diff --git a/.env.template b/.env.template
index 03b0218f5..5670b3587 100644
--- a/.env.template
+++ b/.env.template
@@ -30,7 +30,7 @@ GRAPH_DATABASE_URL=
 GRAPH_DATABASE_USERNAME=
 GRAPH_DATABASE_PASSWORD=
 
-# "qdrant", "pgvector", "weaviate", "milvus" or "lancedb"
+# "qdrant", "pgvector", "weaviate", "milvus", "lancedb" or "chromadb"
 VECTOR_DB_PROVIDER="lancedb"
 # Not needed if using "lancedb" or "pgvector"
 VECTOR_DB_URL=
diff --git a/.github/workflows/test_chromadb.yml b/.github/workflows/test_chromadb.yml
new file mode 100644
index 000000000..bec73a3ef
--- /dev/null
+++ b/.github/workflows/test_chromadb.yml
@@ -0,0 +1,63 @@
+name: test | chromadb
+
+on:
+  workflow_dispatch:
+  pull_request:
+    types: [labeled, synchronize]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+
+env:
+  RUNTIME__LOG_LEVEL: ERROR
+
+jobs:
+  run_chromadb_integration_test:
+    name: chromadb test
+    runs-on: ubuntu-22.04
+    defaults:
+      run:
+        shell: bash
+    services:
+      chromadb:
+        image: chromadb/chroma:0.6.3
+        volumes:
+          - chroma-data:/chroma/chroma
+        ports:
+          - 3002:8000
+
+    steps:
+      - name: Check out
+        uses: actions/checkout@master
+
+      - name: Setup Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11.x'
+
+      - name: Install Poetry
+        uses: snok/install-poetry@v1.4.1
+        with:
+          virtualenvs-create: true
+          virtualenvs-in-project: true
+          installer-parallel: true
+
+      - name: Install dependencies
+        run: poetry install --no-interaction
+
+      - name: Run chromadb test
+        env:
+          ENV: 'dev'
+          VECTOR_DB_PROVIDER: chromadb
+          VECTOR_DB_URL: http://localhost:3002
+          VECTOR_DB_KEY: test-token
+          LLM_MODEL: ${{ secrets.LLM_MODEL }}
+          LLM_ENDPOINT: ${{ secrets.LLM_ENDPOINT }}
+          LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
+          LLM_API_VERSION: ${{ secrets.LLM_API_VERSION }}
+          EMBEDDING_MODEL: ${{ secrets.EMBEDDING_MODEL }}
+          EMBEDDING_ENDPOINT: ${{ secrets.EMBEDDING_ENDPOINT }}
+          EMBEDDING_API_KEY: ${{ secrets.EMBEDDING_API_KEY }}
+          EMBEDDING_API_VERSION: ${{ secrets.EMBEDDING_API_VERSION }}
+        run: poetry run python ./cognee/tests/test_chromadb.py
diff --git a/.gitignore b/.gitignore
index 90a5d720a..3750b6bc1 100644
--- a/.gitignore
+++ b/.gitignore
@@ -186,3 +186,6 @@ node_modules/
 
 # Evals
 SWE-bench_testsample/
+
+# ChromaDB Data
+.chromadb_data/
\ No newline at end of file
diff --git a/cognee/api/v1/settings/routers/get_settings_router.py b/cognee/api/v1/settings/routers/get_settings_router.py
index e2842e3cd..f4e33414e 100644
--- a/cognee/api/v1/settings/routers/get_settings_router.py
+++ b/cognee/api/v1/settings/routers/get_settings_router.py
@@ -27,7 +27,13 @@ class LLMConfigInputDTO(InDTO):
 
 
 class VectorDBConfigInputDTO(InDTO):
-    provider: Union[Literal["lancedb"], Literal["qdrant"], Literal["weaviate"], Literal["pgvector"]]
+    provider: Union[
+        Literal["lancedb"],
+        Literal["chromadb"],
+        Literal["qdrant"],
+        Literal["weaviate"],
+        Literal["pgvector"],
+    ]
     url: str
     api_key: str
 
