id stringlengths 53 86 | api_name stringlengths 2 76 | api_description stringlengths 1 500 ⌀ | api_score float64 0 10 ⌀ | endpoint_name stringlengths 1 190 | endpoint_description stringlengths 0 500 | response_status_code int64 100 505 | response_summary stringlengths 1 68 ⌀ | response_json stringlengths 6 50k | response_json_schema stringlengths 14 150k |
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72f17854-7524-4e82-b2b3-0ec53025cb5c/5b9a1e98-7de0-45b6-9ea1-76423b78eb11/0/0 | Paratrooper | Fast and Accurate word-by-word text similarity and text clustering API. | null | Cluster | Given an array of strings, this endpoint returns an array of cluster numbers. Text with similarity percent above threshold will be assigned to the same cluster number. | 200 | Cluster Example Response | [1, 1, 2, 3, 2, 1] | {"type": "array", "items": {"type": "integer"}} |
72f17854-7524-4e82-b2b3-0ec53025cb5c/230eaad2-14ec-44f4-8f62-876261c9bcba/0/0 | Paratrooper | Fast and Accurate word-by-word text similarity and text clustering API. | null | Find Cluster | Finds the closest cluster for given text. Clusters with similarity below threshold will be ignored. Cluster with highest similarity will be returned. | 200 | Find Cluster Response | [1, 2] | {"type": "array", "items": {"type": "integer"}} |
72f17854-7524-4e82-b2b3-0ec53025cb5c/4783bd60-1535-4e39-9ce6-2bd26a2434c6/0/0 | Paratrooper | Fast and Accurate word-by-word text similarity and text clustering API. | null | GetSimilarity | Returns similarity ratios between given string arrays. | 200 | Get Similarity Response Example | [[0.924, 0.94, 0.429, 0, 0.432, 0.912], [0.364, 0.362, 0.898, 0, 0.866, 0.567]] | {"type": "array", "items": {"type": "array", "items": {"type": "number"}}} |
d61ad898-9aee-4ea8-9edd-2fe9842290fe/6b5c80db-b5aa-43fa-928c-f8c101534ffc/2/0 | iDox-ai Document | The iDox.ai API provides high-performance document processing tools for anyone. Developers can find APIs for privacy, legal, and document. | null | Upload Document | Upload a document to iDox.ai. PDF and MS Word (DOC, DOCX) file formats are supported. | 200 | 200 Success | {"jobId": "620b6a4bd1906f17440723d0", "taskCategory": "DOC_TOOL", "taskSubcategory": "PRE_PROCESSING", "status": "Processing", "startDateTime": "2022-02-15T08:42:10.144Z", "expirationDateTime": "2022-02-16T08:42:10.144Z"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"jobId": {"type": "string"}, "taskCategory": {"type": "string"}, "taskSubcategory": {"type": "string"}, "status": {"type": "string"}, "startDateTime": {"type": "string"}, "expirationDateTime": {"type": "string"}}, "required": ["expirationDateTime", "jobId", "startDateTime", "status", "taskCategory", "taskSubcategory"]} |
d61ad898-9aee-4ea8-9edd-2fe9842290fe/f909f965-c7ff-4bd2-adb7-9b0466252c56/0/0 | iDox-ai Document | The iDox.ai API provides high-performance document processing tools for anyone. Developers can find APIs for privacy, legal, and document. | null | Find job status | Return the job status. | 200 | 200 Success | {"jobId": "620b6a4bd1906f17440723d0", "taskCategory": "DOC_TOOL", "taskSubcategory": "PRE_PROCESSING", "status": "Succeeded", "startDateTime": "2022-02-15T08:54:35.711Z", "completeDateTime": "2022-02-15T08:54:46.466Z", "expirationDateTime": "2022-02-16T08:54:35.711Z", "payload": {"filename": "Bill sample 2.pdf", "docId": "620b6a4bd1906f17440723d1"}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"jobId": {"type": "string"}, "taskCategory": {"type": "string"}, "taskSubcategory": {"type": "string"}, "status": {"type": "string"}, "startDateTime": {"type": "string"}, "completeDateTime": {"type": "string"}, "expirationDateTime": {"type": "string"}, "payload": {"type": "object", "properties": {"filename": {"type": "string"}, "docId": {"type": "string"}}, "required": ["docId", "filename"]}}, "required": ["completeDateTime", "expirationDateTime", "jobId", "payload", "startDateTime", "status", "taskCategory", "taskSubcategory"]} |
81c09f1a-9529-468e-a34d-a3223764dd47/56fafbf2-f6f5-4bdc-a251-52f96c9e814d/0/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanUploadV3 | Triggers a scan of the file identified by the provided fileID. As the underlying file might be arbitrarily large, this scan is conducted asynchronously. Results from the scan are delivered to the webhook URL provided in the request payload. | 500 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/56fafbf2-f6f5-4bdc-a251-52f96c9e814d/1/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanUploadV3 | Triggers a scan of the file identified by the provided fileID. As the underlying file might be arbitrarily large, this scan is conducted asynchronously. Results from the scan are delivered to the webhook URL provided in the request payload. | 429 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/56fafbf2-f6f5-4bdc-a251-52f96c9e814d/2/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanUploadV3 | Triggers a scan of the file identified by the provided fileID. As the underlying file might be arbitrarily large, this scan is conducted asynchronously. Results from the scan are delivered to the webhook URL provided in the request payload. | 401 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/56fafbf2-f6f5-4bdc-a251-52f96c9e814d/3/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanUploadV3 | Triggers a scan of the file identified by the provided fileID. As the underlying file might be arbitrarily large, this scan is conducted asynchronously. Results from the scan are delivered to the webhook URL provided in the request payload. | 409 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/56fafbf2-f6f5-4bdc-a251-52f96c9e814d/4/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanUploadV3 | Triggers a scan of the file identified by the provided fileID. As the underlying file might be arbitrarily large, this scan is conducted asynchronously. Results from the scan are delivered to the webhook URL provided in the request payload. | 422 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/56fafbf2-f6f5-4bdc-a251-52f96c9e814d/5/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanUploadV3 | Triggers a scan of the file identified by the provided fileID. As the underlying file might be arbitrarily large, this scan is conducted asynchronously. Results from the scan are delivered to the webhook URL provided in the request payload. | 200 | Example_1 | {"findings": [[{"finding": "", "redactedFinding": "", "beforeContext": "", "afterContext": "", "detector": {"name": "", "uuid": ""}, "confidence": "VERY_UNLIKELY", "location": {"byteRange": {"start": 0, "end": 0}, "codepointRange": {"start": 0, "end": 0}}, "redactedLocation": {"byteRange": {"start": 0, "end": 0}, "codepointRange": {"start": 0, "end": 0}}}]], "redactedPayload": []} | {"type": "object", "properties": {"findings": {"type": "array", "description": "A list of all findings that were detected in the request payload. Each item in the list is a list of all findings that occurred at the corresponding list index from the input payload.", "items": {"type": "array", "items": {"type": "object", "properties": {"finding": {"type": "string", "description": "The string that triggered a match during the scan."}, "redactedFinding": {"type": "string", "description": "The redacted version of finding. This key is omitted if no redactionConfig was configured the detector that triggered the match."}, "beforeContext": {"type": "string", "description": "The sequence of bytes that occurred directly prior to the matched finding. The number of bytes is usually equal to the requested number from the request config, but it could be smaller if the finding occurs near the beginning of the payload. This key is omitted if no context was requested."}, "afterContext": {"type": "string", "description": "The sequence of bytes that occurred directly after the matched finding. The number of bytes is usually equal to the requested number from the request config, but it could be smaller if the finding occurs near the end of the payload. This key is omitted if no context was requested."}, "detector": {"type": "object", "properties": {"name": {"type": "string", "description": "The display name of the detector that matched the finding."}, "uuid": {"type": "string", "format": "uuid", "description": "The UUID of the detector that matched the finding. This UUID can be looked up in the Nightfall dashboard."}}, "description": "Metadata describing the detector that matched the finding."}, "confidence": {"type": "string", "enum": ["VERY_UNLIKELY", "UNLIKELY", "POSSIBLE", "LIKELY", "VERY_LIKELY"], "description": "The confidence level of a finding."}, "location": {"type": "object", "properties": {"byteRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting byte."}, "end": {"type": "integer", "description": "The index of the fragment's ending byte."}}}, "codepointRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting codepoint character."}, "end": {"type": "integer", "description": "The index of the fragment's ending codepoint character."}}}}, "description": "The location of the finding in the corresponding original input payload string."}, "redactedLocation": {"type": "object", "properties": {"byteRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting byte."}, "end": {"type": "integer", "description": "The index of the fragment's ending byte."}}}, "codepointRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting codepoint character."}, "end": {"type": "integer", "description": "The index of the fragment's ending codepoint character."}}}}, "description": "The location of the redacted finding in the corresponding redactedPayload string."}}}}}, "redactedPayload": {"type": "array", "items": {"type": "string"}, "description": "A list containing the the redacted version of each string in the input payload. If no redactions were applied, the corresponding string will be empty."}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/56fafbf2-f6f5-4bdc-a251-52f96c9e814d/6/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanUploadV3 | Triggers a scan of the file identified by the provided fileID. As the underlying file might be arbitrarily large, this scan is conducted asynchronously. Results from the scan are delivered to the webhook URL provided in the request payload. | 400 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/56fafbf2-f6f5-4bdc-a251-52f96c9e814d/7/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanUploadV3 | Triggers a scan of the file identified by the provided fileID. As the underlying file might be arbitrarily large, this scan is conducted asynchronously. Results from the scan are delivered to the webhook URL provided in the request payload. | 404 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/0ac29980-8dff-41b0-90b1-89dce1cf826c/0/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanPayloadV3 | Provide a list of arbitrary string data, and scan each item with the provided detectors to uncover sensitive information. Returns a list equal in size to the number of provided string payloads. The item at each list index will be a list of all matches for the provided detectors, or an empty list if no occurrences are found. | 400 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/0ac29980-8dff-41b0-90b1-89dce1cf826c/1/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanPayloadV3 | Provide a list of arbitrary string data, and scan each item with the provided detectors to uncover sensitive information. Returns a list equal in size to the number of provided string payloads. The item at each list index will be a list of all matches for the provided detectors, or an empty list if no occurrences are found. | 200 | Response | {"findings": [[{"finding": "458-02-6124", "detector": {"name": "US Social Security Number", "uuid": "e30d9a87-f6c7-46b9-a8f4-16547901e069"}, "confidence": "VERY_LIKELY", "location": {"byteRange": {"start": 39, "end": 50}, "codepointRange": {"start": 39, "end": 50}, "rowRange": null, "columnRange": null, "commitHash": ""}, "matchedDetectionRuleUUIDs": [], "matchedDetectionRules": ["My Match Rule"]}], [], [{"finding": "5310-2768-6832-9293", "redactedFinding": "####-####-####-####", "detector": {"name": "Credit Card Number", "uuid": "74c1815e-c0c3-4df5-8b1e-6cf98864a454"}, "confidence": "VERY_LIKELY", "location": {"byteRange": {"start": 25, "end": 44}, "codepointRange": {"start": 25, "end": 44}, "rowRange": null, "columnRange": null, "commitHash": ""}, "redactedLocation": {"byteRange": {"start": 25, "end": 44}, "codepointRange": {"start": 25, "end": 44}, "rowRange": null, "columnRange": null, "commitHash": ""}, "matchedDetectionRuleUUIDs": [], "matchedDetectionRules": ["My Match Rule"]}]], "redactedPayload": ["", "", "My credit card number is ####-####-####-####"]} | {"type": "object", "properties": {"findings": {"type": "array", "description": "A list of all findings that were detected in the request payload. Each item in the list is a list of all findings that occurred at the corresponding list index from the input payload.", "items": {"type": "array", "items": {"type": "object", "properties": {"finding": {"type": "string", "description": "The string that triggered a match during the scan."}, "redactedFinding": {"type": "string", "description": "The redacted version of finding. This key is omitted if no redactionConfig was configured the detector that triggered the match."}, "beforeContext": {"type": "string", "description": "The sequence of bytes that occurred directly prior to the matched finding. The number of bytes is usually equal to the requested number from the request config, but it could be smaller if the finding occurs near the beginning of the payload. This key is omitted if no context was requested."}, "afterContext": {"type": "string", "description": "The sequence of bytes that occurred directly after the matched finding. The number of bytes is usually equal to the requested number from the request config, but it could be smaller if the finding occurs near the end of the payload. This key is omitted if no context was requested."}, "detector": {"type": "object", "properties": {"name": {"type": "string", "description": "The display name of the detector that matched the finding."}, "uuid": {"type": "string", "format": "uuid", "description": "The UUID of the detector that matched the finding. This UUID can be looked up in the Nightfall dashboard."}}, "description": "Metadata describing the detector that matched the finding."}, "confidence": {"type": "string", "enum": ["VERY_UNLIKELY", "UNLIKELY", "POSSIBLE", "LIKELY", "VERY_LIKELY"], "description": "The confidence level of a finding."}, "location": {"type": "object", "properties": {"byteRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting byte."}, "end": {"type": "integer", "description": "The index of the fragment's ending byte."}}}, "codepointRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting codepoint character."}, "end": {"type": "integer", "description": "The index of the fragment's ending codepoint character."}}}}, "description": "The location of the finding in the corresponding original input payload string."}, "redactedLocation": {"type": "object", "properties": {"byteRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting byte."}, "end": {"type": "integer", "description": "The index of the fragment's ending byte."}}}, "codepointRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting codepoint character."}, "end": {"type": "integer", "description": "The index of the fragment's ending codepoint character."}}}}, "description": "The location of the redacted finding in the corresponding redactedPayload string."}}}}}, "redactedPayload": {"type": "array", "items": {"type": "string"}, "description": "A list containing the the redacted version of each string in the input payload. If no redactions were applied, the corresponding string will be empty."}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/0ac29980-8dff-41b0-90b1-89dce1cf826c/2/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanPayloadV3 | Provide a list of arbitrary string data, and scan each item with the provided detectors to uncover sensitive information. Returns a list equal in size to the number of provided string payloads. The item at each list index will be a list of all matches for the provided detectors, or an empty list if no occurrences are found. | 500 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/0ac29980-8dff-41b0-90b1-89dce1cf826c/3/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanPayloadV3 | Provide a list of arbitrary string data, and scan each item with the provided detectors to uncover sensitive information. Returns a list equal in size to the number of provided string payloads. The item at each list index will be a list of all matches for the provided detectors, or an empty list if no occurrences are found. | 401 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/0ac29980-8dff-41b0-90b1-89dce1cf826c/4/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanPayloadV3 | Provide a list of arbitrary string data, and scan each item with the provided detectors to uncover sensitive information. Returns a list equal in size to the number of provided string payloads. The item at each list index will be a list of all matches for the provided detectors, or an empty list if no occurrences are found. | 422 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/0ac29980-8dff-41b0-90b1-89dce1cf826c/5/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | ScanPayloadV3 | Provide a list of arbitrary string data, and scan each item with the provided detectors to uncover sensitive information. Returns a list equal in size to the number of provided string payloads. The item at each list index will be a list of all matches for the provided detectors, or an empty list if no occurrences are found. | 429 | Example_1 | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/d8f8e927-53d7-4df6-b9b1-83fc3ed4702f/0/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | CompleteUploadV3 | Validates that all bytes of the file have been uploaded, and that the content type is supported by Nightfall. | 404 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/d8f8e927-53d7-4df6-b9b1-83fc3ed4702f/1/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | CompleteUploadV3 | Validates that all bytes of the file have been uploaded, and that the content type is supported by Nightfall. | 429 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/d8f8e927-53d7-4df6-b9b1-83fc3ed4702f/2/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | CompleteUploadV3 | Validates that all bytes of the file have been uploaded, and that the content type is supported by Nightfall. | 200 | null | {"findings": [[{"finding": "", "redactedFinding": "", "beforeContext": "", "afterContext": "", "detector": {"name": "", "uuid": ""}, "confidence": "VERY_UNLIKELY", "location": {"byteRange": {"start": 0, "end": 0}, "codepointRange": {"start": 0, "end": 0}}, "redactedLocation": {"byteRange": {"start": 0, "end": 0}, "codepointRange": {"start": 0, "end": 0}}}]], "redactedPayload": []} | {"type": "object", "properties": {"findings": {"type": "array", "description": "A list of all findings that were detected in the request payload. Each item in the list is a list of all findings that occurred at the corresponding list index from the input payload.", "items": {"type": "array", "items": {"type": "object", "properties": {"finding": {"type": "string", "description": "The string that triggered a match during the scan."}, "redactedFinding": {"type": "string", "description": "The redacted version of finding. This key is omitted if no redactionConfig was configured the detector that triggered the match."}, "beforeContext": {"type": "string", "description": "The sequence of bytes that occurred directly prior to the matched finding. The number of bytes is usually equal to the requested number from the request config, but it could be smaller if the finding occurs near the beginning of the payload. This key is omitted if no context was requested."}, "afterContext": {"type": "string", "description": "The sequence of bytes that occurred directly after the matched finding. The number of bytes is usually equal to the requested number from the request config, but it could be smaller if the finding occurs near the end of the payload. This key is omitted if no context was requested."}, "detector": {"type": "object", "properties": {"name": {"type": "string", "description": "The display name of the detector that matched the finding."