From 87acf8eb1711a3d7c4c8077accda4c714ab3b19f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Miguel=20Brand=C3=A3o?= <555migalves555@gmail.com> Date: Mon, 24 Jul 2023 11:00:15 +0100 Subject: [PATCH] refactored docs MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Signed-off-by: Miguel Brandão <555migalves555@gmail.com> --- .../examples/dummy_nlp_annotator/README.MD | 159 +------- .../examples/dummy_qa_generator/README.MD | 66 +-- .../simple_geo_nlp_annotator/README.MD | 298 +------------- docs/guide/index.md | 3 + docs/guide/model.md | 381 ++++++++++++++++++ mkdocs.yml | 1 + 6 files changed, 391 insertions(+), 517 deletions(-) create mode 100644 docs/guide/model.md diff --git a/deepsearch/model/examples/dummy_nlp_annotator/README.MD b/deepsearch/model/examples/dummy_nlp_annotator/README.MD index c0b86f6b..4b1e444c 100644 --- a/deepsearch/model/examples/dummy_nlp_annotator/README.MD +++ b/deepsearch/model/examples/dummy_nlp_annotator/README.MD @@ -1,7 +1,4 @@ # DummyNlpAnnotator -## Introduction -This is an example dummy NLP kind annotator it supports text data and annotates entities. - ## Running the Annotator To run this example make sure you've installed the full environment including the optional installs provided in poetry @@ -11,158 +8,6 @@ Then simply start the server with python -m deepsearch.model.examples.dummy_nlp_annotator.main -## Simple Interaction with the Annotator - -You can direcly access the API via a browser to the provided url on the console upon running the application, usually: - - http://127.0.0.1:8000 -This will take you to the landing page. Here you will likely find that you are not authenticated, however you can still check if the API is responsive by accessing the /health endpoint - - http://127.0.0.1:8000/health -It will be easier to interact with the application via the provided documentation endpoint - - http://127.0.0.1:8000/docs - -## Security -By default, the API requires an API-key to be used with every request to most endpoints, this key is defined on: - - deepsearch/model/examples/dummy_nlp_annotator/main.py -this API key must be provided on the authorization header, sample request headers to /: - - {'host': '127.0.0.1:8000', 'connection': 'keep-alive', 'sec-ch-ua': '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"', 'accept': 'application/json', 'sec-ch-ua-mobile': '?0', 'authorization': 'example123', 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36', 'sec-ch-ua-platform': '"Linux"', 'sec-fetch-site': 'same-origin', 'sec-fetch-mode': 'cors', 'sec-fetch-dest': 'empty', 'referer': 'http://127.0.0.1:8000/docs', 'accept-encoding': 'gzip, deflate, br', 'accept-language': 'en-US,en;q=0.9'} - -## Advanced Interaction with the Annotator -On the /docs endpoint after inserting the api key you may see the following information about the API server - -on endpoint: - - - / - A list of all the annotators hosted on this server, in this example you will find only "DummyNLPAnnotator" on each annotator you will find its annotation capabilities as well as the kind of annotator it is (NLPAnnotator) which in turn tells you how to make requests to the annotator - - /model/{model_name} - You will find the annotation capabilities for the given annotator as well as it's kind. - - /model/{model_name}/predict - You can make POST requests to have the model annotate your data, refer to [Sample Requests](#Sample-Requests) - -## Sample Requests - -```python - { - "apiVersion": "string", - "kind": "NLPModel", - "metadata": { - "annotations": { - "deepsearch.res.ibm.com/x-deadline": "2038-01-18T00:00:00.000Z", - "deepsearch.res.ibm.com/x-transaction-id": "string", - "deepsearch.res.ibm.com/x-attempt-number": "string", - "deepsearch.res.ibm.com/x-max-attempts": "string" - } - }, - "spec": { - "findEntities": { - "entityNames": ["entity_foo", "entity_bar"], - "objectType": "text", - "texts": [ - "A piece of text", - "Yet another piece of text" - ] - } - } - } -``` - - - You may alter entityNames to have any number of the entity types the annotator declares it can annotate, or an empty list to annotate all. - - This annotator has declared that it can only annotate text, as such the objectType must be text - - texts may be as long or as short as you