diff --git a/cognee/infrastructure/databases/vector/chromadb/ChromaDBAdapter.py b/cognee/infrastructure/databases/vector/chromadb/ChromaDBAdapter.py
new file mode 100644
index 000000000..91d135f08
--- /dev/null
+++ b/cognee/infrastructure/databases/vector/chromadb/ChromaDBAdapter.py
@@ -0,0 +1,367 @@
+import logging
+from typing import Dict, List, Optional, Any
+import os
+import json
+from uuid import UUID
+
+from chromadb import AsyncHttpClient, Settings
+
+from cognee.exceptions import InvalidValueError
+from cognee.infrastructure.engine.utils import parse_id
+from cognee.infrastructure.engine import DataPoint
+from cognee.infrastructure.databases.vector.models.ScoredResult import ScoredResult
+
+from ..embeddings.EmbeddingEngine import EmbeddingEngine
+from ..vector_db_interface import VectorDBInterface
+from ..utils import normalize_distances
+
+logger = logging.getLogger("ChromaDBAdapter")
+
+
+class IndexSchema(DataPoint):
+    text: str
+
+    metadata: dict = {"index_fields": ["text"]}
+
+    def model_dump(self):
+        data = super().model_dump()
+        return process_data_for_chroma(data)
+
+
+def process_data_for_chroma(data):
+    """Convert complex data types to a format suitable for ChromaDB storage."""
+    processed_data = {}
+    for key, value in data.items():
+        if isinstance(value, UUID):
+            processed_data[key] = str(value)
+        elif isinstance(value, dict):
+            # Store dictionaries as JSON strings with special prefix
+            processed_data[f"{key}__dict"] = json.dumps(value)
+        elif isinstance(value, list):
+            # Store lists as JSON strings with special prefix
+            processed_data[f"{key}__list"] = json.dumps(value)
+        elif isinstance(value, (str, int, float, bool)) or value is None:
+            processed_data[key] = value
+        else:
+            processed_data[key] = str(value)
+    return processed_data
+
+
+def restore_data_from_chroma(data):
+    """Restore original data structure from ChromaDB storage format."""
+    restored_data = {}
+    dict_keys = []
+    list_keys = []
+
+    # First, identify all special keys
+    for key in data.keys():
+        if key.endswith("__dict"):
+            dict_keys.append(key)
+        elif key.endswith("__list"):
+            list_keys.append(key)
+        else:
+            restored_data[key] = data[key]
+
+    # Process dictionary fields
+    for key in dict_keys:
+        original_key = key[:-6]  # Remove '__dict' suffix
+        try:
+            restored_data[original_key] = json.loads(data[key])
+        except Exception as e:
+            logger.debug(f"Error restoring dictionary from JSON: {e}")
+            restored_data[key] = data[key]
+
+    # Process list fields
+    for key in list_keys:
+        original_key = key[:-6]  # Remove '__list' suffix
+        try:
+            restored_data[original_key] = json.loads(data[key])
+        except Exception as e:
+            logger.debug(f"Error restoring list from JSON: {e}")
+            restored_data[key] = data[key]
+
+    return restored_data
+
+
+class ChromaDBAdapter(VectorDBInterface):
+    name = "ChromaDB"
+    url: str
+    api_key: str
+    connection: AsyncHttpClient = None
+
+    def __init__(
+        self, url: Optional[str], api_key: Optional[str], embedding_engine: EmbeddingEngine
+    ):
+        self.embedding_engine = embedding_engine
+        self.url = url
+        self.api_key = api_key
+
+    async def get_connection(self) -> AsyncHttpClient:
+        if self.connection is None:
+            settings = Settings(
+                chroma_client_auth_provider="token", chroma_client_auth_credentials=self.api_key
+            )
+            self.connection = await AsyncHttpClient(host=self.url, settings=settings)
+
+        return self.connection
+
+    async def embed_data(self, data: list[str]) -> list[list[float]]:
+        return await self.embedding_engine.embed_text(data)
+
+    async def has_collection(self, collection_name: str) -> bool:
+        client = await self.get_connection()
+        collections = await client.list_collections()
+        # In ChromaDB v0.6.0, list_collections returns collection names directly
+        return collection_name in collections
+
+    async def create_collection(self, collection_name: str, payload_schema=None):
+        client = await self.get_connection()
+
+        if not await self.has_collection(collection_name):
+            await client.create_collection(name=collection_name, metadata={"hnsw:space": "cosine"})
+
+    async def create_data_points(self, collection_name: str, data_points: list[DataPoint]):
+        client = await self.get_connection()
+
+        if not await self.has_collection(collection_name):
+            await self.create_collection(collection_name)
+
+        collection = await client.get_collection(collection_name)
+
+        texts = [DataPoint.get_embeddable_data(data_point) for data_point in data_points]
+        embeddings = await self.embed_data(texts)
+        ids = [str(data_point.id) for data_point in data_points]
+
+        metadatas = []
+        for data_point in data_points:
+            metadata = data_point.model_dump()
+            metadatas.append(process_data_for_chroma(metadata))
+
+        await collection.upsert(
+            ids=ids, embeddings=embeddings, metadatas=metadatas, documents=texts
+        )
+
+    async def create_vector_index(self, index_name: str, index_property_name: str):
+        """Create a vector index as a ChromaDB collection."""
+        await self.create_collection(f"{index_name}_{index_property_name}")
+
+    async def index_data_points(
+        self, index_name: str, index_property_name: str, data_points: list[DataPoint]
+    ):
+        """Index data points using the specified index property."""
+        await self.create_data_points(
+            f"{index_name}_{index_property_name}",
+            [
+                IndexSchema(
+                    id=data_point.id,
+                    text=getattr(data_point, data_point.metadata["index_fields"][0]),
+                )
+                for data_point in data_points
+            ],
+        )
+
+    async def retrieve(self, collection_name: str, data_point_ids: list[str]):
+        """Retrieve data points by their IDs from a collection."""
+        client = await self.get_connection()
+        collection = await client.get_collection(collection_name)
+        results = await collection.get(ids=data_point_ids, include=["metadatas"])
+
+        return [
+            ScoredResult(
+                id=parse_id(id),
+                payload=restore_data_from_chroma(metadata),
+                score=0,
+            )
+            for id, metadata in zip(results["ids"], results["metadatas"])
+        ]
+
+    async def get_distance_from_collection_elements(
+        self, collection_name: str, query_text: str = None, query_vector: List[float] = None
+    ):
+        """Calculate distance between query and all elements in a collection."""
+        if query_text is None and query_vector is None:
+            raise InvalidValueError(message="One of query_text or query_vector must be provided!")
+
+        if query_text and not query_vector:
+            query_vector = (await self.embedding_engine.embed_text([query_text]))[0]
+
+        client = await self.get_connection()
+        try:
+            collection = await client.get_collection(collection_name)
+
+            collection_count = await collection.count()
+
+            results = await collection.query(
+                query_embeddings=[query_vector],
+                include=["metadatas", "distances"],
+                n_results=collection_count,
+            )
+
+            result_values = []
+            for i, (id, metadata, distance) in enumerate(
+                zip(results["ids"][0], results["metadatas"][0], results["distances"][0])
+            ):
+                result_values.append(
+                    {
+                        "id": parse_id(id),
+                        "payload": restore_data_from_chroma(metadata),
+                        "_distance": distance,
+                    }
+                )
+
+            normalized_values = normalize_distances(result_values)
+
+            scored_results = []
+            for i, result in enumerate(result_values):
+                scored_results.append(
+                    ScoredResult(
+                        id=result["id"],
+                        payload=result["payload"],
+                        score=normalized_values[i],
+                    )
+                )
+
+            return scored_results
+        except Exception as e:
+            logger.error(f"Error in get_distance_from_collection_elements: {str(e)}")
+            return []
+
+    async def search(
+        self,
+        collection_name: str,
+        query_text: str = None,
+        query_vector: List[float] = None,
+        limit: int = 5,
+        with_vector: bool = False,
+        normalized: bool = True,
+    ):
+        """Search for similar items in a collection using text or vector query."""
+        if query_text is None and query_vector is None:
+            raise InvalidValueError(message="One of query_text or query_vector must be provided!")
+
+        if query_text and not query_vector:
+            query_vector = (await self.embedding_engine.embed_text([query_text]))[0]
+
+        try:
+            client = await self.get_connection()
+            collection = await client.get_collection(collection_name)
+
+            results = await collection.query(
+                query_embeddings=[query_vector],
+                include=["metadatas", "distances", "embeddings"]
+                if with_vector
+                else ["metadatas", "distances"],
+                n_results=limit,
+            )
+
+            vector_list = []
+            for i, (id, metadata, distance) in enumerate(
+                zip(results["ids"][0], results["metadatas"][0], results["distances"][0])
+            ):
+                item = {
+                    "id": parse_id(id),
+                    "payload": restore_data_from_chroma(metadata),
+                    "_distance": distance,
+                }
+
+                if with_vector and "embeddings" in results:
+                    item["vector"] = results["embeddings"][0][i]
+
+                vector_list.append(item)
+
+            # Normalize vector distance
+            normalized_values = normalize_distances(vector_list)
+            for i in range(len(normalized_values)):
+                vector_list[i]["score"] = normalized_values[i]
+
+            # Create and return ScoredResult objects
+            return [
+                ScoredResult(
+                    id=row["id"],
+                    payload=row["payload"],
+                    score=row["score"],
+                    vector=row.get("vector") if with_vector else None,
+                )
+                for row in vector_list
+            ]
+        except Exception as e:
+            logger.error(f"Error in search: {str(e)}")
+            return []
+
+    async def batch_search(
+        self,
+        collection_name: str,
+        query_texts: List[str],
+        limit: int = 5,
+        with_vectors: bool = False,
+    ):
+        """Perform multiple searches in a single request for efficiency."""
+        query_vectors = await self.embed_data(query_texts)
+
+        client = await self.get_connection()
+        collection = await client.get_collection(collection_name)
+
+        results = await collection.query(
+            query_embeddings=query_vectors,
+            include=["metadatas", "distances", "embeddings"]
+            if with_vectors
+            else ["metadatas", "distances"],
+            n_results=limit,
+        )
+
+        all_results = []
+        for i in range(len(query_texts)):
+            vector_list = []
+
+            for j, (id, metadata, distance) in enumerate(
+                zip(results["ids"][i], results["metadatas"][i], results["distances"][i])
+            ):
+                item = {
+                    "id": parse_id(id),
+                    "payload": restore_data_from_chroma(metadata),
+                    "_distance": distance,
+                }
+
+                if with_vectors and "embeddings" in results:
+                    item["vector"] = results["embeddings"][i][j]
+
+                vector_list.append(item)
+
+            normalized_values = normalize_distances(vector_list)
+
+            query_results = []
+            for j, item in enumerate(vector_list):
+                result = ScoredResult(
+                    id=item["id"],
+                    payload=item["payload"],
+                    score=normalized_values[j],
+                )
+
+                if with_vectors and "embeddings" in results:
+                    result.vector = item.get("vector")
+
+                query_results.append(result)
+
+            all_results.append(query_results)
+
+        return all_results
+
+    async def delete_data_points(self, collection_name: str, data_point_ids: list[str]):
+        """Remove data points from a collection by their IDs."""
+        client = await self.get_connection()
+        collection = await client.get_collection(collection_name)
+        await collection.delete(ids=data_point_ids)
+        return True
+
+    async def prune(self):
+        """Delete all collections in the ChromaDB database."""
+        client = await self.get_connection()
+        collections = await client.list_collections()
+        for collection_name in collections:
+            await client.delete_collection(collection_name)
+        return True
+
+    async def get_collection_names(self):
+        """Get a list of all collection names in the database."""
+        client = await self.get_connection()
+        return await client.list_collections()
diff --git a/cognee/infrastructure/databases/vector/chromadb/__init__.py b/cognee/infrastructure/databases/vector/chromadb/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/cognee/infrastructure/databases/vector/create_vector_engine.py b/cognee/infrastructure/databases/vector/create_vector_engine.py
index f5d458061..e49a2c4a8 100644
--- a/cognee/infrastructure/databases/vector/create_vector_engine.py
+++ b/cognee/infrastructure/databases/vector/create_vector_engine.py
@@ -82,6 +82,22 @@ def create_vector_engine(
             embedding_engine=embedding_engine,
         )
 
