Fix graphiti-mcp-varming package for PyPI publication

MCP Server Package Fixes:
- Add build-system configuration to pyproject.toml
- Fix module imports to use relative imports for proper packaging
- Fix TypedDict import for Python 3.10 compatibility
- Remove unsupported MCP SDK parameters (tags, meta)
- Add GitHub Actions workflow for automatic PyPI publishing
- Add PyPI publishing documentation and checklist

Code Quality Improvements:
- Fix code formatting in graphiti_core (line length, whitespace)

This prepares v1.0.0 for publication to PyPI, enabling users to install
with: uvx graphiti-mcp-varming

🤖 Generated with Claude Code (https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

.github/workflows/publish-mcp-pypi.yml

@@ -0,0 +1,50 @@
+name: Publish MCP Server to PyPI
+
+on:
+  push:
+    tags:
+      - 'mcp-v*.*.*'  # Triggers on tags like mcp-v1.0.0
+  workflow_dispatch:  # Allow manual triggering
+
+jobs:
+  publish:
+    name: Publish to PyPI
+    runs-on: ubuntu-latest
+    
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v4
+        with:
+          enable-cache: true
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.10'
+
+      - name: Build package
+        working-directory: mcp_server
+        run: |
+          # Remove local graphiti-core override for PyPI build
+          sed -i '/\[tool\.uv\.sources\]/,/graphiti-core/d' pyproject.toml
+          
+          # Build the package
+          uv build
+
+      - name: Publish to PyPI
+        working-directory: mcp_server
+        env:
+          UV_PUBLISH_TOKEN: ${{ secrets.PYPI_API_TOKEN }}
+        run: |
+          uv publish
+
+      - name: Create GitHub Release
+        uses: softprops/action-gh-release@v1
+        with:
+          files: mcp_server/dist/*
+          generate_release_notes: true
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

graphiti_core/llm_client/openai_base_client.py

@@ -166,13 +166,17 @@ class BaseOpenAIClient(LLMClient):
         except openai.RateLimitError as e:
             raise RateLimitError from e
         except openai.AuthenticationError as e:
-            logger.error(f'OpenAI Authentication Error: {e}. Please verify your API key is correct.')
+            logger.error(
+                f'OpenAI Authentication Error: {e}. Please verify your API key is correct.'
+            )
             raise
         except Exception as e:
             # Provide more context for connection errors
             error_msg = str(e)
             if 'Connection error' in error_msg or 'connection' in error_msg.lower():
-                logger.error(f'Connection error communicating with OpenAI API. Please check your network connection and API key. Error: {e}')
+                logger.error(
+                    f'Connection error communicating with OpenAI API. Please check your network connection and API key. Error: {e}'
+                )
             else:
                 logger.error(f'Error in generating LLM response: {e}')
             raise

graphiti_core/llm_client/openai_client.py

@@ -74,7 +74,9 @@ class OpenAIClient(BaseOpenAIClient):
     ):
         """Create a structured completion using OpenAI's beta parse API."""
         # Reasoning models (gpt-5 family) don't support temperature
-        is_reasoning_model = model.startswith('gpt-5') or model.startswith('o1') or model.startswith('o3')
+        is_reasoning_model = (
+            model.startswith('gpt-5') or model.startswith('o1') or model.startswith('o3')
+        )
 
         response = await self.client.responses.parse(
             model=model,
@@ -100,7 +102,9 @@ class OpenAIClient(BaseOpenAIClient):
     ):
         """Create a regular completion with JSON format."""
         # Reasoning models (gpt-5 family) don't support temperature
-        is_reasoning_model = model.startswith('gpt-5') or model.startswith('o1') or model.startswith('o3')
+        is_reasoning_model = (
+            model.startswith('gpt-5') or model.startswith('o1') or model.startswith('o3')
+        )
 
