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- Introduction
- Filter Plugin Classes
- Filter Plugin Initialization Options Classes
- Filter Plugin Options Classes
TBD
Base class for plugins to operate on a vcon.
FilterPlugin take a Vcon and some options as input and output a Vcon which may be the input Vcon modified.
A FilterPlugin as three primary operations:
-
Initialization (init) which is invoked with a derived class specific set of initialization options (derived from FilterPluginInitOptions(
-
filtering (filter) which is the actual method that operates on a Vcon.
-
teardown (del) which performs any shutdown or release of resources for the plugin.
Initialization and teardown are only performed once.
FilterPlugins is an abstract class. One must implement a derived class to use it. The derived class must implement the following:
-
init method SHOULD invoke super().init
-
filter method to performe the actual Vcon operation
-
init_options_type MUST be defined and set to a derived class of FilterPluginInitOptions which is the type of the only argument to the derived class's init method.
To be used the derived class and a specific set of initialization options must be registered using FilterPluginRegistry.register. A FilterPlugin is dynamically loaded only the first time that it is actually used. It stays loaded until the system exits.
Methods:
__init__(self, options: 'FilterPluginInitOptions', options_type: 'typing.Type[FilterPluginOptions]')
Instance stores the initialization options that were used.
Instance also stores the FilterPluginOptions type/class that is used by the derived class's filter method. This is used to enforce typing and defaults for the options passed into the filter method.
options - vcon.filter_plugins.FilterPluginInitOptions
filter(self, in_vcon: 'Vcon', options: 'FilterPluginOptions') -> 'Vcon'
Abstract method which performs an operation on an input Vcon and provides the modified Vcon as output.
Parameters: in_vcon (vcon.Vcon) - input Vcon upon which an operation is to be performed by the plugin. options (FilterPluginOptions) - derived options specific to the filter method/opearation
Returns: vcon.Vcon - the modified Vcon
options - vcon.filter_plugins.FilterPluginOptions
__del__(self)
Teardown/uninitialization method for the plugin
Parameters: None
FilterPlugin to for transcription using Deepgram
Methods:
__init__(self, init_options: vcon.filter_plugins.impl.deepgram.DeepgramInitOptions)
Parameters: init_options (DeepgramInitOptions) - the initialization options for the Deepgram transcription plugin
init_options - vcon.filter_plugins.impl.deepgram.DeepgramInitOptions
filter(self, in_vcon: vcon.Vcon, options: vcon.filter_plugins.impl.deepgram.DeepgramOptions) -> vcon.Vcon
Transcribe the recording dialog objects using Deepgram.
Parameters: options (DeepgramOptions)
Returns: the modified Vcon with added transcript analysis objects for the recording dialogs.
options - vcon.filter_plugins.impl.deepgram.DeepgramOptions
__del__(self)
Teardown/uninitialization method for the plugin
Parameters: None
FilterPlugin to for generative AI using OpenAI chat completion (e.g. ChatGPT)
OpenAIChatCompletion differs from OpenAICompletion in that is uses the context of all of the text dialog and transcribe analysis objects as input labeled by time and party and generates a single prompt response or answer in one new analysis object. In contrast, OpenAICompletion only imputs a single text dialog or transcribe analysis text when asking for a completion to the prompt, generating a prompt response and a new analysis object for each text dialog and transcribe analysis object analysed.
Methods:
__init__(self, init_options: vcon.filter_plugins.impl.openai.OpenAIChatCompletionInitOptions)
Parameters: init_options (OpenAICompletionInitOptions) - the initialization options for the OpenAI completion plugin
init_options - vcon.filter_plugins.impl.openai.OpenAIChatCompletionInitOptions
filter(self, in_vcon: vcon.Vcon, options: vcon.filter_plugins.impl.openai.OpenAIChatCompletionOptions) -> vcon.Vcon
Perform generative AI using OpenAI chat completion on the text dialogs and/or transcription analysis objects in the given Vcon using the given options.prompt.