+    elif vector_db_provider == "chromadb":
+        try:
+            import chromadb
+        except ImportError:
+            raise ImportError(
+                "ChromaDB is not installed. Please install it with 'pip install chromadb'"
+            )
+
+        from .chromadb.ChromaDBAdapter import ChromaDBAdapter
+
+        return ChromaDBAdapter(
+            url=vector_db_url,
+            api_key=vector_db_key,
+            embedding_engine=embedding_engine,
+        )
+
     else:
         from .lancedb.LanceDBAdapter import LanceDBAdapter
 
diff --git a/cognee/tests/test_chromadb.py b/cognee/tests/test_chromadb.py
new file mode 100644
index 000000000..6b7f0bc3f
--- /dev/null
+++ b/cognee/tests/test_chromadb.py
@@ -0,0 +1,169 @@
+import os
+import logging
+import pathlib
+import cognee
+
+from cognee.modules.data.models import Data
+from cognee.modules.search.types import SearchType
+from cognee.modules.retrieval.utils.brute_force_triplet_search import brute_force_triplet_search
+from cognee.modules.users.methods import get_default_user
+
+logging.basicConfig(level=logging.DEBUG)
+
+
+async def test_local_file_deletion(data_text, file_location):
+    from sqlalchemy import select
+    import hashlib
+    from cognee.infrastructure.databases.relational import get_relational_engine
+
+    engine = get_relational_engine()
+
+    async with engine.get_async_session() as session:
+        # Get hash of data contents
+        encoded_text = data_text.encode("utf-8")
+        data_hash = hashlib.md5(encoded_text).hexdigest()
+        # Get data entry from database based on hash contents
+        data = (await session.scalars(select(Data).where(Data.content_hash == data_hash))).one()
+        assert os.path.isfile(data.raw_data_location), (
+            f"Data location doesn't exist: {data.raw_data_location}"
+        )
+        # Test deletion of data along with local files created by cognee
+        await engine.delete_data_entity(data.id)
+        assert not os.path.exists(data.raw_data_location), (
+            f"Data location still exists after deletion: {data.raw_data_location}"
+        )
+
+    async with engine.get_async_session() as session:
+        # Get data entry from database based on file path
+        data = (
+            await session.scalars(select(Data).where(Data.raw_data_location == file_location))
+        ).one()
+        assert os.path.isfile(data.raw_data_location), (
+            f"Data location doesn't exist: {data.raw_data_location}"
+        )
+        # Test local files not created by cognee won't get deleted
+        await engine.delete_data_entity(data.id)
+        assert os.path.exists(data.raw_data_location), (
+            f"Data location doesn't exists: {data.raw_data_location}"
+        )
+
+
+async def test_getting_of_documents(dataset_name_1):
+    # Test getting of documents for search per dataset
+    from cognee.modules.users.permissions.methods import get_document_ids_for_user
+
+    user = await get_default_user()
+    document_ids = await get_document_ids_for_user(user.id, [dataset_name_1])
+    assert len(document_ids) == 1, (
+        f"Number of expected documents doesn't match {len(document_ids)} != 1"
+    )
+
+    # Test getting of documents for search when no dataset is provided
+    user = await get_default_user()
+    document_ids = await get_document_ids_for_user(user.id)
+    assert len(document_ids) == 2, (
+        f"Number of expected documents doesn't match {len(document_ids)} != 2"
+    )
+
+
+async def main():
+    cognee.config.set_vector_db_config(
+        {
+            "vector_db_url": "http://localhost:3002",
+            "vector_db_key": "test-token",
+            "vector_db_provider": "chromadb",
+        }
+    )
+
+    data_directory_path = str(
+        pathlib.Path(
+            os.path.join(pathlib.Path(__file__).parent, ".data_storage/test_chromadb")
+        ).resolve()
+    )
+    cognee.config.data_root_directory(data_directory_path)
+    cognee_directory_path = str(
+        pathlib.Path(
+            os.path.join(pathlib.Path(__file__).parent, ".cognee_system/test_chromadb")
+        ).resolve()
+    )
+    cognee.config.system_root_directory(cognee_directory_path)
+
+    await cognee.prune.prune_data()
+    await cognee.prune.prune_system(metadata=True)
+
+    dataset_name_1 = "natural_language"
+    dataset_name_2 = "quantum"
+
+    explanation_file_path = os.path.join(
+        pathlib.Path(__file__).parent, "test_data/Natural_language_processing.txt"
+    )
+    await cognee.add([explanation_file_path], dataset_name_1)
+
+    text = """A quantum computer is a computer that takes advantage of quantum mechanical phenomena.
+    At small scales, physical matter exhibits properties of both particles and waves, and quantum computing leverages this behavior, specifically quantum superposition and entanglement, using specialized hardware that supports the preparation and manipulation of quantum states.
+    Classical physics cannot explain the operation of these quantum devices, and a scalable quantum computer could perform some calculations exponentially faster (with respect to input size scaling) than any modern "classical" computer. In particular, a large-scale quantum computer could break widely used encryption schemes and aid physicists in performing physical simulations; however, the current state of the technology is largely experimental and impractical, with several obstacles to useful applications. Moreover, scalable quantum computers do not hold promise for many practical tasks, and for many important tasks quantum speedups are proven impossible.
+    The basic unit of information in quantum computing is the qubit, similar to the bit in traditional digital electronics. Unlike a classical bit, a qubit can exist in a superposition of its two "basis" states. When measuring a qubit, the result is a probabilistic output of a classical bit, therefore making quantum computers nondeterministic in general. If a quantum computer manipulates the qubit in a particular way, wave interference effects can amplify the desired measurement results. The design of quantum algorithms involves creating procedures that allow a quantum computer to perform calculations efficiently and quickly.
+    Physically engineering high-quality qubits has proven challenging. If a physical qubit is not sufficiently isolated from its environment, it suffers from quantum decoherence, introducing noise into calculations. Paradoxically, perfectly isolating qubits is also undesirable because quantum computations typically need to initialize qubits, perform controlled qubit interactions, and measure the resulting quantum states. Each of those operations introduces errors and suffers from noise, and such inaccuracies accumulate.
+    In principle, a non-quantum (classical) computer can solve the same computational problems as a quantum computer, given enough time. Quantum advantage comes in the form of time complexity rather than computability, and quantum complexity theory shows that some quantum algorithms for carefully selected tasks require exponentially fewer computational steps than the best known non-quantum algorithms. Such tasks can in theory be solved on a large-scale quantum computer whereas classical computers would not finish computations in any reasonable amount of time. However, quantum speedup is not universal or even typical across computational tasks, since basic tasks such as sorting are proven to not allow any asymptotic quantum speedup. Claims of quantum supremacy have drawn significant attention to the discipline, but are demonstrated on contrived tasks, while near-term practical use cases remain limited.
+    """
+
+    await cognee.add([text], dataset_name_2)
+
+    await cognee.cognify([dataset_name_2, dataset_name_1])
+
+    from cognee.infrastructure.databases.vector import get_vector_engine
+
+    await test_getting_of_documents(dataset_name_1)
+
+    vector_engine = get_vector_engine()
+    random_node = (await vector_engine.search("Entity_name", "Quantum computer"))[0]
+    random_node_name = random_node.payload["text"]
+
+    search_results = await cognee.search(
+        query_type=SearchType.INSIGHTS, query_text=random_node_name
+    )
+    assert len(search_results) != 0, "The search results list is empty."
+    print("\n\nExtracted sentences are:\n")
+    for result in search_results:
+        print(f"{result}\n")
+
+    search_results = await cognee.search(
+        query_type=SearchType.CHUNKS, query_text=random_node_name, datasets=[dataset_name_2]
+    )
+    assert len(search_results) != 0, "The search results list is empty."
+    print("\n\nExtracted chunks are:\n")
+    for result in search_results:
+        print(f"{result}\n")
+
+    graph_completion = await cognee.search(
+        query_type=SearchType.GRAPH_COMPLETION,
+        query_text=random_node_name,
+        datasets=[dataset_name_2],
+    )
+    assert len(graph_completion) != 0, "Completion result is empty."
+    print("Completion result is:")
+    print(graph_completion)
+
+    search_results = await cognee.search(
+        query_type=SearchType.SUMMARIES, query_text=random_node_name
+    )
+    assert len(search_results) != 0, "Query related summaries don't exist."
+    print("\n\nExtracted summaries are:\n")
+    for result in search_results:
+        print(f"{result}\n")
+
+    history = await cognee.get_search_history()
+    assert len(history) == 8, "Search history is not correct."
+
+    await cognee.prune.prune_data()
+    assert not os.path.isdir(data_directory_path), "Local data files are not deleted"
+
+    await cognee.prune.prune_system(metadata=True)
+    tables_in_database = await vector_engine.get_table_names()
+    assert len(tables_in_database) == 0, "ChromaDB database is not empty"
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    asyncio.run(main())
diff --git a/docker-compose.yml b/docker-compose.yml
index dc9bd2f7b..c075cf7c5 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -60,6 +60,25 @@ services:
       - 3001:3000
     networks:
       - cognee-network
+
+  chromadb:
+    image: chromadb/chroma:0.6.3
+    container_name: chromadb
+    profiles:
+      - chromadb
+    environment:
+      - IS_PERSISTENT=TRUE
+      - CHROMA_SERVER_AUTH_CREDENTIALS=${VECTOR_DB_KEY}
+      - CHROMA_SERVER_AUTH_CREDENTIALS_PROVIDER=chromadb.auth.token.TokenConfigServerAuthCredentialsProvider
+      - CHROMA_SERVER_AUTH_TOKEN_TRANSPORT_HEADER=AUTHORIZATION
+      - CHROMA_SERVER_AUTH_PROVIDER=chromadb.auth.token.TokenAuthServerProvider
+    volumes:
+      - .chromadb_data/:/chroma/chroma/
+    networks:
+      - cognee-network
+    ports:
+      - "3002:8000"
+
   # UNCOMMENT IF USING POSTGRES
   # postgres:
   #   image: pgvector/pgvector:pg17
@@ -75,12 +94,12 @@ services:
   #   networks:
   #     - cognee-network
   # UNCOMMENT THE VOLUES SECTION BELOW AS WELL TO USE POSTGRES
+
 networks:
   cognee-network:
     name: cognee-network
 