}, "uuid": {"type": "string", "format": "uuid", "description": "The UUID of the detector that matched the finding. This UUID can be looked up in the Nightfall dashboard."}}, "description": "Metadata describing the detector that matched the finding."}, "confidence": {"type": "string", "enum": ["VERY_UNLIKELY", "UNLIKELY", "POSSIBLE", "LIKELY", "VERY_LIKELY"], "description": "The confidence level of a finding."}, "location": {"type": "object", "properties": {"byteRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting byte."}, "end": {"type": "integer", "description": "The index of the fragment's ending byte."}}}, "codepointRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting codepoint character."}, "end": {"type": "integer", "description": "The index of the fragment's ending codepoint character."}}}}, "description": "The location of the finding in the corresponding original input payload string."}, "redactedLocation": {"type": "object", "properties": {"byteRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting byte."}, "end": {"type": "integer", "description": "The index of the fragment's ending byte."}}}, "codepointRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting codepoint character."}, "end": {"type": "integer", "description": "The index of the fragment's ending codepoint character."}}}}, "description": "The location of the redacted finding in the corresponding redactedPayload string."}}}}}, "redactedPayload": {"type": "array", "items": {"type": "string"}, "description": "A list containing the the redacted version of each string in the input payload. If no redactions were applied, the corresponding string will be empty."}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/d8f8e927-53d7-4df6-b9b1-83fc3ed4702f/3/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | CompleteUploadV3 | Validates that all bytes of the file have been uploaded, and that the content type is supported by Nightfall. | 500 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/d8f8e927-53d7-4df6-b9b1-83fc3ed4702f/4/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | CompleteUploadV3 | Validates that all bytes of the file have been uploaded, and that the content type is supported by Nightfall. | 409 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/d8f8e927-53d7-4df6-b9b1-83fc3ed4702f/5/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | CompleteUploadV3 | Validates that all bytes of the file have been uploaded, and that the content type is supported by Nightfall. | 401 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/d8f8e927-53d7-4df6-b9b1-83fc3ed4702f/6/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | CompleteUploadV3 | Validates that all bytes of the file have been uploaded, and that the content type is supported by Nightfall. | 400 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/c1cf7059-cd22-4954-b971-0f58febd0be4/0/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | InitiateUploadV3 | Creates a new file upload session. If this operation returns successfully, the ID returned as part of the response object shall be used to refer to the file in all subsequent upload and scanning operations. | 200 | null | {"id": "", "fileSizeBytes": 0, "chunkSize": 0, "mimeType": ""} | {"type": "object", "properties": {"id": {"type": "string", "format": "uuid", "description": "a UUID to uniquely identify a particular file upload"}, "fileSizeBytes": {"type": "integer", "description": "the size of the file in bytes"}, "chunkSize": {"type": "integer", "description": "the number of bytes to upload in each chunk upload request"}, "mimeType": {"type": "string", "description": "an RFC2045 media type that describes the underlying content type"}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/c1cf7059-cd22-4954-b971-0f58febd0be4/1/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | InitiateUploadV3 | Creates a new file upload session. If this operation returns successfully, the ID returned as part of the response object shall be used to refer to the file in all subsequent upload and scanning operations. | 401 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/c1cf7059-cd22-4954-b971-0f58febd0be4/2/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | InitiateUploadV3 | Creates a new file upload session. If this operation returns successfully, the ID returned as part of the response object shall be used to refer to the file in all subsequent upload and scanning operations. | 500 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/c1cf7059-cd22-4954-b971-0f58febd0be4/3/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | InitiateUploadV3 | Creates a new file upload session. If this operation returns successfully, the ID returned as part of the response object shall be used to refer to the file in all subsequent upload and scanning operations. | 400 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/c1cf7059-cd22-4954-b971-0f58febd0be4/4/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | InitiateUploadV3 | Creates a new file upload session. If this operation returns successfully, the ID returned as part of the response object shall be used to refer to the file in all subsequent upload and scanning operations. | 429 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/6995a326-650a-487c-beb6-3e6f8e4ddf81/0/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | UploadChunkV3 | Upload all bytes contained in the request body to the file identified by the ID in the path parameter. | 500 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/6995a326-650a-487c-beb6-3e6f8e4ddf81/1/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | UploadChunkV3 | Upload all bytes contained in the request body to the file identified by the ID in the path parameter. | 200 | null | {"findings": [[{"finding": "", "redactedFinding": "", "beforeContext": "", "afterContext": "", "detector": {"name": "", "uuid": ""}, "confidence": "VERY_UNLIKELY", "location": {"byteRange": {"start": 0, "end": 0}, "codepointRange": {"start": 0, "end": 0}}, "redactedLocation": {"byteRange": {"start": 0, "end": 0}, "codepointRange": {"start": 0, "end": 0}}}]], "redactedPayload": []} | {"type": "object", "properties": {"findings": {"type": "array", "description": "A list of all findings that were detected in the request payload. Each item in the list is a list of all findings that occurred at the corresponding list index from the input payload.", "items": {"type": "array", "items": {"type": "object", "properties": {"finding": {"type": "string", "description": "The string that triggered a match during the scan."}, "redactedFinding": {"type": "string", "description": "The redacted version of finding. This key is omitted if no redactionConfig was configured the detector that triggered the match."}, "beforeContext": {"type": "string", "description": "The sequence of bytes that occurred directly prior to the matched finding. The number of bytes is usually equal to the requested number from the request config, but it could be smaller if the finding occurs near the beginning of the payload. This key is omitted if no context was requested."}, "afterContext": {"type": "string", "description": "The sequence of bytes that occurred directly after the matched finding. The number of bytes is usually equal to the requested number from the request config, but it could be smaller if the finding occurs near the end of the payload. This key is omitted if no context was requested."}, "detector": {"type": "object", "properties": {"name": {"type": "string", "description": "The display name of the detector that matched the finding."}, "uuid": {"type": "string", "format": "uuid", "description": "The UUID of the detector that matched the finding. This UUID can be looked up in the Nightfall dashboard."}}, "description": "Metadata describing the detector that matched the finding."}, "confidence": {"type": "string", "enum": ["VERY_UNLIKELY", "UNLIKELY", "POSSIBLE", "LIKELY", "VERY_LIKELY"], "description": "The confidence level of a finding."}, "location": {"type": "object", "properties": {"byteRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting byte."}, "end": {"type": "integer", "description": "The index of the fragment's ending byte."}}}, "codepointRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting codepoint character."}, "end": {"type": "integer", "description": "The index of the fragment's ending codepoint character."}}}}, "description": "The location of the finding in the corresponding original input payload string."}, "redactedLocation": {"type": "object", "properties": {"byteRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting byte."}, "end": {"type": "integer", "description": "The index of the fragment's ending byte."}}}, "codepointRange": {"type": "object", "properties": {"start": {"type": "integer", "description": "The index of the fragment's starting codepoint character."}, "end": {"type": "integer", "description": "The index of the fragment's ending codepoint character."}}}}, "description": "The location of the redacted finding in the corresponding redactedPayload string."}}}}}, "redactedPayload": {"type": "array", "items": {"type": "string"}, "description": "A list containing the the redacted version of each string in the input payload. If no redactions were applied, the corresponding string will be empty."}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/6995a326-650a-487c-beb6-3e6f8e4ddf81/2/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | UploadChunkV3 | Upload all bytes contained in the request body to the file identified by the ID in the path parameter. | 404 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/6995a326-650a-487c-beb6-3e6f8e4ddf81/3/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | UploadChunkV3 | Upload all bytes contained in the request body to the file identified by the ID in the path parameter. | 429 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/6995a326-650a-487c-beb6-3e6f8e4ddf81/4/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | UploadChunkV3 | Upload all bytes contained in the request body to the file identified by the ID in the path parameter. | 401 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
81c09f1a-9529-468e-a34d-a3223764dd47/6995a326-650a-487c-beb6-3e6f8e4ddf81/5/0 | NightfallAI | This API exposes detectors for sensitive data in arbitrary string payloads. | null | UploadChunkV3 | Upload all bytes contained in the request body to the file identified by the ID in the path parameter. | 400 | null | {"code": 0, "message": "", "description": "", "additionalData": {}} | {"type": "object", "properties": {"code": {"type": "integer", "description": "A status code to uniquely describe this error."}, "message": {"type": "string", "description": "A message associated with the status code."}, "description": {"type": "string", "description": "Additional details to explain what may have occurred. Omitted if empty."}, "additionalData": {"type": "object", "description": "Extra tags and metadata that provide debugging information surrounding the error. Omitted if empty.", "additionalProperties": true}}} |
baace558-9f53-46ec-8fc2-dae735bede0c/171837fb-a2cf-487b-93ee-256ffde79343/0/0 | Lemmatizer | Lemmatisation (or lemmatization) in linguistics is the process of grouping together the inflected forms of a word so they can be analysed as a single item, identified by the word's lemma, or dictionary form. | 0 | lemmatize | Lemmatization endpoint | 200 | Response | {"author": "codewalker7", "email": "codewalker7@pm.me", "lemma": {"as": 2, "do": 2, "go": 1, "how": 1, "it": 1, "long": 1, "matter": 1, "not": 2, "slowly": 1, "stop": 1, "you": 2}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "lemma": {"type": "object", "properties": {"as": {"type": "integer"}, "do": {"type": "integer"}, "go": {"type": "integer"}, "how": {"type": "integer"}, "it": {"type": "integer"}, "long": {"type": "integer"}, "matter": {"type": "integer"}, "not": {"type": "integer"}, "slowly": {"type": "integer"}, "stop": {"type": "integer"}, "you": {"type": "integer"}}, "required": ["as", "do", "go", "how", "it", "long", "matter", "not", "slowly", "stop", "you"]}}, "required": ["author", "email", "lemma"]} |
85adde56-2bd7-4ef4-835c-79d434f719f8/bfe72e44-b216-4ce7-bd32-7a7cb1badf4a/0/0 | Financial summarization | Abstractive Financial Summarization is a task in Natural Language Processing (NLP) that aims to generate a concise summary of a source text. ... Abstractive financial summarization yields a number of applications in different domains, from books and literature, to science and R&D, to financial research and legal documents analysis. | null | fsummarize | Financial Summarize | 200 | Response | {"author": "codewalker7", "email": "codewalker7@pm.me", "financial_summarize": "National Commercial Bank to pay about 55.7 billion riyals. Deal will create Gulf region\u2019s third-largest lender"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "financial_summarize": {"type": "string"}}, "required": ["author", "email", "financial_summarize"]} |
1900823a-fe83-4dff-a930-f04c3b30f93e/55fea90a-2e61-4474-b071-4b406ba71b43/1/0 | NSFW Text Dection | NSFW Text Detection API, a cutting-edge tool designed to analyze text content based on its appropriateness. By simply providing a text input or prompt, the API returns two float values between 0 and 1, representing the Safe For Work (SFW) and Not Safe For Work (NSFW) probabilities. Utilizing AI, NSFW Text Detection allows for efficient content moderation, ensuring a safe and professional environment across your platforms. | null | predict_predict_nsfw_post | 422 | null | {"detail": [{"loc": [], "msg": "", "type": ""}]} | {"title": "HTTPValidationError", "type": "object", "properties": {"detail": {"title": "Detail", "type": "array", "items": {"title": "ValidationError", "required": ["loc", "msg", "type"], "type": "object", "properties": {"loc": {"title": "Location", "type": "array", "items": {"anyOf": [{"type": "string"}, {"type": "integer"}]}}, "msg": {"title": "Message", "type": "string"}, "type": {"title": "Error Type", "type": "string"}}}}}} | |
308803f8-4878-4092-8bdc-c8839939c0ed/f535772c-8df1-446a-a47e-371da4b6d881/0/0 | Username Guardian | Integrate Samurai’s automation for username moderation with your product seamlessly. Our well-documented and customizable API simplifies scalability. Understand precisely why Samurai is making a decision through its nuanced categories and detailed output. | 8.8 | username | An API endpoint which returns a linguistic analysis of a given username with regard to toxicity. | 200 | Default Example | {"username": "jackass1", "result": {"toxic": 1, "details": {"en": {"exact": 1, "categories": ["offensive"]}}}} | {"type": "object", "properties": {"username": {"type": "string", "description": "Verified username"}, "result": {"type": "object", "description": "Classification result", "properties": {"toxic": {"type": "integer", "description": "Username toxicity"}, "details": {"type": "object", "description": "Detection details", "properties": {"en": {"type": "object", "description": "Detected language", "properties": {"exact": {"type": "integer", "description": "0 - offensive phrase is embedded into another phrase; 1 - offensive phrase is clearly distinguished in the username"}, "categories": {"type": "array", "description": "Detected categories", "items": {"type": "string"}}}}}}}}}} |
4c059248-d9bb-4270-921c-0cc285e157be/b193e04d-806d-4687-ac33-ead5b570445e/0/0 | Bad Words Profanity Filter | Automatically detect and filter offensive, inappropriate, or profane content within text data. With this API, you can seamlessly integrate profanity filtering capabilities into your applications, platforms, or services, enabling you to maintain a safe and respectful environment for your users. | 6.9 | Filter Bad Words | Filter Bad Words | 200 | Success | {"status": "ok", "error": null, "data": {"isProfane": true, "text": "I just has a **** good meal. Too bad the reviews being left were a bit **** considering how good it was", "trimmed": false}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"status": {"type": "string"}, "error": {"type": "null"}, "data": {"type": "object", "properties": {"isProfane": {"type": "boolean"}, "text": {"type": "string"}, "trimmed": {"type": "boolean"}}, "required": ["isProfane", "text", "trimmed"]}}, "required": ["data", "error", "status"]} |
4c059248-d9bb-4270-921c-0cc285e157be/38ee553e-93ff-423f-86d0-cb056452ccc5/0/0 | Bad Words Profanity Filter | Automatically detect and filter offensive, inappropriate, or profane content within text data. With this API, you can seamlessly integrate profanity filtering capabilities into your applications, platforms, or services, enabling you to maintain a safe and respectful environment for your users. | 6.9 | Detect Bad Words | Detect Bad Words | 200 | Success | {"status": "ok", "error": null, "data": {"isProfane": true, "words": ["damn", "crap"], "trimmed": false}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"status": {"type": "string"}, "error": {"type": "null"}, "data": {"type": "object", "properties": {"isProfane": {"type": "boolean"}, "words": {"type": "array", "items": {"type": "string"}}, "trimmed": {"type": "boolean"}}, "required": ["isProfane", "trimmed", "words"]}}, "required": ["data", "error", "status"]} |
96c190e5-cf9b-4b92-891b-3288b615db73/98f0ee7e-5bd8-496e-8f1c-03eda8b05e10/0/0 | GPT Summarization | Summarize text using an abstractive summarizer based on the GPT machine learning model. | 9 | summarize | Summarizes text.
Parameters:
text: Text to summarize (can be preprocessed)
OPTIONAL num_sentences: Rough number of sentences to return (default: 3)
Returns:
summary: Summarized text | 200 | Response | {"summary": "GPT-3 is part of a trend in natural language processing (NLP) systems of pre-trained language representations. It was created by OpenAI, a San Francisco-based artificial intelligence research laboratory. The quality of the text generated by the model is so high that it is difficult to distinguish from that written by a human."} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"summary": {"type": "string"}}, "required": ["summary"]} |
0403f20b-260c-42aa-b3be-9c3df46b72d4/92594c8c-ba93-404d-8922-666d06fbf099/0/0 | Address Parser - Advanced NLP | Parse unstructured address strings into address components, using advanced NLP methods. | 0.2 | Parse Address | Parses unstructured address string | 200 | Response | {"AddressNumber": "325", "CountryName": "USA", "PlaceName": "Salina", "StateName": "UT", "StreetName": "100", "StreetNamePostDirectional": "N", "StreetNamePreDirectional": "E", "ZipCode": "84654", "_AddressType": "Street Address"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"AddressNumber": {"type": "string"}, "CountryName": {"type": "string"}, "PlaceName": {"type": "string"}, "StateName": {"type": "string"}, "StreetName": {"type": "string"}, "StreetNamePostDirectional": {"type": "string"}, "StreetNamePreDirectional": {"type": "string"}, "ZipCode": {"type": "string"}, "_AddressType": {"type": "string"}}, "required": ["AddressNumber", "CountryName", "PlaceName", "StateName", "StreetName", "StreetNamePostDirectional", "StreetNamePreDirectional", "ZipCode", "_AddressType"]} |
6ed528f5-340c-49d2-8461-1e8504f645ea/10a21b2b-70a8-46d5-b91d-ad8dba98e521/0/0 | Rapid Translate Multi Traduction | We developed a NEW RAPID MULTI TRANSLATE API that allow you translate multi texts in one fast query, wish help you improve response time and your service quality. The Unlimited Multi Translate API makes advantage of Google's neural machine translation technology to translate html, text, words, phrases, and paragraphs in real time across more than +100 languages. Example: https://codepen.io/oussamasibari/pen/JjLLxxv | 9.8 | Rapid Translate Multi Traduction | Rapid Translate Multi Traduction | 200 | Bulk Translate Response Example | ["\u0623\u0647\u0644\u0627", "\u0645\u0627 \u0647\u0649", "<h1 style=\";text-align:right;direction:rtl\">\u0627\u062e\u062a\u0628\u0627\u0631</h1>", "\u062a\u0631\u062c\u0645\u0629 API", "\u062a\u0631\u062c\u0645\u0629 \u0633\u0631\u064a\u0639\u0629 \u0645\u062a\u0639\u062f\u062f\u0629 Traduction"] | {"type": "array", "items": {"type": "string"}} |
8688df91-0ba9-4fad-90a9-df1013023a98/57fcccb3-8e9a-4255-9a16-c10204d0e392/0/0 | Walnut Topic | AI powered topic extraction from texts. | 6.3 | wrt_transformer | Gets the text and set of possible topics separated by a comma.
