bac3602503e04c2ddb27e164"},
@@ -2581,9 +2596,10 @@ dev = ["flake8", "markdown", "twine", "wheel"]
 name = "gitdb"
 version = "4.0.12"
 description = "Git Object Database"
-optional = false
+optional = true
 python-versions = ">=3.7"
 groups = ["main"]
+markers = "extra == \"dlt\" or extra == \"dev\""
 files = [
     {file = "gitdb-4.0.12-py3-none-any.whl", hash = "sha256:67073e15955400952c6565cc3e707c554a4eea2e428946f7a4c162fab9bd9bcf"},
     {file = "gitdb-4.0.12.tar.gz", hash = "sha256:5ef71f855d191a3326fcfbc0d5da835f26b13fbcba60c32c21091c349ffdb571"},
@@ -2596,9 +2612,10 @@ smmap = ">=3.0.1,<6"
 name = "gitpython"
 version = "3.1.45"
 description = "GitPython is a Python library used to interact with Git repositories"
-optional = false
+optional = true
 python-versions = ">=3.7"
 groups = ["main"]
+markers = "extra == \"dlt\" or extra == \"dev\""
 files = [
     {file = "gitpython-3.1.45-py3-none-any.whl", hash = "sha256:8908cb2e02fb3b93b7eb0f2827125cb699869470432cc885f019b8fd0fccff77"},
     {file = "gitpython-3.1.45.tar.gz", hash = "sha256:85b0ee964ceddf211c41b9f27a49086010a190fd8132a24e21f362a4b36a791c"},
@@ -2615,9 +2632,10 @@ test = ["coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock ; python_version < \"3.
 name = "giturlparse"
 version = "0.12.0"
 description = "A Git URL parsing module (supports parsing and rewriting)"
-optional = false
+optional = true
 python-versions = ">=3.8"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "giturlparse-0.12.0-py2.py3-none-any.whl", hash = "sha256:412b74f2855f1da2fefa89fd8dde62df48476077a72fc19b62039554d27360eb"},
     {file = "giturlparse-0.12.0.tar.gz", hash = "sha256:c0fff7c21acc435491b1779566e038757a205c1ffdcb47e4f81ea52ad8c3859a"},
@@ -3110,9 +3128,10 @@ hyperframe = ">=6.1,<7"
 name = "hexbytes"
 version = "1.3.1"
 description = "hexbytes: Python `bytes` subclass that decodes hex, with a readable console output"
-optional = false
+optional = true
 python-versions = "<4,>=3.8"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "hexbytes-1.3.1-py3-none-any.whl", hash = "sha256:da01ff24a1a9a2b1881c4b85f0e9f9b0f51b526b379ffa23832ae7899d29c2c7"},
     {file = "hexbytes-1.3.1.tar.gz", hash = "sha256:a657eebebdfe27254336f98d8af6e2236f3f83aed164b87466b6cf6c5f5a4765"},
@@ -3371,9 +3390,10 @@ pyreadline3 = {version = "*", markers = "sys_platform == \"win32\" and python_ve
 name = "humanize"
 version = "4.13.0"
 description = "Python humanize utilities"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "humanize-4.13.0-py3-none-any.whl", hash = "sha256:b810820b31891813b1673e8fec7f1ed3312061eab2f26e3fa192c393d11ed25f"},
     {file = "humanize-4.13.0.tar.gz", hash = "sha256:78f79e68f76f0b04d711c4e55d32bebef5be387148862cb1ef83d2b58e7935a0"},
@@ -3399,9 +3419,10 @@ files = [
 name = "identify"
 version = "2.6.14"
 description = "File identification library for Python"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"dev\""
 files = [
     {file = "identify-2.6.14-py2.py3-none-any.whl", hash = "sha256:11a073da82212c6646b1f39bb20d4483bfb9543bd5566fec60053c4bb309bf2e"},
     {file = "identify-2.6.14.tar.gz", hash = "sha256:663494103b4f717cb26921c52f8751363dc89db64364cd836a9bf1535f53cd6a"},
@@ -3834,9 +3855,10 @@ files = [
 name = "jmespath"
 version = "1.0.1"
 description = "JSON Matching Expressions"
-optional = false
+optional = true
 python-versions = ">=3.7"
 groups = ["main"]
+markers = "extra == \"neptune\" or extra == \"aws\""
 files = [
     {file = "jmespath-1.0.1-py3-none-any.whl", hash = "sha256:02e2e4cc71b5bcab88332eebf907519190dd9e6e82107fa7f83b1003a6252980"},
     {file = "jmespath-1.0.1.tar.gz", hash = "sha256:90261b206d6defd58fdd5e85f478bf633a2901798906be2ad389150c5c60edbe"},
@@ -3846,9 +3868,10 @@ files = [
 name = "joblib"
 version = "1.5.2"
 description = "Lightweight pipelining with Python functions"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"llama-index\" or extra == \"docs\" or extra == \"evals\""
 files = [
     {file = "joblib-1.5.2-py3-none-any.whl", hash = "sha256:4e1f0bdbb987e6d843c70cf43714cb276623def372df3c22fe5266b2670bc241"},
     {file = "joblib-1.5.2.tar.gz", hash = "sha256:3faa5c39054b2f03ca547da9b2f52fde67c06240c31853f306aea97f13647b55"},
@@ -3902,9 +3925,10 @@ jsonpointer = ">=1.9"
 name = "jsonpath-ng"
 version = "1.7.0"
 description = "A final implementation of JSONPath for Python that aims to be standard compliant, including arithmetic and binary comparison operators and providing clear AST for metaprogramming."
