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Using the REST API

If you prefer to use the LlamaExtract API directly, that's great! You can use it in any language that can make HTTP requests. Here are some sample calls:

Upload the files​

curl -X 'POST' \
  'https://api.cloud.llamaindex.ai/api/v1/files' \
  -H 'accept: application/json' \
  -H 'Content-Type: multipart/form-data' \
  -H "Authorization: Bearer $LLAMA_CLOUD_API_KEY" \
  -F 'upload_file=@/path/to/your/file.pdf;type=application/pdf'

Infer and create a schema​

curl -X 'POST' \
  'https://api.cloud.llamaindex.ai/api/v1/extraction/schemas/infer' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -H "Authorization: Bearer $LLAMA_CLOUD_API_KEY" \
  -d '{"name":"Schema Name","file_ids":["<file_id_1>", "<file_id_2>"]}'

Start an extraction job​

curl -X 'POST' \
  'https://api.cloud.llamaindex.ai/api/v1/extraction/jobs' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -H "Authorization: Bearer $LLAMA_CLOUD_API_KEY" \
  -d '{"schema_id":"<schema_id>","file_id":"<file_id_1>"}'

Or in batch:

curl -X 'POST' \
  'https://api.cloud.llamaindex.ai/api/v1/extraction/jobs/batch' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -H "Authorization: Bearer $LLAMA_CLOUD_API_KEY" \
  -d '{"schema_id":"<schema_id>","file_ids":["<file_id_1>", "<file_id_2>"]}'

Check the status of the extraction job:​

curl -X 'GET' \
  'https://api.cloud.llamaindex.ai/api/v1/extraction/jobs/<job_id>' \
  -H 'accept: application/json' \
  -H "Authorization: Bearer $LLAMA_CLOUD_API_KEY"

Get the results​

curl -X 'GET' \
  'https://api.cloud.llamaindex.ai/api/v1/extraction/jobs/<job_id>/result' \
  -H 'accept: application/json' \
  -H "Authorization: Bearer $LLAMA_CLOUD_API_KEY"

You can see all the available endpoints in our full API documentation -->