Returns the ranking of topics from most relevant to least relevant. | 200 | Response | {"result": {"topic_relevance_1": "urgent", "topic_relevance_2": "billing", "topic_relevance_3": "eletronics", "topic_relevance_4": "design", "topic_relevance_5": "promotion", "topic_relevance_6": "books", "topic_relevance_7": "furniture"}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"result": {"type": "object", "properties": {"topic_relevance_1": {"type": "string"}, "topic_relevance_2": {"type": "string"}, "topic_relevance_3": {"type": "string"}, "topic_relevance_4": {"type": "string"}, "topic_relevance_5": {"type": "string"}, "topic_relevance_6": {"type": "string"}, "topic_relevance_7": {"type": "string"}}, "required": ["topic_relevance_1", "topic_relevance_2", "topic_relevance_3", "topic_relevance_4", "topic_relevance_5", "topic_relevance_6", "topic_relevance_7"]}}, "required": ["result"]} |
97e9b16a-911e-4c20-a9dc-13057ba620e6/59774976-cff9-4913-ba7f-d7c495cf6b3e/0/0 | Aspect Based Sentiment Analysis | Extract topics (also known as aspects or entities) from the input text and analyze the sentiment towards each of the topics. | null | Topic Sentiments | Extract topics (or aspects/entities) and get sentiments for each topic. | 200 | New Example | {"Response": [{"Aspect": "Device", "Sentiment": "Positive"}, {"Aspect": "Weight", "Sentiment": "Negative"}, {"Aspect": "Size", "Sentiment": "Neutral"}, {"Aspect": "Screen", "Sentiment": "Neutral"}]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"Response": {"type": "array", "items": {"type": "object", "properties": {"Aspect": {"type": "string"}, "Sentiment": {"type": "string"}}, "required": ["Aspect", "Sentiment"]}}}, "required": ["Response"]} |
3076178c-5cfc-4692-8c93-e5e3da3fd452/119d7409-ab05-4833-9a5e-d8e05900593c/0/0 | Ultra Fast Translation | We developed a Ultra Fast Translation API that allow you translate multi texts in one fast query, wish help you improve response time and your service quality. The Ultra Fast Translation API makes advantage of Google's neural machine translation technology to translate html, text, words, phrases, and paragraphs in real time across more than +100 languages. Example: https://codepen.io/oussamasibari/pen/JjLLxxv | 8.8 | Multi Line Super Fast | Multi Line Super Ultra Fast Translation | 200 | success | ["\u0623\u0647\u0644\u0627", "\u0645\u0627 \u0647\u0649", "<h1>\u0627\u062e\u062a\u0628\u0627\u0631</h1>", "\u062a\u0631\u062c\u0645\u0629 API", "\u062a\u0631\u062c\u0645\u0629 \u0633\u0631\u064a\u0639\u0629 \u0645\u062a\u0639\u062f\u062f\u0629 Traduction"] | {"$schema": "http://json-schema.org/schema#", "type": "array", "items": {"type": "string"}} |
91c07b0e-3527-46ff-9728-1a7dad1cc69f/endpoint_5e51817c-51a7-4dcb-8062-0360d860ddd5/0/0 | ADA NLP | Collection of NLP services that supports 6 languages. Named entity recognition (NER), tokenization and sentence dependencies. | null | entities | Show entities from the specified text. | 200 | New Example | {"entities": [{"start": 0, "end": 7, "type": "ORG", "text": "Samsung"}, {"start": 52, "end": 61, "type": "DATE", "text": "last year"}, {"start": 108, "end": 113, "type": "GPE", "text": "China"}, {"start": 115, "end": 120, "type": "GPE", "text": "India"}, {"start": 122, "end": 139, "type": "GPE", "text": "the United States"}, {"start": 144, "end": 150, "type": "GPE", "text": "Russia"}]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"entities": {"type": "array", "items": {"type": "object", "properties": {"start": {"type": "integer"}, "end": {"type": "integer"}, "type": {"type": "string"}, "text": {"type": "string"}}, "required": ["end", "start", "text", "type"]}}}, "required": ["entities"]} |
91c07b0e-3527-46ff-9728-1a7dad1cc69f/endpoint_e820bb26-956d-4e97-9752-ddc5cfa9071a/0/0 | ADA NLP | Collection of NLP services that supports 6 languages. Named entity recognition (NER), tokenization and sentence dependencies. | null | tokens | Show tokens from the specified text. | 200 | New Example | {"tokens": [{"start": 0, "end": 3, "index": 0, "text": "Las", "whitespace_after": true}, {"start": 4, "end": 9, "index": 1, "text": "Vegas", "whitespace_after": true}, {"start": 10, "end": 12, "index": 2, "text": "is", "whitespace_after": true}, {"start": 13, "end": 14, "index": 3, "text": "a", "whitespace_after": true}, {"start": 15, "end": 22, "index": 4, "text": "popular", "whitespace_after": true}, {"start": 23, "end": 34, "index": 5, "text": "destination", "whitespace_after": true}, {"start": 35, "end": 37, "index": 6, "text": "in", "whitespace_after": true}, {"start": 38, "end": 41, "index": 7, "text": "the", "whitespace_after": true}, {"start": 42, "end": 49, "index": 8, "text": "western", "whitespace_after": true}, {"start": 50, "end": 57, "index": 9, "text": "portion", "whitespace_after": true}, {"start": 58, "end": 60, "index": 10, "text": "of", "whitespace_after": true}, {"start": 61, "end": 64, "index": 11, "text": "the", "whitespace_after": true}, {"start": 65, "end": 71, "index": 12, "text": "United", "whitespace_after": true}, {"start": 72, "end": 78, "index": 13, "text": "States", "whitespace_after": false}, {"start": 78, "end": 79, "index": 14, "text": ".", "whitespace_after": true}, {"start": 80, "end": 83, "index": 15, "text": "The", "whitespace_after": true}, {"start": 84, "end": 88, "index": 16, "text": "town", "whitespace_after": true}, {"start": 89, "end": 91, "index": 17, "text": "is", "whitespace_after": true}, {"start": 92, "end": 96, "index": 18, "text": "most", "whitespace_after": true}, {"start": 97, "end": 104, "index": 19, "text": "popular", "whitespace_after": true}, {"start": 105, "end": 108, "index": 20, "text": "for", "whitespace_after": true}, {"start": 109, "end": 112, "index": 21, "text": "its", "whitespace_after": true}, {"start": 113, "end": 120, "index": 22, "text": "casinos", "whitespace_after": false}, {"start": 120, "end": 121, "index": 23, "text": ",", "whitespace_after": true}, {"start": 122, "end": 128, "index": 24, "text": "hotels", "whitespace_after": false}, {"start": 128, "end": 129, "index": 25, "text": ",", "whitespace_after": true}, {"start": 130, "end": 133, "index": 26, "text": "and", "whitespace_after": true}, {"start": 134, "end": 142, "index": 27, "text": "exciting", "whitespace_after": true}, {"start": 143, "end": 152, "index": 28, "text": "nightlife", "whitespace_after": false}, {"start": 152, "end": 153, "index": 29, "text": ".", "whitespace_after": false}]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"tokens": {"type": "array", "items": {"type": "object", "properties": {"start": {"type": "integer"}, "end": {"type": "integer"}, "index": {"type": "integer"}, "text": {"type": "string"}, "whitespace_after": {"type": "boolean"}}, "required": ["end", "index", "start", "text", "whitespace_after"]}}}, "required": ["tokens"]} |
91c07b0e-3527-46ff-9728-1a7dad1cc69f/endpoint_330ea863-5c4d-49a5-a0a1-15a638b9d336/0/0 | ADA NLP | Collection of NLP services that supports 6 languages. Named entity recognition (NER), tokenization and sentence dependencies. | null | sentence-dependencies | Show sentences and words from the specified text. | 200 | New Example | {"sentences": [{"text": "Christina visited Miami during her winter vacation.", "index": 0, "words": [{"text": "Christina", "whitespace_after": true, "word_type": "PROPN", "index": 0, "start": 0, "end": 9}, {"text": "visited", "whitespace_after": true, "word_type": "VERB", "index": 1, "start": 10, "end": 17}, {"text": "Miami", "whitespace_after": true, "word_type": "PROPN", "index": 2, "start": 18, "end": 23}, {"text": "during", "whitespace_after": true, "word_type": "ADP", "index": 3, "start": 24, "end": 30}, {"text": "her", "whitespace_after": true, "word_type": "PRON", "index": 4, "start": 31, "end": 34}, {"text": "winter", "whitespace_after": true, "word_type": "NOUN", "index": 5, "start": 35, "end": 41}, {"text": "vacation", "whitespace_after": false, "word_type": "NOUN", "index": 6, "start": 42, "end": 50}, {"text": ".", "whitespace_after": true, "word_type": "PUNCT", "index": 7, "start": 50, "end": 51}]}, {"text": "She is from Boston, where it is cold during the winter months.", "index": 1, "words": [{"text": "She", "whitespace_after": true, "word_type": "PRON", "index": 8, "start": 52, "end": 55}, {"text": "is", "whitespace_after": true, "word_type": "AUX", "index": 9, "start": 56, "end": 58}, {"text": "from", "whitespace_after": true, "word_type": "ADP", "index": 10, "start": 59, "end": 63}, {"text": "Boston", "whitespace_after": false, "word_type": "PROPN", "index": 11, "start": 64, "end": 70}, {"text": ",", "whitespace_after": true, "word_type": "PUNCT", "index": 12, "start": 70, "end": 71}, {"text": "where", "whitespace_after": true, "word_type": "ADV", "index": 13, "start": 72, "end": 77}, {"text": "it", "whitespace_after": true, "word_type": "PRON", "index": 14, "start": 78, "end": 80}, {"text": "is", "whitespace_after": true, "word_type": "VERB", "index": 15, "start": 81, "end": 83}, {"text": "cold", "whitespace_after": true, "word_type": "ADJ", "index": 16, "start": 84, "end": 88}, {"text": "during", "whitespace_after": true, "word_type": "ADP", "index": 17, "start": 89, "end": 95}, {"text": "the", "whitespace_after": true, "word_type": "DET", "index": 18, "start": 96, "end": 99}, {"text": "winter", "whitespace_after": true, "word_type": "NOUN", "index": 19, "start": 100, "end": 106}, {"text": "months", "whitespace_after": false, "word_type": "NOUN", "index": 20, "start": 107, "end": 113}, {"text": ".", "whitespace_after": true, "word_type": "PUNCT", "index": 21, "start": 113, "end": 114}]}, {"text": "Miami, however, has a very warm climate.", "index": 2, "words": [{"text": "Miami", "whitespace_after": false, "word_type": "PROPN", "index": 22, "start": 115, "end": 120}, {"text": ",", "whitespace_after": true, "word_type": "PUNCT", "index": 23, "start": 120, "end": 121}, {"text": "however", "whitespace_after": false, "word_type": "ADV", "index": 24, "start": 122, "end": 129}, {"text": ",", "whitespace_after": true, "word_type": "PUNCT", "index": 25, "start": 129, "end": 130}, {"text": "has", "whitespace_after": true, "word_type": "VERB", "index": 26, "start": 131, "end": 134}, {"text": "a", "whitespace_after": true, "word_type": "DET", "index": 27, "start": 135, "end": 136}, {"text": "very", "whitespace_after": true, "word_type": "ADV", "index": 28, "start": 137, "end": 141}, {"text": "warm", "whitespace_after": true, "word_type": "ADJ", "index": 29, "start": 142, "end": 146}, {"text": "climate", "whitespace_after": false, "word_type": "NOUN", "index": 30, "start": 147, "end": 154}, {"text": ".", "whitespace_after": true, "word_type": "PUNCT", "index": 31, "start": 154, "end": 155}]}, {"text": "There are many sunny days in Miami, and people can go to the beach all year long.", "index": 3, "words": [{"text": "There", "whitespace_after": true, "word_type": "PRON", "index": 32, "start": 156, "end": 161}, {"text": "are", "whitespace_after": true, "word_type": "AUX", "index": 33, "start": 162, "end": 165}, {"text": "many", "whitespace_after": true, "word_type": "ADJ", "index": 34, "start": 166, "end": 170}, {"text": "sunny", "whitespace_after": true, "word_type": "ADJ", "index": 35, "start": 171, "end": 176}, {"text": "days", "whitespace_after": true, "word_type": "NOUN", "index": 36, "start": 177, "end": 181}, {"text": "in", "whitespace_after": true, "word_type": "ADP", "index": 37, "start": 182, "end": 184}, {"text": "Miami", "whitespace_after": false, "word_type": "PROPN", "index": 38, "start": 185, "end": 190}, {"text": ",", "whitespace_after": true, "word_type": "PUNCT", "index": 39, "start": 190, "end": 191}, {"text": "and", "whitespace_after": true, "word_type": "CCONJ", "index": 40, "start": 192, "end": 195}, {"text": "people", "whitespace_after": true, "word_type": "NOUN", "index": 41, "start": 196, "end": 202}, {"text": "can", "whitespace_after": true, "word_type": "AUX", "index": 42, "start": 203, "end": 206}, {"text": "go", "whitespace_after": true, "word_type": "VERB", "index": 43, "start": 207, "end": 209}, {"text": "to", "whitespace_after": true, "word_type": "ADP", "index": 44, "start": 210, "end": 212}, {"text": "the", "whitespace_after": true, "word_type": "DET", "index": 45, "start": 213, "end": 216}, {"text": "beach", "whitespace_after": true, "word_type": "NOUN", "index": 46, "start": 217, "end": 222}, {"text": "all", "whitespace_after": true, "word_type": "DET", "index": 47, "start": 223, "end": 226}, {"text": "year", "whitespace_after": true, "word_type": "NOUN", "index": 48, "start": 227, "end": 231}, {"text": "long", "whitespace_after": false, "word_type": "ADV", "index": 49, "start": 232, "end": 236}, {"text": ".", "whitespace_after": true, "word_type": "PUNCT", "index": 50, "start": 236, "end": 237}]}, {"text": "Christina spent a good portion of her trip on the beach to relax and sunbathe.", "index": 4, "words": [{"text": "Christina", "whitespace_after": true, "word_type": "PROPN", "index": 51, "start": 238, "end": 247}, {"text": "spent", "whitespace_after": true, "word_type": "VERB", "index": 52, "start": 248, "end": 253}, {"text": "a", "whitespace_after": true, "word_type": "DET", "index": 53, "start": 254, "end": 255}, {"text": "good", "whitespace_after": true, "word_type": "ADJ", "index": 54, "start": 256, "end": 260}, {"text": "portion", "whitespace_after": true, "word_type": "NOUN", "index": 55, "start": 261, "end": 268}, {"text": "of", "whitespace_after": true, "word_type": "ADP", "index": 56, "start": 269, "end": 271}, {"text": "her", "whitespace_after": true, "word_type": "PRON", "index": 57, "start": 272, "end": 275}, {"text": "trip", "whitespace_after": true, "word_type": "NOUN", "index": 58, "start": 276, "end": 280}, {"text": "on", "whitespace_after": true, "word_type": "ADP", "index": 59, "start": 281, "end": 283}, {"text": "the", "whitespace_after": true, "word_type": "DET", "index": 60, "start": 284, "end": 287}, {"text": "beach", "whitespace_after": true, "word_type": "NOUN", "index": 61, "start": 288, "end": 293}, {"text": "to", "whitespace_after": true, "word_type": "PART", "index": 62, "start": 294, "end": 296}, {"text": "relax", "whitespace_after": true, "word_type": "VERB", "index": 63, "start": 297, "end": 302}, {"text": "and", "whitespace_after": true, "word_type": "CCONJ", "index": 64, "start": 303, "end": 306}, {"text": "sunbathe", "whitespace_after": false, "word_type": "VERB", "index": 65, "start": 307, "end": 315}, {"text": ".", "whitespace_after": true, "word_type": "PUNCT", "index": 66, "start": 315, "end": 316}]}, {"text": "However, she also explored Miami and its surroundings.", "index": 5, "words": [{"text": "However", "whitespace_after": false, "word_type": "ADV", "index": 67, "start": 317, "end": 324}, {"text": ",", "whitespace_after": true, "word_type": "PUNCT", "index": 68, "start": 324, "end": 325}, {"text": "she", "whitespace_after": true, "word_type": "PRON", "index": 69, "start": 326, "end": 329}, {"text": "also", "whitespace_after": true, "word_type": "ADV", "index": 70, "start": 330, "end": 334}, {"text": "explored", "whitespace_after": true, "word_type": "VERB", "index": 71, "start": 335, "end": 343}, {"text": "Miami", "whitespace_after": true, "word_type": "PROPN", "index": 72, "start": 344, "end": 349}, {"text": "and", "whitespace_after": true, "word_type": "CCONJ", "index": 73, "start": 350, "end": 353}, {"text": "its", "whitespace_after": true, "word_type": "PRON", "index": 74, "start": 354, "end": 357}, {"text": "surroundings", "whitespace_after": false, "word_type": "NOUN", "index": 75, "start": 358, "end": 370}, {"text": ".", "whitespace_after": false, "word_type": "PUNCT", "index": 76, "start": 370, "end": 371}]}]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"sentences": {"type": "array", "items": {"type": "object", "properties": {"text": {"type": "string"}, "index": {"type": "integer"}, "words": {"type": "array", "items": {"type": "object", "properties": {"text": {"type": "string"}, "whitespace_after": {"type": "boolean"}, "word_type": {"type": "string"}, "index": {"type": "integer"}, "start": {"type": "integer"}, "end": {"type": "integer"}}, "required": ["end", "index", "start", "text", "whitespace_after", "word_type"]}}}, "required": ["index", "text", "words"]}}}, "required": ["sentences"]} |