-optional = false
+optional = true
 python-versions = "*"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "jsonpath-ng-1.7.0.tar.gz", hash = "sha256:f6f5f7fd4e5ff79c785f1573b394043b39849fb2bb47bcead935d12b00beab3c"},
 ]
@@ -4212,9 +4236,10 @@ test = ["hatch", "ipykernel", "openapi-core (>=0.18.0,<0.19.0)", "openapi-spec-v
 name = "kiwisolver"
 version = "1.4.9"
 description = "A fast implementation of the Cassowary constraint solver"
-optional = false
+optional = true
 python-versions = ">=3.10"
 groups = ["main"]
+markers = "extra == \"evals\""
 files = [
     {file = "kiwisolver-1.4.9-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:b4b4d74bda2b8ebf4da5bd42af11d02d04428b2c32846e4c2c93219df8a7987b"},
     {file = "kiwisolver-1.4.9-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:fb3b8132019ea572f4611d770991000d7f58127560c4889729248eb5852a102f"},
@@ -4555,9 +4580,10 @@ six = "*"
 name = "langfuse"
 version = "2.60.10"
 description = "A client library for accessing langfuse"
-optional = false
+optional = true
 python-versions = "<4.0,>=3.9"
 groups = ["main"]
+markers = "extra == \"monitoring\""
 files = [
     {file = "langfuse-2.60.10-py3-none-any.whl", hash = "sha256:815c6369194aa5b2a24f88eb9952f7c3fc863272c41e90642a71f3bc76f4a11f"},
     {file = "langfuse-2.60.10.tar.gz", hash = "sha256:a26d0d927a28ee01b2d12bb5b862590b643cc4e60a28de6e2b0c2cfff5dbfc6a"},
@@ -4776,10 +4802,9 @@ server = ["starlette (>=0.39.0)", "uvicorn (>=0.32.0)"]
 name = "loguru"
 version = "0.7.3"
 description = "Python logging made (stupidly) simple"
-optional = true
+optional = false
 python-versions = "<4.0,>=3.5"
 groups = ["main"]
-markers = "extra == \"codegraph\" and python_version <= \"3.12\""
 files = [
     {file = "loguru-0.7.3-py3-none-any.whl", hash = "sha256:31a33c10c8e1e10422bfd431aeb5d351c7cf7fa671e3c4df004162264b28220c"},
     {file = "loguru-0.7.3.tar.gz", hash = "sha256:19480589e77d47b8d85b2c827ad95d49bf31b0dcde16593892eb51dd18706eb6"},
@@ -5130,9 +5155,10 @@ tests = ["pytest", "simplejson"]
 name = "matplotlib"
 version = "3.10.6"
 description = "Python plotting package"
-optional = false
+optional = true
 python-versions = ">=3.10"
 groups = ["main"]
+markers = "extra == \"evals\""
 files = [
     {file = "matplotlib-3.10.6-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:bc7316c306d97463a9866b89d5cc217824e799fa0de346c8f68f4f3d27c8693d"},
     {file = "matplotlib-3.10.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d00932b0d160ef03f59f9c0e16d1e3ac89646f7785165ce6ad40c842db16cc2e"},
@@ -5491,10 +5517,9 @@ mkdocstrings = ">=0.26"
 name = "mmh3"
 version = "5.2.0"
 description = "Python extension for MurmurHash (MurmurHash3), a set of fast and robust hash functions."
-optional = true
+optional = false
 python-versions = ">=3.9"
 groups = ["main"]
-markers = "(extra == \"codegraph\" or extra == \"chromadb\") and (python_version <= \"3.12\" or extra == \"chromadb\")"
 files = [
     {file = "mmh3-5.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:81c504ad11c588c8629536b032940f2a359dda3b6cbfd4ad8f74cb24dcd1b0bc"},
     {file = "mmh3-5.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0b898cecff57442724a0f52bf42c2de42de63083a91008fb452887e372f9c328"},
@@ -6092,9 +6117,10 @@ test-extras = ["pytest-mpl", "pytest-randomly"]
 name = "nltk"
 version = "3.9.1"
 description = "Natural Language Toolkit"
-optional = false
+optional = true
 python-versions = ">=3.8"
 groups = ["main"]
+markers = "extra == \"llama-index\" or extra == \"docs\""
 files = [
     {file = "nltk-3.9.1-py3-none-any.whl", hash = "sha256:4fa26829c5b00715afe3061398a8989dc643b92ce7dd93fb4585a70930d168a1"},
     {file = "nltk-3.9.1.tar.gz", hash = "sha256:87d127bd3de4bd89a4f81265e5fa59cb1b199b27440175370f7417d2bc7ae868"},
@@ -6118,9 +6144,10 @@ twitter = ["twython"]
 name = "nodeenv"
 version = "1.9.1"
 description = "Node.js virtual environment builder"
-optional = false
+optional = true
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 groups = ["main"]
+markers = "extra == \"dev\""
 files = [
     {file = "nodeenv-1.9.1-py2.py3-none-any.whl", hash = "sha256:ba11c9782d29c27c70ffbdda2d7415098754709be8a7056d79a737cd901155c9"},
     {file = "nodeenv-1.9.1.tar.gz", hash = "sha256:6ec12890a2dab7946721edbfbcd91f3319c6ccc9aec47be7c7e6b7011ee6645f"},
@@ -6644,10 +6671,10 @@ test = ["pytest (>=8.3.0,<8.4.0)", "pytest-benchmark (>=5.1.0,<5.2.0)", "pytest-
 name = "orjson"
 version = "3.11.3"
 description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
-markers = "(sys_platform != \"emscripten\" or platform_python_implementation != \"PyPy\" or extra == \"chromadb\") and (sys_platform != \"emscripten\" or extra == \"neptune\" or extra == \"langchain\" or extra == \"chromadb\")"
+markers = "(sys_platform != \"emscripten\" or platform_python_implementation != \"PyPy\" or extra == \"chromadb\") and (sys_platform != \"emscripten\" or extra == \"neptune\" or extra == \"langchain\" or extra == \"chromadb\") and (platform_python_implementation != \"PyPy\" or extra == \"chromadb\" or extra == \"dlt\") and (extra == \"neptune\" or extra == \"langchain\" or extra == \"chromadb\" or extra == \"dlt\")"
 files = [
     {file = "orjson-3.11.3-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:29cb1f1b008d936803e2da3d7cba726fc47232c45df531b29edf0b232dd737e7"},
     {file = "orjson-3.11.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:97dceed87ed9139884a55db8722428e27bd8452817fbf1869c58b49fecab1120"},
@@ -6779,9 +6806,10 @@ lint = ["black"]
 name = "pandas"
 version = "2.3.2"
 description = "Powerful data structures for data analysis, time series, and statistics"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"docs\" or extra == \"evals\""
 files = [
     {file = "pandas-2.3.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:52bc29a946304c360561974c6542d1dd628ddafa69134a7131fdfd6a5d7a1a35"},
     {file = "pandas-2.3.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:220cc5c35ffaa764dd5bb17cf42df283b5cb7fdf49e10a7b053a06c9cb48ee2b"},
@@ -6909,9 +6937,10 @@ files = [
 name = "pathvalidate"
 version = "3.3.1"
 description = "pathvalidate is a Python library to sanitize/validate a string such as filenames/file-paths/etc."