Parameters: options (OpenAICompletionOptions)
Returns: the modified Vcon with a single analysis object added in total for all of the text dialogs and transcription analysis object analysed.
options - vcon.filter_plugins.impl.openai.OpenAIChatCompletionOptions
__del__(self)
Close down OpenAI client if created.
FilterPlugin to for generative AI using OpenAI completion (e.g. ChatGPT)
OpenAICompletion differs from OpenAIChatCompletion in that is uses only imputs a single text dialog or transcribe analysis text when asking for a completion to the prompt. OpenAIChatCompletion by default will iterate through all of the text dialog or transcribe analysis text, but it evaluates the prompt for only one text input at a time. Thus generating a prompt answer as a new analysis obejct for each text dialog or transcribe analysis text analysed.
In contrast, OpenAIChatCompletion inputs the context of all of the text dialog and transcribe analysis objects as input labeled by time and party and will generate a single prompt response as one new analysis object.
Methods:
__init__(self, init_options: vcon.filter_plugins.impl.openai.OpenAICompletionInitOptions)
Parameters: init_options (OpenAICompletionInitOptions) - the initialization options for the OpenAI completion plugin
init_options - vcon.filter_plugins.impl.openai.OpenAICompletionInitOptions
filter(self, in_vcon: vcon.Vcon, options: vcon.filter_plugins.impl.openai.OpenAICompletionOptions) -> vcon.Vcon
Perform generative AI using OpenAI completion on the text dialogs and/or transcription analysis objects in the given Vcon using the given options.prompt.
Parameters: options (OpenAICompletionOptions)
Returns: the modified Vcon with added analysis objects for the text dialogs and transcription analysis.
options - vcon.filter_plugins.impl.openai.OpenAICompletionOptions
__del__(self)
Close down OpenAI client if created.
FilterPlugin to generate transcriptions for a Vcon
Methods:
__init__(self, init_options: vcon.filter_plugins.impl.whisper.WhisperInitOptions)
Parameters: init_options (WhisperInitOptions) - the initialization options for the Whisper trascription plugin
init_options - vcon.filter_plugins.impl.whisper.WhisperInitOptions
filter(self, in_vcon: vcon.Vcon, options: vcon.filter_plugins.impl.whisper.WhisperOptions) -> vcon.Vcon
Transcribe recording dialogs in given Vcon using the Whisper implementation
Parameters: options (WhisperOptions)
options.output_types List[str] - list of output types to generate. Current set of value supported are:
- "vendor" - add the Whisper specific JSON format transcript as an analysis object
- "word_srt" - add a .srt file with timing on a word or small phrase basis as an analysis object
- "word_ass" - add a .ass file with sentence and highlighted word timeing as an analysis object
Not specifing "output_type" assumes all of the above will be output, each as a separate analysis object.
Returns: the modified Vcon with added analysis objects for the transcription.
options - vcon.filter_plugins.impl.whisper.WhisperOptions
__del__(self)
Teardown/uninitialization method for the plugin
Parameters: None
- FilterPluginInitOptions
base class for FilterPlugin initialization options
None
- Deepgram transcription FilterPlugin intialization object
A DeepgramInitOptions object is provided to the Deepgram FilterPlugin.init method when it is first loaded. Its attributes effect how the registered FilterPlugin functions.
Deepgram API key
The deepgram_key is used to access the Deepgram RESTful transcription service. It is required to use this FilterPlugin.
You can get one at: https://console.deepgram.com/signup?jump=keys
example: 123456789e96a1da774e57abcdefghijklmnop
default: ""
- OpenAI/ChatGPT Chat Completion FilterPlugin intialization object
A OpenAIInitOptions object is provided to the OpenAI FilterPlugin.init method when it is first loaded. Its attributes effect how the registered FilterPlugin functions.
OpenAI API key
The openai_api_key is used to access the OpenAI RESTful service. It is required to use this FilterPlugin.