-# UNCOMMENT IF USING POSTGRES         
-# volumes:                           
-#   postgres_data:                  
-
-
+volumes:
+  chromadb_data:
+# UNCOMMENT IF USING POSTGRES
+#   postgres_data:
diff --git a/poetry.lock b/poetry.lock
index 4c9d84913..d4a9e244c 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -344,6 +344,24 @@ types-python-dateutil = ">=2.8.10"
 doc = ["doc8", "sphinx (>=7.0.0)", "sphinx-autobuild", "sphinx-autodoc-typehints", "sphinx_rtd_theme (>=1.3.0)"]
 test = ["dateparser (==1.*)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2021.1)", "simplejson (==3.*)"]
 
+[[package]]
+name = "asgiref"
+version = "3.8.1"
+description = "ASGI specs, helper code, and adapters"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "asgiref-3.8.1-py3-none-any.whl", hash = "sha256:3e1e3ecc849832fe52ccf2cb6686b7a55f82bb1d6aee72a58826471390335e47"},
+    {file = "asgiref-3.8.1.tar.gz", hash = "sha256:c343bd80a0bec947a9860adb4c432ffa7db769836c64238fc34bdc3fec84d590"},
+]
+
+[package.dependencies]
+typing-extensions = {version = ">=4", markers = "python_version < \"3.11\""}
+
+[package.extras]
+tests = ["mypy (>=0.800)", "pytest", "pytest-asyncio"]
+
 [[package]]
 name = "astroid"
 version = "3.3.9"
@@ -737,14 +755,39 @@ urllib3 = {version = ">=1.25.4,<2.2.0 || >2.2.0,<3", markers = "python_version >
 [package.extras]
 crt = ["awscrt (==0.23.8)"]
 
+[[package]]
+name = "build"
+version = "1.2.2.post1"
+description = "A simple, correct Python build frontend"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "build-1.2.2.post1-py3-none-any.whl", hash = "sha256:1d61c0887fa860c01971625baae8bdd338e517b836a2f70dd1f7aa3a6b2fc5b5"},
+    {file = "build-1.2.2.post1.tar.gz", hash = "sha256:b36993e92ca9375a219c99e606a122ff365a760a2d4bba0caa09bd5278b608b7"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "os_name == \"nt\""}
+importlib-metadata = {version = ">=4.6", markers = "python_full_version < \"3.10.2\""}
+packaging = ">=19.1"
+pyproject_hooks = "*"
+tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
+
+[package.extras]
+docs = ["furo (>=2023.08.17)", "sphinx (>=7.0,<8.0)", "sphinx-argparse-cli (>=1.5)", "sphinx-autodoc-typehints (>=1.10)", "sphinx-issues (>=3.0.0)"]
+test = ["build[uv,virtualenv]", "filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0) ; python_version < \"3.10\"", "setuptools (>=56.0.0) ; python_version == \"3.10\"", "setuptools (>=56.0.0) ; python_version == \"3.11\"", "setuptools (>=67.8.0) ; python_version >= \"3.12\"", "wheel (>=0.36.0)"]
+typing = ["build[uv]", "importlib-metadata (>=5.1)", "mypy (>=1.9.0,<1.10.0)", "tomli", "typing-extensions (>=3.7.4.3)"]
+uv = ["uv (>=0.1.18)"]
+virtualenv = ["virtualenv (>=20.0.35)"]
+
 [[package]]
 name = "cachetools"
 version = "5.5.2"
 description = "Extensible memoizing collections and decorators"
-optional = true
+optional = false
 python-versions = ">=3.7"
 groups = ["main"]
-markers = "extra == \"gemini\""
 files = [
     {file = "cachetools-5.5.2-py3-none-any.whl", hash = "sha256:d26a22bcc62eb95c3beabd9f1ee5e820d3d2704fe2967cbe350e20c8ffcd3f0a"},
     {file = "cachetools-5.5.2.tar.gz", hash = "sha256:1a661caa9175d26759571b2e19580f9d6393969e5dfca11fdb1f947a23e640d4"},
@@ -969,6 +1012,90 @@ files = [
     {file = "charset_normalizer-3.4.1.tar.gz", hash = "sha256:44251f18cd68a75b56585dd00dae26183e102cd5e0f9f1466e6df5da2ed64ea3"},
 ]
 
+[[package]]
+name = "chroma-hnswlib"
+version = "0.7.6"
+description = "Chromas fork of hnswlib"
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
+    {file = "chroma_hnswlib-0.7.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:f35192fbbeadc8c0633f0a69c3d3e9f1a4eab3a46b65458bbcbcabdd9e895c36"},
+    {file = "chroma_hnswlib-0.7.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:6f007b608c96362b8f0c8b6b2ac94f67f83fcbabd857c378ae82007ec92f4d82"},
+    {file = "chroma_hnswlib-0.7.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:456fd88fa0d14e6b385358515aef69fc89b3c2191706fd9aee62087b62aad09c"},
+    {file = "chroma_hnswlib-0.7.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5dfaae825499c2beaa3b75a12d7ec713b64226df72a5c4097203e3ed532680da"},
+    {file = "chroma_hnswlib-0.7.6-cp310-cp310-win_amd64.whl", hash = "sha256:2487201982241fb1581be26524145092c95902cb09fc2646ccfbc407de3328ec"},
+    {file = "chroma_hnswlib-0.7.6-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:81181d54a2b1e4727369486a631f977ffc53c5533d26e3d366dda243fb0998ca"},
+    {file = "chroma_hnswlib-0.7.6-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:4b4ab4e11f1083dd0a11ee4f0e0b183ca9f0f2ed63ededba1935b13ce2b3606f"},
+    {file = "chroma_hnswlib-0.7.6-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:53db45cd9173d95b4b0bdccb4dbff4c54a42b51420599c32267f3abbeb795170"},
+    {file = "chroma_hnswlib-0.7.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5c093f07a010b499c00a15bc9376036ee4800d335360570b14f7fe92badcdcf9"},
+    {file = "chroma_hnswlib-0.7.6-cp311-cp311-win_amd64.whl", hash = "sha256:0540b0ac96e47d0aa39e88ea4714358ae05d64bbe6bf33c52f316c664190a6a3"},
+    {file = "chroma_hnswlib-0.7.6-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:e87e9b616c281bfbe748d01705817c71211613c3b063021f7ed5e47173556cb7"},
+    {file = "chroma_hnswlib-0.7.6-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:ec5ca25bc7b66d2ecbf14502b5729cde25f70945d22f2aaf523c2d747ea68912"},
+    {file = "chroma_hnswlib-0.7.6-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:305ae491de9d5f3c51e8bd52d84fdf2545a4a2bc7af49765cda286b7bb30b1d4"},
+    {file = "chroma_hnswlib-0.7.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:822ede968d25a2c88823ca078a58f92c9b5c4142e38c7c8b4c48178894a0a3c5"},
+    {file = "chroma_hnswlib-0.7.6-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:2fe6ea949047beed19a94b33f41fe882a691e58b70c55fdaa90274ae78be046f"},
+    {file = "chroma_hnswlib-0.7.6-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:feceff971e2a2728c9ddd862a9dd6eb9f638377ad98438876c9aeac96c9482f5"},
+    {file = "chroma_hnswlib-0.7.6-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb0633b60e00a2b92314d0bf5bbc0da3d3320be72c7e3f4a9b19f4609dc2b2ab"},
+    {file = "chroma_hnswlib-0.7.6-cp37-cp37m-win_amd64.whl", hash = "sha256:a566abe32fab42291f766d667bdbfa234a7f457dcbd2ba19948b7a978c8ca624"},
+    {file = "chroma_hnswlib-0.7.6-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:6be47853d9a58dedcfa90fc846af202b071f028bbafe1d8711bf64fe5a7f6111"},
+    {file = "chroma_hnswlib-0.7.6-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:3a7af35bdd39a88bffa49f9bb4bf4f9040b684514a024435a1ef5cdff980579d"},
+    {file = "chroma_hnswlib-0.7.6-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a53b1f1551f2b5ad94eb610207bde1bb476245fc5097a2bec2b476c653c58bde"},
+    {file = "chroma_hnswlib-0.7.6-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3085402958dbdc9ff5626ae58d696948e715aef88c86d1e3f9285a88f1afd3bc"},
+    {file = "chroma_hnswlib-0.7.6-cp38-cp38-win_amd64.whl", hash = "sha256:77326f658a15adfb806a16543f7db7c45f06fd787d699e643642d6bde8ed49c4"},
+    {file = "chroma_hnswlib-0.7.6-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:93b056ab4e25adab861dfef21e1d2a2756b18be5bc9c292aa252fa12bb44e6ae"},
+    {file = "chroma_hnswlib-0.7.6-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:fe91f018b30452c16c811fd6c8ede01f84e5a9f3c23e0758775e57f1c3778871"},
+    {file = "chroma_hnswlib-0.7.6-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e6c0e627476f0f4d9e153420d36042dd9c6c3671cfd1fe511c0253e38c2a1039"},
+    {file = "chroma_hnswlib-0.7.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3e9796a4536b7de6c6d76a792ba03e08f5aaa53e97e052709568e50b4d20c04f"},
+    {file = "chroma_hnswlib-0.7.6-cp39-cp39-win_amd64.whl", hash = "sha256:d30e2db08e7ffdcc415bd072883a322de5995eb6ec28a8f8c054103bbd3ec1e0"},
+    {file = "chroma_hnswlib-0.7.6.tar.gz", hash = "sha256:4dce282543039681160259d29fcde6151cc9106c6461e0485f57cdccd83059b7"},
+]
+
+[package.dependencies]
+numpy = "*"
+
+[[package]]
+name = "chromadb"
+version = "0.6.3"
+description = "Chroma."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "chromadb-0.6.3-py3-none-any.whl", hash = "sha256:4851258489a3612b558488d98d09ae0fe0a28d5cad6bd1ba64b96fdc419dc0e5"},
+    {file = "chromadb-0.6.3.tar.gz", hash = "sha256:c8f34c0b704b9108b04491480a36d42e894a960429f87c6516027b5481d59ed3"},
+]
+
+[package.dependencies]
+bcrypt = ">=4.0.1"
+build = ">=1.0.3"
+chroma-hnswlib = "0.7.6"
+fastapi = ">=0.95.2"
+grpcio = ">=1.58.0"
+httpx = ">=0.27.0"
+importlib-resources = "*"
+kubernetes = ">=28.1.0"
+mmh3 = ">=4.0.1"
+numpy = ">=1.22.5"
+onnxruntime = ">=1.14.1"
+opentelemetry-api = ">=1.2.0"
+opentelemetry-exporter-otlp-proto-grpc = ">=1.2.0"
+opentelemetry-instrumentation-fastapi = ">=0.41b0"
+opentelemetry-sdk = ">=1.2.0"
+orjson = ">=3.9.12"
+overrides = ">=7.3.1"
+posthog = ">=2.4.0"
+pydantic = ">=1.9"
+pypika = ">=0.48.9"
+PyYAML = ">=6.0.0"
+rich = ">=10.11.0"
+tenacity = ">=8.2.3"
+tokenizers = ">=0.13.2"
+tqdm = ">=4.65.0"
+typer = ">=0.9.0"
+typing_extensions = ">=4.5.0"
+uvicorn = {version = ">=0.18.3", extras = ["standard"]}
+
 [[package]]
 name = "click"
 version = "8.1.8"
@@ -995,16 +1122,15 @@ files = [
     {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
-markers = {main = "platform_system == \"Windows\" or sys_platform == \"win32\"", dev = "platform_system == \"Windows\" or sys_platform == \"win32\""}
+markers = {main = "platform_system == \"Windows\" or os_name == \"nt\" or sys_platform == \"win32\"", dev = "platform_system == \"Windows\" or sys_platform == \"win32\""}
 