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "pathvalidate-3.3.1-py3-none-any.whl", hash = "sha256:5263baab691f8e1af96092fa5137ee17df5bdfbd6cff1fcac4d6ef4bc2e1735f"},
     {file = "pathvalidate-3.3.1.tar.gz", hash = "sha256:b18c07212bfead624345bb8e1d6141cdcf15a39736994ea0b94035ad2b1ba177"},
@@ -6926,9 +6955,10 @@ test = ["Faker (>=1.0.8)", "allpairspy (>=2)", "click (>=6.2)", "pytest (>=6.0.1
 name = "pendulum"
 version = "3.1.0"
 description = "Python datetimes made easy"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "pendulum-3.1.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:aa545a59e6517cf43597455a6fb44daa4a6e08473d67a7ad34e4fa951efb9620"},
     {file = "pendulum-3.1.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:299df2da6c490ede86bb8d58c65e33d7a2a42479d21475a54b467b03ccb88531"},
@@ -7206,9 +7236,10 @@ kaleido = ["kaleido (>=1.0.0)"]
 name = "pluggy"
 version = "1.6.0"
 description = "plugin and hook calling mechanisms for python"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"deepeval\" or extra == \"dev\" or extra == \"dlt\""
 files = [
     {file = "pluggy-1.6.0-py3-none-any.whl", hash = "sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746"},
     {file = "pluggy-1.6.0.tar.gz", hash = "sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3"},
@@ -7222,9 +7253,10 @@ testing = ["coverage", "pytest", "pytest-benchmark"]
 name = "ply"
 version = "3.11"
 description = "Python Lex & Yacc"
-optional = false
+optional = true
 python-versions = "*"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "ply-3.11-py2.py3-none-any.whl", hash = "sha256:096f9b8350b65ebd2fd1346b12452efe5b9607f7482813ffca50c22722a807ce"},
     {file = "ply-3.11.tar.gz", hash = "sha256:00c7c1aaa88358b9c765b6d3000c6eec0ba42abca5351b095321aef446081da3"},
@@ -7297,9 +7329,10 @@ test = ["anthropic", "coverage", "django", "flake8", "freezegun (==1.5.1)", "lan
 name = "pre-commit"
 version = "4.3.0"
 description = "A framework for managing and maintaining multi-language pre-commit hooks."
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"dev\""
 files = [
     {file = "pre_commit-4.3.0-py2.py3-none-any.whl", hash = "sha256:2b0747ad7e6e967169136edffee14c16e148a778a54e4f967921aa1ebf2308d8"},
     {file = "pre_commit-4.3.0.tar.gz", hash = "sha256:499fe450cc9d42e9d58e606262795ecb64dd05438943c62b66f6a8673da30b16"},
@@ -7667,10 +7700,9 @@ bcrypt = ["bcrypt (>=4.1.2,<5)"]
 name = "py-rust-stemmers"
 version = "0.1.5"
 description = "Fast and parallel snowball stemmer"
-optional = true
+optional = false
 python-versions = "*"
 groups = ["main"]
-markers = "extra == \"codegraph\" and python_version <= \"3.12\""
 files = [
     {file = "py_rust_stemmers-0.1.5-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:bfbd9034ae00419ff2154e33b8f5b4c4d99d1f9271f31ed059e5c7e9fa005844"},
     {file = "py_rust_stemmers-0.1.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c7162ae66df2bb0fc39b350c24a049f5f5151c03c046092ba095c2141ec223a2"},
@@ -8268,66 +8300,6 @@ files = [
 [package.extras]
 dev = ["build", "flake8", "mypy", "pytest", "twine"]
 
-[[package]]
-name = "pyside6"
-version = "6.9.2"
-description = "Python bindings for the Qt cross-platform application and UI framework"
-optional = true
-python-versions = "<3.14,>=3.9"
-groups = ["main"]
-markers = "extra == \"gui\""
-files = [
-    {file = "pyside6-6.9.2-cp39-abi3-macosx_12_0_universal2.whl", hash = "sha256:71245c76bfbe5c41794ffd8546730ec7cc869d4bbe68535639e026e4ef8a7714"},
-    {file = "pyside6-6.9.2-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:64a9e2146e207d858e00226f68d7c1b4ab332954742a00dcabb721bb9e4aa0cd"},
-    {file = "pyside6-6.9.2-cp39-abi3-manylinux_2_39_aarch64.whl", hash = "sha256:a78fad16241a1f2ed0fa0098cf3d621f591fc75b4badb7f3fa3959c9d861c806"},
-    {file = "pyside6-6.9.2-cp39-abi3-win_amd64.whl", hash = "sha256:d1afbf48f9a5612b9ee2dc7c384c1a65c08b5830ba5e7d01f66d82678e5459df"},
-    {file = "pyside6-6.9.2-cp39-abi3-win_arm64.whl", hash = "sha256:1499b1d7629ab92119118e2636b4ace836b25e457ddf01003fdca560560b8c0a"},
-]
-
-[package.dependencies]
-PySide6_Addons = "6.9.2"
-PySide6_Essentials = "6.9.2"
-shiboken6 = "6.9.2"
-
-[[package]]
-name = "pyside6-addons"
-version = "6.9.2"
-description = "Python bindings for the Qt cross-platform application and UI framework (Addons)"
-optional = true
-python-versions = "<3.14,>=3.9"
-groups = ["main"]
-markers = "extra == \"gui\""
-files = [
-    {file = "pyside6_addons-6.9.2-cp39-abi3-macosx_12_0_universal2.whl", hash = "sha256:7019fdcc0059626eb1608b361371f4dc8cb7f2d02f066908fd460739ff5a07cd"},
-    {file = "pyside6_addons-6.9.2-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:24350e5415317f269e743d1f7b4933fe5f59d90894aa067676c9ce6bfe9e7988"},
-    {file = "pyside6_addons-6.9.2-cp39-abi3-manylinux_2_39_aarch64.whl", hash = "sha256:af8dee517de8d336735a6543f7dd496eb580e852c14b4d2304b890e2a29de499"},
-    {file = "pyside6_addons-6.9.2-cp39-abi3-win_amd64.whl", hash = "sha256:98d2413904ee4b2b754b077af7875fa6ec08468c01a6628a2c9c3d2cece4874f"},
-    {file = "pyside6_addons-6.9.2-cp39-abi3-win_arm64.whl", hash = "sha256:b430cae782ff1a99fb95868043557f22c31b30c94afb9cf73278584e220a2ab6"},
-]
-
-[package.dependencies]
-PySide6_Essentials = "6.9.2"
-shiboken6 = "6.9.2"
-
-[[package]]
-name = "pyside6-essentials"
-version = "6.9.2"
-description = "Python bindings for the Qt cross-platform application and UI framework (Essentials)"
-optional = true
-python-versions = "<3.14,>=3.9"
-groups = ["main"]
-markers = "extra == \"gui\""
-files = [