need it. - - The x-deadline must lie some time in the future - - This annotator has declared that it is of kind NLPModel as such the kind for the request must match - - refer to the /docs for details on the NLPRequest type - -Will result in the following output: +## Interaction with the Annotator -```python -{ - "entities":[ - { - "entity_foo":[ - { - "type":"entity_foo", - "match":"a 'entity_foo' match in 'A piece of text'", - "original":"a 'entity_foo' original in 'A piece of text'", - "range":[ - 1, - 5 - ] - }, - { - "type":"entity_foo", - "match":"another 'entity_foo' match in 'A piece of text'", - "original":"another 'entity_foo' original in 'A piece of text'", - "range":[ - 12, - 42 - ] - } - ], - "entity_bar":[ - { - "type":"entity_bar", - "match":"a 'entity_bar' match in 'A piece of text'", - "original":"a 'entity_bar' original in 'A piece of text'", - "range":[ - 1, - 5 - ] - }, - { - "type":"entity_bar", - "match":"another 'entity_bar' match in 'A piece of text'", - "original":"another 'entity_bar' original in 'A piece of text'", - "range":[ - 12, - 42 - ] - } - ] - }, - { - "entity_foo":[ - { - "type":"entity_foo", - "match":"a 'entity_foo' match in 'Yet another piece of text'", - "original":"a 'entity_foo' original in 'Yet another piece of text'", - "range":[ - 1, - 5 - ] - }, - { - "type":"entity_foo", - "match":"another 'entity_foo' match in 'Yet another piece of text'", - "original":"another 'entity_foo' original in 'Yet another piece of text'", - "range":[ - 12, - 42 - ] - } - ], - "entity_bar":[ - { - "type":"entity_bar", - "match":"a 'entity_bar' match in 'Yet another piece of text'", - "original":"a 'entity_bar' original in 'Yet another piece of text'", - "range":[ - 1, - 5 - ] - }, - { - "type":"entity_bar", - "match":"another 'entity_bar' match in 'Yet another piece of text'", - "original":"another 'entity_bar' original in 'Yet another piece of text'", - "range":[ - 12, - 42 - ] - } - ] - } - ] -} -``` \ No newline at end of file +refer to [https://ds4sd.github.io/deepsearch-toolkit/guide/](https://ds4sd.github.io/deepsearch-toolkit/guide/model/) diff --git a/deepsearch/model/examples/dummy_qa_generator/README.MD b/deepsearch/model/examples/dummy_qa_generator/README.MD index 6f66f737..98d9f2ff 100644 --- a/deepsearch/model/examples/dummy_qa_generator/README.MD +++ b/deepsearch/model/examples/dummy_qa_generator/README.MD @@ -11,68 +11,6 @@ Then simply start the server with python -m deepsearch.model.examples.dummy_qa_generator.main -## Simple Interaction with the Annotator +## Interaction with the Annotator -You can direcly access the API via a browser to the provided url on the console upon running the application, usually: - - http://127.0.0.1:8000 -This will take you to the landing page. Here you will likely find that you are not authenticated, however you can still check if the API is responsive by accessing the /health endpoint - - http://127.0.0.1:8000/health -It will be easier to interact with the application via the provided documentation endpoint - - http://127.0.0.1:8000/docs - -## Security -By default, the API requires an API-key to be used with every request to most endpoints, this key is defined on: - - deepsearch/model/examples/dummy_qa_generator/main.py -this API key must be provided on the authorization header, sample request headers to /: - - {'host': '127.0.0.1:8000', 'connection': 'keep-alive', 'sec-ch-ua': '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"', 'accept': 'application/json', 'sec-ch-ua-mobile': '?0', 'authorization': 'example123', 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36', 'sec-ch-ua-platform': '"Linux"', 'sec-fetch-site': 'same-origin', 'sec-fetch-mode': 'cors', 'sec-fetch-dest': 'empty', 'referer': 'http://127.0.0.1:8000/docs', 'accept-encoding': 'gzip, deflate, br', 'accept-language': 'en-US,en;q=0.9'} - -## Advanced Interaction with the Annotator -On the /docs endpoint after inserting the api key you may see the following information about the API server - -on endpoint: - - - / - A list of all the annotators hosted on this server, in this example you will find only "DummyQAGenerator" on each annotator you will find its annotation capabilities as well as the kind of annotator it is (QAGenModel) which