[BUG] Running the server against a sample project returns blank disconnected nodes

[ylli2000]

Running the Graphiti MCP server and telling Claude-Code to study a sample project for the first time.

It returns blank disconnected nodes. As you can see from the photos I got a bunch of nodes, but they don't have names, and they don't have relations.

I see a bunch of warnings in the terminal, I guess the issue is related.

Have anyone experienced this and can guess what I did wrong?

Some error section fragments look like this:

INFO:     127.0.0.1:56433 - "POST /messages/?session_id=f3b8328e6b8645d98474d6a0d1b49809 HTTP/1.1" 202 Accepted
2025-08-02 22:58:12,675 - mcp.server.lowlevel.server - INFO - Processing request of type CallToolRequest
2025-08-02 22:58:13,482 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-08-02 22:58:14,114 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-08-02 22:58:14,551 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-08-02 22:58:14,589 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: name_embedding)} {position: line: 4, column: 44, offset: 135} for query: '\n        MATCH (n:Entity)\n        WHERE n.group_id IS NOT NULL AND n.group_id IN $group_ids\n        WITH n, vector.similarity.cosine(n.name_embedding, $search_vector) AS score\n        WHERE score > $min_score\n        RETURN\n            n.uuid As uuid, \n            n.name AS name,\n            n.group_id AS group_id,\n            n.created_at AS created_at, \n            n.summary AS summary,\n            labels(n) AS labels,\n            properties(n) AS attributes\n            \n        ORDER BY score DESC\n        LIMIT $limit\n            '
2025-08-02 22:58:14,617 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-08-02 22:58:14,620 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-08-02 22:58:14,631 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-08-02 22:58:14,632 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-08-02 22:58:14,633 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-08-02 22:58:14,639 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-08-02 22:58:14,640 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: name_embedding)} {position: line: 4, column: 44, offset: 135} for query: '\n        MATCH (n:Entity)\n        WHERE n.group_id IS NOT NULL AND n.group_id IN $group_ids\n        WITH n, vector.similarity.cosine(n.name_embedding, $search_vector) AS score\n        WHERE score > $min_score\n        RETURN\n            n.uuid As uuid, \n            n.name AS name,\n            n.group_id AS group_id,\n            n.created_at AS created_at, \n            n.summary AS summary,\n            labels(n) AS labels,\n            properties(n) AS attributes\n            \n        ORDER BY score DESC\n        LIMIT $limit\n            '
2025-08-02 22:58:14,641 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: name_embedding)} {position: line: 4, column: 44, offset: 135} for query: '\n        MATCH (n:Entity)\n        WHERE n.group_id IS NOT NULL AND n.group_id IN $group_ids\n        WITH n, vector.similarity.cosine(n.name_embedding, $search_vector) AS score\n        WHERE score > $min_score\n        RETURN\n            n.uuid As uuid, \n            n.name AS name,\n            n.group_id AS group_id,\n            n.created_at AS created_at, \n            n.summary AS summary,\n            labels(n) AS labels,\n            properties(n) AS attributes\n            \n        ORDER BY score DESC\n        LIMIT $limit\n            '
2025-08-02 22:58:14,642 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: name_embedding)} {position: line: 4, column: 44, offset: 135} for query: '\n        MATCH (n:Entity)\n        WHERE n.group_id IS NOT NULL AND n.group_id IN $group_ids\n        WITH n, vector.similarity.cosine(n.name_embedding, $search_vector) AS score\n        WHERE score > $min_score\n        RETURN\n            n.uuid As uuid, \n            n.name AS name,\n            n.group_id AS group_id,\n            n.created_at AS created_at, \n            n.summary AS summary,\n            labels(n) AS labels,\n            properties(n) AS attributes\n            \n        ORDER BY score DESC\n        LIMIT $limit\n            '
2025-08-02 22:58:14,642 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: name_embedding)} {position: line: 4, column: 44, offset: 135} for query: '\n        MATCH (n:Entity)\n        WHERE n.group_id IS NOT NULL AND n.group_id IN $group_ids\n        WITH n, vector.similarity.cosine(n.name_embedding, $search_vector) AS score\n        WHERE score > $min_score\n        RETURN\n            n.uuid As uuid, \n            n.name AS name,\n            n.group_id AS group_id,\n            n.created_at AS created_at, \n            n.summary AS summary,\n            labels(n) AS labels,\n            properties(n) AS attributes\n            \n        ORDER BY score DESC\n        LIMIT $limit\n            '
2025-08-02 22:58:14,643 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: name_embedding)} {position: line: 4, column: 44, offset: 135} for query: '\n        MATCH (n:Entity)\n        WHERE n.group_id IS NOT NULL AND n.group_id IN $group_ids\n        WITH n, vector.similarity.cosine(n.name_embedding, $search_vector) AS score\n        WHERE score > $min_score\n        RETURN\n            n.uuid As uuid, \n            n.name AS name,\n            n.group_id AS group_id,\n            n.created_at AS created_at, \n            n.summary AS summary,\n            labels(n) AS labels,\n            properties(n) AS attributes\n            \n        ORDER BY score DESC\n        LIMIT $limit\n            '