-    {file = "pyside6_essentials-6.9.2-cp39-abi3-macosx_12_0_universal2.whl", hash = "sha256:713eb8dcbb016ff10e6fca129c1bf2a0fd8cfac979e689264e0be3b332f9398e"},
-    {file = "pyside6_essentials-6.9.2-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:84b8ca4fa56506e2848bdb4c7a0851a5e7adcb916bef9bce25ce2eeb6c7002cc"},
-    {file = "pyside6_essentials-6.9.2-cp39-abi3-manylinux_2_39_aarch64.whl", hash = "sha256:d0f701503974bd51b408966539aa6956f3d8536e547ea8002fbfb3d77796bbc3"},
-    {file = "pyside6_essentials-6.9.2-cp39-abi3-win_amd64.whl", hash = "sha256:b2f746f795138ac63eb173f9850a6db293461a1b6ce22cf6dafac7d194a38951"},
-    {file = "pyside6_essentials-6.9.2-cp39-abi3-win_arm64.whl", hash = "sha256:ecd7b5cd9e271f397fb89a6357f4ec301d8163e50869c6c557f9ccc6bed42789"},
-]
-
-[package.dependencies]
-shiboken6 = "6.9.2"
-
 [[package]]
 name = "pysocks"
 version = "1.7.1"
@@ -8621,9 +8593,10 @@ XlsxWriter = ">=0.5.7"
 name = "pytz"
 version = "2025.2"
 description = "World timezone definitions, modern and historical"
-optional = false
+optional = true
 python-versions = "*"
 groups = ["main"]
+markers = "extra == \"neo4j\" or extra == \"graphiti\" or extra == \"docs\" or extra == \"evals\" or extra == \"dlt\""
 files = [
     {file = "pytz-2025.2-py2.py3-none-any.whl", hash = "sha256:5ddf76296dd8c44c26eb8f4b6f35488f3ccbf6fbbd7adee0b7262d43f0ec2f00"},
     {file = "pytz-2025.2.tar.gz", hash = "sha256:360b9e3dbb49a209c21ad61809c7fb453643e048b38924c765813546746e81c3"},
@@ -8636,7 +8609,7 @@ description = "Python for Window Extensions"
 optional = false
 python-versions = "*"
 groups = ["main"]
-markers = "sys_platform == \"win32\" or platform_system == \"Windows\""
+markers = "(sys_platform == \"win32\" or platform_system == \"Windows\") and (platform_python_implementation != \"PyPy\" or platform_system == \"Windows\" or extra == \"dlt\")"
 files = [
     {file = "pywin32-311-cp310-cp310-win32.whl", hash = "sha256:d03ff496d2a0cd4a5893504789d4a15399133fe82517455e78bad62efbb7f0a3"},
     {file = "pywin32-311-cp310-cp310-win_amd64.whl", hash = "sha256:797c2772017851984b97180b0bebe4b620bb86328e8a884bb626156295a63b3b"},
@@ -8863,19 +8836,6 @@ files = [
 [package.dependencies]
 cffi = {version = "*", markers = "implementation_name == \"pypy\""}
 
-[[package]]
-name = "qasync"
-version = "0.27.1"
-description = "Python library for using asyncio in Qt-based applications"
-optional = true
-python-versions = ">=3.8,<4.0"
-groups = ["main"]
-markers = "extra == \"gui\""
-files = [
-    {file = "qasync-0.27.1-py3-none-any.whl", hash = "sha256:5d57335723bc7d9b328dadd8cb2ed7978640e4bf2da184889ce50ee3ad2602c7"},
-    {file = "qasync-0.27.1.tar.gz", hash = "sha256:8dc768fd1ee5de1044c7c305eccf2d39d24d87803ea71189d4024fb475f4985f"},
-]
-
 [[package]]
 name = "rapidfuzz"
 version = "3.14.1"
@@ -9231,9 +9191,10 @@ requests = ">=2.0.1,<3.0.0"
 name = "requirements-parser"
 version = "0.13.0"
 description = "This is a small Python module for parsing Pip requirement files."
-optional = false
+optional = true
 python-versions = "<4.0,>=3.8"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "requirements_parser-0.13.0-py3-none-any.whl", hash = "sha256:2b3173faecf19ec5501971b7222d38f04cb45bb9d87d0ad629ca71e2e62ded14"},
     {file = "requirements_parser-0.13.0.tar.gz", hash = "sha256:0843119ca2cb2331de4eb31b10d70462e39ace698fd660a915c247d2301a4418"},
@@ -9313,9 +9274,10 @@ jupyter = ["ipywidgets (>=7.5.1,<9)"]
 name = "rich-argparse"
 version = "1.7.1"
 description = "Rich help formatters for argparse and optparse"
-optional = false
+optional = true
 python-versions = ">=3.8"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "rich_argparse-1.7.1-py3-none-any.whl", hash = "sha256:a8650b42e4a4ff72127837632fba6b7da40784842f08d7395eb67a9cbd7b4bf9"},
     {file = "rich_argparse-1.7.1.tar.gz", hash = "sha256:d7a493cde94043e41ea68fb43a74405fa178de981bf7b800f7a3bd02ac5c27be"},
@@ -9539,9 +9501,10 @@ files = [
 name = "s3fs"
 version = "2025.3.2"
 description = "Convenient Filesystem interface over S3"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"aws\""
 files = [
     {file = "s3fs-2025.3.2-py3-none-any.whl", hash = "sha256:81eae3f37b4b04bcc08845d7bcc607c6ca45878813ef7e6a28d77b2688417130"},
     {file = "s3fs-2025.3.2.tar.gz", hash = "sha256:6798f896ec76dd3bfd8beb89f0bb7c5263cb2760e038bae0978505cd172a307c"},
@@ -9563,9 +9526,10 @@ boto3 = ["aiobotocore[boto3] (>=2.5.4,<3.0.0)"]
 name = "s3transfer"
 version = "0.13.1"
 description = "An Amazon S3 Transfer Manager"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"neptune\" or extra == \"aws\""
 files = [
     {file = "s3transfer-0.13.1-py3-none-any.whl", hash = "sha256:a981aa7429be23fe6dfc13e80e4020057cbab622b08c0315288758d67cabc724"},
     {file = "s3transfer-0.13.1.tar.gz", hash = "sha256:c3fdba22ba1bd367922f27ec8032d6a1cf5f10c934fb5d68cf60fd5a23d936cf"},
@@ -9621,9 +9585,10 @@ torch = ["safetensors[numpy]", "torch (>=1.10)"]
 name = "scikit-learn"
 version = "1.7.2"
 description = "A set of python modules for machine learning and data mining"
-optional = false
+optional = true
 python-versions = ">=3.10"
 groups = ["main"]
+markers = "extra == \"evals\""
 files = [
     {file = "scikit_learn-1.7.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:6b33579c10a3081d076ab403df4a4190da4f4432d443521674637677dc91e61f"},
     {file = "scikit_learn-1.7.2-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:36749fb62b3d961b1ce4fedf08fa57a1986cd409eff2d783bca5d4b9b5fce51c"},
@@ -9677,10 +9642,10 @@ tests = ["matplotlib (>=3.5.0)", "mypy (>=1.15)", "numpydoc (>=1.2.0)", "pandas