 [[package]]
 name = "coloredlogs"
 version = "15.0.1"
 description = "Colored terminal output for Python's logging module"
-optional = true
+optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 groups = ["main"]
-markers = "(python_version == \"3.10\" or python_version == \"3.11\" or python_version == \"3.12\") and extra == \"codegraph\""
 files = [
     {file = "coloredlogs-15.0.1-py2.py3-none-any.whl", hash = "sha256:612ee75c546f53e92e70049c9dbfcc18c935a2b9a53b66085ce9ef6a6e5c0934"},
     {file = "coloredlogs-15.0.1.tar.gz", hash = "sha256:7c991aa71a4577af2f82600d8f8f3a89f936baeaf9b50a9c197da014e5bf16b0"},
@@ -1458,10 +1584,9 @@ files = [
 name = "deprecated"
 version = "1.2.18"
 description = "Python @deprecated decorator to deprecate old python classes, functions or methods."
-optional = true
+optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7"
 groups = ["main"]
-markers = "extra == \"llama-index\" or extra == \"deepeval\""
 files = [
     {file = "Deprecated-1.2.18-py2.py3-none-any.whl", hash = "sha256:bd5011788200372a32418f888e326a09ff80d0214bd961147cfed01b5c018eec"},
     {file = "deprecated-1.2.18.tar.gz", hash = "sha256:422b6f6d859da6f2ef57857761bfb392480502a64c3028ca9bbe86085d72115d"},
@@ -1779,6 +1904,18 @@ files = [
     {file = "docx2txt-0.8.tar.gz", hash = "sha256:2c06d98d7cfe2d3947e5760a57d924e3ff07745b379c8737723922e7009236e5"},
 ]
 
+[[package]]
+name = "durationpy"
+version = "0.9"
+description = "Module for converting between datetime.timedelta and Go's Duration strings."
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
+    {file = "durationpy-0.9-py3-none-any.whl", hash = "sha256:e65359a7af5cedad07fb77a2dd3f390f8eb0b74cb845589fa6c057086834dd38"},
+    {file = "durationpy-0.9.tar.gz", hash = "sha256:fd3feb0a69a0057d582ef643c355c40d2fa1c942191f914d12203b1a01ac722a"},
+]
+
 [[package]]
 name = "email-validator"
 version = "2.2.0"
@@ -2026,10 +2163,9 @@ files = [
 name = "flatbuffers"
 version = "25.2.10"
 description = "The FlatBuffers serialization format for Python"
-optional = true
+optional = false
 python-versions = "*"
 groups = ["main"]
-markers = "(python_version == \"3.10\" or python_version == \"3.11\" or python_version == \"3.12\") and extra == \"codegraph\""
 files = [
     {file = "flatbuffers-25.2.10-py2.py3-none-any.whl", hash = "sha256:ebba5f4d5ea615af3f7fd70fc310636fbb2bbd1f566ac0a23d98dd412de50051"},
     {file = "flatbuffers-25.2.10.tar.gz", hash = "sha256:97e451377a41262f8d9bd4295cc836133415cc03d8cb966410a4af92eb00d26e"},
@@ -2435,10 +2571,9 @@ uritemplate = ">=3.0.1,<5"
 name = "google-auth"
 version = "2.38.0"
 description = "Google Authentication Library"
-optional = true
+optional = false
 python-versions = ">=3.7"
 groups = ["main"]
-markers = "extra == \"gemini\""
 files = [
     {file = "google_auth-2.38.0-py2.py3-none-any.whl", hash = "sha256:e7dae6694313f434a2727bf2906f27ad259bae090d7aa896590d86feec3d9d4a"},
     {file = "google_auth-2.38.0.tar.gz", hash = "sha256:8285113607d3b80a3f1543b75962447ba8a09fe85783432a784fdeef6ac094c4"},
@@ -2503,10 +2638,9 @@ dev = ["Pillow", "absl-py", "black", "ipython", "nose2", "pandas", "pytype", "py
 name = "googleapis-common-protos"
 version = "1.69.1"
 description = "Common protobufs used in Google APIs"
-optional = true
+optional = false
 python-versions = ">=3.7"
 groups = ["main"]
-markers = "python_version == \"3.10\" and (extra == \"deepeval\" or extra == \"gemini\") or extra == \"gemini\" or extra == \"deepeval\""
 files = [
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@@ -2707,10 +2841,9 @@ typing-extensions = ">=4.7,<5"
 name = "grpcio"
 version = "1.67.1"
 description = "HTTP/2-based RPC framework"
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "python_version == \"3.10\" and (extra == \"qdrant\" or extra == \"weaviate\" or extra == \"deepeval\" or extra == \"milvus\" or extra == \"gemini\") or extra == \"gemini\" or extra == \"qdrant\" or extra == \"weaviate\" or extra == \"deepeval\" or extra == \"milvus\""
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@@ -3030,6 +3163,62 @@ files = [
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+[[package]]
+name = "httptools"
+version = "0.6.4"
+description = "A collection of framework independent HTTP protocol utils."
+optional = false
+python-versions = ">=3.8.0"
+groups = ["main"]
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+    {file = "httptools-0.6.4-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:0e563e54979e97b6d13f1bbc05a96109923e76b901f786a5eae36e99c01237bd"},
+    {file = "httptools-0.6.4-cp39-cp39-win_amd64.whl", hash = "sha256:b799de31416ecc589ad79dd85a0b2657a8fe39327944998dea368c1d4c9e55e6"},
+    {file = "httptools-0.6.4.tar.gz", hash = "sha256:4e93eee4add6493b59a5c514da98c939b244fce4a0d8879cd3f466562f4b7d5c"},
+]
+
+[package.extras]
+test = ["Cython (>=0.29.24)"]
+
 [[package]]
 name = "httpx"
 version = "0.27.0"
@@ -3108,10 +3297,9 @@ typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "t
 name = "humanfriendly"
 version = "10.0"
 description = "Human friendly output for text interfaces using Python"
-optional = true
+optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 groups = ["main"]
-markers = "(python_version == \"3.10\" or python_version == \"3.11\" or python_version == \"3.12\") and extra == \"codegraph\""
 files = [
     {file = "humanfriendly-10.0-py2.py3-none-any.whl", hash = "sha256:1697e1a8a8f550fd43c2865cd84542fc175a61dcb779b6fee18cf6b6ccba1477"},
     {file = "humanfriendly-10.0.tar.gz", hash = "sha256:6b0b831ce8f15f7300721aa49829fc4e83921a9a301cc7f606be6686a2288ddc"},
@@ -3202,6 +3390,26 @@ perf = ["ipython"]
 test = ["flufl.flake8", "importlib-resources (>=1.3) ; python_version < \"3.9\"", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
 type = ["pytest-mypy"]
 