9a805d8e-2737-4514-afb4-7b47004def8e/3646040d-4669-44bb-8595-45e7c2cd4241/0/0 | French NLU | Lettria's French NLU. | null | Extract NLU | Retrieve Natural Language Understanding results (NLU) within your text. Get semantic insights about your sentence or document. | 200 | Extract NLU Standard Return | [[{"dep": "root", "lemma": "etre", "lexicon": [], "meaning": [{"derivates": null, "extra": null, "intensity": 1, "sub": "action_be", "super": "ACTION"}], "nlp": [{"lemmatizer": [{"confidence": 0.99, "conjugate": [{"mode": "indicative", "pronom": 3, "temps": "present"}], "infinit": "etre"}], "source": "est", "tag": "V"}], "ref": -1, "source": "est", "tag": "V"}, {"dep": "obj", "lemma": "voiture", "lexicon": [], "meaning": [{"derivates": null, "extra": null, "intensity": 1, "sub": "car", "super": "VEHICLE"}, {"derivates": null, "extra": null, "intensity": 1, "sub": "vehicule", "super": "VEHICLE"}], "nlp": [{"lemmatizer": {"confidence": 0.99, "gender": {"female": true, "plural": false}}, "source": "voiture", "tag": "N"}], "ref": 1, "source": "voiture", "tag": "N"}, {"dep": "amod", "lemma": "vert", "lexicon": [], "meaning": [{"derivates": null, "extra": null, "intensity": 0, "sub": "Color", "super": null}], "nlp": [{"lemmatizer": {"confidence": 0.99, "gender": {"female": true, "plural": false}}, "source": "verte", "tag": "JJ"}], "ref": 3, "source": "verte", "tag": "JJ"}, {"dep": "acl:relcl", "lemma": "casser", "lexicon": [], "meaning": [{"derivates": null, "extra": null, "intensity": 1, "sub": "action_break", "super": "ACTION"}, {"derivates": null, "extra": null, "intensity": 1, "sub": "action_damage", "super": "ACTION"}], "nlp": [{"auxiliary": "avoir", "lemmatizer": {"confidence": 0.99, "conjugate": [{"mode": "indicative", "pronom": 3, "temps": "past"}], "gender": {"female": false, "plural": false}, "infinit": "casser", "source": "casse"}, "source": "a casse", "tag": "V"}], "ref": 3, "source": "a casse", "tag": "V"}, {"dep": "obj", "lemma": "voiture", "lexicon": [], "meaning": [{"derivates": null, "extra": null, "intensity": 1, "sub": "car", "super": "VEHICLE"}, {"derivates": null, "extra": null, "intensity": 1, "sub": "vehicule", "super": "VEHICLE"}], "nlp": [{"lemmatizer": {"confidence": 0.99, "gender": {"female": true, "plural": false}}, "source": "voiture", "tag": "N"}], "ref": 6, "source": "voiture", "tag": "N"}], [{"dep": "nsubj", "lemma": "chien", "lexicon": [], "meaning": [{"derivates": null, "extra": null, "intensity": 1, "sub": "dog", "super": "ANIMAL"}], "nlp": [{"lemmatizer": {"confidence": 0.99, "gender": {"female": false, "plural": true}}, "source": "chiens", "tag": "N"}], "ref": 2, "source": "chiens", "tag": "N"}, {"dep": "root", "lemma": "etre", "lexicon": [], "meaning": [{"derivates": null, "extra": null, "intensity": 1, "sub": "action_be", "super": "ACTION"}], "nlp": [{"lemmatizer": [{"confidence": 0.99, "conjugate": [{"mode": "indicative", "pronom": 6, "temps": "present"}], "infinit": "etre"}], "source": "sont", "tag": "V"}], "ref": -1, "source": "sont", "tag": "V"}]] | {"$schema": "http://json-schema.org/schema#", "type": "array", "items": {"type": "array", "items": {"type": "object", "properties": {"dep": {"type": "string"}, "lemma": {"type": "string"}, "lexicon": {"type": "array"}, "meaning": {"type": "array", "items": {"type": "object", "properties": {"derivates": {"type": "null"}, "extra": {"type": "null"}, "intensity": {"type": "integer"}, "sub": {"type": "string"}, "super": {"type": ["null", "string"]}}, "required": ["derivates", "extra", "intensity", "sub", "super"]}}, "nlp": {"type": "array", "items": {"type": "object", "properties": {"lemmatizer": {"anyOf": [{"type": "array", "items": {"type": "object", "properties": {"confidence": {"type": "number"}, "conjugate": {"type": "array", "items": {"type": "object", "properties": {"mode": {"type": "string"}, "pronom": {"type": "integer"}, "temps": {"type": "string"}}, "required": ["mode", "pronom", "temps"]}}, "infinit": {"type": "string"}}, "required": ["confidence", "conjugate", "infinit"]}}, {"type": "object", "properties": {"confidence": {"type": "number"}, "gender": {"type": "object", "properties": {"female": {"type": "boolean"}, "plural": {"type": "boolean"}}, "required": ["female", "plural"]}, "conjugate": {"type": "array", "items": {"type": "object", "properties": {"mode": {"type": "string"}, "pronom": {"type": "integer"}, "temps": {"type": "string"}}, "required": ["mode", "pronom", "temps"]}}, "infinit": {"type": "string"}, "source": {"type": "string"}}, "required": ["confidence", "gender"]}]}, "source": {"type": "string"}, "tag": {"type": "string"}, "auxiliary": {"type": "string"}}, "required": ["lemmatizer", "source", "tag"]}}, "ref": {"type": "integer"}, "source": {"type": "string"}, "tag": {"type": "string"}}, "required": ["dep", "lemma", "lexicon", "meaning", "nlp", "ref", "source", "tag"]}}} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/4f278d36-c361-412c-9442-a055c742d64a/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Analyze | The Analyze query is an extension of the Simple Search. It analyzes the search string and brings out all the search keywords separately for a more refined result of your query in a simple search. | 200 | New Example | [{"start": 0, "end": 15, "entity": "Project Manager", "type": "JobTitle", "weight": 36.84}, {"start": 72, "end": 77, "entity": "Wipro", "type": "Organization", "weight": 15.79}, {"start": 48, "end": 54, "entity": "B.tech", "type": "Degree", "weight": 15.79}, {"start": 98, "end": 102, "entity": "Java", "type": "Skill", "weight": 7.89}, {"start": 107, "end": 110, "entity": "Php", "type": "Skill", "weight": 7.89}, {"start": 60, "end": 64, "entity": "Pune", "type": "City", "weight": 5.26}, {"start": 20, "end": 29, "entity": " 15 Year ", "type": "ExperienceLevel", "weight": 10.53}] | {"$schema": "http://json-schema.org/schema#", "type": "array", "items": {"type": "object", "properties": {"start": {"type": "integer"}, "end": {"type": "integer"}, "entity": {"type": "string"}, "type": {"type": "string"}, "weight": {"type": "number"}}, "required": ["end", "entity", "start", "type", "weight"]}} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/79f3f5ed-6cc0-4fe1-869c-41b376988ada/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Index Count | This API is used to returns the number of documents indexed for an Index key. | 200 | New Example | {"totalCount": 2, "count": {"Jd": 1, "Resume": 1}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"totalCount": {"type": "integer"}, "count": {"type": "object", "properties": {"Jd": {"type": "integer"}, "Resume": {"type": "integer"}}, "required": ["Jd", "Resume"]}}, "required": ["count", "totalCount"]} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/35fd2d1d-b04b-49ed-b11c-92eb3518f883/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Boolean Search | In the boolean search you can customize your search by specifying search parameters like - Job Profile, Company, Degree, etc.
Boolean Search gives more flexibility in searching by specifying required/optional search parameters. You can search values for multiple fields with multiple values. Multiple values are searched based on the OR conditions. Multiple Fields are searched in the required conditions on the basis of AND condition while in the optional condition it is search with OR condition. | 200 | New Example | {"count": 241, "pageStart": 0, "pageSize": 25, "records": [{"score": 100, "CurrentEmployer": "NUCSOFT Ltd", "TotalExperienceInYear": 1.7, "CurrentJobProfile": "SOFTWARE ENGINEER", "State": "Maharashtra", "FullName": "Abhishek Vijay Borkar", "Country": "India", "id": "1912010352261226", "City": "Mumbai"}, {"score": 75, "CurrentEmployer": "ModeFinServer Pvt. Ltd", "TotalExperienceInYear": 5.6, "CurrentJobProfile": "Software Engineer", "FullName": "TULASI VARA PRASAD CHENNAMSETTI", "id": "1911281017271127"}, {"score": 75, "CurrentEmployer": "Tech Mahindra", "TotalExperienceInYear": 5.7, "CurrentJobProfile": "Software Engineer", "FullName": "SNEHA KEMBHAVI", "id": "1911281020291129"}, {"score": 75, "CurrentEmployer": "Tata Consultancy Services TCS", "TotalExperienceInYear": 4.4, "CurrentJobProfile": "Software Engineer", "State": "CA", "FullName": "ANKUSH GUMBER", "Country": "USA", "id": "1911281025121112", "City": "Los Angeles"}, {"score": 75, "CurrentEmployer": "Persistent Systems Limited", "TotalExperienceInYear": 3.11, "CurrentJobProfile": "Software Engineer", "FullName": "Mala Shanbhag", "id": "1911281030281128"}, {"score": 75, "CurrentEmployer": "Sankhya InfoTech Ltd", "TotalExperienceInYear": 5.1, "CurrentJobProfile": "Software Engineer", "FullName": "Gummadi Durga Prasad", "id": "1911281053221122"}, {"score": 75, "CurrentEmployer": "NetApp", "TotalExperienceInYear": 5.7, "CurrentJobProfile": "Software Engineer", "State": "NC", "FullName": "Amit Borulkar", "Country": "USA", "id": "1911281109531153", "City": "Morrisville"}, {"score": 75, "CurrentEmployer": "CricbuzzBackend Bangalore", "TotalExperienceInYear": 5.8, "CurrentJobProfile": "Software Engineer", "State": "Karnataka", "FullName": "AkshayJha", "Country": "India", "id": "1911281136421142", "City": "Bangalore"}, {"score": 75, "CurrentEmployer": "PeopleStrong", "TotalExperienceInYear": 7.4, "CurrentJobProfile": "Software Engineer", "FullName": "Raghvendra Mishra", "id": "191128115000110", "City": "Allahabad"}, {"score": 75, "CurrentEmployer": "Y3 Technologies", "CurrentJobProfile": "Software Engineer", "FullName": "Ixwaku Ranjan Sharma", "id": "191128115205115", "City": "Kanpur"}, {"score": 75, "CurrentEmployer": "Orange Business Services", "TotalExperienceInYear": 8.3, "CurrentJobProfile": "Software Engineer", "State": "Rajasthan", "FullName": "HEMANT SAIN", "Country": "India", "id": "191128122206116", "City": "Alwar"}, {"score": 75, "CurrentEmployer": "Tech Mahindra", "TotalExperienceInYear": 2.1, "CurrentJobProfile": "Software Engineer", "State": "CA", "FullName": "ANUSHA BILAKANTI", "Country": "USA", "id": "1911281235561156", "City": "Los Angeles"}, {"score": 75, "CurrentEmployer": "Rediff.com", "TotalExperienceInYear": 5, "CurrentJobProfile": "Software Engineer", "FullName": "Akshay Hazari", "id": "191128125000110"}, {"score": 75, "CurrentEmployer": "Intern@HPE Security", "TotalExperienceInYear": 3.1, "CurrentJobProfile": "Software Engineer", "State": "AZ", "FullName": "YOGESH PANDEY", "Country": "USA", "id": "191128010301111", "City": "Tempe"}, {"score": 75, "CurrentEmployer": "HSBC Software Development", "TotalExperienceInYear": 2.1, "CurrentJobProfile": "SOFTWARE ENGINEER", "State": "Arizona", "FullName": "AAAMIR SSHAIKH", "Country": "USA", "id": "1911280110581158", "City": "Tempe"}, {"score": 75, "CurrentEmployer": "Cerner Corporation", "TotalExperienceInYear": 7.5, "CurrentJobProfile": "Software Engineer", "State": "KS", "FullName": "Santosh Desani", "Country": "U.S.", "id": "1911280116291129", "City": "Overland Park"}, {"score": 75, "CurrentEmployer": "Yashitechnologies", "TotalExperienceInYear": 4.7, "CurrentJobProfile": "Software Engineer", "FullName": "KUSUMA DEVI NAIDU", "id": "1911280222341134"}, {"score": 75, "CurrentEmployer": "Atos Origin Ltd", "TotalExperienceInYear": 15.2, "CurrentJobProfile": "Software Engineer", "State": "Maharashtra", "FullName": "Aashish Sinha", "Country": "India", "id": "1911280234101110", "City": "Mumbai"}, {"score": 75, "CurrentEmployer": "SAP LABS INDIA", "TotalExperienceInYear": 5.5, "CurrentJobProfile": "Software Engineer", "State": "Karnataka", "FullName": "MOHAMMED ASHRAF", "Country": "India", "id": "1911280239331133", "City": "Bangalore"}, {"score": 75, "CurrentEmployer": "The Ladders Inc", "TotalExperienceInYear": 10.9, "CurrentJobProfile": "Software Engineer", "FullName": "ANITHA SUBRAMANIAN", "id": "1911280244301130"}, {"score": 75, "CurrentEmployer": "TESCO Bengaluru", "TotalExperienceInYear": 1.2, "CurrentJobProfile": "Software Engineer", "State": "Karnataka", "FullName": "Dhananjay R B", "Country": "India", "id": "1911280254151115", "City": "Bangalore"}, {"score": 75, "CurrentEmployer": "HCL", "TotalExperienceInYear": 6.6, "CurrentJobProfile": "Software engineer", "FullName": "CHANTI K", "id": "1911280257191119"}, {"score": 75, "CurrentEmployer": "Liftoff LLC", "TotalExperienceInYear": 5.9, "CurrentJobProfile": "Software Engineer", "FullName": "HARSHA SAGAR K M", "id": "1911280607191119"}, {"score": 75, "CurrentEmployer": "PayU Payments Private Ltd", "TotalExperienceInYear": 6.6, "CurrentJobProfile": "Software Engineer", "FullName": "Ankit Rustagi", "id": "1911280657161116", "City": "Ghaziabad"}, {"score": 75, "CurrentEmployer": "FUSION INFORMATICS TECHNOLOGY PVT LTD", "TotalExperienceInYear": 10.7, "CurrentJobProfile": "SOFTWARE ENGINEER", "State": "Gujarat", "FullName": "Majidkhan Imtiyazkhan Pathan", "Country": "India", "id": "1911280725501150", "City": "Ahmedabad"}]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"count": {"type": "integer"}, "pageStart": {"type": "integer"}, "pageSize": {"type": "integer"}, "records": {"type": "array", "items": {"type": "object", "properties": {"score": {"type": "integer"}, "CurrentEmployer": {"type": "string"}, "TotalExperienceInYear": {"type": "number"}, "CurrentJobProfile": {"type": "string"}, "State": {"type": "string"}, "FullName": {"type": "string"}, "Country": {"type": "string"}, "id": {"type": "string"}, "City": {"type": "string"}}, "required": ["CurrentEmployer", "CurrentJobProfile", "FullName", "id", "score"]}}}, "required": ["count", "pageSize", "pageStart", "records"]} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/7b909a67-d754-4f87-957a-b1c75759ed30/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Match with ID | This API find Resumes/Job descriptions matching your input documents ID's.