in turn tells you how to make requests to the annotator - - /model/{model_name} - You will find the annotation capabilities for the given annotator as well as it's kind. - - /model/{model_name}/predict - You can make POST requests to have the model generate your data, refer to [Sample Requests](#Sample-Requests) - -## Sample Requests - -```python -{ - "apiVersion": "string", - "kind": "QAGenModel", - "metadata": { - "annotations": { - "deepsearch.res.ibm.com/x-deadline": "2038-01-18T00:00:00.000Z", - "deepsearch.res.ibm.com/x-transaction-id": "string", - "deepsearch.res.ibm.com/x-attempt-number": "string", - "deepsearch.res.ibm.com/x-max-attempts": "string" - } - }, - "spec": { - "generateAnswers": { - "contexts": [ - ["What is the best model"] - ], - "questions": [ - "If you are a dummy repeat what I said!" - ] - } - } -} -``` - -Will result in the following output: - -```python -{ - "answers": [ - "If you are a dummy repeat what I said!" - ] -} -``` \ No newline at end of file +refer to [https://ds4sd.github.io/deepsearch-toolkit/guide/](https://ds4sd.github.io/deepsearch-toolkit/guide/model/) \ No newline at end of file diff --git a/deepsearch/model/examples/simple_geo_nlp_annotator/README.MD b/deepsearch/model/examples/simple_geo_nlp_annotator/README.MD index 6a32a10e..fa5cb54b 100644 --- a/deepsearch/model/examples/simple_geo_nlp_annotator/README.MD +++ b/deepsearch/model/examples/simple_geo_nlp_annotator/README.MD @@ -11,300 +11,6 @@ Then simply start the server with python -m deepsearch.model.examples.simple_geo_nlp_annotator.main -## Simple Interaction with the Annotator +## Interaction with the Annotator -You can direcly access the API via a browser to the provided url on the console upon running the application, usually: - - http://127.0.0.1:8000 -This will take you to the landing page. Here you will likely find that you are not authenticated, however you can still check if the API is responsive by accessing the /health endpoint - - http://127.0.0.1:8000/health -It will be easier to interact with the application via the provided documentation endpoint - - http://127.0.0.1:8000/docs - -## Security -By default, the API requires an API-key to be used with every request to most endpoints, this key is defined on: - - deepsearch/model/examples/simple_geo_nlp_annotator/main.py -this API key must be provided on the authorization header, sample request headers to /: - - {'host': '127.0.0.1:8000', 'connection': 'keep-alive', 'sec-ch-ua': '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"', 'accept': 'application/json', 'sec-ch-ua-mobile': '?0', 'authorization': 'example123', 'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36', 'sec-ch-ua-platform': '"Linux"', 'sec-fetch-site': 'same-origin', 'sec-fetch-mode': 'cors', 'sec-fetch-dest': 'empty', 'referer': 'http://127.0.0.1:8000/docs', 'accept-encoding': 'gzip, deflate, br', 'accept-language': 'en-US,en;q=0.9'} - -## Advanced Interaction with the Annotator -On the /docs endpoint after inserting the api key you may see the following information about the API server - -on endpoint: - - - / - A list of all the annotators hosted on this server, in this example you will find only "SimpleGeoNLPAnnotator" on each annotator you will find its annotation capabilities as well as the kind of annotator it is (NLPAnnotator) which in turn tells you how to make requests to the annotator - - /model/{model_name} - You will find the annotation capabilities for the given annotator as well as it's kind. - - /model/{model_name}/predict - You can make POST requests to have the model annotate your data, refer to [Sample Requests](#Sample-Requests) - -## Sample Requests - -### Sample Entity Annotation - -```python -{ - "apiVersion": "string", - "kind": "NLPModel", - "metadata": { - "annotations": { - "deepsearch.res.ibm.com/x-deadline": "2038-01-18T00:00:00.000Z", - "deepsearch.res.ibm.com/x-transaction-id": "string", - "deepsearch.res.ibm.com/x-attempt-number": "string", - "deepsearch.res.ibm.com/x-max-attempts": "string" - } - }, - "spec": { - "findEntities": { - "entityNames": ["cities", "countries", "provinces"], - "objectType": "text", - "texts": [ - "Lisbon, Madrid, Paris and Zurich are Capitals of european countries", - "Berlin