+[[package]]
+name = "importlib-resources"
+version = "6.5.2"
+description = "Read resources from Python packages"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "importlib_resources-6.5.2-py3-none-any.whl", hash = "sha256:789cfdc3ed28c78b67a06acb8126751ced69a3d5f79c095a98298cd8a760ccec"},
+    {file = "importlib_resources-6.5.2.tar.gz", hash = "sha256:185f87adef5bcc288449d98fb4fba07cea78bc036455dd44c5fc4a2fe78fed2c"},
+]
+
+[package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""]
+cover = ["pytest-cov"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["jaraco.test (>=5.4)", "pytest (>=6,!=8.1.*)", "zipp (>=3.17)"]
+type = ["pytest-mypy"]
+
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -3988,6 +4196,34 @@ files = [
     {file = "kiwisolver-1.4.8.tar.gz", hash = "sha256:23d5f023bdc8c7e54eb65f03ca5d5bb25b601eac4d7f1a042888a1f45237987e"},
 ]
 
+[[package]]
+name = "kubernetes"
+version = "32.0.1"
+description = "Kubernetes python client"
+optional = false
+python-versions = ">=3.6"
+groups = ["main"]
+files = [
+    {file = "kubernetes-32.0.1-py2.py3-none-any.whl", hash = "sha256:35282ab8493b938b08ab5526c7ce66588232df00ef5e1dbe88a419107dc10998"},
+    {file = "kubernetes-32.0.1.tar.gz", hash = "sha256:42f43d49abd437ada79a79a16bd48a604d3471a117a8347e87db693f2ba0ba28"},
+]
+
+[package.dependencies]
+certifi = ">=14.05.14"
+durationpy = ">=0.7"
+google-auth = ">=1.0.1"
+oauthlib = ">=3.2.2"
+python-dateutil = ">=2.5.3"
+pyyaml = ">=5.4.1"
+requests = "*"
+requests-oauthlib = "*"
+six = ">=1.9.0"
+urllib3 = ">=1.24.2"
+websocket-client = ">=0.32.0,<0.40.0 || >0.40.0,<0.41.dev0 || >=0.43.dev0"
+
+[package.extras]
+adal = ["adal (>=1.0.2)"]
+
 [[package]]
 name = "lancedb"
 version = "0.16.0"
@@ -5218,10 +5454,9 @@ mkdocstrings = ">=0.26"
 name = "mmh3"
 version = "5.1.0"
 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 = "(python_version == \"3.10\" or python_version == \"3.11\" or python_version == \"3.12\") and extra == \"codegraph\""
 files = [
     {file = "mmh3-5.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:eaf4ac5c6ee18ca9232238364d7f2a213278ae5ca97897cafaa123fcc7bb8bec"},
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@@ -5318,10 +5553,9 @@ type = ["mypy (==1.14.1)"]
 name = "monotonic"
 version = "1.6"
 description = "An implementation of time.monotonic() for Python 2 & < 3.3"
-optional = true
+optional = false
 python-versions = "*"
 groups = ["main"]
-markers = "extra == \"posthog\""
 files = [
     {file = "monotonic-1.6-py2.py3-none-any.whl", hash = "sha256:68687e19a14f11f26d140dd5c86f3dba4bf5df58003000ed467e0e2a69bca96c"},
     {file = "monotonic-1.6.tar.gz", hash = "sha256:3a55207bcfed53ddd5c5bae174524062935efed17792e9de2ad0205ce9ad63f7"},
@@ -5331,10 +5565,9 @@ files = [
 name = "mpmath"
 version = "1.3.0"
 description = "Python library for arbitrary-precision floating-point arithmetic"
-optional = true
+optional = false
 python-versions = "*"
 groups = ["main"]
-markers = "(python_version == \"3.10\" or python_version == \"3.11\" or python_version == \"3.12\") and extra == \"codegraph\""
 files = [
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     {file = "mpmath-1.3.0.tar.gz", hash = "sha256:7a28eb2a9774d00c7bc92411c19a89209d5da7c4c9a9e227be8330a23a25b91f"},
@@ -5841,7 +6074,7 @@ version = "3.2.2"
 description = "A generic, spec-compliant, thorough implementation of the OAuth request-signing logic"
 optional = false
 python-versions = ">=3.6"
-groups = ["dev"]
+groups = ["main", "dev"]
 files = [
     {file = "oauthlib-3.2.2-py3-none-any.whl", hash = "sha256:8139f29aac13e25d502680e9e19963e83f16838d48a0d71c287fe40e7067fbca"},
     {file = "oauthlib-3.2.2.tar.gz", hash = "sha256:9859c40929662bec5d64f34d01c99e093149682a3f38915dc0655d5a633dd918"},
@@ -5889,10 +6122,9 @@ pydantic = ">=2.9.0,<3.0.0"
 name = "onnxruntime"
 version = "1.21.0"
 description = "ONNX Runtime is a runtime accelerator for Machine Learning models"
-optional = true
+optional = false
 python-versions = ">=3.10"
 groups = ["main"]
-markers = "(python_version == \"3.10\" or python_version == \"3.11\" or python_version == \"3.12\") and extra == \"codegraph\""
 files = [
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@@ -5968,10 +6200,9 @@ et-xmlfile = "*"
 name = "opentelemetry-api"
 version = "1.30.0"
 description = "OpenTelemetry Python API"
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "extra == \"deepeval\""
 files = [
     {file = "opentelemetry_api-1.30.0-py3-none-any.whl", hash = "sha256:d5f5284890d73fdf47f843dda3210edf37a38d66f44f2b5aedc1e89ed455dc09"},
     {file = "opentelemetry_api-1.30.0.tar.gz", hash = "sha256:375893400c1435bf623f7dfb3bcd44825fe6b56c34d0667c542ea8257b1a1240"},
@@ -5985,10 +6216,9 @@ importlib-metadata = ">=6.0,<=8.5.0"
 name = "opentelemetry-exporter-otlp-proto-common"
 version = "1.30.0"
 description = "OpenTelemetry Protobuf encoding"
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "extra == \"deepeval\""
 files = [
     {file = "opentelemetry_exporter_otlp_proto_common-1.30.0-py3-none-any.whl", hash = "sha256:5468007c81aa9c44dc961ab2cf368a29d3475977df83b4e30aeed42aa7bc3b38"},
     {file = "opentelemetry_exporter_otlp_proto_common-1.30.0.tar.gz", hash = "sha256:ddbfbf797e518411857d0ca062c957080279320d6235a279f7b64ced73c13897"},
@@ -6001,10 +6231,9 @@ opentelemetry-proto = "1.30.0"
 name = "opentelemetry-exporter-otlp-proto-grpc"
 version = "1.30.0"
 description = "OpenTelemetry Collector Protobuf over gRPC Exporter"
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "extra == \"deepeval\""
 files = [
     {file = "opentelemetry_exporter_otlp_proto_grpc-1.30.0-py3-none-any.whl", hash = "sha256:2906bcae3d80acc54fd1ffcb9e44d324e8631058b502ebe4643ca71d1ff30830"},
     {file = "opentelemetry_exporter_otlp_proto_grpc-1.30.0.tar.gz", hash = "sha256:d0f10f0b9b9a383b7d04a144d01cb280e70362cccc613987e234183fd1f01177"},
@@ -6019,14 +6248,75 @@ opentelemetry-exporter-otlp-proto-common = "1.30.0"
 opentelemetry-proto = "1.30.0"
 opentelemetry-sdk = ">=1.30.0,<1.31.0"
 
