Hi, i am using Rasa 3 but i didn’t manage to implement a sentiment analysis vader sentiment . I didn’t understand how it works … Is it possible to have a tutorial détailed about it? How to use graph component. How to find the way to put from something import SentimentAnalyzer ? Thank you for all your effort for rasa and i hope i will quickly understand all of this ^^

Hello @Hajer and welcome to the forum! You can start with this blog post: How to Enhance Rasa NLU Models with Custom Components | Rasa Blog | The Rasa Blog | Rasa hope this will give you a better idea.

Thank you Nik202 but the version of rasa is 2 not 3. I already read it.

@Hajer Hmmm…but try to implement and see the results, coding will be the same?

Graph component is here to connect a new node with other components. In graphcomponent class, i put : from nltk.sentiment.vader import SentimentIntensityAnalyzer In sentiment.py i don’t know how to call SentimentIntensityAnalyzer… do i have to put from rasa.models import SentimentIntensityAnalyzer ?? but it doesn’t work … I don’t understand this part.

share the complete code? import nltk from nltk.sentiment.vader import SentimentIntensityAnalyzer OR pip install vaderSentiment from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer

Yes okay from __future__ import annotations from typing import Dict, Text, Any from rasa.engine.graph import GraphComponent, ExecutionContext from rasa.engine.storage.resource import Resource from rasa.engine.storage.storage import ModelStorage #from rasa.models import SentimentIntensityAnalyzer import os from pathlib import Path from rasa.shared.nlu.training_data.training_data import TrainingData from rasa.engine.recipes.default_recipe import DefaultV1Recipe import json @DefaultV1Recipe.register( DefaultV1Recipe.ComponentType.MODEL_LOADER, is_trainable=True ) class SentimentAnalyzer(GraphComponent, SentimentIntensityAnalyzer): """A pre-trained sentiment component""" name = "sentiment" provides = ["entities"] requires = [] defaults = {} language_list = ["fr"] def __init__(self, component_config= Dict[Text, Any]) -> None: self.component_config = component_config @classmethod def create( cls, config: Dict[Text, Any], model_storage: ModelStorage, resource: Resource, execution_context: ExecutionContext, ) -> GraphComponent: return cls(config) def train(self, training_data, cfg, **kwargs): """Load the sentiment polarity labels from the text file, retrieve training tokens and after formatting data train the classifier.""" pass def convert_to_rasa(self, value, confidence): """Convert model output into the Rasa NLU compatible output format.""" entity = {"value": value, "confidence": confidence, "entity": "sentiment", "extractor": "sentiment_extractor"} return entity def process(self, message, **kwargs): """Retrieve the text message, pass it to the classifier and append the prediction results to the message class.""" sid = SentimentIntensityAnalyzer() res = sid.polarity_scores(message.text) key, value = max(res.items(), key=lambda x: x[1]) entity = self.convert_to_rasa(key, value) message.set("entities", [entity], add_to_output=True) def persist(self, file_name, model_dir): """Pass because a pre-trained model is already persisted""" pass @classmethod def load( cls, config: Dict[Text, Any], model_storage: ModelStorage, resource: Resource, execution_context: ExecutionContext, **kwargs: Any, ) -> SentimentAnalyzer: model_data = {} try: with model_storage.read_from(resource) as path: model_data_file = path / "model_data.json" model_data = json.loads(rasa.shared.utils.io.read_file(model_data_file)) except (ValueError, FileNotFoundError, FileIOException): logger.debug( f"Couldn't load metadata for component '{cls.__name__}' as the persisted " f"model data couldn't be loaded." ) return cls( config, model_data=model_data ) from __future__ import annotations import nltk from nltk.sentiment.vader import SentimentIntensityAnalyzer from typing import List, Type, Dict, Text, Any, Optional from rasa.engine.graph import ExecutionContext from rasa.engine.storage.resource import Resource from rasa.engine.storage.st…

@Hajer please check the above post of mine, and please format the code for me in a single one.

I dit import nltk from nltk.sentiment.vader import SentimentIntensityAnalyzer I put the two code in one code. i hope it’s okay now. Thank you for your help

when i run my code, i got this message : GraphSchemaValidationException: Your model uses a graph component ‘SentimentAnalyzer’ which does not have the required method ‘provide’. Please make sure you’re either using the right component or that your component is registered with the correct component type.See Custom Graph Components for more information. import nltk from nltk.sentiment.vader import SentimentIntensityAnalyzer these sentences i put them in graph component if i am not wrong. I think it’s because i have to replace this : from rasa.models import SentimentIntensityAnalyzer by something else in sentiment.py

Custom graph component

Rasa Open Source

nik202 (NiK202) December 16, 2021, 12:09pm 10

@Hajer can you check this thread and code used? Sentiment component - #20 by Fares

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Custom graph component

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