is the capital of Germany" - ] - } - } -} -``` - - - You may alter propertyNames to have any number of the property types the annotator declares it can annotate, or an empty list to annotate all. - - This annotator has declared that it can only annotate text, as such the objectType must be text - - texts may be as long or as short as you need it. - - The x-deadline must lie some time in the future - - This annotator has declared that it is of kind NLPModel as such the kind for the request must match - - refer to the /docs for details on the NLPRequest type - -Will result in the following output: - -```python -{ - "entities": [ - { - "cities": [ - { - "type": "cities", - "match": "Lisbon", - "original": "Lisbon", - "range": [ - 0, - 6 - ] - }, - { - "type": "cities", - "match": "Madrid", - "original": "Madrid", - "range": [ - 8, - 14 - ] - }, - { - "type": "cities", - "match": "Paris", - "original": "Paris", - "range": [ - 16, - 21 - ] - } - ], - "countries": [] - }, - { - "cities": [ - { - "type": "cities", - "match": "Berlin", - "original": "Berlin", - "range": [ - 0, - 6 - ] - } - ], - "countries": [ - { - "type": "countries", - "match": "Germany", - "original": "Germany", - "range": [ - 25, - 32 - ] - } - ] - } - ] -} -``` - -### Sample Relationship Annotation - -```python -{ - "apiVersion":"string", - "kind":"NLPModel", - "metadata":{ - "annotations":{ - "deepsearch.res.ibm.com/x-deadline":"2038-01-18T00:00:00.000Z", - "deepsearch.res.ibm.com/x-transaction-id":"string", - "deepsearch.res.ibm.com/x-attempt-number":"string", - "deepsearch.res.ibm.com/x-max-attempts":"string" - } - }, - "spec":{ - "findRelationships":{ - "relationshipNames": null, - "objectType":"text", - "texts":[ - "Lisbon, Madrid, Paris and Zurich are Capitals of european countries", - "Berlin is the capital of Germany" - ], - "entities":[ - { - "cities":[ - { - "type":"cities", - "match":"Lisbon", - "original":"Lisbon", - "range":[ - 0, - 6 - ] - }, - { - "type":"cities", - "match":"Madrid", - "original":"Madrid", - "range":[ - 8, - 14 - ] - }, - { - "type":"cities", - "match":"Paris", - "original":"Paris", - "range":[ - 16, - 21 - ] - } - ], - "countries":[ - - ] - }, - { - "cities":[ - { - "type":"cities", - "match":"Berlin", - "original":"Berlin", - "range":[ - 0, - 6 - ] - } - ], - "countries":[ - { - "type":"countries", - "match":"Germany", - "original":"Germany", - "range":[ - 25, - 32 - ] - } - ] - } - ] - } - } -} -``` - - Note that for relationship annotation it is required that you provide an annotation of the entities of those same pieces of text - - You may alter propertyNames to have any number of the property types the annotator declares it can annotate, or an empty list to annotate all. - - This annotator has declared that it can only annotate text, as such the objectType must be text - - texts may be as long or as short as you need it. - - The x-deadline must lie some time in the future - - This annotator has declared that it is of kind NLPModel as such the kind for the request must match - - refer to the /docs for details on the NLPRequest type - -Will result in the following output: - -```python -{ - "relationships": [ - { - "cities-to-countries": { - "header": [ - "cities", - "countries", - "weight", - "source" - ], - "data": [] - }, - "cities-to-provincies": { - "header": [ - "cities", - "provincies", - "weight", - "source" - ], - "data": [] - }, - "provincies-to-countries": { - "header": [ - "provincies", - "countries", - "weight", - "source" - ], - "data": [] - } - }, - { - "cities-to-countries": { - "header": [ - "cities", - "countries", - "weight", - "source" - ], - "data": [ - [ - "cities.0", - "countries.0", - 1, - "entities" - ] - ] - }, - "cities-to-provincies": { - "header": [ - "cities", - "provincies", - "weight", - "source" - ], - "data": [] - }, - "provincies-to-countries": { - "header": [ - "provincies", - "countries", - "weight", - "source" - ], - "data": [] - } - } - ] -} -``` \ No newline at end of file +refer to [https://ds4sd.github.io/deepsearch-toolkit/guide/](https://ds4sd.github.io/deepsearch-toolkit/guide/model/) \ No newline at end of file diff --git a/docs/guide/index.md b/docs/guide/index.md index 885bf761..65073eaf 100644 --- a/docs/guide/index.md +++ b/docs/guide/index.md @@ -16,3 +16,6 @@ - [List and manage KGs](./kgs.md) - [Operate with manual API calls](./apis.md) - [Custom CLI plugins](./cli_plugins.md) + +## Custom models +- [Custom model examples](./model.md) diff --git a/docs/guide/model.md b/docs/guide/model.md new file mode 100644 index 00000000..35b21893 --- /dev/null +++ b/docs/guide/model.md @@ -0,0 +1,381 @@ +## Launching a model + +To run this example make sure you've installed the full environment including the optional installs provided in poetry + + poetry install --all-extras + +Then run the model with: + + python -m deepsearch.model.examples.. + +Illustrated by running the dummy_nlp_annotator example below + + python -m deepsearch.model.examples.dummy_nlp_annotator.main + +### Security + +By default, the API requires an API-key to be used with every request to most endpoints, this key is defined on a per model basis, as an example: + +```python + # deepsearch/model/examples/dummy_nlp_annotator/main.py + ... + + def run(): + -> settings = Settings(api_key="example123") <- + app = ModelApp(settings) + app.register_model(DummyNLPAnnotator()) + ... +``` +this API key must be provided on the authorization header for most application endpoints + +## A map of the annotator endpoints + + - / - A list of all the annotators hosted on this server with all their information. + - /model/{model_name} - You will find the annotation capabilities for the given annotator. + - /model/{model_name}/predict - You can make POST requests to have the model annotate your data, refer to the [Sample Requests](#Sample NLP kind models requests and responses) + - /health - An endpoint that will respond with a preset message letting you know that the webserver is healthy. + +### Annotator API endpoints guide + +You can direcly access the API via a browser to the provided url on the console upon running the application, usually: + + http://127.0.0.1:8000 +This will take you to the landing page. Here you will likely find that you are not authenticated, however you can still check if the API is responsive by accessing the /health endpoint + + http://127.0.0.1:8000/health +It will be easier to interact with the application prediction capabilities via the provided documentation endpoint + + http://127.0.0.1:8000/docs + +## Sample NLP kind models requests and responses + +### Entity annotation + +```json + { + "apiVersion": "string", + "kind": "NLPModel", + "metadata": { + "annotations": { + "deepsearch.res.ibm.com/x-deadline": "2038-01-18T00:00:00.000Z", + "deepsearch.res.ibm.com/x-transaction-id": "string", + "deepsearch.res.ibm.com/x-attempt-number": "string", + "deepsearch.res.ibm.com/x-max-attempts": "string" + } + }, + "spec": { + "findEntities": { + "entityNames": ["entity_foo", "entity_bar"], + "objectType": "text", + "texts": [ + "A piece of text", + "Yet another piece of text" + ] + } + } + } +``` + +response + +```json +{ + "entities":[ + { + "entity_foo":[ + { + "type":"entity_foo", + "match":"a 'entity_foo' match in 'A piece of text'", + "original":"a 'entity_foo' original in 'A piece of text'", + "range":[ + 1, + 5 + ] + }, + { + "type":"entity_foo", + "match":"another 'entity_foo' match in 'A piece of text'", + "original":"another 'entity_foo' original in 'A piece of text'", + "range":[ + 12, + 42 + ] + } + ], + "entity_bar":[ + { + "type":"entity_bar", + "match":"a 'entity_bar' match in 'A piece of text'", + "original":"a 'entity_bar' original in 'A piece of text'", + "range":[ + 1, + 5 + ] + }, + { + "type":"entity_bar", + "match":"another 'entity_bar' match in 'A piece of text'", + "original":"another 'entity_bar' original in 'A piece of text'", + "range":[ + 12, + 42 + ] + } + ] + }, + { + "entity_foo":[ + { + "type":"entity_foo", + "match":"a 'entity_foo' match in 'Yet another piece of text'", + "original":"a 'entity_foo' original in 'Yet another piece of text'", + "range":[ + 1, + 5 + ] + }, + { + "type":"entity_foo", + "match":"another 'entity_foo' match in 'Yet another piece of text'", + "original":"another 'entity_foo' original in 'Yet another piece of text'", + "range":[ + 12, + 42 + ] + } + ], + "entity_bar":[ + { + "type":"entity_bar", + "match":"a 'entity_bar' match in 'Yet another piece of text'", + "original":"a 