Metadata-Version: 2.1
Name: dfagent
Version: 0.1
Summary: Dialogflow agent is a library for online or offline handling of Dialogflow agents.
Home-page: https://github.com/aitechnologies-it/dialogflow-agent
Author: Luigi Di Sotto, Diego Giorgini
Author-email: luigi.disotto@aitechnologies.it, diego.giorgini@aitechnologies.it
License: UNKNOWN
Description: # dfagent 🤖
        The dfagent is a package for the handling of Dialogflow agents. You can for example retrieve training examples and save into a preferred format, or you can use it to update an intent by simply feeding it training examples you stored in a preferred format.
        
        ## Overview
        
        * [dfagent/](dfagent) contains all the core code to extend dfagent.
        
        ## Install
        
        To install the dfagent package you only need to run [install.sh](install.sh) script.
        
        ## Usage
        Once dfagent is installed you can simply import it in your code. 
        
        ### Save training phrases [remote]
        
        The following snippet illustrates a simple example to get and save training examples from an online Dialogflow agent.
        
        To create a Dialogflow agent you only need that
        
        ```Python
        import dfagent
        
        agent = dfagent.DialogFlowAgent(
            local_path_or_url='my_gcp_project_id',
            service_account='path/to/sa.json',
            content_type='json',
            output_format='default'
        )
        ```
        
        Then you can get a list of dialogflow examples for saving as follows
        
        ```Python
        examples = agent.get_training_examples()
        agent.save_training_examples(examples, output_dir='path/to/dir')
        ```
        
        ### Update intent with new training phrases [remote]
        
        In the following is a snippet that illustrates an example to update a remote Dialogflow agent using training phrases you stored as a raw text file. Remember that dfagent can be extended to support any input or output file format.
        
        Once you instante a df agent
        
        ```Python
        import dfagent
        
        agent = dfagent.DialogFlowAgent(
            local_path_or_url='my_gcp_project_id',
            service_account='path/to/sa.json',
            input_format='default',
        )
        ```
        
        You can update your remote Dialoflow agent in that way
        
        ```Python
        response, raw_examples, df_examples = agent.add_training_examples(
            intent_name='help.cooking',
            input_dir_or_file='path/to/phrases.train',
            lang='en'
        )
        ```
        
        ### From local or zip
        
        In case you already have exported your Dialogflow on your local computer, you can give as local_path_or_url the path to the zip or unzipped exported agent.
        
        ```Python
        import dfagent
        
        agent = dfagent.DialogFlowAgent(
            local_path_or_url='path/to/myagent.zip',
            ...
        )
        ```
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.8
Description-Content-Type: text/markdown