         return await self.client.chat.completions.create(
             model=model,

mcp_server/PUBLISHING_CHECKLIST.md

@@ -0,0 +1,64 @@
+# Publishing Checklist
+
+Use this checklist for your first PyPI publication.
+
+## Pre-Publishing Setup
+
+- [ ] **Update email in `pyproject.toml`** (optional but recommended)
+  - File: `mcp_server/pyproject.toml`
+  - Line: `{name = "Varming", email = "your-email@example.com"}`
+
+- [ ] **Add PyPI token to GitHub Secrets**
+  - URL: https://github.com/Varming73/graphiti/settings/secrets/actions
+  - Secret name: `PYPI_API_TOKEN`
+  - Secret value: Your PyPI token from https://pypi.org/manage/account/token/
+
+## Publishing Steps
+
+- [ ] **Commit all changes**
+  ```bash
+  git add .
+  git commit -m "Prepare graphiti-mcp-varming v1.0.0 for PyPI"
+  git push
+  ```
+
+- [ ] **Create and push release tag**
+  ```bash
+  git tag mcp-v1.0.0
+  git push origin mcp-v1.0.0
+  ```
+
+- [ ] **Monitor GitHub Actions workflow**
+  - URL: https://github.com/Varming73/graphiti/actions
+  - Workflow name: "Publish MCP Server to PyPI"
+  - Expected duration: 2-3 minutes
+
+## Post-Publishing Verification
+
+- [ ] **Check PyPI page**
+  - URL: https://pypi.org/project/graphiti-mcp-varming/
+  - Verify version shows as `1.0.0`
+  - Check description and links are correct
+
+- [ ] **Test installation**
+  ```bash
+  uvx graphiti-mcp-varming --help
+  ```
+
+- [ ] **Test in LibreChat** (if applicable)
+  - Update `librechat.yaml` with `uvx graphiti-mcp-varming`
+  - Restart LibreChat
+  - Verify tools appear in UI
+
+## If Something Goes Wrong
+
+Common issues and solutions in `PYPI_PUBLISHING.md`
+
+- Authentication error → Check token in GitHub secrets
+- File already exists → Version already published, bump version number
+- Workflow doesn't trigger → Check tag format is `mcp-v*.*.*`
+- Package not found → Wait a few minutes for PyPI to propagate
+
+---
+
+**After first successful publish, this checklist can be deleted!**