There are four types of matching cases as follows:
Resume to Resume: Get resumes from the index which matches the input resume.
Resume to JD: Get Job Descriptions from the index which matches the input resume.
JD to JD: Get Job Descriptions from the index which matches the input Job Descriptions.
JD To Resume: Get resumes from the index which matches with input Job Descriptions.
| 200 | New Example | {"count": 580, "pageStart": 0, "pageSize": 10, "records": [{"score": 100, "CurrentEmployer": "Henry Ford Hospital", "TotalExperienceInYear": 11.6, "CurrentJobProfile": "Cardiologist", "State": "IL", "FullName": "John Deo", "Country": "USA", "id": "unique subuser id1", "City": "Chicago"}]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"count": {"type": "integer"}, "pageStart": {"type": "integer"}, "pageSize": {"type": "integer"}, "records": {"type": "array", "items": {"type": "object", "properties": {"score": {"type": "integer"}, "CurrentEmployer": {"type": "string"}, "TotalExperienceInYear": {"type": "number"}, "CurrentJobProfile": {"type": "string"}, "State": {"type": "string"}, "FullName": {"type": "string"}, "Country": {"type": "string"}, "id": {"type": "string"}, "City": {"type": "string"}}, "required": ["City", "Country", "CurrentEmployer", "CurrentJobProfile", "FullName", "State", "TotalExperienceInYear", "id", "score"]}}}, "required": ["count", "pageSize", "pageStart", "records"]} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/4785d776-902c-47d0-b414-9a85197bab29/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Parse and Index | To search resume's and JD's using RChilli Search and Match API, you require to parse the resume/JD and index them. The indexing provides operations for managing the indexes. This includes adding and updating the index as well as removing from it and rebuilding it. | 200 | New Example | {"status": "200", "indexType": "Resume", "subUserId": "unique subuser id", "action": "indexed", "id": "", "doc": ""} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"status": {"type": "string"}, "indexType": {"type": "string"}, "subUserId": {"type": "string"}, "action": {"type": "string"}, "id": {"type": "string"}, "doc": {"type": "string"}}, "required": ["action", "doc", "id", "indexType", "status", "subUserId"]} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/9efe331f-e359-466b-bb43-d672ddac348c/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Spell Checking | If you give any wrong input while searching, this API will check and correct it. | 200 | New Example | [{"SearchWord": "projct manager", "Suggestions": ["project manager", "product manager"]}] | {"$schema": "http://json-schema.org/schema#", "type": "array", "items": {"type": "object", "properties": {"SearchWord": {"type": "string"}, "Suggestions": {"type": "array", "items": {"type": "string"}}}, "required": ["SearchWord", "Suggestions"]}} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/4d84af61-09cb-42eb-9e25-af1c717d64ab/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Simple Search | The Simple Search API method empowers you to make your document searchable with a string query without specifying search parameters. In Simple Search API call, you get candidates - Score (out of 100), FullName, CurrentJobProfile, CurrentEmployer, TotalExperienceInYear, City, State, Country, id (Index). | 200 | New Example | {"count": 21, "pageStart": 0, "pageSize": 10, "records": [{"score": 74.73, "CurrentEmployer": "IGATE Computer System", "TotalExperienceInYear": 16.1, "CurrentJobProfile": "Tech Lead Hardware", "State": "Maharashtra", "FullName": "SATISH GHARIYA", "Country": "India", "id": "Resume_0001111200122045338138", "City": "Pune"}, {"score": 69.74, "CurrentEmployer": "HSBC plc", "TotalExperienceInYear": 13.1, "CurrentJobProfile": "Software Consultant", "State": "Maharashtra", "FullName": "Nilay Singh", "Country": "India", "id": "0001111200212103015215", "City": "Pune"}, {"score": 69.74, "CurrentEmployer": "HSBC plc", "TotalExperienceInYear": 13.1, "CurrentJobProfile": "Software Consultant", "State": "Maharashtra", "FullName": "Nilay Singh", "Country": "India", "id": "0001111200212123428228", "City": "Pune"}, {"score": 69.74, "CurrentEmployer": "HSBC plc", "TotalExperienceInYear": 13.1, "CurrentJobProfile": "Software Consultant", "State": "Maharashtra", "FullName": "Nilay Singh", "Country": "India", "id": "0001111200212031534234", "City": "Pune"}, {"score": 69.74, "CurrentEmployer": "HSBC plc", "TotalExperienceInYear": 13.1, "CurrentJobProfile": "Software Consultant", "State": "Maharashtra", "FullName": "Nilay Singh", "Country": "India", "id": "0001111200212031417217", "City": "Pune"}, {"score": 69.74, "CurrentEmployer": "HSBC plc", "TotalExperienceInYear": 13.1, "CurrentJobProfile": "Software Consultant", "State": "Maharashtra", "FullName": "Nilay Singh", "Country": "India", "id": "000111120021306280929", "City": "Pune"}, {"score": 69.74, "CurrentEmployer": "HSBC plc", "TotalExperienceInYear": 13.1, "CurrentJobProfile": "Software Consultant", "State": "Maharashtra", "FullName": "Nilay Singh", "Country": "India", "id": "0001111200210115354254", "City": "Pune"}, {"score": 69.74, "CurrentEmployer": "HSBC plc", "TotalExperienceInYear": 13.1, "CurrentJobProfile": "Software Consultant", "State": "Maharashtra", "FullName": "Nilay Singh", "Country": "India", "id": "0001111200212103339239", "City": "Pune"}, {"score": 69.74, "CurrentEmployer": "HSBC plc", "TotalExperienceInYear": 13.1, "CurrentJobProfile": "Software Consultant", "State": "Maharashtra", "FullName": "Nilay Singh", "Country": "India", "id": "0001111200212123546246", "City": "Pune"}, {"score": 69.74, "CurrentEmployer": "HSBC plc", "TotalExperienceInYear": 13.1, "CurrentJobProfile": "Software Consultant", "State": "Maharashtra", "FullName": "Nilay Singh", "Country": "India", "id": "0001111200214112610210", "City": "Pune"}], "facet": {"Skill": [{"value": "C#.net", "count": 12}, {"value": "Ide", "count": 12}, {"value": "Operating Systems", "count": 12}, {"value": "Ado.net", "count": 11}, {"value": "C++", "count": 11}, {"value": "Database Management", "count": 11}, {"value": "Hp-ux", "count": 11}, {"value": "Mercury Quality Control", "count": 11}, {"value": "Universe", "count": 11}, {"value": "Visio", "count": 11}], "CurrentEmployer": [{"value": "Hsbc Plc", "count": 11}, {"value": "Axa Business Services", "count": 1}, {"value": "Capgemini India Pvt Ltd", "count": 1}, {"value": "Citibank N.a", "count": 1}, {"value": "Experience In Om Sai Decoplast Pvt Ltd Manufacturing Company", "count": 1}, {"value": "First Insight Software Solutions Pvt Ltd", "count": 1}, {"value": "Hcl Designation : Group Operations Manager, Band E4", "count": 1}, {"value": "Igate Computer System", "count": 1}, {"value": "Real Place", "count": 1}, {"value": "Speakwell Enterprises Pvt Ltd", "count": 1}], "CurrentJobProfile": [{"value": "Software Consultant", "count": 11}, {"value": "An Accounts Executive", "count": 1}, {"value": "Home Loan Counselor", "count": 1}, {"value": "Office Assitant", "count": 1}, {"value": "Operations Officer", "count": 1}, {"value": "Project Manager It", "count": 1}, {"value": "Regional Sales Manager, Commercial Banking Acquisitions", "count": 1}, {"value": "Software Engineer (l2", "count": 1}, {"value": "Specialist", "count": 1}, {"value": "Tech Lead Hardware", "count": 1}]}, "explainScore": [{"id": "000111120021306280929", "explaination": {"score": 69.74, "maxScore": 100, "Search": {"score": 19.74, "maxScore": 50, "detailScore": [{"score": 14.74, "maxScore": 18.42, "entity": "JobProfile", "value": "software developer"}, {"score": 0, "maxScore": 7.89, "entity": "Employer", "value": "Wipro"}, {"score": 0, "maxScore": 7.89, "entity": "Degree", "value": "B.tech"}, {"score": 0, "maxScore": 5.26, "entity": "TotalExperienceInYear", "value": "[15 TO *]"}, {"score": 0, "maxScore": 3.95, "entity": "Skill", "value": "Java"}, {"score": 0, "maxScore": 3.95, "entity": "Skill", "value": "Php"}, {"score": 2.63, "maxScore": 2.63, "entity": "City", "value": "pune"}, {"score": 2.37, "maxScore": 2.63, "entity": "EmployerCity", "value": "pune"}]}, "geoSearh": {"score": 50, "maxScore": 50, "detailScore": "50.0= sum of:\n 50.0 = Location=Pune,Maharashtra,India, Geocode=73.8500,18.5300 Radius=30.0"}}}, {"id": "Resume_0001111200122045338138", "explaination": {"score": 74.73, "maxScore": 100, "Search": {"score": 24.73, "maxScore": 50, "detailScore": [{"score": 0, "maxScore": 18.42, "entity": "JobProfile", "value": "Software Developer"}, {"score": 6.32, "maxScore": 7.89, "entity": "Degree", "value": "btech, ([Degree:bachelor of techology]) btec, ([Degree:bachelor of engineering]) b.e, ([Degree:bachelor of technology]) b.tech])"}, {"score": 7.89, "maxScore": 7.89, "entity": "HighestDegree", "value": "btech, ([HighestDegree:bachelor of techology]) btec, ([HighestDegree:bachelor of engineering]) b.e, ([HighestDegree:bachelor of technology]) b.tech])"}, {"score": 0, "maxScore": 7.89, "entity": "Employer", "value": "Wipro"}, {"score": 5.26, "maxScore": 5.26, "entity": "TotalExperienceInYear", "value": "[15.0 TO Infinity]"}, {"score": 0, "maxScore": 3.95, "entity": "Skill", 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"maxScore": 50, "detailScore": "50.0= sum of:\n 50.0 = Location=Pune,Maharashtra,India, Geocode=73.8500,18.5300 Radius=30.0"}}}, {"id": "0001111200214112610210", "explaination": {"score": 69.74, "maxScore": 100, "Search": {"score": 19.74, "maxScore": 50, "detailScore": [{"score": 14.74, "maxScore": 18.42, "entity": "JobProfile", "value": "software developer"}, {"score": 0, "maxScore": 7.89, "entity": "Employer", "value": "Wipro"}, {"score": 0, "maxScore": 7.89, "entity": "Degree", "value": "B.tech"}, {"score": 0, "maxScore": 5.26, "entity": "TotalExperienceInYear", "value": "[15 TO *]"}, {"score": 0, "maxScore": 3.95, "entity": "Skill", "value": "Java"}, {"score": 0, "maxScore": 3.95, "entity": "Skill", "value": "Php"}, {"score": 2.63, "maxScore": 2.63, "entity": "City", "value": "pune"}, {"score": 2.37, "maxScore": 2.63, "entity": "EmployerCity", "value": "pune"}]}, "geoSearh": {"score": 50, "maxScore": 50, "detailScore": "50.0= sum of:\n 50.0 = Location=Pune,Maharashtra,India, 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{"score": 69.74, "maxScore": 100, "Search": {"score": 19.74, "maxScore": 50, "detailScore": [{"score": 14.74, "maxScore": 18.42, "entity": "JobProfile", "value": "software developer"}, {"score": 0, "maxScore": 7.89, "entity": "Employer", "value": "Wipro"}, {"score": 0, "maxScore": 7.89, "entity": "Degree", "value": "B.tech"}, {"score": 0, "maxScore": 5.26, "entity": "TotalExperienceInYear", "value": "[15 TO *]"}, {"score": 0, "maxScore": 3.95, "entity": "Skill", "value": "Java"}, {"score": 0, "maxScore": 3.95, "entity": "Skill", "value": "Php"}, {"score": 2.63, "maxScore": 2.63, "entity": "City", "value": "pune"}, {"score": 2.37, "maxScore": 2.63, "entity": "EmployerCity", "value": "pune"}]}, "geoSearh": {"score": 50, "maxScore": 50, "detailScore": "50.0= sum of:\n 50.0 = Location=Pune,Maharashtra,India, Geocode=73.8500,18.5300 Radius=30.0"}}}, {"id": "0001111200212031534234", "explaination": {"score": 69.74, "maxScore": 100, "Search": {"score": 19.74, "maxScore": 50, "detailScore": 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"records"]} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/962d3539-4299-4e13-934c-3201ab1fac86/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Suggestions | This API is used to returns the suggestions for different search fields like JobProfile, Skill, and Degree. | 200 | New Example | [{"Suggestions": ["Soft Support Specialist", "Softball Instructor", "Software Account Manager", "Software Administrator", "Software Analyst", "Software Analyst/computer Support", "Software And Electrical Engineer", "Software And Network Engineer", "Software And Web Developer Trainee", "Software Application Developer", "Software Application Tester", "Software Applications Developer", "Software Architect", "Software Architect/business Analyst", "Software Architect Consultant", "Software Architect & Developer", "Software Architect/lead Developer", "Software Architect, Owner", "Software Architect/senior Software Engineer", "Software Architect, Technical Lead", "Software Architecture", "Software Associate Manager", "Software Applications Specialist Ii/developer"]}] | {"$schema": "http://json-schema.org/schema#", "type": "array", "items": {"type": "object", "properties": {"Suggestions": {"type": "array", "items": {"type": "string"}}}, "required": ["Suggestions"]}} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/4beeffdc-e8ec-4c0f-a9cb-1f071a46e734/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Delete All Documents | This API is used to delete all indexed files from the database. | 200 | New Example | {"status": "200", "indexType": "Resume", "output": "indexes deleted successfully"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"status": {"type": "string"}, "indexType": {"type": "string"}, "output": {"type": "string"}}, "required": ["indexType", "output", "status"]} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/a189c9c2-e1d1-4814-9d0a-142387ffdd9e/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Delete | This API is used to delete indexed files, from the database, by providing document ID. | 200 | New Example | {"status": "200", "indexType": "Resume", "output": "indexes deleted successfully"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"status": {"type": "string"}, "indexType": {"type": "string"}, "output": {"type": "string"}}, "required": ["indexType", "output", "status"]} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/b33210c8-4554-411d-a0c1-5911632c3b77/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Get Document Detail | This API is used to get a particular indexed document detail by providing document ID. | 200 | New Example | {"document": {"id": "DocumentId", "ResumeLanguage": "English", "ResumeCountry": "Pakistan", "FullName": "Hafiz M Saleem", "FirstName": "Hafiz", "MiddleName": "M", "LastName": "Saleem", "Category": "Information", "SubCategory": "Software Developers and Programmers", "CurrentJobProfile": "Senior Software Engineer", "CurrentEmployer": "Datasmith", "TotalExperienceInMonths": 163, "TotalExperienceInYear": 13.7, "TotalExperienceRange": "GREATER THAN 10 YEAR", "City": "Rawalpindi", "State": "Punjab", "Country": "Pakistan", "Institute": ["Muhammad Ali Jinnah University", "Comsats Institute of Information Technology", "H. I.T Dgree College", "H. M.C Boys High School"], "Degrees": ["Master", "Bachelor", "Higher Secondary school Certificate", "High School-Matriculation", "Master of Science"], "Skill": ["Microsoft Dynamics GP", "Customization", "Developing", "Progressive", "SQL Server", "Asp.net", "PHP"]}} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"document": {"type": "object", "properties": {"id": {"type": "string"}, "ResumeLanguage": {"type": "string"}, "ResumeCountry": {"type": "string"}, "FullName": {"type": "string"}, "FirstName": {"type": "string"}, "MiddleName": {"type": "string"}, "LastName": {"type": "string"}, "Category": {"type": "string"}, "SubCategory": {"type": "string"}, "CurrentJobProfile": {"type": "string"}, "CurrentEmployer": {"type": "string"}, "TotalExperienceInMonths": {"type": "integer"}, "TotalExperienceInYear": {"type": "number"}, "TotalExperienceRange": {"type": "string"}, "City": {"type": "string"}, "State": {"type": "string"}, "Country": {"type": "string"}, "Institute": {"type": "array", "items": {"type": "string"}}, "Degrees": {"type": "array", "items": {"type": "string"}}, "Skill": {"type": "array", "items": {"type": "string"}}}, "required": ["Category", "City", "Country", "CurrentEmployer", "CurrentJobProfile", "Degrees", "FirstName", "FullName", "Institute", "LastName", "MiddleName", "ResumeCountry", "ResumeLanguage", "Skill", "State", "SubCategory", "TotalExperienceInMonths", "TotalExperienceInYear", "TotalExperienceRange", "id"]}}, "required": ["document"]} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/989b492a-be92-477e-908b-4c0b8bdb6e4f/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Get Document Ids | This API is used to get all the indexed document ID's. | 200 | New Example | {"count": 12, "pageStart": 0, "pageSize": 10, "records": [{"id": "Document Id 1"}, {"id": "Document Id 2"}, {"id": "Document Id 3"}, {"id": "Document Id 4"}, {"id": "Document Id 5"}]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"count": {"type": "integer"}, "pageStart": {"type": "integer"}, "pageSize": {"type": "integer"}, "records": {"type": "array", "items": {"type": "object", "properties": {"id": {"type": "string"}}, "required": ["id"]}}}, "required": ["count", "pageSize", "pageStart", "records"]} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/8ee87b47-e14e-4a68-b23b-f455de128d6e/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | One To One Match | This API matches the candidate CV with the JD. The API responds the detailed matching score once the candidate CV matches with the JD. | 200 | New Example | {"ResumeJSON": "Resume Parsed Data in JSON Form", "JDJSON": "JD Parsed Data in JSON Form", "explainScore": [{"explaination": {"score": 54.93348, "maxScore": 100, "Match": {"score": 54.933481, "maxScore": 100, "detailScore": [{"score": 0, "maxScore": 50, "entity": "JobProfileTitle", "value": "Sr. Business Relations Manager"}, {"score": 0, "maxScore": 10.71, "entity": "QualificationsPreferred", "value": "Bachelors degree"}, {"score": 0, "maxScore": 10.71, "entity": "QualificationsPreferred", "value": "Bachelors degree in business administration"}, {"score": 0, "maxScore": 3.97, "entity": "RequiredSkillSet", "value": "Marketing"}, {"score": 0, "maxScore": 3.97, "entity": "RequiredSkillSet", "value": "Advertising"}, {"score": 0, "maxScore": 3.97, "entity": "RequiredSkillSet", "value": "Communication Skills"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Sales And Commercial"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Selling And Trading"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Sales"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Marketing And Communications"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Marketing"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Administration/Assistance"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Administration And Secretary Services"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Mechanical Engineering"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Civil Engineering"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "ICT"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Engineering"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Planning"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Tactics"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Implementation and Development"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Public Relations"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Packaging"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Distribution"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Marketing Materials"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Vendors"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Promote"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Communication"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Information Flow"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Development"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Product Promotion"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Presentations"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Business Plans"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Communications"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Business Communications"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Business Administration"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Marketing Communications"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Operating Systems"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Problem Management"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Interpersonal Skills"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Upper Management"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Ability to work independently"}]}}}]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"ResumeJSON": {"type": "string"}, "JDJSON": {"type": "string"}, "explainScore": {"type": "array", "items": {"type": "object", "properties": {"explaination": {"type": "object", "properties": {"score": {"type": "number"}, "maxScore": {"type": "integer"}, "Match": {"type": "object", "properties": {"score": {"type": "number"}, "maxScore": {"type": "integer"}, "detailScore": {"type": "array", "items": {"type": "object", "properties": {"score": {"type": "integer"}, "maxScore": {"type": "number"}, "entity": {"type": "string"}, "value": {"type": "string"}}, "required": ["entity", "maxScore", "score", "value"]}}}, "required": ["detailScore", "maxScore", "score"]}}, "required": ["Match", "maxScore", "score"]}}, "required": ["explaination"]}}}, "required": ["JDJSON", "ResumeJSON", "explainScore"]} |
6a032f02-205b-4383-a9c2-6b2a69cd6f99/4b6a395c-3694-46aa-8362-4ccb16e40926/0/0 | RChilli Search and Match | RChilli Search & Match API allows you to search and match candidates and jobs with great relevancy and accuracy than simple database searching and matching algorithms. | null | Match | This API find Resumes/Job Descriptions matching your input documents.
