Hi, im using rasa 3 and i’m trying to implement a custom graph component for sentiment analysis. I’m using a pretrained model with vadersentiment. My sentiment.py code : from __future__ import annotations from rasa.engine.graph import GraphComponent, ExecutionContext from rasa.shared.nlu.training_data.training_data import TrainingData from rasa.engine.recipes.default_recipe import DefaultV1Recipe 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.storage import ModelStorage from rasa.shared.nlu.training_data.message import Message from rasa.shared.nlu.constants import TEXT from rasa.nlu.extractors.extractor import EntityExtractorMixin from nltk.sentiment.vader import SentimentIntensityAnalyzer @DefaultV1Recipe.register( DefaultV1Recipe.ComponentType.ENTITY_EXTRACTOR, is_trainable=False ) class SentimentAnalyzer(GraphComponent, EntityExtractorMixin): """A pre-trained sentiment component""" name = "sentiment" provides = ["entities"] requires = [] defaults = {} language_list = ["en"] 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: TrainingData) -> Resource: 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, messages: List[Message]) -> List[Message]: """Retrieve the text message, pass it to the classifier and append the prediction results to the message class.""" sid = SentimentIntensityAnalyzer() for message in messages: res = sid.polarity_scores(message.get(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) return messages def persist(self, file_name, model_dir): """Pass because a pre-trained model is already persisted""" pass I have this errors : 2022-01-14 15:05:34 ERROR rasa.server - An unexpected error occurred. Error: Error running graph component for node run_sentiment.SentimentAnalyzer9. 2022-01-14 15:05:34 ERROR rasa.core.training.interactive - An exception occurred while recording messages. Traceback (most recent call last): File "c:\users\hp\pycharmprojects\newpr\venv\li…

Hello and Welcome to the forum @Alaa . Can you confirm that you are running rasa action server at the back end? Can you even share me the rasa --version whilst activating the environment? If you can share me the tutorial link which you are following that will be great for me to comment or suggest. Thanks.

Hi, nik202 and Thank you for the answer. I’m using rasa 3. Yes, i’m running rasa action server at the back end. I followed this tutorial “ How to Enhance Rasa NLU Models with Custom Components | Rasa Blog | The Rasa Blog | Rasa ”, but i needed to modify the code, because the tutorial is too old and don’t work for rasa 3

@Alaa Yeps, I’m aware of this blog post. @Alaa I’d recommend to please use rasa 2.x as the original blog post was initially developed on 2. x or please check the Juste repo on GitHub or even you can tag her here. I can only help you here on this itself as I didn’t work on this personally. But, I tried my level best to help you. Good Luck!

pinging @Fares for the suggestion and help, please :slight_smile: I hope you don’t mind?

@Fares Thank you for the prompt reply Ben :slight_smile: and wish you a very awesome 2022 :bouquet::pray:

thanks Nik , thanks Fares. I will change my Rasa version from 3 to 2.8 and try the code that Fares sent me

@Alaa great, please do remember to close this thread as solution and good luck!

Hi all, I was just wondering whether downgrading to RASA 2.8 is the only solution or whether there is a way to run sentiment analysis also with RASA 3.0? Thank you!

Custom graph component for sentiment analysis

Rasa Open Source

Fares (Ben Ayed) January 14, 2022, 9:17pm 7

I’d recommend to use rasa 2.8 and try this Pretrained sentiment component nltk and if you have any error please let me know

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Custom graph component for sentiment analysis

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