 name = "scipy"
 version = "1.15.3"
 description = "Fundamental algorithms for scientific computing in Python"
-optional = false
+optional = true
 python-versions = ">=3.10"
 groups = ["main"]
-markers = "python_version == \"3.10\""
+markers = "python_version == \"3.10\" and extra == \"evals\""
 files = [
     {file = "scipy-1.15.3-cp310-cp310-macosx_10_13_x86_64.whl", hash = "sha256:a345928c86d535060c9c2b25e71e87c39ab2f22fc96e9636bd74d1dbf9de448c"},
     {file = "scipy-1.15.3-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:ad3432cb0f9ed87477a8d97f03b763fd1d57709f1bbde3c9369b1dff5503b253"},
@@ -9742,10 +9707,10 @@ test = ["Cython", "array-api-strict (>=2.0,<2.1.1)", "asv", "gmpy2", "hypothesis
 name = "scipy"
 version = "1.16.2"
 description = "Fundamental algorithms for scientific computing in Python"
-optional = false
+optional = true
 python-versions = ">=3.11"
 groups = ["main"]
-markers = "python_version >= \"3.11\""
+markers = "python_version >= \"3.11\" and extra == \"evals\""
 files = [
     {file = "scipy-1.16.2-cp311-cp311-macosx_10_14_x86_64.whl", hash = "sha256:6ab88ea43a57da1af33292ebd04b417e8e2eaf9d5aa05700be8d6e1b6501cd92"},
     {file = "scipy-1.16.2-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:c95e96c7305c96ede73a7389f46ccd6c659c4da5ef1b2789466baeaed3622b6e"},
@@ -9822,9 +9787,10 @@ test = ["Cython", "array-api-strict (>=2.3.1)", "asv", "gmpy2", "hypothesis (>=6
 name = "semver"
 version = "3.0.4"
 description = "Python helper for Semantic Versioning (https://semver.org)"
-optional = false
+optional = true
 python-versions = ">=3.7"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "semver-3.0.4-py3-none-any.whl", hash = "sha256:9c824d87ba7f7ab4a1890799cec8596f15c1241cb473404ea1cb0c55e4b04746"},
     {file = "semver-3.0.4.tar.gz", hash = "sha256:afc7d8c584a5ed0a11033af086e8af226a9c0b206f313e0301f8dd7b6b589602"},
@@ -9852,9 +9818,10 @@ win32 = ["pywin32 ; sys_platform == \"win32\""]
 name = "sentry-sdk"
 version = "2.38.0"
 description = "Python client for Sentry (https://sentry.io)"
-optional = false
+optional = true
 python-versions = ">=3.6"
 groups = ["main"]
+markers = "extra == \"deepeval\" or extra == \"monitoring\""
 files = [
     {file = "sentry_sdk-2.38.0-py2.py3-none-any.whl", hash = "sha256:2324aea8573a3fa1576df7fb4d65c4eb8d9929c8fa5939647397a07179eef8d0"},
     {file = "sentry_sdk-2.38.0.tar.gz", hash = "sha256:792d2af45e167e2f8a3347143f525b9b6bac6f058fb2014720b40b84ccbeb985"},
@@ -9911,9 +9878,10 @@ unleash = ["UnleashClient (>=6.0.1)"]
 name = "setuptools"
 version = "80.9.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"notebook\" or extra == \"dev\" or extra == \"llama-index\" or extra == \"deepeval\" or extra == \"dlt\""
 files = [
     {file = "setuptools-80.9.0-py3-none-any.whl", hash = "sha256:062d34222ad13e0cc312a4c02d73f059e86a4acbfbdea8f8f76b28c99f306922"},
     {file = "setuptools-80.9.0.tar.gz", hash = "sha256:f36b47402ecde768dbfafc46e8e4207b4360c654f1f3bb84475f0a28628fb19c"},
@@ -9940,22 +9908,6 @@ files = [
     {file = "shellingham-1.5.4.tar.gz", hash = "sha256:8dbca0739d487e5bd35ab3ca4b36e11c4078f3a234bfce294b0a0291363404de"},
 ]
 
-[[package]]
-name = "shiboken6"
-version = "6.9.2"
-description = "Python/C++ bindings helper module"
-optional = true
-python-versions = "<3.14,>=3.9"
-groups = ["main"]
-markers = "extra == \"gui\""
-files = [
-    {file = "shiboken6-6.9.2-cp39-abi3-macosx_12_0_universal2.whl", hash = "sha256:8bb1c4326330e53adeac98bfd9dcf57f5173a50318a180938dcc4825d9ca38da"},
-    {file = "shiboken6-6.9.2-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:3b54c0a12ea1b03b9dc5dcfb603c366e957dc75341bf7cb1cc436d0d848308ee"},
-    {file = "shiboken6-6.9.2-cp39-abi3-manylinux_2_39_aarch64.whl", hash = "sha256:a5f5985938f5acb604c23536a0ff2efb3cccb77d23da91fbaff8fd8ded3dceb4"},
-    {file = "shiboken6-6.9.2-cp39-abi3-win_amd64.whl", hash = "sha256:68c33d565cd4732be762d19ff67dfc53763256bac413d392aa8598b524980bc4"},
-    {file = "shiboken6-6.9.2-cp39-abi3-win_arm64.whl", hash = "sha256:c5b827797b3d89d9b9a3753371ff533fcd4afc4531ca51a7c696952132098054"},
-]
-
 [[package]]
 name = "sigtools"
 version = "4.0.1"
@@ -9980,9 +9932,10 @@ tests = ["coverage", "mock", "repeated-test (>=2.2.1)", "sphinx"]
 name = "simplejson"
 version = "3.20.1"
 description = "Simple, fast, extensible JSON encoder/decoder for Python"
-optional = false
+optional = true
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.5"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "simplejson-3.20.1-cp27-cp27m-manylinux1_i686.whl", hash = "sha256:f5272b5866b259fe6c33c4a8c5073bf8b359c3c97b70c298a2f09a69b52c7c41"},
     {file = "simplejson-3.20.1-cp27-cp27m-manylinux1_x86_64.whl", hash = "sha256:5c0de368f3052a59a1acf21f8b2dd28686a9e4eba2da7efae7ed9554cb31e7bc"},
@@ -10112,9 +10065,10 @@ files = [
 name = "smmap"
 version = "5.0.2"
 description = "A pure Python implementation of a sliding window memory map manager"
-optional = false
+optional = true
 python-versions = ">=3.7"
 groups = ["main"]
+markers = "extra == \"dlt\" or extra == \"dev\""
 files = [
     {file = "smmap-5.0.2-py3-none-any.whl", hash = "sha256:b30115f0def7d7531d22a0fb6502488d879e75b260a9db4d0819cfb25403af5e"},
     {file = "smmap-5.0.2.tar.gz", hash = "sha256:26ea65a03958fa0c8a1c7e8c7a58fdc77221b8910f6be2131affade476898ad5"},
@@ -10245,9 +10199,10 @@ sqlcipher = ["sqlcipher3_binary"]
 name = "sqlglot"
 version = "27.16.3"
 description = "An easily customizable SQL parser and transpiler"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"dlt\""