There are four types of matching cases as follows:
Resume to Resume: Get resumes from the index which matches the input resume.
Resume to JD: Get Job Descriptions from the index which matches the input resume.
JD to JD: Get Job Descriptions from the index which matches the input Job Descriptions.
JD To Resume: Get resumes from the index which matches with input Job Descriptions. | 200 | New Example | {"count": 580, "pageStart": 0, "pageSize": 10, "records": [{"score": 100, "CurrentEmployer": "Henry Ford Hospital", "TotalExperienceInYear": 11.6, "CurrentJobProfile": "Cardiologist", "State": "IL", "FullName": "John Deo", "Country": "USA", "id": "unique subuser id", "City": "Chicago"}, {"score": 100, "CurrentEmployer": "Henry Ford Hospital", "TotalExperienceInYear": 11.6, "CurrentJobProfile": "Cardiologist", "State": "IL", "FullName": "John Deo", "Country": "USA", "id": "unique subuser id", "City": "Chicago"}, {"score": 22.09, "CurrentEmployer": "ILLINOIS STATE UNIVERSITY", "TotalExperienceInYear": 47.6, "CurrentJobProfile": "MOTORCYCLE SAFETY PROGRAM INSTRUCTOR", "State": "IL", "FullName": "BRUCE M. GRZEGORZEWSKI", "Country": "USA", "id": "unique subuser id", "City": "Chillicothe"}, {"score": 20.88, "CurrentEmployer": "Navarro Discount Pharmacies", "TotalExperienceInYear": 22.1, "CurrentJobProfile": "Director of Pharmacy Systems", "State": "Florida", "FullName": "Meghann Chilcott", "Country": "USA", "id": "unique subuser id", "City": "Sunrise"}, {"score": 20.59, "CurrentEmployer": "Caterpillar Inc", "TotalExperienceInYear": 18.1, "CurrentJobProfile": "Engineer", "State": "IL", "FullName": "YUXIANG GU", "Country": "USA", "id": "unique subuser id", "City": "DUNLAP"}, {"score": 18.9, "CurrentEmployer": "Hub Group", "TotalExperienceInYear": 12, "CurrentJobProfile": "Oracle Fusion HCM Consultant", "State": "IL", "FullName": "Karthik Chennuri", "Country": "USA", "id": "unique subuser id", "City": "Oak Brook"}, {"score": 18.66, "CurrentEmployer": "Navistar International Trucking", "TotalExperienceInYear": 26, "CurrentJobProfile": "Engineering Analyst", "State": "MI", "FullName": "CHANDRA RACHAKONDA", "Country": "USA", "id": "unique subuser id", "City": "Saline"}, {"score": 17.98, "CurrentEmployer": "DaimlerChrysler Corporation", "TotalExperienceInYear": 23.11, "CurrentJobProfile": "Program Management Analyst", "State": "MI", "FullName": "Beth L. Sommers", "Country": "USA", "id": "unique subuser id", "City": "Goodrich"}, {"score": 17.98, "TotalExperienceInYear": 18.5, "CurrentJobProfile": "Independent Consultant", "State": "IL", "FullName": "Richard F. Bailey", "Country": "USA", "id": "unique subuser id", "City": "Oak Park"}, {"score": 17.849998, "CurrentEmployer": "IBM", "TotalExperienceInYear": 14.1, "CurrentJobProfile": "Staff Software Engineer", "State": "CA", "FullName": "Paul Ellsworth", "Country": "USA", "id": "unique subuser id", "City": "Morgan Hill"}]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"count": {"type": "integer"}, "pageStart": {"type": "integer"}, "pageSize": {"type": "integer"}, "records": {"type": "array", "items": {"type": "object", "properties": {"score": {"type": "number"}, "CurrentEmployer": {"type": "string"}, "TotalExperienceInYear": {"type": "number"}, "CurrentJobProfile": {"type": "string"}, "State": {"type": "string"}, "FullName": {"type": "string"}, "Country": {"type": "string"}, "id": {"type": "string"}, "City": {"type": "string"}}, "required": ["City", "Country", "CurrentJobProfile", "FullName", "State", "TotalExperienceInYear", "id", "score"]}}}, "required": ["count", "pageSize", "pageStart", "records"]} |
6fbd1eab-9347-49cd-984f-3977755efd89/de41fffd-9c22-40c2-b6f1-373ada9c4ddb/0/0 | HTML to Gemtext or Markdown | Convert HTML to Markdown and then to Gemtext.
See https://rimu.geek.nz/a-html-to-gemtext-conversion-api/ for an overview of how to use it.
There is an endpoint to convert HTML straight to Gemtext without exposing the Markdown intermediate data or you can convert HTML -> Markdown and Markdown->Gemtext using more endpoints. | 7.9 | html2gmi | Convert the supplied HTML into Gemtext, via Markdown as an intermediate step.
Options to control the HTML to Markdown phase are set in "html2md_options" while the Markdown to Gemtext phase is controlled by "md2gmi_options". See these pages for more documentation:
https://pypi.org/project/markdownify/
https://pypi.org/project/md2gemini/ | 422 | Example_1 | {"detail": [{"loc": [], "msg": "", "type": ""}]} | {"title": "HTTPValidationError", "type": "object", "properties": {"detail": {"title": "Detail", "type": "array", "items": {"title": "ValidationError", "required": ["loc", "msg", "type"], "type": "object", "properties": {"loc": {"title": "Location", "type": "array", "items": {"anyOf": [{"type": "string"}, {"type": "integer"}]}}, "msg": {"title": "Message", "type": "string"}, "type": {"title": "Error Type", "type": "string"}}}}}} |
6fbd1eab-9347-49cd-984f-3977755efd89/262850c8-8977-41c8-ac56-76eafa26ccb7/0/0 | HTML to Gemtext or Markdown | Convert HTML to Markdown and then to Gemtext.
See https://rimu.geek.nz/a-html-to-gemtext-conversion-api/ for an overview of how to use it.
There is an endpoint to convert HTML straight to Gemtext without exposing the Markdown intermediate data or you can convert HTML -> Markdown and Markdown->Gemtext using more endpoints. | 7.9 | md2gmi | Convert Markdown to Gemtext. See https://pypi.org/project/md2gemini/ for options to control how the Gemtext is generated. | 422 | Example_1 | {"detail": [{"loc": [], "msg": "", "type": ""}]} | {"title": "HTTPValidationError", "type": "object", "properties": {"detail": {"title": "Detail", "type": "array", "items": {"title": "ValidationError", "required": ["loc", "msg", "type"], "type": "object", "properties": {"loc": {"title": "Location", "type": "array", "items": {"anyOf": [{"type": "string"}, {"type": "integer"}]}}, "msg": {"title": "Message", "type": "string"}, "type": {"title": "Error Type", "type": "string"}}}}}} |
6fbd1eab-9347-49cd-984f-3977755efd89/262850c8-8977-41c8-ac56-76eafa26ccb7/1/0 | HTML to Gemtext or Markdown | Convert HTML to Markdown and then to Gemtext.
See https://rimu.geek.nz/a-html-to-gemtext-conversion-api/ for an overview of how to use it.
There is an endpoint to convert HTML straight to Gemtext without exposing the Markdown intermediate data or you can convert HTML -> Markdown and Markdown->Gemtext using more endpoints. | 7.9 | md2gmi | Convert Markdown to Gemtext. See https://pypi.org/project/md2gemini/ for options to control how the Gemtext is generated. | 200 | Example_1 | {"result": "# test heading"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"result": {"type": "string"}}, "required": ["result"]} |
6fbd1eab-9347-49cd-984f-3977755efd89/dd243f2d-95e1-4c26-886b-bc25ab6bd4f7/0/0 | HTML to Gemtext or Markdown | Convert HTML to Markdown and then to Gemtext.
See https://rimu.geek.nz/a-html-to-gemtext-conversion-api/ for an overview of how to use it.
There is an endpoint to convert HTML straight to Gemtext without exposing the Markdown intermediate data or you can convert HTML -> Markdown and Markdown->Gemtext using more endpoints. | 7.9 | html2md | Put the HTML to be converted in 'html' and see https://pypi.org/project/markdownify/ for details about the meaning of the other options. | 422 | Example_1 | {"detail": [{"loc": [], "msg": "", "type": ""}]} | {"title": "HTTPValidationError", "type": "object", "properties": {"detail": {"title": "Detail", "type": "array", "items": {"title": "ValidationError", "required": ["loc", "msg", "type"], "type": "object", "properties": {"loc": {"title": "Location", "type": "array", "items": {"anyOf": [{"type": "string"}, {"type": "integer"}]}}, "msg": {"title": "Message", "type": "string"}, "type": {"title": "Error Type", "type": "string"}}}}}} |
6fbd1eab-9347-49cd-984f-3977755efd89/dd243f2d-95e1-4c26-886b-bc25ab6bd4f7/1/0 | HTML to Gemtext or Markdown | Convert HTML to Markdown and then to Gemtext.
See https://rimu.geek.nz/a-html-to-gemtext-conversion-api/ for an overview of how to use it.
There is an endpoint to convert HTML straight to Gemtext without exposing the Markdown intermediate data or you can convert HTML -> Markdown and Markdown->Gemtext using more endpoints. | 7.9 | html2md | Put the HTML to be converted in 'html' and see https://pypi.org/project/markdownify/ for details about the meaning of the other options. | 200 | Example_1 | {"result": "# markdown text"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"result": {"type": "string"}}, "required": ["result"]} |
ccee27dd-ccf4-4bda-a9fd-ff5c4bade253/7e485b06-2298-4aba-9adb-c36289722044/0/0 | Ultimate Word Paraphraser / Rephraser - Article Fiesta | Create perfect paraphrases for any text. High quality, and easily defeats AI detection checks when using technologies like GPT | null | Paraphrase | This is the endpoint you use to get your paraphrased data back.
Ultimately this can accept inputs or any length, however the longer you have as input the longer it will take to paraphrase. I would suggest breaking it down into sentences, but its up to you.
Results can be tweaked to provide multiple inline paraphrases, or you can opt for just a single one. | 200 | Single Variation | {"result": "This sentence is intended to be paraphrased. Compared to Article Fiesta's API, QuillBot's paraphrasing is terrible."} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"result": {"type": "string"}}, "required": ["result"]} |
ccee27dd-ccf4-4bda-a9fd-ff5c4bade253/7e485b06-2298-4aba-9adb-c36289722044/0/1 | Ultimate Word Paraphraser / Rephraser - Article Fiesta | Create perfect paraphrases for any text. High quality, and easily defeats AI detection checks when using technologies like GPT | null | Paraphrase | This is the endpoint you use to get your paraphrased data back.
Ultimately this can accept inputs or any length, however the longer you have as input the longer it will take to paraphrase. I would suggest breaking it down into sentences, but its up to you.
