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import requests
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from flask import Flask, request, jsonify,render_template
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from flask_cors import CORS
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import time
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import pandas as pd
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app = Flask(__name__)
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CORS(app)
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app.static_folder = 'static'
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# Define the Rasa server URL
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rasa_server_url = "http://localhost:5005/webhooks/rest/webhook"
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@app.route("/")
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def home():
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return render_template("index.html")
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@app.route('/webhook', methods=['POST','GET'])
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def webhook():
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user_ip = request.remote_addr
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print("user ip is :",user_ip)
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message = request.json['message']
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#recipient_id = request.json['recipient_id']
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# Send the message to the Rasa server
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rasa_response = requests.post(rasa_server_url, json={"message": message,"sender":user_ip}).json()
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# Return the Rasa response as a JSON object
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print(rasa_response)
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if len(rasa_response)==0:
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return jsonify([
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{
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"recipient_id": "default",
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"text": "I'm sorry, I didn't understand that. Can you please rephrase?"
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}])
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else:
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return jsonify(rasa_response)
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@app.route("/get")
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def get_bot_response():
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userText = request.args.get('msg')
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return chatbot_response(userText)
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if __name__ == '__main__':
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app.run(host='0.0.0.0',port=5020)
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# The config recipe.
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# https://rasa.com/docs/rasa/model-configuration/
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recipe: default.v1
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# The assistant project unique identifier
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# This default value must be replaced with a unique assistant name within your deployment
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assistant_id: 20230807-114046-drab-rectangle
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# Configuration for Rasa NLU.
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# https://rasa.com/docs/rasa/nlu/components/
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language: en
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pipeline: null
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# # No configuration for the NLU pipeline was provided. The following default pipeline was used to train your model.
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# # If you'd like to customize it, uncomment and adjust the pipeline.
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# # See https://rasa.com/docs/rasa/tuning-your-model for more information.
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# - name: WhitespaceTokenizer
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# - name: RegexFeaturizer
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# - name: LexicalSyntacticFeaturizer
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# - name: CountVectorsFeaturizer
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# - name: CountVectorsFeaturizer
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# analyzer: char_wb
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# min_ngram: 1
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# max_ngram: 4
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# - name: DIETClassifier
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# epochs: 100
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# constrain_similarities: true
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# - name: EntitySynonymMapper
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# - name: ResponseSelector
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# epochs: 100
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# constrain_similarities: true
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# - name: FallbackClassifier
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# threshold: 0.3
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# ambiguity_threshold: 0.1
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# Configuration for Rasa Core.
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# https://rasa.com/docs/rasa/core/policies/
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policies:
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- name: RulePolicy
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# This file contains the credentials for the voice & chat platforms
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# which your bot is using.
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# https://rasa.com/docs/rasa/messaging-and-voice-channels
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rest:
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# # you don't need to provide anything here - this channel doesn't
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# # require any credentials
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#facebook:
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# verify: "<verify>"
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# secret: "<your secret>"
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# page-access-token: "<your page access token>"
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#slack:
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# slack_token: "<your slack token>"
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# slack_channel: "<the slack channel>"
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# slack_signing_secret: "<your slack signing secret>"
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#socketio:
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# user_message_evt: <event name for user message>
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# bot_message_evt: <event name for bot messages>
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# session_persistence: <true/false>
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#mattermost:
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# url: "https://<mattermost instance>/api/v4"
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# token: "<bot token>"
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# webhook_url: "<callback URL>"
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# This entry is needed if you are using Rasa Enterprise. The entry represents credentials
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# for the Rasa Enterprise "channel", i.e. Talk to your bot and Share with guest testers.
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rasa:
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url: "http://localhost:5002/api"
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version: "3.1"
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intents:
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- greet
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- goodbye
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- affirm
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- deny
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- mood_great
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- mood_unhappy
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- bot_challenge
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- request_names
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entities:
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- first_name
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- last_name
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- phone_num
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- email_id
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slots:
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first_name:
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type: text
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influence_conversation: true
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mappings:
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- type: from_text
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conditions:
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- active_loop: name_form
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requested_slot: first_name
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last_name:
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type: text
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influence_conversation: true
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mappings:
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- type: from_text
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conditions:
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- active_loop: name_form
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requested_slot: last_name
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phone_num:
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type: text
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influence_conversation: true
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mappings:
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- type: from_text
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conditions:
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- active_loop: name_form
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requested_slot: phone_num
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email_id:
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type: text
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influence_conversation: true
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mappings:
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- type: from_text
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conditions:
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- active_loop: name_form
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requested_slot: email_id
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forms:
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name_form:
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required_slots:
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- first_name
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- last_name
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- phone_num
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- email_id
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responses:
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utter_greet:
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- text: "Hey! How are you?"
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utter_cheer_up:
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- text: "Here is something to cheer you up:"
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image: "https://i.imgur.com/nGF1K8f.jpg"
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utter_did_that_help:
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- text: "Did that help you?"
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utter_happy:
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- text: "Great, carry on!"
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utter_goodbye:
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- text: "Bye"
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utter_iamabot:
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- text: "I am a bot, powered by Rasa."
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utter_ask_first_name:
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- text: "What is your first name?"
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utter_ask_last_name:
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- text: "What is your last name?"
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utter_ask_phone_num:
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- text: "What is your phone number?"
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utter_ask_email_id:
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- text: "What is your email id?"
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utter_submit:
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- text: Ok. Thanks!
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utter_slots_values:
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- text: I will remember that your name is {first_name} {last_name} number {phone_num} and id is {email_id}!
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actions:
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- utter_slots_values
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- utter_submit
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- get_slot_data
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- slots_to_clear
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session_config:
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session_expiration_time: 60
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carry_over_slots_to_new_session: true
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@@ -0,0 +1,42 @@
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# This file contains the different endpoints your bot can use.
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# Server where the models are pulled from.
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# https://rasa.com/docs/rasa/model-storage#fetching-models-from-a-server
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#models:
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# url: http://my-server.com/models/default_core@latest
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# wait_time_between_pulls: 10 # [optional](default: 100)
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# Server which runs your custom actions.
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# https://rasa.com/docs/rasa/custom-actions
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action_endpoint:
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url: "http://localhost:5055/webhook"
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# Tracker store which is used to store the conversations.
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# By default the conversations are stored in memory.
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# https://rasa.com/docs/rasa/tracker-stores
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#tracker_store:
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# type: redis
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# url: <host of the redis instance, e.g. localhost>
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# port: <port of your redis instance, usually 6379>
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# db: <number of your database within redis, e.g. 0>
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# password: <password used for authentication>
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# use_ssl: <whether or not the communication is encrypted, default false>
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#tracker_store:
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# type: mongod
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# url: <url to your mongo instance, e.g. mongodb://localhost:27017>
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# db: <name of the db within your mongo instance, e.g. rasa>
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# username: <username used for authentication>
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# password: <password used for authentication>
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# Event broker which all conversation events should be streamed to.
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# https://rasa.com/docs/rasa/event-brokers
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#event_broker:
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# url: localhost
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# username: username
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# password: password
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# queue: queue
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