+[[package]]
+name = "opentelemetry-instrumentation"
+version = "0.51b0"
+description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "opentelemetry_instrumentation-0.51b0-py3-none-any.whl", hash = "sha256:c6de8bd26b75ec8b0e54dff59e198946e29de6a10ec65488c357d4b34aa5bdcf"},
+    {file = "opentelemetry_instrumentation-0.51b0.tar.gz", hash = "sha256:4ca266875e02f3988536982467f7ef8c32a38b8895490ddce9ad9604649424fa"},
+]
+
+[package.dependencies]
+opentelemetry-api = ">=1.4,<2.0"
+opentelemetry-semantic-conventions = "0.51b0"
+packaging = ">=18.0"
+wrapt = ">=1.0.0,<2.0.0"
+
+[[package]]
+name = "opentelemetry-instrumentation-asgi"
+version = "0.51b0"
+description = "ASGI instrumentation for OpenTelemetry"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "opentelemetry_instrumentation_asgi-0.51b0-py3-none-any.whl", hash = "sha256:e8072993db47303b633c6ec1bc74726ba4d32bd0c46c28dfadf99f79521a324c"},
+    {file = "opentelemetry_instrumentation_asgi-0.51b0.tar.gz", hash = "sha256:b3fe97c00f0bfa934371a69674981d76591c68d937b6422a5716ca21081b4148"},
+]
+
+[package.dependencies]
+asgiref = ">=3.0,<4.0"
+opentelemetry-api = ">=1.12,<2.0"
+opentelemetry-instrumentation = "0.51b0"
+opentelemetry-semantic-conventions = "0.51b0"
+opentelemetry-util-http = "0.51b0"
+
+[package.extras]
+instruments = ["asgiref (>=3.0,<4.0)"]
+
+[[package]]
+name = "opentelemetry-instrumentation-fastapi"
+version = "0.51b0"
+description = "OpenTelemetry FastAPI Instrumentation"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "opentelemetry_instrumentation_fastapi-0.51b0-py3-none-any.whl", hash = "sha256:10513bbc11a1188adb9c1d2c520695f7a8f2b5f4de14e8162098035901cd6493"},
+    {file = "opentelemetry_instrumentation_fastapi-0.51b0.tar.gz", hash = "sha256:1624e70f2f4d12ceb792d8a0c331244cd6723190ccee01336273b4559bc13abc"},
+]
+
+[package.dependencies]
+opentelemetry-api = ">=1.12,<2.0"
+opentelemetry-instrumentation = "0.51b0"
+opentelemetry-instrumentation-asgi = "0.51b0"
+opentelemetry-semantic-conventions = "0.51b0"
+opentelemetry-util-http = "0.51b0"
+
+[package.extras]
+instruments = ["fastapi (>=0.58,<1.0)"]
+
 [[package]]
 name = "opentelemetry-proto"
 version = "1.30.0"
 description = "OpenTelemetry Python Proto"
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "extra == \"deepeval\""
 files = [
     {file = "opentelemetry_proto-1.30.0-py3-none-any.whl", hash = "sha256:c6290958ff3ddacc826ca5abbeb377a31c2334387352a259ba0df37c243adc11"},
     {file = "opentelemetry_proto-1.30.0.tar.gz", hash = "sha256:afe5c9c15e8b68d7c469596e5b32e8fc085eb9febdd6fb4e20924a93a0389179"},
@@ -6039,10 +6329,9 @@ protobuf = ">=5.0,<6.0"
 name = "opentelemetry-sdk"
 version = "1.30.0"
 description = "OpenTelemetry Python SDK"
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "extra == \"deepeval\""
 files = [
     {file = "opentelemetry_sdk-1.30.0-py3-none-any.whl", hash = "sha256:14fe7afc090caad881addb6926cec967129bd9260c4d33ae6a217359f6b61091"},
     {file = "opentelemetry_sdk-1.30.0.tar.gz", hash = "sha256:c9287a9e4a7614b9946e933a67168450b9ab35f08797eb9bc77d998fa480fa18"},
@@ -6057,10 +6346,9 @@ typing-extensions = ">=3.7.4"
 name = "opentelemetry-semantic-conventions"
 version = "0.51b0"
 description = "OpenTelemetry Semantic Conventions"
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "extra == \"deepeval\""
 files = [
     {file = "opentelemetry_semantic_conventions-0.51b0-py3-none-any.whl", hash = "sha256:fdc777359418e8d06c86012c3dc92c88a6453ba662e941593adb062e48c2eeae"},
     {file = "opentelemetry_semantic_conventions-0.51b0.tar.gz", hash = "sha256:3fabf47f35d1fd9aebcdca7e6802d86bd5ebc3bc3408b7e3248dde6e87a18c47"},
@@ -6070,6 +6358,18 @@ files = [
 deprecated = ">=1.2.6"
 opentelemetry-api = "1.30.0"
 
+[[package]]
+name = "opentelemetry-util-http"
+version = "0.51b0"
+description = "Web util for OpenTelemetry"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "opentelemetry_util_http-0.51b0-py3-none-any.whl", hash = "sha256:0561d7a6e9c422b9ef9ae6e77eafcfcd32a2ab689f5e801475cbb67f189efa20"},
+    {file = "opentelemetry_util_http-0.51b0.tar.gz", hash = "sha256:05edd19ca1cc3be3968b1e502fd94816901a365adbeaab6b6ddb974384d3a0b9"},
+]
+
 [[package]]
 name = "orderly-set"
 version = "5.3.0"
@@ -6090,7 +6390,6 @@ description = "Fast, correct Python JSON library supporting dataclasses, datetim
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "platform_python_implementation != \"PyPy\""
 files = [
     {file = "orjson-3.10.15-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:552c883d03ad185f720d0c09583ebde257e41b9521b74ff40e08b7dec4559c04"},
     {file = "orjson-3.10.15-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:616e3e8d438d02e4854f70bfdc03a6bcdb697358dbaa6bcd19cbe24d24ece1f8"},
@@ -6695,10 +6994,9 @@ tests = ["pytest (>=5.4.1)", "pytest-cov (>=2.8.1)", "pytest-mypy (>=0.8.0)", "p
 name = "posthog"
 version = "3.19.1"
 description = "Integrate PostHog into any python application."
-optional = true
+optional = false
 python-versions = "*"
 groups = ["main"]
-markers = "extra == \"posthog\""
 files = [
     {file = "posthog-3.19.1-py2.py3-none-any.whl", hash = "sha256:7abaa1f0fbcdde8f1c193f744fdc26de852c13a80b5f527c6eeba8516b20df76"},
     {file = "posthog-3.19.1.tar.gz", hash = "sha256:b879bc257de287ea91a9545bab1a3d09ba22586f3c0370ef210e06631c4929bc"},
@@ -6898,10 +7196,9 @@ testing = ["google-api-core (>=1.31.5)"]
 name = "protobuf"
 version = "5.29.3"
 description = ""
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "(python_version == \"3.10\" or python_version == \"3.11\" or python_version == \"3.12\" or extra == \"gemini\" or extra == \"qdrant\" or extra == \"weaviate\" or extra == \"deepeval\" or extra == \"milvus\") and (python_version == \"3.10\" or extra == \"codegraph\" or extra == \"gemini\" or extra == \"qdrant\" or extra == \"weaviate\" or extra == \"deepeval\" or extra == \"milvus\") and (extra == \"codegraph\" or extra == \"qdrant\" or extra == \"weaviate\" or extra == \"deepeval\" or extra == \"gemini\" or extra == \"milvus\")"
 files = [
     {file = "protobuf-5.29.3-cp310-abi3-win32.whl", hash = "sha256:3ea51771449e1035f26069c4c7fd51fba990d07bc55ba80701c78f886bf9c888"},
     {file = "protobuf-5.29.3-cp310-abi3-win_amd64.whl", hash = "sha256:a4fa6f80816a9a0678429e84973f2f98cbc218cca434abe8db2ad0bffc98503a"},
@@ -7144,10 +7441,9 @@ test = ["cffi", "hypothesis", "pandas", "pytest", "pytz"]
 name = "pyasn1"
 version = "0.6.1"
 description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "extra == \"gemini\""
 files = [
     {file = "pyasn1-0.6.1-py3-none-any.whl", hash = "sha256:0d632f46f2ba09143da3a8afe9e33fb6f92fa2320ab7e886e2d0f7672af84629"},
     {file = "pyasn1-0.6.1.tar.gz", hash = "sha256:6f580d2bdd84365380830acf45550f2511469f673cb4a5ae3857a3170128b034"},
@@ -7157,10 +7453,9 @@ files = [
 name = "pyasn1-modules"
 version = "0.4.1"
 description = "A collection of ASN.1-based protocols modules"
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "extra == \"gemini\""
 files = [
     {file = "pyasn1_modules-0.4.1-py3-none-any.whl", hash = "sha256:49bfa96b45a292b711e986f222502c1c9a5e1f4e568fc30e2574a6c7d07838fd"},
     {file = "pyasn1_modules-0.4.1.tar.gz", hash = "sha256:c28e2dbf9c06ad61c71a075c7e0f9fd0f1b0bb2d2ad4377f240d33ac2ab60a7c"},
@@ -7528,14 +7823,37 @@ docs = ["myst_parser", "sphinx", "sphinx_rtd_theme"]
 full = ["Pillow (>=8.0.0)", "cryptography"]
 image = ["Pillow (>=8.0.0)"]
 
