Text focused APIs utilizing generative large language models (LLMs)
MARCIE API (2025-08-18T18:01:56Z)
Lets documents, content and metadata be stored in MARCIE for further API processing. To get this data into the MARCIE store, document decomposition and ingestion, as well as manual document/content submission APIs can be used. Once populated, application APIs provide semantic/syntactic analysis, semantic search and content related querying to be executed at scale. See APPS from the navigation panel for more details.
Content is submitted to endpoints with associated control attributes and results are synchronously returned. Primary examples of these APIs include: content comparison, enrichment, transformation, and analysis (spellcheck, grammar, sentiment, readability). See DOCUMENT and CONTENT from the navigation panel for more details. In this scenario, content is not stored or persisted. 
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Overview
MARCIE Support
Languages
Servers
Mock server
https://marcie.redocly.app/_mock/openapi/
https://w1waoh1clk.execute-api.us-east-1.amazonaws.com/{basePath}/
Bodyapplication/jsonrequired
Two letter language code for the target language to translate the source text into.
Controls the amount of randomness in the generated text. Lowering this will result in the output to be more deterministic.
Default 0
- Mock server
https://marcie.redocly.app/_mock/openapi/text/translation
https://w1waoh1clk.execute-api.us-east-1.amazonaws.com/semantex-qa/text/translation
- curl
- JavaScript
- Node.js
- Python
- Java
- C#
- PHP
- Go
- Ruby
- R
- Payload
curl -i -X POST \
https://marcie.redocly.app/_mock/openapi/text/translation \
-H 'Content-Type: application/json' \
-H 'x-api-key: YOUR_API_KEY_HERE' \
-d '{
"text": "Jupiter is the fifth planet from the Sun and the largest in the Solar System. It is a gas giant with a mass one-thousandth that of the Sun, but two-and-a-half times that of all the other planets in the Solar System combined. Jupiter is one of the brightest objects visible to the naked eye in the night sky, and has been known to ancient civilizations since before recorded history. It is named after the Roman god Jupiter.[19] When viewed from Earth, Jupiter can be bright enough for its reflected light to cast visible shadows,[20] and is on average the third-brightest natural object in the night sky after the Moon and Venus.",
"target": "fr"
}'Response
application/json
{}
Bodyapplication/jsonrequired
Controls the amount of randomness in the generated text. Lowering this will result in the output to be more deterministic.
Default 0
- Mock server
https://marcie.redocly.app/_mock/openapi/text/enrichment/tone
https://w1waoh1clk.execute-api.us-east-1.amazonaws.com/semantex-qa/text/enrichment/tone
- curl
- JavaScript
- Node.js
- Python
- Java
- C#
- PHP
- Go
- Ruby
- R
- Payload
curl -i -X POST \
https://marcie.redocly.app/_mock/openapi/text/enrichment/tone \
-H 'Content-Type: application/json' \
-H 'x-api-key: YOUR_API_KEY_HERE' \
-d '{
"text": "I am afraid I will have to report you. I wish you had behaved better than this."
}'Response
application/json
{}
Bodyapplication/jsonrequired
Controls the amount of randomness in the generated text. Lowering this will result in the output to be more deterministic.
Default 0
- Mock server
https://marcie.redocly.app/_mock/openapi/text/enrichment/sentiment/rewrite
https://w1waoh1clk.execute-api.us-east-1.amazonaws.com/semantex-qa/text/enrichment/sentiment/rewrite
- curl
- JavaScript
- Node.js
- Python
- Java
- C#
- PHP
- Go
- Ruby
- R
- Payload
curl -i -X POST \
https://marcie.redocly.app/_mock/openapi/text/enrichment/sentiment/rewrite \
-H 'Content-Type: application/json' \
-H 'x-api-key: YOUR_API_KEY_HERE' \
-d '{
"text": "If you guys don'\''t make your monthly quotas this month, I will be forced to report you and file an official letter of complaint."
}'Response
application/json
{}
Enrichments/Classification
Text enrichment APIs offer various enrichment functions that take the raw text as its input and provides a specific enrichment/feature corresponding to the input text. An enrichment function is idempotent and its output is determined by the input text and the underlying predictive (deep learning based) linguistic model. Some examples of these include text based sentiment, readability calculation etc. Most of the underlying methods can be used either using a "GET" or a "POST" HTTP method. For smaller text, the GET method offers better performance and allows for network optimizations such as caching.
Operations