You can get one at: https://platform.openai.com/account/api-keys
example: sk-cABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstu
default: None
- OpenAI/ChatGPT Completion FilterPlugin intialization object
A OpenAIInitOptions object is provided to the OpenAI FilterPlugin.init method when it is first loaded. Its attributes effect how the registered FilterPlugin functions.
OpenAI API key
The openai_api_key is used to access the OpenAI RESTful service. It is required to use this FilterPlugin.
You can get one at: https://platform.openai.com/account/api-keys
example: sk-cABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstu
default: None
- Whisper FilterPlugin intialization object
A WhisperInitOptions object is provided to the Whisper FilterPlugin.init method when it is first loaded. Its attributes effect how the registered FilterPlugin functions.
Whisper model size name
Model size name to use for transcription", (e.g. "tiny", "base") as defined on https://github.com/openai/whisper#available-models-and-languages
examples: ['tiny', 'base']
default: "base"
- FilterPluginOptions
base class for FilterPlugin.filter method options
None
- Deepgram transcription filter method options
Options for transcribing the recording dialog objects using Deepgram transcription service. The resulting transcription(s) are added as transcript analysis objects in this Vcon
More details on the OpenAI specific parameters can be found here: https://developers.deepgram.com/reference/pre-recorded
transcription language None
example:
default: "en"
input Vcon recording dialog objects
Indicates which recording dialog objects in the given Vcon are to be transcribed.
- "" (empty str or None) - all recording dialogs are to be transcribed. This is the equivalent of providing "0:".
- n:m (str) - dialog objects having indices n-m are to be transcribed.
- n:m:i (str) - dialog objects having indices n-m using interval i are to be transcribed.
- [] (empty list[int]) - none of the dialog objects are to be transcribed.
- [1, 4, 5, 9] (list[int]) - the dialog objects having the indices in the given list are to be transcribed.
dialog objects in the given sequence or list which are not recording type dialogs are ignored.
examples: ['', '0:', '0:-2', '2:5', '0:6:2', [], [1, 4, 5, 9]]
default:
- OpenAI Chat Completion filter method options
Options for generative AI using OpenAI completion (e.g. ChatGPT) on the text dialogs and/or transcription analysis in the given Vcon
More details on the OpenAI specific parameters can be found here: https://platform.openai.com/docs/api-reference/completions/create
input Vcon text dialog objects
Indicates which text dialog and recording dialog object's associated transcript analysis objects are to be input. Recording dialog objects that do not have transcript analysis objects, are transcribed using the default FilterPlugin transcribe type.
- "" (empty str or None) - all dialogs are fed into OpenAI model to complete the response to the prompt. This is the equivalent of providing "0:".
- n:m (str) - dialog objects having indices n-m are fed into OpenAI model to complete the response to the prompt
- n:m:i (str) - dialog objects having indices n-m using interval i are fed into OpenAI model to complete the response to the prompt
- [] (empty list[int]) - none of the dialog objects are fed to the the model.
- [1, 4, 5, 9] (list[int]) - the dialog objects having the indices in the given list are fed to the the model.
dialog objects in the given sequence or list which are not text or recording type dialogs are ignored.
examples: ['', '0:', '0:-2', '2:5', '0:6:2', [], [1, 4, 5, 9]]
default:
OpenAI model name to use for generative AI
The named model is used to feed the transcription/text and then ask it the given prompt. OpenAI has numerous trained models, the latest of which may not be listed here in examples.