Results can be tweaked to provide multiple inline paraphrases, or you can opt for just a single one. | 200 | Multi Variation | {"result": [["This is a sentence to be paraphrased.", "This sentence should be paraphrased.", "This sentence must be paraphrased.", "This sentence is intended to be paraphrased.", "This is a sentence to be paralysed."], ["Compared to Article Fiesta's API, QuillBot's writing is terrible.", "Compared to Article Fiesta's API, QuillBot's paraphrasing is terrible.", "In comparison to Article Fiesta's API, QuillBot's writing is terrible.", "In comparison to Article Fiesta's API, QuillBot's paraphrasing is terrible.", "When compared to Article Fiesta's API, QuillBot's writing is terrible."]]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"result": {"type": "array", "items": {"type": "array", "items": {"type": "string"}}}}, "required": ["result"]} |
8b4e4b73-3efd-470f-8b9d-3174d71cf8ac/4b183529-4174-439e-86ea-e474716830bf/0/0 | RChilli OneToOne Match | This API matches the candidate CV with the JD. The API responds the detailed matching score once the candidate CV matches with the JD. | null | One To One Match API | This API matches the candidate CV with the JD. The API responds the detailed matching score once the candidate CV matches with the JD. | 200 | New Example | {"ResumeJSON": "Resume Parsed Data in JSON Form", "JDJSON": "JD Parsed Data in JSON Form", "explainScore": [{"explaination": {"score": 54.93348, "maxScore": 100, "Match": {"score": 54.933481, "maxScore": 100, "detailScore": [{"score": 0, "maxScore": 50, "entity": "JobProfileTitle", "value": "Sr. Business Relations Manager"}, {"score": 0, "maxScore": 10.71, "entity": "QualificationsPreferred", "value": "Bachelors degree"}, {"score": 0, "maxScore": 10.71, "entity": "QualificationsPreferred", "value": "Bachelors degree in business administration"}, {"score": 0, "maxScore": 3.97, "entity": "RequiredSkillSet", "value": "Marketing"}, {"score": 0, "maxScore": 3.97, "entity": "RequiredSkillSet", "value": "Advertising"}, {"score": 0, "maxScore": 3.97, "entity": "RequiredSkillSet", "value": "Communication Skills"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Sales And Commercial"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Selling And Trading"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Sales"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Marketing And Communications"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Marketing"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Administration/Assistance"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Administration And Secretary Services"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Mechanical Engineering"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Civil Engineering"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "ICT"}, {"score": 0, "maxScore": 0.65, "entity": "Domains", "value": "Engineering"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Planning"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Tactics"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Implementation and Development"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Public Relations"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Packaging"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Distribution"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Marketing Materials"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Vendors"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Promote"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Communication"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Information Flow"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Development"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Product Promotion"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Presentations"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Business Plans"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Communications"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Business Communications"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Business Administration"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Marketing Communications"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Operating Systems"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Problem Management"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Interpersonal Skills"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Upper Management"}, {"score": 0, "maxScore": 0.4, "entity": "PerferredSkillSet", "value": "Ability to work independently"}]}}}]} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"ResumeJSON": {"type": "string"}, "JDJSON": {"type": "string"}, "explainScore": {"type": "array", "items": {"type": "object", "properties": {"explaination": {"type": "object", "properties": {"score": {"type": "number"}, "maxScore": {"type": "integer"}, "Match": {"type": "object", "properties": {"score": {"type": "number"}, "maxScore": {"type": "integer"}, "detailScore": {"type": "array", "items": {"type": "object", "properties": {"score": {"type": "integer"}, "maxScore": {"type": "number"}, "entity": {"type": "string"}, "value": {"type": "string"}}, "required": ["entity", "maxScore", "score", "value"]}}}, "required": ["detailScore", "maxScore", "score"]}}, "required": ["Match", "maxScore", "score"]}}, "required": ["explaination"]}}}, "required": ["JDJSON", "ResumeJSON", "explainScore"]} |
55389e16e4b082eab6ddd7f3/5538d912e4b06a0d40e6a7f2/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Theme | Get the themes of a word. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "entry": "mask", "request": "mask", "response": "mask", "result_code": "200", "result_msg": "Success", "theme": ["cover", "search", "secret", "wear", "skirt", "boot", "skin", "image", "human"], "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "entry": {"type": "string"}, "request": {"type": "string"}, "response": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "theme": {"type": "array", "items": {"type": "string"}}, "version": {"type": "string"}}, "required": ["author", "email", "entry", "request", "response", "result_code", "result_msg", "theme", "version"]} |
55389e16e4b082eab6ddd7f3/5538d41ee4b030e59e4b20a6/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Association | Get the associations of a word. | 200 | Response | {"assoc_word": ["hide", "hat", "face"], "assoc_word_ex": ["hide", "hat", "face", "veil", "disguise", "camouflage"], "author": "twinword inc.", "email": "help@twinword.com", "entry": "mask", "request": "mask", "response": "mask", "result_code": "200", "result_msg": "Success", "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"assoc_word": {"type": "array", "items": {"type": "string"}}, "assoc_word_ex": {"type": "array", "items": {"type": "string"}}, "author": {"type": "string"}, "email": {"type": "string"}, "entry": {"type": "string"}, "request": {"type": "string"}, "response": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "version": {"type": "string"}}, "required": ["assoc_word", "assoc_word_ex", "author", "email", "entry", "request", "response", "result_code", "result_msg", "version"]} |
55389e16e4b082eab6ddd7f3/5538d695e4b011ca3af28110/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Difficulty | Get the difficulty level of a word. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "entry": "mask", "request": "mask", "response": "mask", "result_code": "200", "result_msg": "Success", "ten_degree": 3, "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "entry": {"type": "string"}, "request": {"type": "string"}, "response": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "ten_degree": {"type": "integer"}, "version": {"type": "string"}}, "required": ["author", "email", "entry", "request", "response", "result_code", "result_msg", "ten_degree", "version"]} |
55389e16e4b082eab6ddd7f3/5538d8b9e4b06a0d40e6a7ef/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Reference | Get the broad terms, narrow terms, related terms, evocations, synonyms, associations, and derived terms of a word. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "entry": "mask", "relation": {"associations": "", "broad_terms": "protective covering, protective cover, protection, party, mask, hiding, hide, disguise, covering, cover, concealment, concealing, conceal", "derived_terms": "death mask, 'Mask house', , a house for masquerades, sleep mask, unmask", "evocations": "disguise", "narrow_terms": "welder's mask, respirator, masquerade ball, masquerade, masked ball, mask, half mask, gasmask, gas helmet, fancy-dress ball, false face, face mask, eye mask, domino, dissimulate, dissemble, cloak, camouflage", "related_terms": "masquerade party, masquerade, masque, dissemble, disguise, cook, cloak, block out", "synonyms": ""}, "request": "mask", "response": "mask", "result_code": "200", "result_msg": "Success", "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "entry": {"type": "string"}, "relation": {"type": "object", "properties": {"associations": {"type": "string"}, "broad_terms": {"type": "string"}, "derived_terms": {"type": "string"}, "evocations": {"type": "string"}, "narrow_terms": {"type": "string"}, "related_terms": {"type": "string"}, "synonyms": {"type": "string"}}, "required": ["associations", "broad_terms", "derived_terms", "evocations", "narrow_terms", "related_terms", "synonyms"]}, "request": {"type": "string"}, "response": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "version": {"type": "string"}}, "required": ["author", "email", "entry", "relation", "request", "response", "result_code", "result_msg", "version"]} |
55389e16e4b082eab6ddd7f3/5538d82ae4b082eab6ddd8ca/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Example | See examples of a word used in a sentence | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "entry": "mask", "example": ["The red figure wears the same hat and mask in the background.", "The conformable mask is then stripped and a new conformable mask laid down.", "She was wearing a Kachina dancer's mask.", "The grandiosity is just a momentary mask.", "The mask is for protection and intimidation.", "The grating in the mask is adjusted.", "The mask of the male mummy is gilded.", "The mask covers the aperture of the telescope.", "Mask and wig celebrates the centennial of the clubhouse.", "The latter disguised his scarred visage with a steel mask."], "request": "mask", "response": "mask", "result_code": "200", "result_msg": "Success", "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "entry": {"type": "string"}, "example": {"type": "array", "items": {"type": "string"}}, "request": {"type": "string"}, "response": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "version": {"type": "string"}}, "required": ["author", "email", "entry", "example", "request", "response", "result_code", "result_msg", "version"]} |
55389e16e4b082eab6ddd7f3/5538d739e4b0bded76bb6d04/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Exam History | See which exams a word has been on | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "entry": "mask", "exam": ["toeic", "toefl", "ielts", "gre", "gmat"], "request": "mask", "response": "mask", "result_code": "200", "result_msg": "Success", "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "entry": {"type": "string"}, "exam": {"type": "array", "items": {"type": "string"}}, "request": {"type": "string"}, "response": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "version": {"type": "string"}}, "required": ["author", "email", "entry", "exam", "request", "response", "result_code", "result_msg", "version"]} |
55389e16e4b082eab6ddd7f3/568f1414e4b0926c52a3c075/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Recommend (post) | Recommend highly related categories for e-commerce and other uses. | 200 | Example_1 | {"author": "twinword inc.", "categories": ["Coffee Maker Water Filters", "Coffee Decanters", "Coffee Filters", "Coffee Maker & Espresso Machine Accessories", "Coffee Filter Baskets", "Coffee Decanter Warmers", "Frothing Pitchers", "Stovetop Espresso Pot Parts", "Coffee", "Coffee Pods"], "categories_scored": {"Coffee": 1, "Coffee Decanter Warmers": 1, "Coffee Decanters": 1, "Coffee Filter Baskets": 1, "Coffee Filters": 1, "Coffee Maker & Espresso Machine Accessories": 1, "Coffee Maker Water Filters": 1, "Coffee Pods": 1, "Frothing Pitchers": 1, "Stovetop Espresso Pot Parts": 1}, "email": "feedback@twinword.com", "keywords": ["maker", "coffee"], "keywords_scored": {"coffee": 1, "maker": 1}, "result_code": "200", "result_msg": "Success", "taxonomy_set": "product_categories", "version": "6.0.0"} | {"properties": {"author": {"type": "string"}, "categories": {"items": {"type": "string"}, "type": "array"}, "categories_scored": {"properties": {"Coffee": {"type": "integer"}, "Coffee Decanter Warmers": {"type": "integer"}, "Coffee Decanters": {"type": "integer"}, "Coffee Filter Baskets": {"type": "integer"}, "Coffee Filters": {"type": "integer"}, "Coffee Maker & Espresso Machine Accessories": {"type": "integer"}, "Coffee Maker Water Filters": {"type": "integer"}, "Coffee Pods": {"type": "integer"}, "Frothing Pitchers": {"type": "integer"}, "Stovetop Espresso Pot Parts": {"type": "integer"}}, "type": "object"}, "email": {"format": "email", "type": "string"}, "keywords": {"items": {"type": "string"}, "type": "array"}, "keywords_scored": {"properties": {"coffee": {"type": "integer"}, "maker": {"type": "integer"}}, "type": "object"}, "result_code": {"format": "color", "type": "string"}, "result_msg": {"type": "string"}, "taxonomy_set": {"type": "string"}, "version": {"type": "string"}}, "type": "object"} |
55389e16e4b082eab6ddd7f3/5538c83de4b0365a2139b831/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Extract (post) | Return the root of a word or roots of a string of words. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "lemma": {"frog": 1, "hop": 1, "rock": 2}, "result_code": "200", "result_msg": "Success", "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "lemma": {"type": "object", "properties": {"frog": {"type": "integer"}, "hop": {"type": "integer"}, "rock": {"type": "integer"}}, "required": ["frog", "hop", "rock"]}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "version": {"type": "string"}}, "required": ["author", "email", "lemma", "result_code", "result_msg", "version"]} |
55389e16e4b082eab6ddd7f3/5538bdf4e4b06a0d40e6a7a4/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Classify (post) | Classify text into product categories or contact us to customize and use your own category sets. Enter some text to find its related product categories: | 200 | Response | {"author": "twinword inc.", "categories": ["Kneeling Chairs", "Bean Bag Chairs", "Arm Chairs", "Slipper Chairs", "Rocking Chairs", "Office Chairs", "Gaming Chairs", "Arm Chairs, Recliners & Sleeper Chairs", "Sleeper Chairs", "Folding Chairs & Stools"], "categories_scored": {"Arm Chairs": 1, "Arm Chairs, Recliners & Sleeper Chairs": 1, "Bean Bag Chairs": 1, "Folding Chairs & Stools": 1, "Gaming Chairs": 1, "Kneeling Chairs": 1, "Office Chairs": 1, "Rocking Chairs": 1, "Sleeper Chairs": 1, "Slipper Chairs": 1}, "email": "help@twinword.com", "keywords": ["chair", "comfort", "protect", "feature", "hot", "level", "cool", "flow", "air", "hour"], "keywords_scored": {"air": 1, "chair": 2, "comfort": 2, "cool": 1, "feature": 1, "flow": 1, "hot": 1, "hour": 1, "level": 1, "protect": 1}, "result_code": "200", "result_msg": "Success", "taxonomy_set": "product_categories", "version": "6.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "categories": {"type": "array", "items": {"type": "string"}}, "categories_scored": {"type": "object", "properties": {"Arm Chairs": {"type": "integer"}, "Arm Chairs, Recliners & Sleeper Chairs": {"type": "integer"}, "Bean Bag Chairs": {"type": "integer"}, "Folding Chairs & Stools": {"type": "integer"}, "Gaming Chairs": {"type": "integer"}, "Kneeling Chairs": {"type": "integer"}, "Office Chairs": {"type": "integer"}, "Rocking Chairs": {"type": "integer"}, "Sleeper Chairs": {"type": "integer"}, "Slipper Chairs": {"type": "integer"}}, "required": ["Arm Chairs", "Arm Chairs, Recliners & Sleeper Chairs", "Bean Bag Chairs", "Folding Chairs & Stools", "Gaming Chairs", "Kneeling Chairs", "Office Chairs", "Rocking Chairs", "Sleeper Chairs", "Slipper Chairs"]}, "email": {"type": "string"}, "keywords": {"type": "array", "items": {"type": "string"}}, "keywords_scored": {"type": "object", "properties": {"air": {"type": "integer"}, "chair": {"type": "integer"}, "comfort": {"type": "integer"}, "cool": {"type": "integer"}, "feature": {"type": "integer"}, "flow": {"type": "integer"}, "hot": {"type": "integer"}, "hour": {"type": "integer"}, "level": {"type": "integer"}, "protect": {"type": "integer"}}, "required": ["air", "chair", "comfort", "cool", "feature", "flow", "hot", "hour", "level", "protect"]}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "taxonomy_set": {"type": "string"}, "version": {"type": "string"}}, "required": ["author", "categories", "categories_scored", "email", "keywords", "keywords_scored", "result_code", "result_msg", "taxonomy_set", "version"]} |
55389e16e4b082eab6ddd7f3/5538b933e4b030e59e4b2058/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Analyze (get) | Return sentiment analysis results with score for the given text. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "keywords": [{"score": 0.797954407, "word": "great"}, {"score": 0.289701948, "word": "price"}, {"score": 0.263316882, "word": "value"}, {"score": 0.152059727, "word": "range"}], "ratio": 1, "result_code": "200", "result_msg": "Success", "score": 0.375758241, "type": "positive", "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "keywords": {"type": "array", "items": {"type": "object", "properties": {"score": {"type": "number"}, "word": {"type": "string"}}, "required": ["score", "word"]}}, "ratio": {"type": "integer"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "score": {"type": "number"}, "type": {"type": "string"}, "version": {"type": "string"}}, "required": ["author", "email", "keywords", "ratio", "result_code", "result_msg", "score", "type", "version"]} |
55389e16e4b082eab6ddd7f3/5538b863e4b06a0d40e6a791/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Analyze (post) | Return sentiment analysis results with score for the given text. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "keywords": [{"score": 0.797954407, "word": "great"}, {"score": 0.289701948, "word": "price"}, {"score": 0.263316882, "word": "value"}, {"score": 0.152059727, "word": "range"}], "ratio": 1, "result_code": "200", "result_msg": "Success", "score": 0.375758241, "type": "positive", "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "keywords": {"type": "array", "items": {"type": "object", "properties": {"score": {"type": "number"}, "word": {"type": "string"}}, "required": ["score", "word"]}}, "ratio": {"type": "integer"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "score": {"type": "number"}, "type": {"type": "string"}, "version": {"type": "string"}}, "required": ["author", "email", "keywords", "ratio", "result_code", "result_msg", "score", "type", "version"]} |