[denisjoshua]

Have same issue. Thanks.

[danielchalef]

Can you share which LLMs you're using for graph building?

[genesiscz]

Same here:

2025-09-28 17:50:08,659 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-09-28 17:50:08,664 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: name_embedding)} {position: line: 4, column: 44, offset: 135} for query: '\n        MATCH (n:Entity)\n        WHERE n.group_id IS NOT NULL AND n.group_id IN $group_ids\n        WITH n, vector.similarity.cosine(n.name_embedding, $search_vector) AS score\n        WHERE score > $min_score\n        RETURN\n            n.uuid As uuid, \n            n.name AS name,\n            n.group_id AS group_id,\n            n.created_at AS created_at, \n            n.summary AS summary,\n            labels(n) AS labels,\n            properties(n) AS attributes\n            \n        ORDER BY score DESC\n        LIMIT $limit\n            '
2025-09-28 17:50:08,704 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-09-28 17:50:08,710 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: name_embedding)} {position: line: 4, column: 44, offset: 135} for query: '\n        MATCH (n:Entity)\n        WHERE n.group_id IS NOT NULL AND n.group_id IN $group_ids\n        WITH n, vector.similarity.cosine(n.name_embedding, $search_vector) AS score\n        WHERE score > $min_score\n        RETURN\n            n.uuid As uuid, \n            n.name AS name,\n            n.group_id AS group_id,\n            n.created_at AS created_at, \n            n.summary AS summary,\n            labels(n) AS labels,\n            properties(n) AS attributes\n            \n        ORDER BY score DESC\n        LIMIT $limit\n            '
2025-09-28 17:50:08,838 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-09-28 17:50:08,851 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: name_embedding)} {position: line: 4, column: 44, offset: 135} for query: '\n        MATCH (n:Entity)\n        WHERE n.group_id IS NOT NULL AND n.group_id IN $group_ids\n        WITH n, vector.similarity.cosine(n.name_embedding, $search_vector) AS score\n        WHERE score > $min_score\n        RETURN\n            n.uuid As uuid, \n            n.name AS name,\n            n.group_id AS group_id,\n            n.created_at AS created_at, \n            n.summary AS summary,\n            labels(n) AS labels,\n            properties(n) AS attributes\n            \n        ORDER BY score DESC\n        LIMIT $limit\n            '
2025-09-28 17:50:14,995 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:24,983 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:25,491 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-09-28 17:50:25,869 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: fact_embedding)} {position: line: 5, column: 50, offset: 226} for query: '\n        UNWIND $edges AS edge\n        MATCH (n:Entity {uuid: edge.source_node_uuid})-[e:RELATES_TO {group_id: edge.group_id}]-(m:Entity {uuid: edge.target_node_uuid})\n        \n        WITH e, edge, vector.similarity.cosine(e.fact_embedding, edge.fact_embedding) AS score\n        WHERE score > $min_score\n        WITH edge, e, score\n        ORDER BY score DESC\n        RETURN edge.uuid AS search_edge_uuid,\n            collect({\n                uuid: e.uuid,\n                source_node_uuid: startNode(e).uuid,\n                target_node_uuid: endNode(e).uuid,\n                created_at: e.created_at,\n                name: e.name,\n                group_id: e.group_id,\n                fact: e.fact,\n                fact_embedding: e.fact_embedding,\n                episodes: e.episodes,\n                expired_at: e.expired_at,\n                valid_at: e.valid_at,\n                invalid_at: e.invalid_at,\n                attributes: properties(e)\n            })[..$limit] AS matches\n        '