'entity_bar' original in 'Yet another piece of text'", + "range":[ + 1, + 5 + ] + }, + { + "type":"entity_bar", + "match":"another 'entity_bar' match in 'Yet another piece of text'", + "original":"another 'entity_bar' original in 'Yet another piece of text'", + "range":[ + 12, + 42 + ] + } + ] + } + ] +} +``` + +### Relationship annotation +request +```json +{ + "apiVersion":"string", + "kind":"NLPModel", + "metadata":{ + "annotations":{ + "deepsearch.res.ibm.com/x-deadline":"2038-01-18T00:00:00.000Z", + "deepsearch.res.ibm.com/x-transaction-id":"string", + "deepsearch.res.ibm.com/x-attempt-number":"string", + "deepsearch.res.ibm.com/x-max-attempts":"string" + } + }, + "spec":{ + "findRelationships":{ + "relationshipNames": null, + "objectType":"text", + "texts":[ + "Lisbon, Madrid, Paris and Zurich are Capitals of european countries", + "Berlin is the capital of Germany" + ], + "entities":[ + { + "cities":[ + { + "type":"cities", + "match":"Lisbon", + "original":"Lisbon", + "range":[ + 0, + 6 + ] + }, + { + "type":"cities", + "match":"Madrid", + "original":"Madrid", + "range":[ + 8, + 14 + ] + }, + { + "type":"cities", + "match":"Paris", + "original":"Paris", + "range":[ + 16, + 21 + ] + } + ], + "countries":[ + + ] + }, + { + "cities":[ + { + "type":"cities", + "match":"Berlin", + "original":"Berlin", + "range":[ + 0, + 6 + ] + } + ], + "countries":[ + { + "type":"countries", + "match":"Germany", + "original":"Germany", + "range":[ + 25, + 32 + ] + } + ] + } + ] + } + } +} +``` + +response + +```json +{ + "relationships": [ + { + "cities-to-countries": { + "header": [ + "cities", + "countries", + "weight", + "source" + ], + "data": [] + }, + "cities-to-provincies": { + "header": [ + "cities", + "provincies", + "weight", + "source" + ], + "data": [] + }, + "provincies-to-countries": { + "header": [ + "provincies", + "countries", + "weight", + "source" + ], + "data": [] + } + }, + { + "cities-to-countries": { + "header": [ + "cities", + "countries", + "weight", + "source" + ], + "data": [ + [ + "cities.0", + "countries.0", + 1, + "entities" + ] + ] + }, + "cities-to-provincies": { + "header": [ + "cities", + "provincies", + "weight", + "source" + ], + "data": [] + }, + "provincies-to-countries": { + "header": [ + "provincies", + "countries", + "weight", + "source" + ], + "data": [] + } + } + ] +} +``` +### Property annotation + +## Sample QAGen kind models requests and responses + +### Generate +Request +```json +{ + "apiVersion": "string", + "kind": "QAGenModel", + "metadata": { + "annotations": { + "deepsearch.res.ibm.com/x-deadline": "2038-01-18T00:00:00.000Z", + "deepsearch.res.ibm.com/x-transaction-id": "string", + "deepsearch.res.ibm.com/x-attempt-number": "string", + "deepsearch.res.ibm.com/x-max-attempts": "string" + } + }, + "spec": { + "generateAnswers": { + "contexts": [ + ["What is the best model"] + ], + "questions": [ + "If you are a dummy repeat what I said!" + ] + } + } +} +``` + +Response + +```json +{ + "answers": [ + "If you are a dummy repeat what I said!" + ] +} +``` + +## Important considerations + +- Each annotator has a kind, for example NLPModel, as such the kind for the request must match. +- For NLP Kind annotators under the spec you must define the appropriate types to be annotated, for the dummyNLPAnnotator +[refer to this example](#marker1) you will find on the request that we would like to find *entity_foo* and *entity_bar* an empty list will lead to +no annotations being made, a null object will lead to *all* possible annotations being made. +- Each annotator declared what sort of input it supports, a list constituted of any number of (text, table and image). +- The x-deadline on each request is already implemented and must lie some time in the future. +- refer to the /docs page on any annotator instance for more specification on the request types \ No newline at end of file diff --git a/mkdocs.yml b/mkdocs.yml index 49f024f1..f0dbcb98 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -60,6 +60,7 @@ nav: - Knowledge graphs: guide/kgs.md - APIs: guide/apis.md - Plugin system: guide/cli_plugins.md + - Custom model examples: guide/model.md - Example gallery: gallery/index.md - API reference: - Toolkit reference: api-reference.md