You can get the current list of of available models for your license/API key using the following:
import openai
openai.api_key = "your key here"
openai.Model.list()
examples: ['davinci', 'gpt-4', 'text-davinci-001', 'text-search-curie-query-001', 'gpt-3.5-turbo', 'gpt-4-0613', 'babbage', 'text-babbage-001', 'curie-instruct-beta', 'davinci-similarity', 'code-davinci-edit-001', 'text-similarity-curie-001', 'ada-code-search-text', 'gpt-3.5-turbo-0613', 'text-search-ada-query-001', 'gpt-3.5-turbo-16k-0613', 'gpt-4-0314', 'babbage-search-query', 'ada-similarity', 'text-curie-001', 'gpt-3.5-turbo-16k', 'text-search-ada-doc-001', 'text-search-babbage-query-001', 'code-search-ada-code-001', 'curie-search-document', 'davinci-002', 'text-search-davinci-query-001', 'text-search-curie-doc-001', 'babbage-search-document', 'babbage-002', 'babbage-code-search-text', 'text-embedding-ada-002', 'davinci-instruct-beta', 'davinci-search-query', 'text-similarity-babbage-001', 'text-davinci-002', 'code-search-babbage-text-001', 'text-davinci-003', 'text-search-davinci-doc-001', 'code-search-ada-text-001', 'ada-search-query', 'text-similarity-ada-001', 'ada-code-search-code', 'whisper-1', 'text-davinci-edit-001', 'davinci-search-document', 'curie-search-query', 'babbage-similarity', 'ada', 'ada-search-document', 'text-ada-001', 'text-similarity-davinci-001', 'curie-similarity', 'babbage-code-search-code', 'code-search-babbage-code-001', 'text-search-babbage-doc-001', 'gpt-3.5-turbo-0301', 'curie']
default: "gpt-4-1106-preview"
the prompt or question to ask about the transcription/text
The OpenAI model is given text from the dialog and given this prompt to instruct it what generative AI text that you would like from it.
example:
default: "Summarize the transcript in these messages."
maximum number of tokens of output
The max_tokens limits the size of the output generative AI text. A token is approximately a syllable. On average a word is 1.33 tokens.
example:
default: 100
OpenAI sampling temperature
lower number is more deterministic, higher is more random.
values should range from 0.0 to 2.0
example:
default: 0.0
jq query of result
The OpenAI completion outputs a JSON Completion Object
The jq_results string contains a jq filter/query string that is applied to the output to determine what is saved in the created Vcon analysis object.
- "." - results in a query that returns the entire JSON object.
- ".choices[0].text" - results in a query which contains only the text portion of the completion output
For more information on creating jq filters see: https://jqlang.github.io/jq/manual/
examples: ['.', '.choices[0].text']
default: ".choices[0].message.content"
the Vcon analysis object type
The results of the completion are saved in a new analysis object which is added to the input Vcon. analysis_type is the analysis type token that is set on the new analysis object in the Vcon.
example:
default: "summary"
- OpenAI Completion filter method options
Options for generative AI using OpenAI completion (e.g. ChatGPT) on the text dialogs and/or transcription analysis in the given Vcon
More details on the OpenAI specific parameters can be found here: https://platform.openai.com/docs/api-reference/completions/create
input Vcon text dialog objects
Indicates which text dialog and recording dialog object's associated transcript analysis objects are to be input. Recording dialog objects that do not have transcript analysis objects, are transcribed using the default FilterPlugin transcribe type.
- "" (empty str or None) - all dialogs are fed into OpenAI model to complete the response to the prompt. This is the equivalent of providing "0:".
- n:m (str) - dialog objects having indices n-m are fed into OpenAI model to complete the response to the prompt
- n:m:i (str) - dialog objects having indices n-m using interval i are fed into OpenAI model to complete the response to the prompt
- [] (empty list[int]) - none of the dialog objects are fed to the the model.
- [1, 4, 5, 9] (list[int]) - the dialog objects having the indices in the given list are fed to the the model.
dialog objects in the given sequence or list which are not text or recording type dialogs are ignored.
examples: ['', '0:', '0:-2', '2:5', '0:6:2', [], [1, 4, 5, 9]]
default:
OpenAI model name to use for generative AI
The named model is used to feed the transcription/text and then ask it the given prompt. OpenAI has numerous trained models, the latest of which may not be listed here in examples.
