Prepare for the presentation, add info

cognitive_architecture/infrastructure/databases/graph/graph_db_interface.py

@@ -3,43 +3,36 @@ from abc import abstractmethod
 from typing import Protocol
 
 class GraphDBInterface(Protocol):
-    """ Graphs """
-    @abstractmethod
-    async def create_graph(
-        self,
-        graph_name: str,
-        graph_config: object
-    ): raise NotImplementedError
-
-    @abstractmethod
-    async def update_graph(
-        self,
-        graph_name: str,
-        graph_config: object
-    ): raise NotImplementedError
-
 
     """ Save and Load Graphs """
 
     @abstractmethod
     async def save_graph(
         self,
-        graph_name: str
+        path: str
     ): raise NotImplementedError
 
     @abstractmethod
     async def load_graph(
         self,
-        graph_name: str
+        path: str
     ): raise NotImplementedError
 
-    """ Collections """
+    @abstractmethod
+    async def delete_graph(
+        self,
+        path: str
+    ): raise NotImplementedError
 
-    # @abstractmethod
-    # async def delete_collection(
-    #     self,
-    #     collection_name: str
-    # ): raise NotImplementedError
+    """ CRUD operations on graph nodes """
+
+    @abstractmethod
+    async def create(self,
+                     user_id:str,
+                     custom_user_properties:str,
+                     required_layers:list,
+                     default_fields:dict
+    ): raise NotImplementedError
 
     # @abstractmethod
     # async def create_vector_index(

cognitive_architecture/infrastructure/databases/graph/networkx/adapter.py

@@ -2,8 +2,8 @@ import pickle
 from datetime import datetime
 import aiofiles
 import networkx as nx
-from databases.graph.graph_db_interface import GraphDBInterface
-
+from cognitive_architecture.infrastructure.databases.graph.graph_db_interface import GraphDBInterface
+import logging
 
 class NetworXDB(GraphDBInterface):
     def __init__(self, filename="cognee_graph.pkl"):
@@ -11,24 +11,39 @@ class NetworXDB(GraphDBInterface):
         self.graph = nx.MultiDiGraph()
 
 
-    async def save_graph(self):
+    async def save_graph(self, path: str):
+        """Asynchronously save the graph to a file."""
+        if path is not None:
+            path = self.filename
         try:
-            async with aiofiles.open(self.filename, "wb") as f:
+            async with aiofiles.open(path, "wb") as f:
                 await f.write(pickle.dumps(self.graph))
-            self.logger.info("Graph saved successfully.")
+            logging.info("Graph saved successfully.")
         except Exception as e:
-            self.logger.error(f"Failed to save graph: {e}")
+            logging.error(f"Failed to save graph: {e}")
 
-    async def load_graph(self):
+    async def load_graph(self, path: str):
+        if path is not None:
+            path = self.filename
         try:
-            async with aiofiles.open(self.filename, "rb") as f:
+            async with aiofiles.open(path, "rb") as f:
                 data = await f.read()
                 self.graph = pickle.loads(data)
-            self.logger.info("Graph loaded successfully.")
+            logging.info("Graph loaded successfully.")
         except Exception as e:
-            self.logger.error(f"Failed to load graph: {e}")
+            logging.error(f"Failed to load graph: {e}")
 
-    async def create_graph(self, user_id, custom_user_properties=None, required_layers=None, default_fields=None):
+    async def delete_graph(self, path: str):
+        if path is not None:
+            path = self.filename
+        try:
+            async with aiofiles.open(path, "wb") as f:
+                await f.write(pickle.dumps(self.graph))
+            logging.info("Graph deleted successfully.")
+        except Exception as e:
+            logging.error(f"Failed to delete graph: {e}")
+
+    async def create(self, user_id, custom_user_properties=None, required_layers=None, default_fields=None):
         """Asynchronously create or update a user content graph based on given parameters."""
         # Assume required_layers is a dictionary-like object; use more robust validation in production
         category_name = required_layers['name']

cognitive_architecture/infrastructure/llm/prompts/generate_graph_prompt.txt

@@ -4,7 +4,7 @@ designed for extracting information in structured formats to build a knowledge g
 - **Edges** represent relationships between concepts. They're akin to Wikipedia links.
 - The aim is to achieve simplicity and clarity in the
 knowledge graph, making it accessible for a vast audience.
-YOU ARE ONLY EXTRACTING DATA FOR COGNITIVE LAYER `{{layer}}`
+YOU ARE ONLY EXTRACTING DATA FOR COGNITIVE LAYER `{{ layer }}`
 ## 2. Labeling Nodes
 - **Consistency**: Ensure you use basic or elementary types for node labels.
   - For example, when you identify an entity representing a person,

cognitive_architecture/modules/cognify/llm/content_to_propositions.py

@@ -5,17 +5,17 @@ from cognitive_architecture.infrastructure.llm.get_llm_client import get_llm_cli
 from cognitive_architecture.shared.data_models import KnowledgeGraph
 from cognitive_architecture.utils import async_render_template
 
-async def generate_graph(filename: str,context, response_model: Type[BaseModel]):
+async def generate_graph(text_input:str, filename: str,context, response_model: Type[BaseModel]):
 
     llm_client = get_llm_client()
 
     formatted_text_input = await async_render_template(filename, context)
-    return await llm_client.acreate_structured_output(formatted_text_input,formatted_text_input, response_model)
+    return await llm_client.acreate_structured_output(text_input,formatted_text_input, response_model)
 
 
 if __name__ == "__main__":
     import asyncio
-    asyncio.run(generate_graph("generate_graph_prompt.txt", {
-        'layer': 'text'
+    asyncio.run(generate_graph(text_input="bla", filename = "generate_graph_prompt.txt",context= {
+        'layer': 'BLA'
     }, response_model=KnowledgeGraph))
 

poetry.lock

@@ -1,5 +1,16 @@
 # This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
 
+[[package]]
+name = "aiofiles"
+version = "23.2.1"
+description = "File support for asyncio."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "aiofiles-23.2.1-py3-none-any.whl", hash = "sha256:19297512c647d4b27a2cf7c34caa7e405c0d60b5560618a29a9fe027b18b0107"},
+    {file = "aiofiles-23.2.1.tar.gz", hash = "sha256:84ec2218d8419404abcb9f0c02df3f34c6e0a68ed41072acfb1cef5cbc29051a"},
+]
+
 [[package]]
 name = "aiohttp"
 version = "3.9.3"
@@ -4231,7 +4242,7 @@ lancedb = []
 motherduck = ["pyarrow"]
 mssql = []
 neo4j = []
-notebook = []
+notebook = ["overrides"]
 parquet = ["pyarrow"]
 pinecone = []
 postgres = []
@@ -4245,4 +4256,4 @@ weaviate = []
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "39962c40053f064940d94532130d182d5a0a0526c915c39a0c48f98f21321630"
+content-hash = "313beec7482cf4513abd8521d453d2e8513c231b7b8d1f89df26f3dc095cf943"

pyproject.toml

@@ -41,6 +41,7 @@ pandas = "^2.2.1"
 greenlet = "^3.0.3"
 ruff = "^0.2.2"
 overrides = "^7.7.0"
+aiofiles = "^23.2.1"
 
 [tool.poetry.extras]
 dbt = ["dbt-core", "dbt-redshift", "dbt-bigquery", "dbt-duckdb", "dbt-snowflake", "dbt-athena-community", "dbt-databricks"]