2025-09-28 17:50:25,870 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: fact_embedding)} {position: line: 18, column: 35, offset: 737} for query: '\n        UNWIND $edges AS edge\n        MATCH (n:Entity {uuid: edge.source_node_uuid})-[e:RELATES_TO {group_id: edge.group_id}]-(m:Entity {uuid: edge.target_node_uuid})\n        \n        WITH e, edge, vector.similarity.cosine(e.fact_embedding, edge.fact_embedding) AS score\n        WHERE score > $min_score\n        WITH edge, e, score\n        ORDER BY score DESC\n        RETURN edge.uuid AS search_edge_uuid,\n            collect({\n                uuid: e.uuid,\n                source_node_uuid: startNode(e).uuid,\n                target_node_uuid: endNode(e).uuid,\n                created_at: e.created_at,\n                name: e.name,\n                group_id: e.group_id,\n                fact: e.fact,\n                fact_embedding: e.fact_embedding,\n                episodes: e.episodes,\n                expired_at: e.expired_at,\n                valid_at: e.valid_at,\n                invalid_at: e.invalid_at,\n                attributes: properties(e)\n            })[..$limit] AS matches\n        '
2025-09-28 17:50:25,870 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: episodes)} {position: line: 19, column: 29, offset: 781} for query: '\n        UNWIND $edges AS edge\n        MATCH (n:Entity {uuid: edge.source_node_uuid})-[e:RELATES_TO {group_id: edge.group_id}]-(m:Entity {uuid: edge.target_node_uuid})\n        \n        WITH e, edge, vector.similarity.cosine(e.fact_embedding, edge.fact_embedding) AS score\n        WHERE score > $min_score\n        WITH edge, e, score\n        ORDER BY score DESC\n        RETURN edge.uuid AS search_edge_uuid,\n            collect({\n                uuid: e.uuid,\n                source_node_uuid: startNode(e).uuid,\n                target_node_uuid: endNode(e).uuid,\n                created_at: e.created_at,\n                name: e.name,\n                group_id: e.group_id,\n                fact: e.fact,\n                fact_embedding: e.fact_embedding,\n                episodes: e.episodes,\n                expired_at: e.expired_at,\n                valid_at: e.valid_at,\n                invalid_at: e.invalid_at,\n                attributes: properties(e)\n            })[..$limit] AS matches\n        '
2025-09-28 17:50:25,878 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: fact_embedding)} {position: line: 6, column: 50, offset: 298} for query: '\n        UNWIND $edges AS edge\n        MATCH (n:Entity)-[e:RELATES_TO {group_id: edge.group_id}]->(m:Entity)\n        WHERE n.uuid IN [edge.source_node_uuid, edge.target_node_uuid] OR m.uuid IN [edge.target_node_uuid, edge.source_node_uuid]\n        \n        WITH edge, e, vector.similarity.cosine(e.fact_embedding, edge.fact_embedding) AS score\n        WHERE score > $min_score\n        WITH edge, e, score\n        ORDER BY score DESC\n        RETURN edge.uuid AS search_edge_uuid,\n            collect({\n                uuid: e.uuid,\n                source_node_uuid: startNode(e).uuid,\n                target_node_uuid: endNode(e).uuid,\n                created_at: e.created_at,\n                name: e.name,\n                group_id: e.group_id,\n                fact: e.fact,\n                fact_embedding: e.fact_embedding,\n                episodes: e.episodes,\n                expired_at: e.expired_at,\n                valid_at: e.valid_at,\n                invalid_at: e.invalid_at,\n                attributes: properties(e)\n            })[..$limit] AS matches\n        '
2025-09-28 17:50:25,878 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: fact_embedding)} {position: line: 19, column: 35, offset: 809} for query: '\n        UNWIND $edges AS edge\n        MATCH (n:Entity)-[e:RELATES_TO {group_id: edge.group_id}]->(m:Entity)\n        WHERE n.uuid IN [edge.source_node_uuid, edge.target_node_uuid] OR m.uuid IN [edge.target_node_uuid, edge.source_node_uuid]\n        \n        WITH edge, e, vector.similarity.cosine(e.fact_embedding, edge.fact_embedding) AS score\n        WHERE score > $min_score\n        WITH edge, e, score\n        ORDER BY score DESC\n        RETURN edge.uuid AS search_edge_uuid,\n            collect({\n                uuid: e.uuid,\n                source_node_uuid: startNode(e).uuid,\n                target_node_uuid: endNode(e).uuid,\n                created_at: e.created_at,\n                name: e.name,\n                group_id: e.group_id,\n                fact: e.fact,\n                fact_embedding: e.fact_embedding,\n                episodes: e.episodes,\n                expired_at: e.expired_at,\n                valid_at: e.valid_at,\n                invalid_at: e.invalid_at,\n                attributes: properties(e)\n            })[..$limit] AS matches\n        '