+[[package]]
+name = "pypika"
+version = "0.48.9"
+description = "A SQL query builder API for Python"
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
+    {file = "PyPika-0.48.9.tar.gz", hash = "sha256:838836a61747e7c8380cd1b7ff638694b7a7335345d0f559b04b2cd832ad5378"},
+]
+
+[[package]]
+name = "pyproject-hooks"
+version = "1.2.0"
+description = "Wrappers to call pyproject.toml-based build backend hooks."
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "pyproject_hooks-1.2.0-py3-none-any.whl", hash = "sha256:9e5c6bfa8dcc30091c74b0cf803c81fdd29d94f01992a7707bc97babb1141913"},
+    {file = "pyproject_hooks-1.2.0.tar.gz", hash = "sha256:1e859bd5c40fae9448642dd871adf459e5e2084186e8d2c2a79a824c970da1f8"},
+]
+
 [[package]]
 name = "pyreadline3"
 version = "3.5.4"
 description = "A python implementation of GNU readline."
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "extra == \"codegraph\" and sys_platform == \"win32\" and (python_version == \"3.10\" or python_version == \"3.11\" or python_version == \"3.12\")"
+markers = "sys_platform == \"win32\""
 files = [
     {file = "pyreadline3-3.5.4-py3-none-any.whl", hash = "sha256:eaf8e6cc3c49bcccf145fc6067ba8643d1df34d604a1ec0eccbf7a18e6d3fae6"},
     {file = "pyreadline3-3.5.4.tar.gz", hash = "sha256:8d57d53039a1c75adba8e50dd3d992b28143480816187ea5efbd5c78e6c885b7"},
@@ -8422,7 +8740,7 @@ version = "1.3.1"
 description = "OAuthlib authentication support for Requests."
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
-groups = ["dev"]
+groups = ["main", "dev"]
 files = [
     {file = "requests-oauthlib-1.3.1.tar.gz", hash = "sha256:75beac4a47881eeb94d5ea5d6ad31ef88856affe2332b9aafb52c6452ccf0d7a"},
     {file = "requests_oauthlib-1.3.1-py2.py3-none-any.whl", hash = "sha256:2577c501a2fb8d05a304c09d090d6e47c306fef15809d102b327cf8364bddab5"},
@@ -8646,10 +8964,9 @@ files = [
 name = "rsa"
 version = "4.9"
 description = "Pure-Python RSA implementation"
-optional = true
+optional = false
 python-versions = ">=3.6,<4"
 groups = ["main"]
-markers = "extra == \"gemini\""
 files = [
     {file = "rsa-4.9-py3-none-any.whl", hash = "sha256:90260d9058e514786967344d0ef75fa8727eed8a7d2e43ce9f4bcf1b536174f7"},
     {file = "rsa-4.9.tar.gz", hash = "sha256:e38464a49c6c85d7f1351b0126661487a7e0a14a50f1675ec50eb34d4f20ef21"},
@@ -9393,10 +9710,9 @@ files = [
 name = "sympy"
 version = "1.13.3"
 description = "Computer algebra system (CAS) in Python"
-optional = true
+optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "(python_version == \"3.10\" or python_version == \"3.11\" or python_version == \"3.12\") and extra == \"codegraph\""
 files = [
     {file = "sympy-1.13.3-py3-none-any.whl", hash = "sha256:54612cf55a62755ee71824ce692986f23c88ffa77207b30c1368eda4a7060f73"},
     {file = "sympy-1.13.3.tar.gz", hash = "sha256:b27fd2c6530e0ab39e275fc9b683895367e51d5da91baa8d3d64db2565fec4d9"},
@@ -10187,12 +10503,72 @@ files = [
 
 [package.dependencies]
 click = ">=7.0"
+colorama = {version = ">=0.4", optional = true, markers = "sys_platform == \"win32\" and extra == \"standard\""}
 h11 = ">=0.8"
+httptools = {version = ">=0.6.3", optional = true, markers = "extra == \"standard\""}
+python-dotenv = {version = ">=0.13", optional = true, markers = "extra == \"standard\""}
+pyyaml = {version = ">=5.1", optional = true, markers = "extra == \"standard\""}
 typing-extensions = {version = ">=4.0", markers = "python_version < \"3.11\""}
+uvloop = {version = ">=0.14.0,<0.15.0 || >0.15.0,<0.15.1 || >0.15.1", optional = true, markers = "sys_platform != \"win32\" and sys_platform != \"cygwin\" and platform_python_implementation != \"PyPy\" and extra == \"standard\""}
+watchfiles = {version = ">=0.13", optional = true, markers = "extra == \"standard\""}
+websockets = {version = ">=10.4", optional = true, markers = "extra == \"standard\""}
 
 [package.extras]
 standard = ["colorama (>=0.4) ; sys_platform == \"win32\"", "httptools (>=0.6.3)", "python-dotenv (>=0.13)", "pyyaml (>=5.1)", "uvloop (>=0.14.0,!=0.15.0,!=0.15.1) ; sys_platform != \"win32\" and sys_platform != \"cygwin\" and platform_python_implementation != \"PyPy\"", "watchfiles (>=0.13)", "websockets (>=10.4)"]
 
+[[package]]
+name = "uvloop"
+version = "0.21.0"
+description = "Fast implementation of asyncio event loop on top of libuv"
+optional = false
+python-versions = ">=3.8.0"
+groups = ["main"]
+markers = "sys_platform != \"win32\" and sys_platform != \"cygwin\" and platform_python_implementation != \"PyPy\""
+files = [
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+    {file = "uvloop-0.21.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:196274f2adb9689a289ad7d65700d37df0c0930fd8e4e743fa4834e850d7719d"},
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 [[package]]
 name = "validators"
 version = "0.34.0"
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 watchmedo = ["PyYAML (>=3.10)"]
 
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+
+[package.dependencies]
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+
 [[package]]
 name = "wcwidth"
 version = "0.2.13"
@@ -10337,9 +10797,9 @@ markers = {main = "extra == \"docs\""}
 name = "websocket-client"
 version = "1.8.0"
 description = "WebSocket client for Python with low level API options"
-optional = true
+optional = false
 python-versions = ">=3.8"
-groups = ["dev"]
+groups = ["main", "dev"]
 files = [
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@@ -10350,6 +10810,85 @@ docs = ["Sphinx (>=6.0)", "myst-parser (>=2.0.0)", "sphinx-rtd-theme (>=1.1.0)"]
 optional = ["python-socks", "wsaccel"]
 test = ["websockets"]
 
+[[package]]
+name = "websockets"
+version = "15.0.1"
+description = "An implementation of the WebSocket Protocol (RFC 6455 & 7692)"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
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+    {file = "websockets-15.0.1.tar.gz", hash = "sha256:82544de02076bafba038ce055ee6412d68da13ab47f0c60cab827346de828dee"},
+]
+
 [[package]]
 name = "win-precise-time"
 version = "1.4.2"
@@ -10799,4 +11338,4 @@ weaviate = ["weaviate-client"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<=3.13"
-content-hash = "d7c274c557b0d86891baf091c00ba85df5f94c784ff4fbf925028607da8f5eb3"
+content-hash = "49992df84ea53be0143c8dbc7bd11cbb97ca762714c61dabd1527c8c3e42fd6b"
diff --git a/pyproject.toml b/pyproject.toml
index ff34ac41f..335dcc85d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -57,6 +57,7 @@ langsmith = {version = "0.2.3", optional = true}
 langdetect = "1.0.9"
 posthog = {version = "^3.5.0", optional = true}
 lancedb = "0.16.0"
+chromadb = "^0.6.0"
 litellm = ">=1.57.4"
 groq = {version = "0.8.0", optional = true}
 langfuse = "^2.32.0"