mcp_server/PYPI_PUBLISHING.md

@@ -0,0 +1,126 @@
+# PyPI Publishing Setup Instructions
+
+This guide explains how to publish the `graphiti-mcp-varming` package to PyPI.
+
+## One-Time Setup
+
+### 1. Add PyPI Token to GitHub Secrets
+
+1. Go to your repository on GitHub: https://github.com/Varming73/graphiti
+2. Click **Settings** → **Secrets and variables** → **Actions**
+3. Click **New repository secret**
+4. Name: `PYPI_API_TOKEN`
+5. Value: Paste your PyPI API token (starts with `pypi-`)
+6. Click **Add secret**
+
+## Publishing a New Version
+
+### Option 1: Automatic Publishing (Recommended)
+
+1. Update the version in `mcp_server/pyproject.toml`:
+   ```toml
+   version = "1.0.1"  # Increment version
+   ```
+
+2. Commit the change:
+   ```bash
+   cd mcp_server
+   git add pyproject.toml
+   git commit -m "Bump MCP server version to 1.0.1"
+   git push
+   ```
+
+3. Create and push a tag:
+   ```bash
+   git tag mcp-v1.0.1
+   git push origin mcp-v1.0.1
+   ```
+
+4. GitHub Actions will automatically:
+   - Build the package
+   - Publish to PyPI
+   - Create a GitHub release
+
+5. Monitor the workflow:
+   - Go to **Actions** tab in GitHub
+   - Watch the "Publish MCP Server to PyPI" workflow
+
+### Option 2: Manual Publishing
+
+If you prefer to publish manually:
+
+```bash
+cd mcp_server
+
+# Remove local graphiti-core override
+sed -i.bak '/\[tool\.uv\.sources\]/,/graphiti-core/d' pyproject.toml
+
+# Build the package
+uv build
+
+# Publish to PyPI
+uv publish --token your-pypi-token-here
+
+# Restore the backup if needed for local development
+mv pyproject.toml.bak pyproject.toml
+```
+
+## After Publishing
+
+Users can install your package with:
+
+```bash
+# Basic installation (Neo4j support included)
+uvx graphiti-mcp-varming
+
+# With FalkorDB support
+uvx --with graphiti-mcp-varming[falkordb] graphiti-mcp-varming
+
+# With all LLM providers (Anthropic, Groq, Gemini, Voyage, etc.)
+uvx --with graphiti-mcp-varming[providers] graphiti-mcp-varming
+
+# With everything
+uvx --with graphiti-mcp-varming[all] graphiti-mcp-varming
+```
+
+## Version Numbering
+
+Follow [Semantic Versioning](https://semver.org/):
+- **MAJOR** (1.0.0 → 2.0.0): Breaking changes
+- **MINOR** (1.0.0 → 1.1.0): New features, backwards compatible
+- **PATCH** (1.0.0 → 1.0.1): Bug fixes
+
+## Tag Naming Convention
+
+Use `mcp-v{VERSION}` format for tags:
+- `mcp-v1.0.0` - Initial release
+- `mcp-v1.0.1` - Patch release
+- `mcp-v1.1.0` - Minor release
+- `mcp-v2.0.0` - Major release
+
+This distinguishes MCP server releases from graphiti-core releases.
+
+## Troubleshooting
+
+### Publishing Fails with "File already exists"
+
+You tried to publish a version that already exists on PyPI. Increment the version number in `pyproject.toml` and try again.
+
+### "Invalid or missing authentication token"
+
+The PyPI token in GitHub secrets is incorrect or expired:
+1. Generate a new token at https://pypi.org/manage/account/token/
+2. Update the `PYPI_API_TOKEN` secret in GitHub
+
+### Workflow doesn't trigger
+
+Make sure:
+- Tag matches pattern `mcp-v*.*.*`
+- Tag is pushed to GitHub: `git push origin mcp-v1.0.0`
+- Workflow file is on the `main` branch
+
+## Checking Published Package
+
+After publishing, verify at:
+- PyPI page: https://pypi.org/project/graphiti-mcp-varming/
+- Test installation: `uvx graphiti-mcp-varming --help`