You can get the current list of of available models for your license/API key using the following:
import openai
openai.api_key = "your key here"
openai.Model.list()
examples: ['davinci', 'gpt-4', 'text-davinci-001', 'text-search-curie-query-001', 'gpt-3.5-turbo', 'gpt-4-0613', 'babbage', 'text-babbage-001', 'curie-instruct-beta', 'davinci-similarity', 'code-davinci-edit-001', 'text-similarity-curie-001', 'ada-code-search-text', 'gpt-3.5-turbo-0613', 'text-search-ada-query-001', 'gpt-3.5-turbo-16k-0613', 'gpt-4-0314', 'babbage-search-query', 'ada-similarity', 'text-curie-001', 'gpt-3.5-turbo-16k', 'text-search-ada-doc-001', 'text-search-babbage-query-001', 'code-search-ada-code-001', 'curie-search-document', 'davinci-002', 'text-search-davinci-query-001', 'text-search-curie-doc-001', 'babbage-search-document', 'babbage-002', 'babbage-code-search-text', 'text-embedding-ada-002', 'davinci-instruct-beta', 'davinci-search-query', 'text-similarity-babbage-001', 'text-davinci-002', 'code-search-babbage-text-001', 'text-davinci-003', 'text-search-davinci-doc-001', 'code-search-ada-text-001', 'ada-search-query', 'text-similarity-ada-001', 'ada-code-search-code', 'whisper-1', 'text-davinci-edit-001', 'davinci-search-document', 'curie-search-query', 'babbage-similarity', 'ada', 'ada-search-document', 'text-ada-001', 'text-similarity-davinci-001', 'curie-similarity', 'babbage-code-search-code', 'code-search-babbage-code-001', 'text-search-babbage-doc-001', 'gpt-3.5-turbo-0301', 'curie']
default: "gpt-4-1106-preview"
the prompt or question to ask about the transcription/text
The OpenAI model is given text from the dialog and given this prompt to instruct it what generative AI text that you would like from it.
example:
default: "Summarize this conversation: "
maximum number of tokens of output
The max_tokens limits the size of the output generative AI text. A token is approximately a syllable. On average a word is 1.33 tokens.
example:
default: 100
OpenAI sampling temperature
lower number is more deterministic, higher is more random.
values should range from 0.0 to 2.0
example:
default: 0.0
jq query of result
The OpenAI completion outputs a JSON Completion Object
The jq_results string contains a jq filter/query string that is applied to the output to determine what is saved in the created Vcon analysis object.
- "." - results in a query that returns the entire JSON object.
- ".choices[0].text" - results in a query which contains only the text portion of the completion output
For more information on creating jq filters see: https://jqlang.github.io/jq/manual/
examples: ['.', '.choices[0].text']
default: ".choices[0].text"
the Vcon analysis object type
The results of the completion are saved in a new analysis object which is added to the input Vcon. analysis_type is the analysis type token that is set on the new analysis object in the Vcon.
example:
default: "summary"
- WhisperOptions
Options for transcribing the one or all dialogs in a Vcon using the OpenAI Whisper implementation.
transcription language None
example:
default: "en"
input Vcon recording dialog objects
Indicates which recording dialog objects in the given Vcon are to be transcribed.
- "" (empty str or None) - all recording dialogs are to be transcribed. This is the equivalent of providing "0:".
- n:m (str) - dialog objects having indices n-m are to be transcribed.
- n:m:i (str) - dialog objects having indices n-m using interval i are to be transcribed.
- [] (empty list[int]) - none of the dialog objects are to be transcribed.
- [1, 4, 5, 9] (list[int]) - the dialog objects having the indices in the given list are to be transcribed.
dialog objects in the given sequence or list which are not recording type dialogs are ignored.
examples: ['', '0:', '0:-2', '2:5', '0:6:2', [], [1, 4, 5, 9]]
default:
transcription output types
List of output types to generate. Current set of value supported are:
- "vendor" - add the Whisper specific JSON format transcript as an analysis object
- "word_srt" - add a .srt file with timing on a word or small phrase basis as an analysis object
- "word_ass" - add a .ass file with sentence and highlighted word timeing as an analysis object Not specifing "output_type" assumes all of the above will be output, each as a separate analysis object.
example:
default: ['vendor', 'word_srt', 'word_ass']