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Add Memgraph integration (#2537)

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Katarina Supe
2025-04-22 12:57:24 +02:00
committed by GitHub
parent cd5c3035ab
commit ba2e479902
10 changed files with 940 additions and 44 deletions
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2
Makefile
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@@ -14,7 +14,7 @@ install_all:
poetry install poetry install
poetry run pip install groq together boto3 litellm ollama chromadb weaviate weaviate-client sentence_transformers vertexai \ poetry run pip install groq together boto3 litellm ollama chromadb weaviate weaviate-client sentence_transformers vertexai \
google-generativeai elasticsearch opensearch-py vecs pinecone pinecone-text faiss-cpu langchain-community \ google-generativeai elasticsearch opensearch-py vecs pinecone pinecone-text faiss-cpu langchain-community \
upstash-vector azure-search-documents upstash-vector azure-search-documents langchain-memgraph
# Format code with ruff # Format code with ruff
format: format:

71
docs/open-source/graph_memory/overview.mdx
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@@ -47,8 +47,14 @@ allowfullscreen
## Initialize Graph Memory ## Initialize Graph Memory
To initialize Graph Memory you'll need to set up your configuration with graph store providers. To initialize Graph Memory you'll need to set up your configuration with graph
Currently, we support Neo4j as a graph store provider. You can setup [Neo4j](https://neo4j.com/) locally or use the hosted [Neo4j AuraDB](https://neo4j.com/product/auradb/). store providers. Currently, we support [Neo4j](#initialize-neo4j) and
[Memgraph](#initialize-memgraph) as graph store providers.
### Initialize Neo4j
You can setup [Neo4j](https://neo4j.com/) locally or use the hosted [Neo4j AuraDB](https://neo4j.com/product/auradb/).
<Note>If you are using Neo4j locally, then you need to install [APOC plugins](https://neo4j.com/labs/apoc/4.1/installation/).</Note> <Note>If you are using Neo4j locally, then you need to install [APOC plugins](https://neo4j.com/labs/apoc/4.1/installation/).</Note>
@@ -163,6 +169,67 @@ const memory = new Memory(config);
If you are using NodeSDK, you need to pass `enableGraph` as `true` in the `config` object. If you are using NodeSDK, you need to pass `enableGraph` as `true` in the `config` object.
</Note> </Note>
### Initialize Memgraph
Run Memgraph with Docker:
```bash
docker run -p 7687:7687 memgraph/memgraph-mage:latest --schema-info-enabled=True
```
The `--schema-info-enabled` flag is set to `True` for more performant schema
generation.
Additional information can be found on [Memgraph
documentation](https://memgraph.com/docs).
User can also customize the LLM for Graph Memory from the [Supported LLM list](https://docs.mem0.ai/components/llms/overview) with three levels of configuration:
1. **Main Configuration**: If `llm` is set in the main config, it will be used for all graph operations.
2. **Graph Store Configuration**: If `llm` is set in the graph_store config, it will override the main config `llm` and be used specifically for graph operations.
3. **Default Configuration**: If no custom LLM is set, the default LLM (`gpt-4o-2024-08-06`) will be used for all graph operations.
Here's how you can do it:
<CodeGroup>
```python Python
from mem0 import Memory
config = {
"graph_store": {
"provider": "memgraph",
"config": {
"url": "bolt://localhost:7687",
"username": "memgraph",
"password": "xxx",
},
},
}
m = Memory.from_config(config_dict=config)
```
```python Python (Advanced)
config = {
"embedder": {
"provider": "openai",
"config": {"model": "text-embedding-3-large", "embedding_dims": 1536},
},
"graph_store": {
"provider": "memgraph",
"config": {
"url": "bolt://localhost:7687",
"username": "memgraph",
"password": "xxx"
}
}
}
m = Memory.from_config(config_dict=config)
```
</CodeGroup>
## Graph Operations ## Graph Operations
The Mem0's graph supports the following operations: The Mem0's graph supports the following operations:

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230
examples/graph-db-demo/memgraph-example.ipynb Normal file
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@@ -0,0 +1,230 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Memgraph as Graph Memory"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Prerequisites\n",
"\n",
"### 1. Install Mem0 with Graph Memory support \n",
"\n",
"To use Mem0 with Graph Memory support, install it using pip:\n",
"\n",
"```bash\n",
"pip install \"mem0ai[graph]\"\n",
"```\n",
"\n",
"This command installs Mem0 along with the necessary dependencies for graph functionality.\n",
"\n",
"### 2. Install Memgraph\n",
"\n",
"To utilize Memgraph as Graph Memory, run it with Docker:\n",
"\n",
"```bash\n",
"docker run -p 7687:7687 memgraph/memgraph-mage:latest --schema-info-enabled=True\n",
"```\n",
"\n",
"The `--schema-info-enabled` flag is set to `True` for more performant schema\n",
"generation.\n",
"\n",
"Additional information can be found on [Memgraph documentation](https://memgraph.com/docs). "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Configuration\n",
"\n",
"Do all the imports and configure OpenAI (enter your OpenAI API key):"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from mem0 import Memory\n",
"\n",
"import os\n",
"\n",
"os.environ[\"OPENAI_API_KEY\"] = (\n",
" \"\"\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Set up configuration to use the embedder model and Memgraph as a graph store:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"config = {\n",
" \"embedder\": {\n",
" \"provider\": \"openai\",\n",
" \"config\": {\"model\": \"text-embedding-3-large\", \"embedding_dims\": 1536},\n",
" },\n",
" \"graph_store\": {\n",
" \"provider\": \"memgraph\",\n",
" \"config\": {\n",
" \"url\": \"bolt://localhost:7687\",\n",
" \"username\": \"memgraph\",\n",
" \"password\": \"mem0graph\",\n",
" },\n",
" },\n",
"}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Graph Memory initializiation \n",
"\n",
"Initialize Memgraph as a Graph Memory store: "