55389e16e4b082eab6ddd7f3/5538be3ee4b0d628aaae306e/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Classify (get) | Classify text into product categories or contact us to customize and use your own category sets. Enter some text to find its related product categories: | 200 | Response | {"author": "twinword inc.", "categories": ["Kneeling Chairs", "Bean Bag Chairs", "Arm Chairs", "Slipper Chairs", "Rocking Chairs", "Office Chairs", "Gaming Chairs", "Arm Chairs, Recliners & Sleeper Chairs", "Sleeper Chairs", "Folding Chairs & Stools"], "categories_scored": {"Arm Chairs": 1, "Arm Chairs, Recliners & Sleeper Chairs": 1, "Bean Bag Chairs": 1, "Folding Chairs & Stools": 1, "Gaming Chairs": 1, "Kneeling Chairs": 1, "Office Chairs": 1, "Rocking Chairs": 1, "Sleeper Chairs": 1, "Slipper Chairs": 1}, "email": "help@twinword.com", "keywords": ["chair", "comfort", "protect", "feature", "hot", "level", "cool", "flow", "air", "hour"], "keywords_scored": {"air": 1, "chair": 2, "comfort": 2, "cool": 1, "feature": 1, "flow": 1, "hot": 1, "hour": 1, "level": 1, "protect": 1}, "result_code": "200", "result_msg": "Success", "taxonomy_set": "product_categories", "version": "6.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "categories": {"type": "array", "items": {"type": "string"}}, "categories_scored": {"type": "object", "properties": {"Arm Chairs": {"type": "integer"}, "Arm Chairs, Recliners & Sleeper Chairs": {"type": "integer"}, "Bean Bag Chairs": {"type": "integer"}, "Folding Chairs & Stools": {"type": "integer"}, "Gaming Chairs": {"type": "integer"}, "Kneeling Chairs": {"type": "integer"}, "Office Chairs": {"type": "integer"}, "Rocking Chairs": {"type": "integer"}, "Sleeper Chairs": {"type": "integer"}, "Slipper Chairs": {"type": "integer"}}, "required": ["Arm Chairs", "Arm Chairs, Recliners & Sleeper Chairs", "Bean Bag Chairs", "Folding Chairs & Stools", "Gaming Chairs", "Kneeling Chairs", "Office Chairs", "Rocking Chairs", "Sleeper Chairs", "Slipper Chairs"]}, "email": {"type": "string"}, "keywords": {"type": "array", "items": {"type": "string"}}, "keywords_scored": {"type": "object", "properties": {"air": {"type": "integer"}, "chair": {"type": "integer"}, "comfort": {"type": "integer"}, "cool": {"type": "integer"}, "feature": {"type": "integer"}, "flow": {"type": "integer"}, "hot": {"type": "integer"}, "hour": {"type": "integer"}, "level": {"type": "integer"}, "protect": {"type": "integer"}}, "required": ["air", "chair", "comfort", "cool", "feature", "flow", "hot", "hour", "level", "protect"]}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "taxonomy_set": {"type": "string"}, "version": {"type": "string"}}, "required": ["author", "categories", "categories_scored", "email", "keywords", "keywords_scored", "result_code", "result_msg", "taxonomy_set", "version"]} |
55389e16e4b082eab6ddd7f3/5538d479e4b03a4c998bbe94/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Definition | Get the definitions of a word. | 200 | Example_1 | {"entry": "mask", "ipa": "m\u0251\u02d0sk", "meaning": {"adjective": "", "adverb": "", "noun": "(nou) a covering to disguise or conceal the face\n(nou) activity that tries to conceal something\n(nou) a party of guests wearing costumes and masks\n(nou) a protective covering worn over the face", "verb": "(vrb) hide under a false appearance\n(vrb) put a mask on or cover with a mask\n(vrb) make unrecognizable\n(vrb) cover with a sauce\n(vrb) shield from light"}, "result_code": "200", "result_msg": "Success"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"entry": {"type": "string"}, "ipa": {"type": "string"}, "meaning": {"type": "object", "properties": {"adjective": {"type": "string"}, "adverb": {"type": "string"}, "noun": {"type": "string"}, "verb": {"type": "string"}}, "required": ["adjective", "adverb", "noun", "verb"]}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}}, "required": ["entry", "ipa", "meaning", "result_code", "result_msg"]} |
55389e16e4b082eab6ddd7f3/5538c87ce4b030e59e4b2080/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Extract (get) | Return the root of a word or roots of a string of words. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "lemma": {"frog": 1, "hop": 1, "rock": 2}, "result_code": "200", "result_msg": "Success", "version": "4.0.0"} | {"author": "twinword inc.", "email": "feedback@twinword.com", "lemma": {"frog": 1, "hop": 1, "rock": 2}, "result_code": "200", "result_msg": "Success", "version": "4.0.0"} |
55389e16e4b082eab6ddd7f3/5538bd68e4b030e59e4b2064/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Generate (get) | Detect and generate human like topics to the given text. | 200 | Example_1 | {"author": "twinword inc.", "email": "feedback@twinword.com", "keyword": {"alternate": 1, "biological": 1, "cell": 1, "compute": 2, "computer": 4, "gene": 1, "information": 2, "science": 2, "structure": 2, "study": 2}, "result_code": "200", "result_msg": "Success", "topic": {"art": 0.20782122905028, "computer science": 0.5010800744879, "development": 0.18472998137803, "human": 0.23091247672253, "machine": 0.23091247672253, "number": 0.18472998137803, "study": 0.30018621973929, "system": 0.23091247672253, "technology": 0.18472998137803}, "version": "5.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "keyword": {"type": "object", "properties": {"alternate": {"type": "integer"}, "biological": {"type": "integer"}, "cell": {"type": "integer"}, "compute": {"type": "integer"}, "computer": {"type": "integer"}, "gene": {"type": "integer"}, "information": {"type": "integer"}, "science": {"type": "integer"}, "structure": {"type": "integer"}, "study": {"type": "integer"}}, "required": ["alternate", "biological", "cell", "compute", "computer", "gene", "information", "science", "structure", "study"]}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "topic": {"type": "object", "properties": {"art": {"type": "number"}, "computer science": {"type": "number"}, "development": {"type": "number"}, "human": {"type": "number"}, "machine": {"type": "number"}, "number": {"type": "number"}, "study": {"type": "number"}, "system": {"type": "number"}, "technology": {"type": "number"}}, "required": ["art", "computer science", "development", "human", "machine", "number", "study", "system", "technology"]}, "version": {"type": "string"}}, "required": ["author", "email", "keyword", "result_code", "result_msg", "topic", "version"]} |
55389e16e4b082eab6ddd7f3/568f1362e4b059e645dc6fa1/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Recommend (get) | Recommend highly related categories for e-commerce and other uses. | 200 | Response | {"author": "twinword inc.", "categories": ["Coffee Maker Water Filters", "Coffee Decanters", "Coffee Filters", "Coffee Filter Baskets", "Coffee Decanter Warmers", "Frothing Pitchers", "Coffee Maker & Espresso Machine Accessories", "Stovetop Espresso Pot Parts", "Coffee", "Bottled Coffee Drinks"], "categories_scored": {"Bottled Coffee Drinks": 1, "Coffee": 1, "Coffee Decanter Warmers": 1, "Coffee Decanters": 1, "Coffee Filter Baskets": 1, "Coffee Filters": 1, "Coffee Maker & Espresso Machine Accessories": 1, "Coffee Maker Water Filters": 1, "Frothing Pitchers": 1, "Stovetop Espresso Pot Parts": 1}, "email": "help@twinword.com", "keywords": ["coffee", "maker"], "keywords_scored": {"coffee": 1, "maker": 1}, "result_code": "200", "result_msg": "Success", "taxonomy_set": "product_categories", "version": "6.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "categories": {"type": "array", "items": {"type": "string"}}, "categories_scored": {"type": "object", "properties": {"Bottled Coffee Drinks": {"type": "integer"}, "Coffee": {"type": "integer"}, "Coffee Decanter Warmers": {"type": "integer"}, "Coffee Decanters": {"type": "integer"}, "Coffee Filter Baskets": {"type": "integer"}, "Coffee Filters": {"type": "integer"}, "Coffee Maker & Espresso Machine Accessories": {"type": "integer"}, "Coffee Maker Water Filters": {"type": "integer"}, "Frothing Pitchers": {"type": "integer"}, "Stovetop Espresso Pot Parts": {"type": "integer"}}, "required": ["Bottled Coffee Drinks", "Coffee", "Coffee Decanter Warmers", "Coffee Decanters", "Coffee Filter Baskets", "Coffee Filters", "Coffee Maker & Espresso Machine Accessories", "Coffee Maker Water Filters", "Frothing Pitchers", "Stovetop Espresso Pot Parts"]}, "email": {"type": "string"}, "keywords": {"type": "array", "items": {"type": "string"}}, "keywords_scored": {"type": "object", "properties": {"coffee": {"type": "integer"}, "maker": {"type": "integer"}}, "required": ["coffee", "maker"]}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "taxonomy_set": {"type": "string"}, "version": {"type": "string"}}, "required": ["author", "categories", "categories_scored", "email", "keywords", "keywords_scored", "result_code", "result_msg", "taxonomy_set", "version"]} |
55389e16e4b082eab6ddd7f3/5538ba45e4b082eab6ddd854/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Generate (post) | Detect and generate human like topics to the given text. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "keyword": {"access": 1, "acquisition": 1, "communication": 1, "computer": 1, "mechanization": 1, "procedure": 1, "processing": 1, "representation": 1, "storage": 1, "underlie": 1}, "result_code": "200", "result_msg": "Success", "topic": {"art": 0.25797503467406, "company": 0.21497919556172, "development": 0.21497919556172, "human": 0.21497919556172, "letter": 0.21497919556172, "number": 0.21497919556172, "object": 0.21497919556172, "science": 0.25797503467406, "study": 0.25797503467406, "system": 0.25797503467406}, "version": "5.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "keyword": {"type": "object", "properties": {"access": {"type": "integer"}, "acquisition": {"type": "integer"}, "communication": {"type": "integer"}, "computer": {"type": "integer"}, "mechanization": {"type": "integer"}, "procedure": {"type": "integer"}, "processing": {"type": "integer"}, "representation": {"type": "integer"}, "storage": {"type": "integer"}, "underlie": {"type": "integer"}}, "required": ["access", "acquisition", "communication", "computer", "mechanization", "procedure", "processing", "representation", "storage", "underlie"]}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "topic": {"type": "object", "properties": {"art": {"type": "number"}, "company": {"type": "number"}, "development": {"type": "number"}, "human": {"type": "number"}, "letter": {"type": "number"}, "number": {"type": "number"}, "object": {"type": "number"}, "science": {"type": "number"}, "study": {"type": "number"}, "system": {"type": "number"}}, "required": ["art", "company", "development", "human", "letter", "number", "object", "science", "study", "system"]}, "version": {"type": "string"}}, "required": ["author", "email", "keyword", "result_code", "result_msg", "topic", "version"]} |
55389e16e4b082eab6ddd7f3/5538ca1ee4b03a4c998bbe6d/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Text (get) | Evaluate the difficulty level of a word, sentence, or paragraph. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "result_code": "200", "result_msg": "Success", "ten_degree": 6, "value": 0.84587472029773, "version": "5.1.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "ten_degree": {"type": "integer"}, "value": {"type": "number"}, "version": {"type": "string"}}, "required": ["author", "email", "result_code", "result_msg", "ten_degree", "value", "version"]} |
55389e16e4b082eab6ddd7f3/5538cc3ce4b03a4c998bbe7b/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Text (post) | Evaluate the difficulty level of a word, sentence, or paragraph. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "result_code": "200", "result_msg": "Success", "ten_degree": 6, "value": 0.84587472029773, "version": "5.1.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "ten_degree": {"type": "integer"}, "value": {"type": "number"}, "version": {"type": "string"}}, "required": ["author", "email", "result_code", "result_msg", "ten_degree", "value", "version"]} |
55389e16e4b082eab6ddd7f3/58dca021e4b0e1be96d356cd/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Text Similarity (get) | Evaluate the similarity of two words, sentences, or paragraphs. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "result_code": "200", "result_msg": "Success", "similarity": 0.86882813106215, "value": 2463079.7207981, "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "similarity": {"type": "number"}, "value": {"type": "number"}, "version": {"type": "string"}}, "required": ["author", "email", "result_code", "result_msg", "similarity", "value", "version"]} |
55389e16e4b082eab6ddd7f3/58dca05de4b0008f5d6738fd/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Text Similarity (post) | Evaluate the similarity of two words, sentences, or paragraphs. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "result_code": "200", "result_msg": "Success", "similarity": 0.86882813106215, "value": 2463079.7207981, "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "similarity": {"type": "number"}, "value": {"type": "number"}, "version": {"type": "string"}}, "required": ["author", "email", "result_code", "result_msg", "similarity", "value", "version"]} |
55389e16e4b082eab6ddd7f3/5538db61e4b03a4c998bbec0/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Type 1 | Customized word association quiz for game and e-learning software. | 200 | Response | {"area": "sat", "author": "twinword inc.", "email": "help@twinword.com", "level": 3, "quizlist": [{"correct": 1, "option": ["conservative", "dying"], "quiz": ["political", "social", "conventional"]}, {"correct": 2, "option": ["venture", "jurisdiction"], "quiz": ["authority", "court", "government"]}, {"correct": 1, "option": ["affiliate", "dancing"], "quiz": ["union", "associate", "combined"]}, {"correct": 2, "option": ["intervention", "integrity"], "quiz": ["credit", "truth", "reliability"]}, {"correct": 1, "option": ["encyclopedia", "god"], "quiz": ["article", "data", "dictionary"]}, {"correct": 1, "option": ["verify", "consequence"], "quiz": ["document", "check", "confirm"]}, {"correct": 2, "option": ["horizontal", "facilitate"], "quiz": ["allow", "enable", "permit"]}, {"correct": 2, "option": ["attendance", "beneficial"], "quiz": ["helpful", "useful", "good"]}, {"correct": 2, "option": ["broadband", "succeed"], "quiz": ["follow", "track", "trace"]}, {"correct": 2, "option": ["cake", "biography"], "quiz": ["article", "life", "publish"]}], "result_code": "200", "result_msg": "Success", "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"area": {"type": "string"}, "author": {"type": "string"}, "email": {"type": "string"}, "level": {"type": "integer"}, "quizlist": {"type": "array", "items": {"type": "object", "properties": {"correct": {"type": "integer"}, "option": {"type": "array", "items": {"type": "string"}}, "quiz": {"type": "array", "items": {"type": "string"}}}, "required": ["correct", "option", "quiz"]}}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "version": {"type": "string"}}, "required": ["area", "author", "email", "level", "quizlist", "result_code", "result_msg", "version"]} |
55389e16e4b082eab6ddd7f3/5538ca8ae4b030e59e4b208a/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Word (get) | Evaluate the difficulty level of a word. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "entry": "sound", "request": "sound", "response": "sound", "result_code": "200", "result_msg": "Success", "ten_degree": 1, "value": 0.027934136461676, "version": "5.1.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "entry": {"type": "string"}, "request": {"type": "string"}, "response": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "ten_degree": {"type": "integer"}, "value": {"type": "number"}, "version": {"type": "string"}}, "required": ["author", "email", "entry", "request", "response", "result_code", "result_msg", "ten_degree", "value", "version"]} |
55389e16e4b082eab6ddd7f3/5538cd53e4b03a4c998bbe7e/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Word (post) | Evaluate the difficulty level of a word. | 200 | Response | {"author": "twinword inc.", "email": "help@twinword.com", "entry": "sound", "request": "sound", "response": "sound", "result_code": "200", "result_msg": "Success", "ten_degree": 1, "value": 0.027934136461676, "version": "5.1.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"author": {"type": "string"}, "email": {"type": "string"}, "entry": {"type": "string"}, "request": {"type": "string"}, "response": {"type": "string"}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "ten_degree": {"type": "integer"}, "value": {"type": "number"}, "version": {"type": "string"}}, "required": ["author", "email", "entry", "request", "response", "result_code", "result_msg", "ten_degree", "value", "version"]} |
55389e16e4b082eab6ddd7f3/5538b6fce4b03a4c998bbe31/0/0 | Twinword Text Analysis Bundle | One API for all your text analysis needs. Sentiment Analysis, Topic Tagging, Lemmatizer, and much more. Various NLP tools all with one plan. Use natural language processing to analyze and understand human sentences. | 9.7 | Word Associations (get) | Get word associations with semantic distance score. | 200 | Response | {"associations": "voice, noise, acoustic, loud, din, croon, octave, thundering, whistle, resonance, resounding, clamorous, screech, bell, strident, reverberate, noisy, echo, decibel, telephony, beep, blare, toot, resonant, tune, vocalization, raucous, hiss, thud, hearing", "associations_array": ["voice", "noise", "acoustic", "loud", "din", "croon", "octave", "thundering", "whistle", "resonance", "resounding", "clamorous", "screech", "bell", "strident", "reverberate", "noisy", "echo", "decibel", "telephony", "beep", "blare", "toot", "resonant", "tune", "vocalization", "raucous", "hiss", "thud", "hearing"], "associations_scored": {"acoustic": 81.605316, "beep": 66.589455, "bell": 68.11078, "blare": 66.47947, "clamorous": 68.41181, "croon": 73.66902, "decibel": 67.142075, "din": 77.225655, "echo": 67.16983, "hearing": 64.96928, "hiss": 65.173454, "loud": 77.41582, "noise": 87.25341, "noisy": 67.46273, "octave": 71.27516, "raucous": 65.305984, "resonance": 69.21003, "resonant": 65.55987, "resounding": 68.69802, "reverberate": 67.772385, "screech": 68.19933, "strident": 68.07913, "telephony": 66.834946, "thud": 65.03899, "thundering": 69.76047, "toot": 65.78224, "tune": 65.53876, "vocalization": 65.52007, "voice": 88.22281, "whistle": 69.58462}, "author": "twinword inc.", "email": "help@twinword.com", "entry": "sound", "request": "sound", "response": {"sound": 1}, "result_code": "200", "result_msg": "Success", "version": "4.0.0"} | {"$schema": "http://json-schema.org/schema#", "type": "object", "properties": {"associations": {"type": "string"}, "associations_array": {"type": "array", "items": {"type": "string"}}, "associations_scored": {"type": "object", "properties": {"acoustic": {"type": "number"}, "beep": {"type": "number"}, "bell": {"type": "number"}, "blare": {"type": "number"}, "clamorous": {"type": "number"}, "croon": {"type": "number"}, "decibel": {"type": "number"}, "din": {"type": "number"}, "echo": {"type": "number"}, "hearing": {"type": "number"}, "hiss": {"type": "number"}, "loud": {"type": "number"}, "noise": {"type": "number"}, "noisy": {"type": "number"}, "octave": {"type": "number"}, "raucous": {"type": "number"}, "resonance": {"type": "number"}, "resonant": {"type": "number"}, "resounding": {"type": "number"}, "reverberate": {"type": "number"}, "screech": {"type": "number"}, "strident": {"type": "number"}, "telephony": {"type": "number"}, "thud": {"type": "number"}, "thundering": {"type": "number"}, "toot": {"type": "number"}, "tune": {"type": "number"}, "vocalization": {"type": "number"}, "voice": {"type": "number"}, "whistle": {"type": "number"}}, "required": ["acoustic", "beep", "bell", "blare", "clamorous", "croon", "decibel", "din", "echo", "hearing", "hiss", "loud", "noise", "noisy", "octave", "raucous", "resonance", "resonant", "resounding", "reverberate", "screech", "strident", "telephony", "thud", "thundering", "toot", "tune", "vocalization", "voice", "whistle"]}, "author": {"type": "string"}, "email": {"type": "string"}, "entry": {"type": "string"}, "request": {"type": "string"}, "response": {"type": "object", "properties": {"sound": {"type": "integer"}}, "required": ["sound"]}, "result_code": {"type": "string"}, "result_msg": {"type": "string"}, "version": {"type": "string"}}, "required": ["associations", "associations_array", "associations_scored", "author", "email", "entry", "request", "response", "result_code", "result_msg", "version"]} |
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