 files = [
     {file = "sqlglot-27.16.3-py3-none-any.whl", hash = "sha256:3765ef1da6c9a04dd9e9ab4bcf24ca54daae72d86d693954aed84dbbbff2ff3b"},
     {file = "sqlglot-27.16.3.tar.gz", hash = "sha256:bf5cc3b7c90c3682365353a318089e69e859939943d7882562ba39be650a6202"},
@@ -10406,9 +10361,10 @@ typing = ["mypy (>=1.6,<2.0)", "traitlets (>=5.11.1)"]
 name = "threadpoolctl"
 version = "3.6.0"
 description = "threadpoolctl"
-optional = false
+optional = true
 python-versions = ">=3.9"
 groups = ["main"]
+markers = "extra == \"evals\""
 files = [
     {file = "threadpoolctl-3.6.0-py3-none-any.whl", hash = "sha256:43a0b8fd5a2928500110039e43a5eed8480b918967083ea48dc3ab9f13c4a7fb"},
     {file = "threadpoolctl-3.6.0.tar.gz", hash = "sha256:8ab8b4aa3491d812b623328249fab5302a68d2d71745c8a4c719a2fcaba9f44e"},
@@ -10575,9 +10531,10 @@ files = [
 name = "tomlkit"
 version = "0.13.3"
 description = "Style preserving TOML library"
-optional = false
+optional = true
 python-versions = ">=3.8"
 groups = ["main"]
+markers = "extra == \"dlt\" or extra == \"dev\""
 files = [
     {file = "tomlkit-0.13.3-py3-none-any.whl", hash = "sha256:c89c649d79ee40629a9fda55f8ace8c6a1b42deb912b2a8fd8d942ddadb606b0"},
     {file = "tomlkit-0.13.3.tar.gz", hash = "sha256:430cf247ee57df2b94ee3fbe588e71d362a941ebb545dec29b53961d61add2a1"},
@@ -10914,9 +10871,10 @@ typing-extensions = ">=4.12.0"
 name = "tzdata"
 version = "2025.2"
 description = "Provider of IANA time zone data"
-optional = false
+optional = true
 python-versions = ">=2"
 groups = ["main"]
+markers = "extra == \"docs\" or extra == \"evals\" or extra == \"dlt\""
 files = [
     {file = "tzdata-2025.2-py2.py3-none-any.whl", hash = "sha256:1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8"},
     {file = "tzdata-2025.2.tar.gz", hash = "sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9"},
@@ -11157,9 +11115,10 @@ test = ["aiohttp (>=3.10.5)", "flake8 (>=5.0,<6.0)", "mypy (>=0.800)", "psutil",
 name = "virtualenv"
 version = "20.34.0"
 description = "Virtual Python Environment builder"
-optional = false
+optional = true
 python-versions = ">=3.8"
 groups = ["main"]
+markers = "extra == \"dev\""
 files = [
     {file = "virtualenv-20.34.0-py3-none-any.whl", hash = "sha256:341f5afa7eee943e4984a9207c025feedd768baff6753cd660c857ceb3e36026"},
     {file = "virtualenv-20.34.0.tar.gz", hash = "sha256:44815b2c9dee7ed86e387b842a84f20b93f7f417f95886ca1996a72a4138eb1a"},
@@ -11495,10 +11454,10 @@ test = ["pytest (>=6.0.0)", "setuptools (>=65)"]
 name = "win-precise-time"
 version = "1.4.2"
 description = ""
-optional = false
+optional = true
 python-versions = ">=3.7"
 groups = ["main"]
-markers = "os_name == \"nt\" and python_version <= \"3.12\""
+markers = "extra == \"dlt\" and os_name == \"nt\" and python_version <= \"3.12\""
 files = [
     {file = "win-precise-time-1.4.2.tar.gz", hash = "sha256:89274785cbc5f2997e01675206da3203835a442c60fd97798415c6b3c179c0b9"},
     {file = "win_precise_time-1.4.2-cp310-cp310-win32.whl", hash = "sha256:7fa13a2247c2ef41cd5e9b930f40716eacc7fc1f079ea72853bd5613fe087a1a"},
@@ -11519,10 +11478,10 @@ files = [
 name = "win32-setctime"
 version = "1.2.0"
 description = "A small Python utility to set file creation time on Windows"
-optional = true
+optional = false
 python-versions = ">=3.5"
 groups = ["main"]
-markers = "sys_platform == \"win32\" and extra == \"codegraph\" and python_version <= \"3.12\""
+markers = "sys_platform == \"win32\""
 files = [
     {file = "win32_setctime-1.2.0-py3-none-any.whl", hash = "sha256:95d644c4e708aba81dc3704a116d8cbc974d70b3bdb8be1d150e36be6e9d1390"},
     {file = "win32_setctime-1.2.0.tar.gz", hash = "sha256:ae1fdf948f5640aae05c511ade119313fb6a30d7eabe25fef9764dca5873c4c0"},
@@ -11909,23 +11868,25 @@ cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and pyt
 anthropic = ["anthropic"]
 api = []
 aws = ["s3fs"]
+baml = ["baml-py"]
 chromadb = ["chromadb", "pypika"]
 codegraph = ["fastembed", "transformers", "tree-sitter", "tree-sitter-python"]
 debug = ["debugpy"]
 deepeval = ["deepeval"]
-dev = ["coverage", "deptry", "gitpython", "mkdocs-material", "mkdocs-minify-plugin", "mkdocstrings", "mypy", "notebook", "pylint", "pytest", "pytest-asyncio", "pytest-cov", "ruff", "tweepy"]
+dev = ["coverage", "deptry", "gitpython", "mkdocs-material", "mkdocs-minify-plugin", "mkdocstrings", "mypy", "notebook", "pre-commit", "pylint", "pytest", "pytest-asyncio", "pytest-cov", "ruff", "tweepy"]
 distributed = ["modal"]
+dlt = ["dlt"]
 docs = ["unstructured"]
-evals = ["gdown", "plotly"]
+evals = ["gdown", "matplotlib", "pandas", "plotly", "scikit-learn"]
 falkordb = ["falkordb"]
 gemini = ["google-generativeai"]
 graphiti = ["graphiti-core"]
 groq = ["groq"]
-gui = ["pyside6", "qasync"]
 huggingface = ["transformers"]
 langchain = ["langchain_text_splitters", "langsmith"]
 llama-index = ["llama-index-core"]
 mistral = ["mistral-common"]
+monitoring = ["langfuse", "sentry-sdk"]
 neo4j = ["neo4j"]
 neptune = ["langchain_aws"]
 notebook = ["notebook"]
@@ -11937,4 +11898,4 @@ posthog = ["posthog"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<=3.13"
-content-hash = "fc32c4e05914cf364d4feb0c3baec9771d149eb65626e5337fa2eb55e7130499"
+content-hash = "49d2d5207803b6b56e0bbf2be871941f4fc4535d0bc823815e0a7cbe61e12574"

pyproject.toml

@@ -20,49 +20,38 @@ classifiers = [
     "Operating System :: Microsoft :: Windows",
 ]
 dependencies = [
-    "openai>=1.80.1,<2.0.0",
+    "openai>=1.80.1",
     "python-dotenv>=1.0.1,<2.0.0",
     "pydantic>=2.10.5,<3.0.0",
     "pydantic-settings>=2.2.1,<3",
     "typing_extensions>=4.12.2,<5.0.0",
-    "nltk>=3.9.1,<4.0.0",
     "numpy>=1.26.4, <=4.0.0",
-    "pandas>=2.2.2,<3.0.0",
-    # Note: New s3fs and boto3 versions don't work well together
-    # Always use comaptible fixed versions of these two dependencies
-    "s3fs[boto3]==2025.3.2",
     "sqlalchemy>=2.0.39,<3.0.0",
     "aiosqlite>=0.20.0,<1.0.0",
     "tiktoken>=0.8.0,<1.0.0",
-    "litellm>=1.71.0, <2.0.0",
+    "litellm>=1.76.0",
     "instructor>=1.9.1,<2.0.0",
-    "langfuse>=2.32.0,<3",
     "filetype>=1.2.0,<2.0.0",
     "aiohttp>=3.11.14,<4.0.0",
     "aiofiles>=23.2.1,<24.0.0",
     "rdflib>=7.1.4,<7.2.0",
     "pypdf>=4.1.0,<7.0.0",
     "jinja2>=3.1.3,<4",
-    "matplotlib>=3.8.3,<4",
-    "networkx>=3.4.2,<4",
     "lancedb>=0.24.0,<1.0.0",
     "nbformat>=5.7.0,<6.0.0",
     "alembic>=1.13.3,<2",
-    "pre-commit>=4.0.1,<5",
-    "scikit-learn>=1.6.1,<2",
     "limits>=4.4.1,<5",
     "fastapi>=0.115.7,<1.0.0",
     "python-multipart>=0.0.20,<1.0.0",
     "fastapi-users[sqlalchemy]>=14.0.1,<15.0.0",
-    "dlt[sqlalchemy]>=1.9.0,<2",
-    "sentry-sdk[fastapi]>=2.9.0,<3",
     "structlog>=25.2.0,<26",
-    "baml-py (==0.206.0)",
     "pympler>=1.1,<2.0.0",
-    "onnxruntime>=1.0.0,<2.0.0",
-    "pylance>=0.22.0,<1.0.0",
+    "onnxruntime<=1.22.1",
+    "pylance>=0.22.0,<=0.36.0",
     "kuzu (==0.11.0)",
     "python-magic-bin<0.5 ; platform_system == 'Windows'", # Only needed for Windows
+    "fastembed<=0.6.0",
+    "networkx>=3.4.2,<4",
     "uvicorn>=0.34.0,<1.0.0",
     "gunicorn>=20.1.0,<24",
     "websockets>=15.0.1,<16.0.0",
@@ -71,6 +60,7 @@ dependencies = [
 
 [project.optional-dependencies]
 api=[]
+
 distributed = [
     "modal>=1.0.5,<2.0.0",
 ]
@@ -116,25 +106,28 @@ codegraph = [
 evals = [
     "plotly>=6.0.0,<7",
     "gdown>=5.2.0,<6",
+    "pandas>=2.2.2,<3.0.0",
+    "matplotlib>=3.8.3,<4",
+    "scikit-learn>=1.6.1,<2",
 ]
-gui = [
-    "pyside6>=6.8.3,<7",
-    "qasync>=0.27.1,<0.28",
-]
+
 graphiti = ["graphiti-core>=0.7.0,<0.8"]
 # Note: New s3fs and boto3 versions don't work well together
 # Always use comaptible fixed versions of these two dependencies
 aws = ["s3fs[boto3]==2025.3.2"]
+dlt = ["dlt[sqlalchemy]>=1.9.0,<2"]
+baml = ["baml-py (==0.206.0)"]
 dev = [
     "pytest>=7.4.0,<8",
     "pytest-cov>=6.1.1,<7.0.0",
     "pytest-asyncio>=0.21.1,<0.22",
     "coverage>=7.3.2,<8",
     "mypy>=1.7.1,<2",
+    "pre-commit>=4.0.1,<5",
     "notebook>=7.1.0,<8",
     "deptry>=0.20.0,<0.21",
     "pylint>=3.0.3,<4",
-    "ruff>=0.9.2,<1.0.0",
+    "ruff>=0.9.2,<=0.13.1",
     "tweepy>=4.14.0,<5.0.0",
     "gitpython>=3.1.43,<4",
     "mkdocs-material>=9.5.42,<10",
@@ -143,6 +136,8 @@ dev = [
 ]
 debug = ["debugpy>=1.8.9,<2.0.0"]
 
+monitoring = ["sentry-sdk[fastapi]>=2.9.0,<3", "langfuse>=2.32.0,<3"]
+
 [project.urls]
 Homepage = "https://www.cognee.ai"
 Repository = "https://github.com/topoteretes/cognee"

uv.lock

@@ -2,16 +2,16 @@ version = 1
 requires-python = ">=3.10, <=3.13"
 resolution-markers = [
     "python_full_version >= '3.13' and platform_python_implementation != 'PyPy' and sys_platform != 'emscripten'",
-    "python_full_version == '3.12.*' and platform_python_implementation != 'PyPy' and sys_platform != 'emscripten'",
-    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and sys_platform != 'emscripten'",
-    "python_full_version < '3.11' and platform_python_implementation != 'PyPy' and sys_platform != 'emscripten'",
     "python_full_version >= '3.13' and platform_python_implementation == 'PyPy' and sys_platform != 'emscripten'",
-    "python_full_version == '3.12.*' and platform_python_implementation == 'PyPy' and sys_platform != 'emscripten'",
-    "python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and sys_platform != 'emscripten'",
-    "python_full_version < '3.11' and platform_python_implementation == 'PyPy' and sys_platform != 'emscripten'",
     "python_full_version >= '3.13' and sys_platform == 'emscripten'",
+    "python_full_version == '3.12.*' and platform_python_implementation != 'PyPy' and sys_platform != 'emscripten'",
+    "python_full_version == '3.12.*' and platform_python_implementation == 'PyPy' and sys_platform != 'emscripten'",
     "python_full_version == '3.12.*' and sys_platform == 'emscripten'",
+    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and sys_platform != 'emscripten'",
+    "python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and sys_platform != 'emscripten'",
     "python_full_version == '3.11.*' and sys_platform == 'emscripten'",
+    "python_full_version < '3.11' and platform_python_implementation != 'PyPy' and sys_platform != 'emscripten'",
+    "python_full_version < '3.11' and platform_python_implementation == 'PyPy' and sys_platform != 'emscripten'",
     "python_full_version < '3.11' and sys_platform == 'emscripten'",
 ]
 
@@ -221,7 +221,7 @@ wheels = [
 
 [[package]]
 name = "anyio"
-version = "4.10.0"
+version = "4.11.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "exceptiongroup", marker = "python_full_version < '3.11'" },
@@ -229,9 +229,9 @@ dependencies = [
     { name = "sniffio" },
     { name = "typing-extensions", marker = "python_full_version < '3.13'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/f1/b4/636b3b65173d3ce9a38ef5f0522789614e590dab6a8d505340a4efe4c567/anyio-4.10.0.tar.gz", hash = "sha256:3f3fae35c96039744587aa5b8371e7e8e603c0702999535961dd336026973ba6", size = 213252 }
+sdist = { url = "https://files.pythonhosted.org/packages/c6/78/7d432127c41b50bccba979505f272c16cbcadcc33645d5fa3a738110ae75/anyio-4.11.0.tar.gz", hash = "sha256:82a8d0b81e318cc5ce71a5f1f8b5c4e63619620b63141ef8c995fa0db95a57c4", size = 219094, upload-time = "2025-09-23T09:19:12.58Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/6f/12/e5e0282d673bb9746bacfb6e2dba8719989d3660cdb2ea79aee9a9651afb/anyio-4.10.0-py3-none-any.whl", hash = "sha256:60e474ac86736bbfd6f210f7a61218939c318f43f9972497381f1c5e930ed3d1", size = 107213 },
+    { url = "https://files.pythonhosted.org/packages/15/b3/9b1a8074496371342ec1e796a96f99c82c945a339cd81a8e73de28b4cf9e/anyio-4.11.0-py3-none-any.whl", hash = "sha256:0287e96f4d26d4149305414d4e3bc32f0dcd0862365a4bddea19d7a1ec38c4fc", size = 109097, upload-time = "2025-09-23T09:19:10.601Z" },
 ]
 
 [[package]]
@@ -296,14 +296,14 @@ wheels = [
 
 [[package]]
 name = "asgiref"
-version = "3.9.1"
+version = "3.9.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "typing-extensions", marker = "python_full_version < '3.11'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/90/61/0aa957eec22ff70b830b22ff91f825e70e1ef732c06666a805730f28b36b/asgiref-3.9.1.tar.gz", hash = "sha256:a5ab6582236218e5ef1648f242fd9f10626cfd4de8dc377db215d5d5098e3142", size = 36870 }
+sdist = { url = "https://files.pythonhosted.org/packages/7f/bf/0f3ecda32f1cb3bf1dca480aca08a7a8a3bdc4bed2343a103f30731565c9/asgiref-3.9.2.tar.gz", hash = "sha256:a0249afacb66688ef258ffe503528360443e2b9a8d8c4581b6ebefa58c841ef1", size = 36894, upload-time = "2025-09-23T15:00:55.136Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/7c/3c/0464dcada90d5da0e71018c04a140ad6349558afb30b3051b4264cc5b965/asgiref-3.9.1-py3-none-any.whl", hash = "sha256:f3bba7092a48005b5f5bacd747d36ee4a5a61f4a269a6df590b43144355ebd2c", size = 23790 },
+    { url = "https://files.pythonhosted.org/packages/c7/d1/69d02ce34caddb0a7ae088b84c356a625a93cd4ff57b2f97644c03fad905/asgiref-3.9.2-py3-none-any.whl", hash = "sha256:0b61526596219d70396548fc003635056856dba5d0d086f86476f10b33c75960", size = 23788, upload-time = "2025-09-23T15:00:53.627Z" },
 ]
 
 [[package]]
@@ -821,31 +821,24 @@ dependencies = [
     { name = "aiohttp" },
     { name = "aiosqlite" },
     { name = "alembic" },
-    { name = "baml-py" },
-    { name = "dlt", extra = ["sqlalchemy"] },
     { name = "fastapi" },
     { name = "fastapi-users", extra = ["sqlalchemy"] },
+    { name = "fastembed" },
     { name = "filetype" },
     { name = "gunicorn" },
     { name = "instructor" },
     { name = "jinja2" },
     { name = "kuzu" },
     { name = "lancedb" },
-    { name = "langfuse" },
     { name = "limits" },
     { name = "litellm" },
-    { name = "matplotlib" },
-    { name = "mistralai" },
     { name = "nbformat" },
     { name = "networkx", version = "3.4.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
     { name = "networkx", version = "3.5", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
-    { name = "nltk" },
     { name = "numpy", version = "1.26.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
     { name = "numpy", version = "2.3.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "onnxruntime" },
     { name = "openai" },
-    { name = "pandas" },
-    { name = "pre-commit" },
     { name = "pydantic" },
     { name = "pydantic-settings" },
     { name = "pylance" },
@@ -855,9 +848,6 @@ dependencies = [
     { name = "python-magic-bin", marker = "sys_platform == 'win32'" },
     { name = "python-multipart" },
     { name = "rdflib" },
-    { name = "s3fs", extra = ["boto3"] },
-    { name = "scikit-learn" },
-    { name = "sentry-sdk", extra = ["fastapi"] },
     { name = "sqlalchemy" },
     { name = "structlog" },
     { name = "tiktoken" },
@@ -873,6 +863,9 @@ anthropic = [
 aws = [
     { name = "s3fs", extra = ["boto3"] },
 ]
+baml = [
+    { name = "baml-py" },
+]
 chromadb = [
     { name = "chromadb" },
     { name = "pypika" },
@@ -898,6 +891,7 @@ dev = [
     { name = "mkdocstrings", extra = ["python"] },
     { name = "mypy" },
     { name = "notebook" },
+    { name = "pre-commit" },
     { name = "pylint" },
     { name = "pytest" },
     { name = "pytest-asyncio" },
@@ -908,12 +902,18 @@ dev = [
 distributed = [
     { name = "modal" },
 ]
+dlt = [
+    { name = "dlt", extra = ["sqlalchemy"] },
+]
 docs = [
     { name = "unstructured", extra = ["csv", "doc", "docx", "epub", "md", "odt", "org", "ppt", "pptx", "rst", "rtf", "tsv", "xlsx"] },
 ]
 evals = [
     { name = "gdown" },
+    { name = "matplotlib" },
+    { name = "pandas" },
     { name = "plotly" },
+    { name = "scikit-learn" },
 ]
 falkordb = [
     { name = "falkordb" },
@@ -927,10 +927,6 @@ graphiti = [
 groq = [
     { name = "groq" },
 ]
-gui = [
-    { name = "pyside6" },
-    { name = "qasync" },
-]
 huggingface = [
     { name = "transformers" },
 ]
@@ -944,6 +940,10 @@ llama-index = [
 mistral = [
     { name = "mistral-common" },
 ]
+monitoring = [
+    { name = "langfuse" },
+    { name = "sentry-sdk", extra = ["fastapi"] },
+]
 neo4j = [
     { name = "neo4j" },
 ]
@@ -979,16 +979,17 @@ requires-dist = [
     { name = "anthropic", marker = "extra == 'anthropic'", specifier = ">=0.27" },
     { name = "asyncpg", marker = "extra == 'postgres'", specifier = ">=0.30.0,<1.0.0" },
     { name = "asyncpg", marker = "extra == 'postgres-binary'", specifier = ">=0.30.0,<1.0.0" },
-    { name = "baml-py", specifier = "==0.206.0" },
+    { name = "baml-py", marker = "extra == 'baml'", specifier = "==0.206.0" },
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