mcp_server/PYPI_SETUP_COMPLETE.md

@@ -0,0 +1,139 @@
+# PyPI Package Setup Complete! 🚀
+
+## Summary
+
+Your Graphiti MCP Server is now ready to be published to PyPI as `graphiti-mcp-varming`!
+
+## What Was Done
+
+### 1. ✅ Package Configuration (`mcp_server/pyproject.toml`)
+- **Name**: `graphiti-mcp-varming` (clearly distinguishes your enhanced fork)
+- **Entry point**: `graphiti-mcp-varming` command added
+- **Dependencies**: Standalone package with:
+  - `graphiti-core>=0.16.0` (includes Neo4j support by default)
+  - All MCP and OpenAI dependencies
+  - Optional extras for FalkorDB, other LLM providers (Anthropic, Groq, Gemini, Voyage)
+- **Metadata**: Proper description, keywords, classifiers for PyPI
+
+### 2. ✅ GitHub Actions Workflow (`.github/workflows/publish-mcp-pypi.yml`)
+- Automatic publishing to PyPI when you push tags like `mcp-v1.0.0`
+- Builds package with `uv build`
+- Publishes with `uv publish`
+- Creates GitHub releases with dist files
+
+### 3. ✅ Documentation Updates
+- **`DOCS/LibreChat-Unraid-Stdio-Setup.md`**: Updated with `uvx` commands
+- **`mcp_server/PYPI_PUBLISHING.md`**: Complete publishing guide
+- **`mcp_server/README.md`**: Added PyPI package notice
+
+## Next Steps (What You Need To Do)
+
+### 1. Add PyPI Token to GitHub
+
+1. Go to: https://github.com/Varming73/graphiti/settings/secrets/actions
+2. Click **"New repository secret"**
+3. Name: `PYPI_API_TOKEN`
+4. Value: Your PyPI token (starts with `pypi-`)
+5. Click **"Add secret"**
+
+### 2. Update Your Email in pyproject.toml (Optional)
+
+Edit `mcp_server/pyproject.toml` line with your real email:
+```toml
+authors = [
+    {name = "Varming", email = "your-real-email@example.com"}
+]
+```
+
+### 3. Publish First Version
+
+```bash
+# Make sure all changes are committed
+git add .
+git commit -m "Prepare graphiti-mcp-varming for PyPI publishing"
+git push
+
+# Create and push the first release tag
+git tag mcp-v1.0.0
+git push origin mcp-v1.0.0
+```
+
+### 4. Monitor Publishing
+
+- Go to: https://github.com/Varming73/graphiti/actions
+- Watch the "Publish MCP Server to PyPI" workflow
+- Should complete in ~2-3 minutes
+
+### 5. Verify Publication
+
+After workflow completes:
+- Check PyPI: https://pypi.org/project/graphiti-mcp-varming/
+- Test installation: `uvx graphiti-mcp-varming --help`
+
+## Usage After Publishing
+
+Users can now install your enhanced MCP server easily:
+
+### Basic Installation (Neo4j support included)
+```bash
+uvx graphiti-mcp-varming
+```
+
+### With FalkorDB Support
+```bash
+uvx --with graphiti-mcp-varming[falkordb] graphiti-mcp-varming
+```
+
+### With All LLM Providers
+```bash
+uvx --with graphiti-mcp-varming[providers] graphiti-mcp-varming
+```
+
+### With Everything
+```bash
+uvx --with graphiti-mcp-varming[all] graphiti-mcp-varming
+```
+
+### In LibreChat (stdio mode)
+```yaml
+mcpServers:
+  graphiti:
+    type: stdio
+    command: uvx
+    args:
+      - graphiti-mcp-varming
+    env:
+      GRAPHITI_GROUP_ID: "{{LIBRECHAT_USER_ID}}"
+      NEO4J_URI: "bolt://neo4j:7687"
+      NEO4J_USER: "neo4j"
+      NEO4J_PASSWORD: "your_password"
+      OPENAI_API_KEY: "${OPENAI_API_KEY}"
+```
+
+## Future Releases
+
+To publish updates:
+
+1. Update version in `mcp_server/pyproject.toml`
+2. Commit and push changes
+3. Create and push new tag: `git tag mcp-v1.0.1 && git push origin mcp-v1.0.1`
+4. GitHub Actions handles the rest!
+
+## Package Features
+
+Your `graphiti-mcp-varming` package includes:
+
+✅ **Standalone**: All dependencies bundled (graphiti-core, neo4j driver, etc.)
+✅ **Multi-database**: Neo4j (default) + optional FalkorDB support
+✅ **Multi-LLM**: OpenAI (default) + optional Anthropic, Groq, Gemini, Azure
+✅ **Enhanced Tools**: Your custom `get_entities_by_type` and `compare_facts_over_time`
+✅ **Per-user Isolation**: Full support for LibreChat multi-user via stdio mode
+✅ **Easy Install**: One command with `uvx`
+
+## Troubleshooting
+
+See `mcp_server/PYPI_PUBLISHING.md` for detailed troubleshooting guide.
+
+---
+
+**Questions?** The publishing guide has all the details: `mcp_server/PYPI_PUBLISHING.md`

mcp_server/pyproject.toml

@@ -1,21 +1,59 @@
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src"]
+
+[tool.hatch.metadata]
+allow-direct-references = true
+
 [project]
-name = "mcp-server"
+name = "graphiti-mcp-varming"
 version = "1.0.0"
-description = "Graphiti MCP Server"
+description = "Graphiti MCP Server - Enhanced fork with additional tools by Varming"
 readme = "README.md"
 requires-python = ">=3.10,<4"
+license = {text = "Apache-2.0"}
+authors = [
+    {name = "Varming", email = "varming@example.com"}
+]
+keywords = ["mcp", "graphiti", "knowledge-graph", "llm", "ai"]
+classifiers = [
+    "Development Status :: 4 - Beta",
+    "Intended Audience :: Developers",
+    "License :: OSI Approved :: Apache Software License",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
+]
 dependencies = [
     "mcp>=1.21.0",
     "openai>=1.91.0",
-    "graphiti-core[falkordb]>=0.16.0",
+    "graphiti-core>=0.16.0",  # Includes neo4j driver by default
     "pydantic-settings>=2.0.0",
     "pyyaml>=6.0",
 ]
 