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/katelatte/repos/forks/mem0/.venv/lib/python3.13/site-packages/neo4j/_sync/driver.py:547: DeprecationWarning: Relying on Driver's destructor to close the session is deprecated. Please make sure to close the session. Use it as a context (`with` statement) or make sure to call `.close()` explicitly. Future versions of the driver will not close drivers automatically.\n",
" _deprecation_warn(\n"
]
}
],
"source": [
"m = Memory.from_config(config_dict=config)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Store memories \n",
"\n",
"Create memories:"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"messages = [\n",
" {\n",
" \"role\": \"user\",\n",
" \"content\": \"I'm planning to watch a movie tonight. Any recommendations?\",\n",
" },\n",
" {\n",
" \"role\": \"assistant\",\n",
" \"content\": \"How about a thriller movies? They can be quite engaging.\",\n",
" },\n",
" {\n",
" \"role\": \"user\",\n",
" \"content\": \"I'm not a big fan of thriller movies but I love sci-fi movies.\",\n",
" },\n",
" {\n",
" \"role\": \"assistant\",\n",
" \"content\": \"Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future.\",\n",
" },\n",
"]\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Store memories in Memgraph:"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"# Store inferred memories (default behavior)\n",
"result = m.add(\n",
" messages, user_id=\"alice\", metadata={\"category\": \"movie_recommendations\"}\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"![](./alice-memories.png)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Search memories"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loves sci-fi movies 0.31536642873408993\n",
"Planning to watch a movie tonight 0.09684523796547778\n",
"Not a big fan of thriller movies 0.09468540071789475\n"
]
}
],
"source": [
"for result in m.search(\"what does alice love?\", user_id=\"alice\")[\"results\"]:\n",
" print(result[\"memory\"], result[\"score\"])"
]
}
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

18
mem0/graphs/configs.py
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@@ -20,6 +20,22 @@ class Neo4jConfig(BaseModel):
if not url or not username or not password: if not url or not username or not password:
raise ValueError("Please provide 'url', 'username' and 'password'.") raise ValueError("Please provide 'url', 'username' and 'password'.")
return values return values
class MemgraphConfig(BaseModel):
url: Optional[str] = Field(None, description="Host address for the graph database")
username: Optional[str] = Field(None, description="Username for the graph database")
password: Optional[str] = Field(None, description="Password for the graph database")
@model_validator(mode="before")
def check_host_port_or_path(cls, values):
url, username, password = (
values.get("url"),
values.get("username"),
values.get("password"),
)
if not url or not username or not password:
raise ValueError("Please provide 'url', 'username' and 'password'.")
return values
class GraphStoreConfig(BaseModel): class GraphStoreConfig(BaseModel):
@@ -35,5 +51,7 @@ class GraphStoreConfig(BaseModel):
provider = values.data.get("provider") provider = values.data.get("provider")
if provider == "neo4j": if provider == "neo4j":
return Neo4jConfig(**v.model_dump()) return Neo4jConfig(**v.model_dump())
elif provider == "memgraph":
return MemgraphConfig(**v.model_dump())
else: else:
raise ValueError(f"Unsupported graph store provider: {provider}") raise ValueError(f"Unsupported graph store provider: {provider}")

5
mem0/memory/main.py
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@@ -59,7 +59,10 @@ class Memory(MemoryBase):
self.enable_graph = False self.enable_graph = False
if self.config.graph_store.config: if self.config.graph_store.config:
from mem0.memory.graph_memory import MemoryGraph if self.config.graph_store.provider == "memgraph":
from mem0.memory.memgraph_memory import MemoryGraph
else:
from mem0.memory.graph_memory import MemoryGraph
self.graph = MemoryGraph(self.config) self.graph = MemoryGraph(self.config)
self.enable_graph = True self.enable_graph = True

516
mem0/memory/memgraph_memory.py Normal file
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@@ -0,0 +1,516 @@
import logging
from mem0.memory.utils import format_entities
try:
from langchain_memgraph import Memgraph
except ImportError:
raise ImportError(
"langchain_memgraph is not installed. Please install it using pip install langchain-memgraph"
)
try:
from rank_bm25 import BM25Okapi
except ImportError:
raise ImportError(
"rank_bm25 is not installed. Please install it using pip install rank-bm25"
)
from mem0.graphs.tools import (
DELETE_MEMORY_STRUCT_TOOL_GRAPH,
DELETE_MEMORY_TOOL_GRAPH,
EXTRACT_ENTITIES_STRUCT_TOOL,
EXTRACT_ENTITIES_TOOL,
RELATIONS_STRUCT_TOOL,
RELATIONS_TOOL,
)
from mem0.graphs.utils import EXTRACT_RELATIONS_PROMPT, get_delete_messages
from mem0.utils.factory import EmbedderFactory, LlmFactory
logger = logging.getLogger(__name__)
class MemoryGraph:
def __init__(self, config):
self.config = config
self.graph = Memgraph(
self.config.graph_store.config.url,
self.config.graph_store.config.username,
self.config.graph_store.config.password,
)
self.embedding_model = EmbedderFactory.create(
self.config.embedder.provider,
self.config.embedder.config,
{"enable_embeddings": True},
)
self.llm_provider = "openai_structured"
if self.config.llm.provider:
self.llm_provider = self.config.llm.provider
if self.config.graph_store.llm:
self.llm_provider = self.config.graph_store.llm.provider
self.llm = LlmFactory.create(self.llm_provider, self.config.llm.config)
self.user_id = None
self.threshold = 0.7
# Setup Memgraph:
# 1. Create vector index (created Entity label on all nodes)
# 2. Create label property index for performance optimizations
embedding_dims = self.config.embedder.config["embedding_dims"]
create_vector_index_query = f"CREATE VECTOR INDEX memzero ON :Entity(embedding) WITH CONFIG {{'dimension': {embedding_dims}, 'capacity': 1000, 'metric': 'cos'}};"
self.graph.query(create_vector_index_query, params={})
create_label_prop_index_query = f"CREATE INDEX ON :Entity(user_id);"
self.graph.query(create_label_prop_index_query, params={})
create_label_index_query = f"CREATE INDEX ON :Entity;"
self.graph.query(create_label_index_query, params={})
def add(self, data, filters):
"""
Adds data to the graph.
Args:
data (str): The data to add to the graph.
filters (dict): A dictionary containing filters to be applied during the addition.
"""
entity_type_map = self._retrieve_nodes_from_data(data, filters)
to_be_added = self._establish_nodes_relations_from_data(
data, filters, entity_type_map
)
search_output = self._search_graph_db(
node_list=list(entity_type_map.keys()), filters=filters
)
to_be_deleted = self._get_delete_entities_from_search_output(
search_output, data, filters
)
# TODO: Batch queries with APOC plugin
# TODO: Add more filter support
deleted_entities = self._delete_entities(to_be_deleted, filters["user_id"])
added_entities = self._add_entities(
to_be_added, filters["user_id"], entity_type_map
)
return {"deleted_entities": deleted_entities, "added_entities": added_entities}
def search(self, query, filters, limit=100):
"""
Search for memories and related graph data.
Args:
query (str): Query to search for.
filters (dict): A dictionary containing filters to be applied during the search.
limit (int): The maximum number of nodes and relationships to retrieve. Defaults to 100.
Returns:
dict: A dictionary containing:
- "contexts": List of search results from the base data store.
- "entities": List of related graph data based on the query.
"""
entity_type_map = self._retrieve_nodes_from_data(query, filters)
search_output = self._search_graph_db(
node_list=list(entity_type_map.keys()), filters=filters
)
if not search_output:
return []
search_outputs_sequence = [
[item["source"], item["relationship"], item["destination"]]
for item in search_output
]
bm25 = BM25Okapi(search_outputs_sequence)
tokenized_query = query.split(" ")
reranked_results = bm25.get_top_n(tokenized_query, search_outputs_sequence, n=5)
search_results = []
for item in reranked_results:
search_results.append(
{"source": item[0], "relationship": item[1], "destination": item[2]}
)
logger.info(f"Returned {len(search_results)} search results")
return search_results
def delete_all(self, filters):
cypher = """
MATCH (n {user_id: $user_id})
DETACH DELETE n
"""
params = {"user_id": filters["user_id"]}
self.graph.query(cypher, params=params)
def get_all(self, filters, limit=100):
"""
Retrieves all nodes and relationships from the graph database based on optional filtering criteria.
Args:
filters (dict): A dictionary containing filters to be applied during the retrieval.
limit (int): The maximum number of nodes and relationships to retrieve. Defaults to 100.
Returns:
list: A list of dictionaries, each containing:
- 'contexts': The base data store response for each memory.
- 'entities': A list of strings representing the nodes and relationships
"""
# return all nodes and relationships
query = """
MATCH (n:Entity {user_id: $user_id})-[r]->(m:Entity {user_id: $user_id})
RETURN n.name AS source, type(r) AS relationship, m.name AS target
LIMIT $limit
"""
results = self.graph.query(
query, params={"user_id": filters["user_id"], "limit": limit}
)
final_results = []
for result in results:
final_results.append(
{
"source": result["source"],
"relationship": result["relationship"],
"target": result["target"],
}
)
logger.info(f"Retrieved {len(final_results)} relationships")
return final_results
def _retrieve_nodes_from_data(self, data, filters):
"""Extracts all the entities mentioned in the query."""
_tools = [EXTRACT_ENTITIES_TOOL]
if self.llm_provider in ["azure_openai_structured", "openai_structured"]:
_tools = [EXTRACT_ENTITIES_STRUCT_TOOL]
search_results = self.llm.generate_response(
messages=[
{
"role": "system",
"content": f"You are a smart assistant who understands entities and their types in a given text. If user message contains self reference such as 'I', 'me', 'my' etc. then use {filters['user_id']} as the source entity. Extract all the entities from the text. ***DO NOT*** answer the question itself if the given text is a question.",
},
{"role": "user", "content": data},
],
tools=_tools,
)
entity_type_map = {}
try:
for tool_call in search_results["tool_calls"]:
if tool_call["name"] != "extract_entities":
continue
for item in tool_call["arguments"]["entities"]:
entity_type_map[item["entity"]] = item["entity_type"]
except Exception as e:
logger.exception(
f"Error in search tool: {e}, llm_provider={self.llm_provider}, search_results={search_results}"
)
entity_type_map = {
k.lower().replace(" ", "_"): v.lower().replace(" ", "_")
for k, v in entity_type_map.items()
}
logger.debug(
f"Entity type map: {entity_type_map}\n search_results={search_results}"
)
return entity_type_map
def _establish_nodes_relations_from_data(self, data, filters, entity_type_map):
"""Eshtablish relations among the extracted nodes."""
if self.config.graph_store.custom_prompt:
messages = [
{
"role": "system",
"content": EXTRACT_RELATIONS_PROMPT.replace(
"USER_ID", filters["user_id"]
).replace(
"CUSTOM_PROMPT", f"4. {self.config.graph_store.custom_prompt}"
),
},
{"role": "user", "content": data},
]
else:
messages = [
{
"role": "system",
"content": EXTRACT_RELATIONS_PROMPT.replace(
"USER_ID", filters["user_id"]
),
},
{
"role": "user",
"content": f"List of entities: {list(entity_type_map.keys())}. \n\nText: {data}",
},
]
_tools = [RELATIONS_TOOL]
if self.llm_provider in ["azure_openai_structured", "openai_structured"]:
_tools = [RELATIONS_STRUCT_TOOL]
extracted_entities = self.llm.generate_response(
messages=messages,
tools=_tools,
)
entities = []
if extracted_entities["tool_calls"]:
entities = extracted_entities["tool_calls"][0]["arguments"]["entities"]
entities = self._remove_spaces_from_entities(entities)
logger.debug(f"Extracted entities: {entities}")
return entities
def _search_graph_db(self, node_list, filters, limit=100):
"""Search similar nodes among and their respective incoming and outgoing relations."""
result_relations = []
for node in node_list:
n_embedding = self.embedding_model.embed(node)
cypher_query = f"""
MATCH (n:Entity {{user_id: $user_id}})-[r]->(m:Entity)
WHERE n.embedding IS NOT NULL
WITH collect(n) AS nodes1, collect(m) AS nodes2, r
CALL node_similarity.cosine_pairwise("embedding", nodes1, nodes2)
YIELD node1, node2, similarity
WITH node1, node2, similarity, r
WHERE similarity >= $threshold
RETURN node1.user_id AS source, id(node1) AS source_id, type(r) AS relationship, id(r) AS relation_id, node2.user_id AS destination, id(node2) AS destination_id, similarity
UNION
MATCH (n:Entity {{user_id: $user_id}})<-[r]-(m:Entity)
WHERE n.embedding IS NOT NULL
WITH collect(n) AS nodes1, collect(m) AS nodes2, r
CALL node_similarity.cosine_pairwise("embedding", nodes1, nodes2)
YIELD node1, node2, similarity
WITH node1, node2, similarity, r
WHERE similarity >= $threshold
RETURN node2.name AS source, id(node2) AS source_id, type(r) AS relationship, id(r) AS relation_id, node1.name AS destination, id(node1) AS destination_id, similarity
ORDER BY similarity DESC
LIMIT $limit;
"""
params = {
"n_embedding": n_embedding,
"threshold": self.threshold,
"user_id": filters["user_id"],
"limit": limit,
}
ans = self.graph.query(cypher_query, params=params)
result_relations.extend(ans)
return result_relations
def _get_delete_entities_from_search_output(self, search_output, data, filters):
"""Get the entities to be deleted from the search output."""
search_output_string = format_entities(search_output)
system_prompt, user_prompt = get_delete_messages(
search_output_string, data, filters["user_id"]
)
_tools = [DELETE_MEMORY_TOOL_GRAPH]
if self.llm_provider in ["azure_openai_structured", "openai_structured"]:
_tools = [
DELETE_MEMORY_STRUCT_TOOL_GRAPH,
]
memory_updates = self.llm.generate_response(
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt},
],
tools=_tools,
)
to_be_deleted = []
for item in memory_updates["tool_calls"]:
if item["name"] == "delete_graph_memory":
to_be_deleted.append(item["arguments"])
# in case if it is not in the correct format
to_be_deleted = self._remove_spaces_from_entities(to_be_deleted)
logger.debug(f"Deleted relationships: {to_be_deleted}")
return to_be_deleted
def _delete_entities(self, to_be_deleted, user_id):
"""Delete the entities from the graph."""
results = []
for item in to_be_deleted:
source = item["source"]
destination = item["destination"]
relationship = item["relationship"]
# Delete the specific relationship between nodes
cypher = f"""
MATCH (n:Entity {{name: $source_name, user_id: $user_id}})
-[r:{relationship}]->
(m {{name: $dest_name, user_id: $user_id}})
DELETE r
RETURN
n.name AS source,
m.name AS target,
type(r) AS relationship
"""
params = {
"source_name": source,
"dest_name": destination,
"user_id": user_id,
}
result = self.graph.query(cypher, params=params)
results.append(result)
return results
# added Entity label to all nodes for vector search to work
def _add_entities(self, to_be_added, user_id, entity_type_map):
"""Add the new entities to the graph. Merge the nodes if they already exist."""
results = []
for item in to_be_added:
# entities
source = item["source"]
destination = item["destination"]
relationship = item["relationship"]
# types
source_type = entity_type_map.get(source, "unknown")
destination_type = entity_type_map.get(destination, "unknown")
# embeddings
source_embedding = self.embedding_model.embed(source)
dest_embedding = self.embedding_model.embed(destination)
# search for the nodes with the closest embeddings; this is basically
# comparison of one embedding to all embeddings in a graph -> vector
# search with cosine similarity metric
source_node_search_result = self._search_source_node(
source_embedding, user_id, threshold=0.9
)
destination_node_search_result = self._search_destination_node(
dest_embedding, user_id, threshold=0.9
)
# TODO: Create a cypher query and common params for all the cases
if not destination_node_search_result and source_node_search_result:
cypher = f"""
MATCH (source:Entity)
WHERE id(source) = $source_id
MERGE (destination:{destination_type}:Entity {{name: $destination_name, user_id: $user_id}})
ON CREATE SET
destination.created = timestamp(),
destination.embedding = $destination_embedding,
destination:Entity
MERGE (source)-[r:{relationship}]->(destination)
ON CREATE SET
r.created = timestamp()
RETURN source.name AS source, type(r) AS relationship, destination.name AS target
"""
params = {
"source_id": source_node_search_result[0]["id(source_candidate)"],
"destination_name": destination,
"destination_embedding": dest_embedding,
"user_id": user_id,
}
elif destination_node_search_result and not source_node_search_result:
cypher = f"""
MATCH (destination:Entity)
WHERE id(destination) = $destination_id
MERGE (source:{source_type}:Entity {{name: $source_name, user_id: $user_id}})
ON CREATE SET
source.created = timestamp(),
source.embedding = $source_embedding,
source:Entity
MERGE (source)-[r:{relationship}]->(destination)
ON CREATE SET
r.created = timestamp()
RETURN source.name AS source, type(r) AS relationship, destination.name AS target
"""
params = {
"destination_id": destination_node_search_result[0][
"id(destination_candidate)"
],
"source_name": source,
"source_embedding": source_embedding,
"user_id": user_id,
}
elif source_node_search_result and destination_node_search_result:
cypher = f"""
MATCH (source:Entity)
WHERE id(source) = $source_id
MATCH (destination:Entity)
WHERE id(destination) = $destination_id
MERGE (source)-[r:{relationship}]->(destination)
ON CREATE SET
r.created_at = timestamp(),
r.updated_at = timestamp()
RETURN source.name AS source, type(r) AS relationship, destination.name AS target
"""
params = {
"source_id": source_node_search_result[0]["id(source_candidate)"],
"destination_id": destination_node_search_result[0][
"id(destination_candidate)"
],
"user_id": user_id,
}
else:
cypher = f"""
MERGE (n:{source_type}:Entity {{name: $source_name, user_id: $user_id}})
ON CREATE SET n.created = timestamp(), n.embedding = $source_embedding, n:Entity
ON MATCH SET n.embedding = $source_embedding
MERGE (m:{destination_type}:Entity {{name: $dest_name, user_id: $user_id}})
ON CREATE SET m.created = timestamp(), m.embedding = $dest_embedding, m:Entity
ON MATCH SET m.embedding = $dest_embedding
MERGE (n)-[rel:{relationship}]->(m)
ON CREATE SET rel.created = timestamp()
RETURN n.name AS source, type(rel) AS relationship, m.name AS target
"""
params = {
"source_name": source,
"dest_name": destination,
"source_embedding": source_embedding,
"dest_embedding": dest_embedding,
"user_id": user_id,
}
result = self.graph.query(cypher, params=params)
results.append(result)
return results
def _remove_spaces_from_entities(self, entity_list):
for item in entity_list:
item["source"] = item["source"].lower().replace(" ", "_")
item["relationship"] = item["relationship"].lower().replace(" ", "_")
item["destination"] = item["destination"].lower().replace(" ", "_")
return entity_list
def _search_source_node(self, source_embedding, user_id, threshold=0.9):
cypher = f"""
CALL vector_search.search("memzero", 1, $source_embedding)
YIELD distance, node, similarity
WITH node AS source_candidate, similarity
WHERE source_candidate.user_id = $user_id AND similarity >= $threshold
RETURN id(source_candidate);
"""
params = {
"source_embedding": source_embedding,
"user_id": user_id,
"threshold": threshold,
}
result = self.graph.query(cypher, params=params)
return result
def _search_destination_node(self, destination_embedding, user_id, threshold=0.9):
cypher = f"""
CALL vector_search.search("memzero", 1, $destination_embedding)
YIELD distance, node, similarity
WITH node AS destination_candidate, similarity
WHERE node.user_id = $user_id AND similarity >= $threshold
RETURN id(destination_candidate);
"""
params = {
"destination_embedding": destination_embedding,
"user_id": user_id,
"threshold": threshold,
}
result = self.graph.query(cypher, params=params)
return result

135
poetry.lock generated
View File

@@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand. # This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand.
[[package]] [[package]]
name = "annotated-types" name = "annotated-types"
@@ -7,6 +7,7 @@ description = "Reusable constraint types to use with typing.Annotated"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
{file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
{file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
@@ -19,6 +20,7 @@ description = "High level compatibility layer for multiple asynchronous event lo
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
{file = "anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c"}, {file = "anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c"},
{file = "anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028"}, {file = "anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028"},
@@ -32,7 +34,7 @@ typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""}
[package.extras] [package.extras]
doc = ["Sphinx (>=8.2,<9.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"] doc = ["Sphinx (>=8.2,<9.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"]
test = ["anyio[trio]", "blockbuster (>=1.5.23)", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "trustme", "truststore (>=0.9.1) ; python_version >= \"3.10\"", "uvloop (>=0.21) ; platform_python_implementation == \"CPython\" and platform_system != \"Windows\" and python_version < \"3.14\""] test = ["anyio[trio]", "blockbuster (>=1.5.23)", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"]
trio = ["trio (>=0.26.1)"] trio = ["trio (>=0.26.1)"]
[[package]] [[package]]
@@ -55,6 +57,7 @@ description = "Function decoration for backoff and retry"
optional = false optional = false
python-versions = ">=3.7,<4.0" python-versions = ">=3.7,<4.0"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
{file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"}, {file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
{file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"}, {file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
@@ -67,6 +70,7 @@ description = "Python package for providing Mozilla's CA Bundle."
optional = false optional = false
python-versions = ">=3.6" python-versions = ">=3.6"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
{file = "certifi-2025.1.31-py3-none-any.whl", hash = "sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe"}, {file = "certifi-2025.1.31-py3-none-any.whl", hash = "sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe"},
{file = "certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651"}, {file = "certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651"},
@@ -79,7 +83,7 @@ description = "Foreign Function Interface for Python calling C code."
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\" and platform_python_implementation == \"PyPy\"" markers = "platform_python_implementation == \"PyPy\" and (python_version <= \"3.12\" or python_version >= \"3.13\")"
files = [ files = [
{file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"}, {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"},
{file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"}, {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"},
@@ -160,6 +164,7 @@ description = "The Real First Universal Charset Detector. Open, modern and activ
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
{file = "charset_normalizer-3.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:91b36a978b5ae0ee86c394f5a54d6ef44db1de0815eb43de826d41d21e4af3de"}, {file = "charset_normalizer-3.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:91b36a978b5ae0ee86c394f5a54d6ef44db1de0815eb43de826d41d21e4af3de"},
{file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7461baadb4dc00fd9e0acbe254e3d7d2112e7f92ced2adc96e54ef6501c5f176"}, {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7461baadb4dc00fd9e0acbe254e3d7d2112e7f92ced2adc96e54ef6501c5f176"},
@@ -266,7 +271,7 @@ files = [
{file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"}, {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"},
{file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"}, {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
] ]
markers = {main = "platform_system == \"Windows\"", dev = "sys_platform == \"win32\"", test = "sys_platform == \"win32\""} markers = {main = "platform_system == \"Windows\" and (python_version <= \"3.12\" or python_version >= \"3.13\")", dev = "sys_platform == \"win32\" and (python_version <= \"3.12\" or python_version >= \"3.13\")", test = "sys_platform == \"win32\" and (python_version <= \"3.12\" or python_version >= \"3.13\")"}
[[package]] [[package]]
name = "distro" name = "distro"
@@ -275,6 +280,7 @@ description = "Distro - an OS platform information API"
optional = false optional = false
python-versions = ">=3.6" python-versions = ">=3.6"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
{file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"}, {file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"},
{file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"}, {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
@@ -303,7 +309,7 @@ description = "File-system specification"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "extra == \"graph\" and (python_version <= \"3.12\" or python_version >= \"3.13\")"
files = [ files = [
{file = "fsspec-2024.12.0-py3-none-any.whl", hash = "sha256:b520aed47ad9804237ff878b504267a3b0b441e97508bd6d2d8774e3db85cee2"}, {file = "fsspec-2024.12.0-py3-none-any.whl", hash = "sha256:b520aed47ad9804237ff878b504267a3b0b441e97508bd6d2d8774e3db85cee2"},
{file = "fsspec-2024.12.0.tar.gz", hash = "sha256:670700c977ed2fb51e0d9f9253177ed20cbde4a3e5c0283cc5385b5870c8533f"}, {file = "fsspec-2024.12.0.tar.gz", hash = "sha256:670700c977ed2fb51e0d9f9253177ed20cbde4a3e5c0283cc5385b5870c8533f"},
@@ -344,7 +350,7 @@ description = "Lightweight in-process concurrent programming"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
groups = ["main"] groups = ["main"]
markers = "(platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\") and python_version < \"3.14\"" markers = "(platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\") and python_version < \"3.14\" and (python_version <= \"3.12\" or python_version >= \"3.13\")"
files = [ files = [
{file = "greenlet-3.1.1-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:0bbae94a29c9e5c7e4a2b7f0aae5c17e8e90acbfd3bf6270eeba60c39fce3563"}, {file = "greenlet-3.1.1-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:0bbae94a29c9e5c7e4a2b7f0aae5c17e8e90acbfd3bf6270eeba60c39fce3563"},
{file = "greenlet-3.1.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0fde093fb93f35ca72a556cf72c92ea3ebfda3d79fc35bb19fbe685853869a83"}, {file = "greenlet-3.1.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0fde093fb93f35ca72a556cf72c92ea3ebfda3d79fc35bb19fbe685853869a83"},
@@ -432,6 +438,7 @@ description = "HTTP/2-based RPC framework"
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
{file = "grpcio-1.71.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:c200cb6f2393468142eb50ab19613229dcc7829b5ccee8b658a36005f6669fdd"}, {file = "grpcio-1.71.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:c200cb6f2393468142eb50ab19613229dcc7829b5ccee8b658a36005f6669fdd"},
{file = "grpcio-1.71.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:b2266862c5ad664a380fbbcdbdb8289d71464c42a8c29053820ee78ba0119e5d"}, {file = "grpcio-1.71.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:b2266862c5ad664a380fbbcdbdb8289d71464c42a8c29053820ee78ba0119e5d"},
@@ -496,6 +503,7 @@ description = "Protobuf code generator for gRPC"
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
{file = "grpcio_tools-1.71.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:f4ad7f0d756546902597053d70b3af2606fbd70d7972876cd75c1e241d22ae00"}, {file = "grpcio_tools-1.71.0-cp310-cp310-linux_armv7l.whl", hash = "sha256:f4ad7f0d756546902597053d70b3af2606fbd70d7972876cd75c1e241d22ae00"},
{file = "grpcio_tools-1.71.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:64bdb291df61cf570b5256777ad5fe2b1db6d67bc46e55dc56a0a862722ae329"}, {file = "grpcio_tools-1.71.0-cp310-cp310-macosx_12_0_universal2.whl", hash = "sha256:64bdb291df61cf570b5256777ad5fe2b1db6d67bc46e55dc56a0a862722ae329"},
@@ -562,6 +570,7 @@ description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
{file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"}, {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
{file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"}, {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
@@ -574,6 +583,7 @@ description = "Pure-Python HTTP/2 protocol implementation"
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
{file = "h2-4.2.0-py3-none-any.whl", hash = "sha256:479a53ad425bb29af087f3458a61d30780bc818e4ebcf01f0b536ba916462ed0"}, {file = "h2-4.2.0-py3-none-any.whl", hash = "sha256:479a53ad425bb29af087f3458a61d30780bc818e4ebcf01f0b536ba916462ed0"},
{file = "h2-4.2.0.tar.gz", hash = "sha256:c8a52129695e88b1a0578d8d2cc6842bbd79128ac685463b887ee278126ad01f"}, {file = "h2-4.2.0.tar.gz", hash = "sha256:c8a52129695e88b1a0578d8d2cc6842bbd79128ac685463b887ee278126ad01f"},
@@ -590,6 +600,7 @@ description = "Pure-Python HPACK header encoding"
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
{file = "hpack-4.1.0-py3-none-any.whl", hash = "sha256:157ac792668d995c657d93111f46b4535ed114f0c9c8d672271bbec7eae1b496"}, {file = "hpack-4.1.0-py3-none-any.whl", hash = "sha256:157ac792668d995c657d93111f46b4535ed114f0c9c8d672271bbec7eae1b496"},
{file = "hpack-4.1.0.tar.gz", hash = "sha256:ec5eca154f7056aa06f196a557655c5b009b382873ac8d1e66e79e87535f1dca"}, {file = "hpack-4.1.0.tar.gz", hash = "sha256:ec5eca154f7056aa06f196a557655c5b009b382873ac8d1e66e79e87535f1dca"},
@@ -602,6 +613,7 @@ description = "A minimal low-level HTTP client."
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
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@@ -624,6 +636,7 @@ description = "The next generation HTTP client."
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
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@@ -637,7 +650,7 @@ httpcore = "==1.*"
idna = "*" idna = "*"
[package.extras] [package.extras]
brotli = ["brotli ; platform_python_implementation == \"CPython\"", "brotlicffi ; platform_python_implementation != \"CPython\""] brotli = ["brotli", "brotlicffi"]
cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"] cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
http2 = ["h2 (>=3,<5)"] http2 = ["h2 (>=3,<5)"]
socks = ["socksio (==1.*)"] socks = ["socksio (==1.*)"]
@@ -650,6 +663,7 @@ description = "Pure-Python HTTP/2 framing"
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
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@@ -662,6 +676,7 @@ description = "Internationalized Domain Names in Applications (IDNA)"
optional = false optional = false
python-versions = ">=3.6" python-versions = ">=3.6"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -677,6 +692,7 @@ description = "brain-dead simple config-ini parsing"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
groups = ["dev", "test"] groups = ["dev", "test"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
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@@ -689,6 +705,7 @@ description = "A Python utility / library to sort Python imports."
optional = false optional = false
python-versions = ">=3.8.0" python-versions = ">=3.8.0"
groups = ["dev"] groups = ["dev"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -704,6 +721,7 @@ description = "Fast iterable JSON parser."
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -790,7 +808,7 @@ description = "A package to repair broken json strings"
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "extra == \"graph\" and (python_version <= \"3.12\" or python_version >= \"3.13\")"
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@@ -803,7 +821,7 @@ description = "Apply JSON-Patches (RFC 6902)"
optional = false optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*" python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -819,7 +837,7 @@ description = "Identify specific nodes in a JSON document (RFC 6901)"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -832,7 +850,7 @@ description = "Building applications with LLMs through composability"
optional = false optional = false
python-versions = "<4.0,>=3.9" python-versions = "<4.0,>=3.9"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "extra == \"graph\" and (python_version <= \"3.12\" or python_version >= \"3.13\")"
files = [ files = [
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@@ -873,7 +891,7 @@ description = "Building applications with LLMs through composability"
optional = false optional = false
python-versions = "<4.0,>=3.9" python-versions = "<4.0,>=3.9"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -891,6 +909,23 @@ PyYAML = ">=5.3"
tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0" tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0"
typing-extensions = ">=4.7" typing-extensions = ">=4.7"
[[package]]
name = "langchain-memgraph"
version = "0.1.1"
description = "An integration package connecting Memgraph and LangChain"
optional = false
python-versions = "<4.0,>=3.9"
groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [
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]
[package.dependencies]
langchain-core = ">=0.3.15,<0.4.0"
neo4j = ">=5.28.1,<6.0.0"
[[package]] [[package]]
name = "langchain-neo4j" name = "langchain-neo4j"
version = "0.4.0" version = "0.4.0"
@@ -898,7 +933,7 @@ description = "An integration package connecting Neo4j and LangChain"
optional = false optional = false
python-versions = "<4.0,>=3.9" python-versions = "<4.0,>=3.9"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "extra == \"graph\" and (python_version <= \"3.12\" or python_version >= \"3.13\")"
files = [ files = [
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@@ -917,7 +952,7 @@ description = "LangChain text splitting utilities"
optional = false optional = false
python-versions = "<4.0,>=3.9" python-versions = "<4.0,>=3.9"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "extra == \"graph\" and (python_version <= \"3.12\" or python_version >= \"3.13\")"
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@@ -933,7 +968,7 @@ description = "Client library to connect to the LangSmith LLM Tracing and Evalua
optional = false optional = false
python-versions = "<4.0,>=3.9" python-versions = "<4.0,>=3.9"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -964,6 +999,7 @@ description = "An implementation of time.monotonic() for Python 2 & < 3.3"
optional = false optional = false
python-versions = "*" python-versions = "*"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -976,7 +1012,7 @@ description = "Neo4j Bolt driver for Python"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
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@@ -997,7 +1033,7 @@ description = "Python package to allow easy integration to Neo4j's GraphRAG feat
optional = false optional = false
python-versions = "<4.0.0,>=3.9.0" python-versions = "<4.0.0,>=3.9.0"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "extra == \"graph\" and (python_version <= \"3.12\" or python_version >= \"3.13\")"
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@@ -1015,9 +1051,9 @@ types-pyyaml = ">=6.0.12.20240917,<7.0.0.0"
[package.extras] [package.extras]
anthropic = ["anthropic (>=0.49.0,<0.50.0)"] anthropic = ["anthropic (>=0.49.0,<0.50.0)"]
cohere = ["cohere (>=5.9.0,<6.0.0)"] cohere = ["cohere (>=5.9.0,<6.0.0)"]
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@@ -1435,7 +1477,7 @@ description = "C parser in Python"
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@@ -1777,7 +1825,7 @@ description = "Various BM25 algorithms for document ranking"
optional = false optional = false
python-versions = "*" python-versions = "*"
groups = ["main"] groups = ["main"]
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@@ -1796,6 +1844,7 @@ description = "Python HTTP for Humans."
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@@ -1818,7 +1867,7 @@ description = "A utility belt for advanced users of python-requests"
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python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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@@ -1834,6 +1883,7 @@ description = "An extremely fast Python linter and code formatter, written in Ru
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
groups = ["dev"] groups = ["dev"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
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@@ -1862,19 +1912,20 @@ description = "Easily download, build, install, upgrade, and uninstall Python pa
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
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[package.extras] [package.extras]
check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\"", "ruff (>=0.8.0) ; sys_platform != \"cygwin\""] check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)", "ruff (>=0.8.0)"]
core = ["importlib_metadata (>=6) ; python_version < \"3.10\"", "jaraco.functools (>=4)", "jaraco.text (>=3.7)", "more_itertools", "more_itertools (>=8.8)", "packaging (>=24.2)", "platformdirs (>=4.2.2)", "tomli (>=2.0.1) ; python_version < \"3.11\"", "wheel (>=0.43.0)"] core = ["importlib_metadata (>=6)", "jaraco.functools (>=4)", "jaraco.text (>=3.7)", "more_itertools", "more_itertools (>=8.8)", "packaging (>=24.2)", "platformdirs (>=4.2.2)", "tomli (>=2.0.1)", "wheel (>=0.43.0)"]
cover = ["pytest-cov"] cover = ["pytest-cov"]
doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"] doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
enabler = ["pytest-enabler (>=2.2)"] enabler = ["pytest-enabler (>=2.2)"]
test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21) ; python_version >= \"3.9\" and sys_platform != \"cygwin\"", "jaraco.envs (>=2.2)", "jaraco.path (>=3.7.2)", "jaraco.test (>=5.5)", "packaging (>=24.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf ; sys_platform != \"cygwin\"", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"] test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.7.2)", "jaraco.test (>=5.5)", "packaging (>=24.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
type = ["importlib_metadata (>=7.0.2) ; python_version < \"3.10\"", "jaraco.develop (>=7.21) ; sys_platform != \"cygwin\"", "mypy (==1.14.*)", "pytest-mypy"] type = ["importlib_metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (==1.14.*)", "pytest-mypy"]
[[package]] [[package]]
name = "six" name = "six"
@@ -1883,6 +1934,7 @@ description = "Python 2 and 3 compatibility utilities"
optional = false optional = false
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -1895,6 +1947,7 @@ description = "Sniff out which async library your code is running under"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -1907,6 +1960,7 @@ description = "Database Abstraction Library"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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{file = "SQLAlchemy-2.0.39-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:67de057fbcb04a066171bd9ee6bcb58738d89378ee3cabff0bffbf343ae1c787"}, {file = "SQLAlchemy-2.0.39-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:67de057fbcb04a066171bd9ee6bcb58738d89378ee3cabff0bffbf343ae1c787"},
@@ -2003,7 +2057,7 @@ description = "Retry code until it succeeds"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
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{file = "tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b"}, {file = "tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b"},
@@ -2063,6 +2117,7 @@ description = "Fast, Extensible Progress Meter"
optional = false optional = false
python-versions = ">=3.7" python-versions = ">=3.7"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -2085,7 +2140,7 @@ description = "Typing stubs for PyYAML"
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "extra == \"graph\" and (python_version <= \"3.12\" or python_version >= \"3.13\")"
files = [ files = [
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@@ -2098,6 +2153,7 @@ description = "Backported and Experimental Type Hints for Python 3.8+"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -2110,13 +2166,14 @@ description = "HTTP library with thread-safe connection pooling, file post, and
optional = false optional = false
python-versions = ">=3.9" python-versions = ">=3.9"
groups = ["main"] groups = ["main"]
markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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] ]
[package.extras] [package.extras]
brotli = ["brotli (>=1.0.9) ; platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; platform_python_implementation != \"CPython\""] brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
h2 = ["h2 (>=4,<5)"] h2 = ["h2 (>=4,<5)"]
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"] socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
zstd = ["zstandard (>=0.18.0)"] zstd = ["zstandard (>=0.18.0)"]
@@ -2128,7 +2185,7 @@ description = "Zstandard bindings for Python"
optional = false optional = false
python-versions = ">=3.8" python-versions = ">=3.8"
groups = ["main"] groups = ["main"]
markers = "extra == \"graph\"" markers = "python_version <= \"3.12\" or python_version >= \"3.13\""
files = [ files = [
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@@ -2236,9 +2293,9 @@ cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\
cffi = ["cffi (>=1.11)"] cffi = ["cffi (>=1.11)"]
[extras] [extras]
graph = ["langchain-neo4j", "neo4j", "rank-bm25"] graph = ["langchain-memgraph", "langchain-neo4j", "neo4j", "rank-bm25"]
[metadata] [metadata]
lock-version = "2.1" lock-version = "2.1"
python-versions = ">=3.9,<4.0" python-versions = ">=3.9,<4.0"
content-hash = "5848e23bdd7b453f938c9b5f6171866faa01bdcc2651bedb83ee9f4fe90e8bc8" content-hash = "2f2496320b637ae8b74ee70707a8ea3431b3cd0ed045af847bb9b660bca334ac"

3
pyproject.toml
View File

@@ -31,9 +31,10 @@ langchain-neo4j = "^0.4.0"
neo4j = "^5.23.1" neo4j = "^5.23.1"
rank-bm25 = "^0.2.2" rank-bm25 = "^0.2.2"
psycopg2-binary = "^2.9.10" psycopg2-binary = "^2.9.10"
langchain-memgraph = "^0.1.1"
[tool.poetry.extras] [tool.poetry.extras]
graph = ["langchain-neo4j", "neo4j", "rank-bm25"] graph = ["langchain-neo4j", "neo4j", "rank-bm25", "langchain-memgraph"]
[tool.poetry.group.test.dependencies] [tool.poetry.group.test.dependencies]
pytest = "^8.2.2" pytest = "^8.2.2"

4
server/main.py
View File

@@ -25,6 +25,10 @@ NEO4J_URI = os.environ.get("NEO4J_URI", "bolt://neo4j:7687")
NEO4J_USERNAME = os.environ.get("NEO4J_USERNAME", "neo4j") NEO4J_USERNAME = os.environ.get("NEO4J_USERNAME", "neo4j")
NEO4J_PASSWORD = os.environ.get("NEO4J_PASSWORD", "mem0graph") NEO4J_PASSWORD = os.environ.get("NEO4J_PASSWORD", "mem0graph")
MEMGRAPH_URI = os.environ.get("MEMGRAPH_URI", "bolt://localhost:7687")
MEMGRAPH_USERNAME = os.environ.get("MEMGRAPH_USERNAME", "memgraph")
MEMGRAPH_PASSWORD = os.environ.get("MEMGRAPH_PASSWORD", "mem0graph")
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY") OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
HISTORY_DB_PATH = os.environ.get("HISTORY_DB_PATH", "/app/history/history.db") HISTORY_DB_PATH = os.environ.get("HISTORY_DB_PATH", "/app/history/history.db")