2025-09-28 17:50:25,879 - neo4j.notifications - WARNING - Received notification from DBMS server: {severity: WARNING} {code: Neo.ClientNotification.Statement.UnknownPropertyKeyWarning} {category: UNRECOGNIZED} {title: The provided property key is not in the database} {description: One of the property names in your query is not available in the database, make sure you didn't misspell it or that the label is available when you run this statement in your application (the missing property name is: episodes)} {position: line: 20, column: 29, offset: 853} for query: '\n        UNWIND $edges AS edge\n        MATCH (n:Entity)-[e:RELATES_TO {group_id: edge.group_id}]->(m:Entity)\n        WHERE n.uuid IN [edge.source_node_uuid, edge.target_node_uuid] OR m.uuid IN [edge.target_node_uuid, edge.source_node_uuid]\n        \n        WITH edge, e, vector.similarity.cosine(e.fact_embedding, edge.fact_embedding) AS score\n        WHERE score > $min_score\n        WITH edge, e, score\n        ORDER BY score DESC\n        RETURN edge.uuid AS search_edge_uuid,\n            collect({\n                uuid: e.uuid,\n                source_node_uuid: startNode(e).uuid,\n                target_node_uuid: endNode(e).uuid,\n                created_at: e.created_at,\n                name: e.name,\n                group_id: e.group_id,\n                fact: e.fact,\n                fact_embedding: e.fact_embedding,\n                episodes: e.episodes,\n                expired_at: e.expired_at,\n                valid_at: e.valid_at,\n                invalid_at: e.invalid_at,\n                attributes: properties(e)\n            })[..$limit] AS matches\n        '
2025-09-28 17:50:26,195 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-09-28 17:50:26,263 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:26,441 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:26,554 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:26,604 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:26,624 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:26,655 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:26,747 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:26,963 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:26,988 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:27,029 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:27,243 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:27,259 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:27,431 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:27,639 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:27,710 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:28,190 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:28,212 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:28,355 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2025-09-28 17:50:28,706 - httpx - INFO - HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"
2025-09-28 17:50:29,667 - graphiti_core.graphiti - INFO - Completed add_episode in 28540.39192199707 ms
2025-09-28 17:50:29,667 - __main__ - INFO - Episode 'ReservineBack Project Overview' added successfully
2025-09-28 17:50:29,667 - __main__ - INFO - Episode 'ReservineBack Project Overview' processed successfully

it looks like it added something tho.

[claude[bot]]

@ylli2000 Is this still an issue? Please confirm within 14 days or this issue will be closed.

[claude[bot]]

@ylli2000 Is this still an issue? Please confirm within 14 days or this issue will be closed.