+[project.scripts]
+graphiti-mcp-varming = "src.graphiti_mcp_server:main"
+
+[project.urls]
+Homepage = "https://github.com/Varming73/graphiti"
+Repository = "https://github.com/Varming73/graphiti"
+Issues = "https://github.com/Varming73/graphiti/issues"
+
 [project.optional-dependencies]
+# FalkorDB support (Neo4j is included in graphiti-core by default)
+falkordb = ["graphiti-core[falkordb]>=0.16.0"]
+
+# Azure support
 azure = [
     "azure-identity>=1.21.0",
 ]
+
+# LLM/Embedder providers
 providers = [
     "google-genai>=1.8.0",
     "anthropic>=0.49.0",
@@ -23,6 +61,18 @@ providers = [
     "voyageai>=0.2.3",
     "sentence-transformers>=2.0.0",
 ]
+
+# All optional features
+all = [
+    "graphiti-core[falkordb]>=0.16.0",
+    "azure-identity>=1.21.0",
+    "google-genai>=1.8.0",
+    "anthropic>=0.49.0",
+    "groq>=0.2.0",
+    "voyageai>=0.2.3",
+    "sentence-transformers>=2.0.0",
+]
+
 dev = [
     "graphiti-core>=0.16.0",
     "httpx>=0.28.1",
@@ -63,8 +113,9 @@ quote-style = "single"
 indent-style = "space"
 docstring-code-format = true
 
-[tool.uv.sources]
+# Note: For local development, you can override graphiti-core source:
-graphiti-core = { path = "../", editable = true }
+# [tool.uv.sources]
+# graphiti-core = { path = "../", editable = true }
 
 [dependency-groups]
 dev = [

mcp_server/src/graphiti_mcp_server.py

@@ -21,8 +21,8 @@ from mcp.server.fastmcp import FastMCP
 from pydantic import BaseModel
 from starlette.responses import JSONResponse
 
-from config.schema import GraphitiConfig, ServerConfig
+from .config.schema import GraphitiConfig, ServerConfig
-from models.response_types import (
+from .models.response_types import (
     EpisodeSearchResponse,
     ErrorResponse,
     FactSearchResponse,
@@ -31,9 +31,9 @@ from models.response_types import (
     StatusResponse,
     SuccessResponse,
 )
-from services.factories import DatabaseDriverFactory, EmbedderFactory, LLMClientFactory
+from .services.factories import DatabaseDriverFactory, EmbedderFactory, LLMClientFactory
-from services.queue_service import QueueService
+from .services.queue_service import QueueService
-from utils.formatting import format_fact_result
+from .utils.formatting import format_fact_result
 
