Import Grok, Claude and ChatGPT chats into open-webui.

This importer tool has two Python scripts: one for converting the model JSON files to openweb-ui format JSON, the second for creating a SQL script to import the JSON into the openweb-ui SQLite database.

The imported chats are given the tags imported-chatgpt, imported-claude and imported-grok.

Any private-use Unicode characters occasionally found in model exports are stripped from the message text during conversion.

There were problems exporting chats from Gemini, so it's not currently supported. DeepSeek and others could be added without much effort.

python .\convert_chatgpt.py --userid="get-this-from-your-webui.db" .\chatgpt.json python .\create_sql.py ./output/chatgpt --tags="imported-chatgpt" --output=chatgpt.sql 

docker run --rm -v $(pwd)/data:/data \ ghcr.io/yetanotherchris/openwebui-importer:latest \ python convert_chatgpt.py --userid="your-user-id" --output-dir=/data/output /data/chatgpt.json docker run --rm -v $(pwd)/data:/data \ ghcr.io/yetanotherchris/openwebui-importer:latest \ python create_sql.py /data/output/chatgpt --tags="imported-chatgpt" --output=/data/chatgpt.sql

docker run --rm -v ${PWD}/data:/data ` ghcr.io/yetanotherchris/openwebui-importer:latest ` python convert_chatgpt.py --userid="your-user-id" --output-dir=/data/output /data/chatgpt.json docker run --rm -v ${PWD}/data:/data ` ghcr.io/yetanotherchris/openwebui-importer:latest ` python create_sql.py /data/output/chatgpt --tags="imported-chatgpt" --output=/data/chatgpt.sql

Full example for GPT and Grok:

python .\convert_chatgpt.py --userid="example-9cef-4387-8ee4-b82eb2e1c637" .\chatgpt.json python .\convert_chatgpt.py --userid="example-9cef-4387-8ee4-b82eb2e1c637" .\chatgpt.json python .\convert_grok.py --userid="example-9cef-4387-8ee4-b82eb2e1c637" .\grok.json python .\create_sql.py ./output/chatgpt --tags="imported-chatgpt" --output=chatgpt.sql python .\create_sql.py ./output/grok --tags="imported-grok" --output=grok.sql # Now run the scripts inside DB Browser and hit save 

Install the required Python dependencies first:

pip install -r requirements.txt

usage: convert_chatgpt.py [-h] --userid USERID [--output-dir OUTPUT_DIR] files [files ...] Convert ChatGPT exports to open-webui JSON 

usage: convert_grok.py [-h] --userid USERID [--output-dir OUTPUT_DIR] files [files ...] Convert Grok exports to open-webui JSON 

usage: convert_claude.py [-h] --userid USERID [--output-dir OUTPUT_DIR] files [files ...] Convert Claude exports to open-webui JSON 

All converter scripts name the output files using the original conversation ID so running them again will produce the same filename for the same conversation. Converted files are saved in a subdirectory named after the model (for example output/grok or output/claude).

usage: create_sql.py [-h] [--tags TAGS] [--output OUTPUT] files [files ...] Create SQL inserts for open-webui chats. Existing chat records are deleted before inserting so they are replaced if already present. Tags are inserted with UPSERT statements, ensuring the default import tags (and any tags passed via `--tags`) exist for each user. positional arguments: files Chat JSON files or directories options: -h, --help show this help message and exit --tags TAGS Comma-separated tags for the meta field --output OUTPUT Write SQL statements to this file 

1. Create an export from Claude, ChatGPT or Grok.
2. Unzip the archive and locate the JSON file (for Grok this is prod-grok-backend.json).
3. Convert the export to open-webui JSON using the appropriate script:

   python ./convert_grok.py --userid="d95194d2-9cef-4387-8ee4-b82eb2e1c637" ./grok.json

   The converter writes JSON files to a subdirectory such as output/grok.
4. Generate SQL statements from the converted JSON files:

   python ./create_sql.py ./output --tags="imported-grok" --output=grok.sql

   The resulting SQL removes any existing chats with the same IDs before inserting new ones, while tags are inserted using UPSERTs so they are updated if they already exist. Any tags passed with --tags are also created for each user.
5. Make a copy of your webui.db database.
6. Execute the generated SQL using a tool such as DB Browser for SQLite. Ensure you save the database.