 # Load .env file from mcp_server directory
 mcp_server_dir = Path(__file__).parent.parent
@@ -326,12 +326,6 @@ class GraphitiService:
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'write', 'memory', 'ingestion', 'core'},
-    meta={
-        'version': '1.0',
-        'category': 'core',
-        'priority': 0.9,
-    },
 )
 async def add_memory(
     name: str,
@@ -440,12 +434,6 @@ async def add_memory(
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'search', 'entities', 'memory', 'core'},
-    meta={
-        'version': '1.0',
-        'category': 'core',
-        'priority': 0.8,
-    },
 )
 async def search_nodes(
     query: str,
@@ -566,12 +554,6 @@ async def search_nodes(
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'search', 'entities', 'legacy', 'compatibility'},
-    meta={
-        'version': '1.0',
-        'category': 'compatibility',
-        'priority': 0.7,
-    },
 )
 async def search_memory_nodes(
     query: str,
@@ -618,12 +600,6 @@ async def search_memory_nodes(
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'search', 'entities', 'browse', 'classification'},
-    meta={
-        'version': '1.0',
-        'category': 'discovery',
-        'priority': 0.75,
-    },
 )
 async def get_entities_by_type(
     entity_types: list[str],
@@ -748,12 +724,6 @@ async def get_entities_by_type(
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'search', 'facts', 'relationships', 'memory', 'core'},
-    meta={
-        'version': '1.0',
-        'category': 'core',
-        'priority': 0.85,
-    },
 )
 async def search_memory_facts(
     query: str,
@@ -849,12 +819,6 @@ async def search_memory_facts(
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'search', 'facts', 'temporal', 'analysis', 'evolution'},
-    meta={
-        'version': '1.0',
-        'category': 'analytics',
-        'priority': 0.6,
-    },
 )
 async def compare_facts_over_time(
     query: str,
@@ -1076,12 +1040,6 @@ async def compare_facts_over_time(
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'delete', 'destructive', 'facts', 'admin'},
-    meta={
-        'version': '1.0',
-        'category': 'maintenance',
-        'priority': 0.3,
-    },
 )
 async def delete_entity_edge(uuid: str) -> SuccessResponse | ErrorResponse:
     """Delete a specific relationship/fact. **DESTRUCTIVE - Cannot be undone.**
@@ -1137,12 +1095,6 @@ async def delete_entity_edge(uuid: str) -> SuccessResponse | ErrorResponse:
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'delete', 'destructive', 'episodes', 'admin'},
-    meta={
-        'version': '1.0',
-        'category': 'maintenance',
-        'priority': 0.3,
-    },
 )
 async def delete_episode(uuid: str) -> SuccessResponse | ErrorResponse:
     """Delete a specific episode. **DESTRUCTIVE - Cannot be undone.**
@@ -1199,12 +1151,6 @@ async def delete_episode(uuid: str) -> SuccessResponse | ErrorResponse:
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'retrieval', 'facts', 'uuid', 'direct-access'},
-    meta={
-        'version': '1.0',
-        'category': 'direct-access',
-        'priority': 0.5,
-    },
 )
 async def get_entity_edge(uuid: str) -> dict[str, Any] | ErrorResponse:
     """Retrieve a specific relationship/fact by its UUID. **Direct lookup only.**
@@ -1254,12 +1200,6 @@ async def get_entity_edge(uuid: str) -> dict[str, Any] | ErrorResponse:
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'retrieval', 'episodes', 'history', 'changelog'},
-    meta={
-        'version': '1.0',
-        'category': 'direct-access',
-        'priority': 0.5,
-    },
 )
 async def get_episodes(
     group_id: str | None = None,
@@ -1368,12 +1308,6 @@ async def get_episodes(
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'delete', 'destructive', 'admin', 'bulk', 'danger'},
-    meta={
-        'version': '1.0',
-        'category': 'admin',
-        'priority': 0.1,
-    },
 )
 async def clear_graph(
     group_id: str | None = None,
@@ -1453,12 +1387,6 @@ async def clear_graph(
         'idempotentHint': True,
         'openWorldHint': True,
     },
-    tags={'admin', 'health', 'status', 'diagnostics'},
-    meta={
-        'version': '1.0',
-        'category': 'admin',
-        'priority': 0.4,
-    },
 )
 async def get_status() -> StatusResponse:
     """Check server health and database connectivity.

mcp_server/src/models/response_types.py

@@ -1,6 +1,7 @@
 """Response type definitions for Graphiti MCP Server."""
 
-from typing import Any, TypedDict
+from typing import Any
+from typing_extensions import TypedDict
 
 
 class ErrorResponse(TypedDict):

mcp_server/src/services/factories.py

@@ -2,7 +2,7 @@
 
 from openai import AsyncAzureOpenAI
 
-from config.schema import (
+from ..config.schema import (
     DatabaseConfig,
     EmbedderConfig,
     LLMConfig,
@@ -70,7 +70,7 @@ try:
     HAS_GROQ = True
 except ImportError:
     HAS_GROQ = False
-from utils.utils import create_azure_credential_token_provider
+from ..utils.utils import create_azure_credential_token_provider
 
 
 def _validate_api_key(provider_name: str, api_key: str | None, logger) -> str: