v0.8 (#3)

README.md

@@ -1,19 +1,19 @@
-# DFF Project Template
+# Chatsky Project Template
 
-This repository is a template for DFF projects.
+This repository is a template for Chatsky projects.
 
 ## How to use it
 
 ### Clone the repo:
 
 ```shell
-git clone https://github.com/deeppavlov/DFF-template.git
-cd DFF-template
+git clone https://github.com/deeppavlov/chatsky-template.git
+cd chatsky-template
 ```
 
 Alternatively, you can create a new repository using this one as a template via GitHub:
 
-https://github.com/new?template_name=DFF-template&template_owner=deeppavlov
+https://github.com/new?template_name=chatsky-template&template_owner=deeppavlov
 
 ### Edit project files
 
@@ -22,7 +22,7 @@ https://github.com/new?template_name=DFF-template&template_owner=deeppavlov
    (cd services/bot && pip install -r requirements.txt)
    ```
 1. Write your custom functions (e.g. custom responses, custom services) into `bot/custom`.
-2. Edit DFF script at `bot/script.py`.
+2. Edit Chatsky script at `bot/script.py`.
 3. Save Telegram bot token into `secrets/tg_token.txt`. (currently this template only supports telegram bots)
 
 ### Test the bot

services/bot/Dockerfile

@@ -1,7 +1,7 @@
 # syntax=docker/dockerfile:1
 FROM python as base
 
-WORKDIR /dff_pipeline
+WORKDIR /chatsky_pipeline
 
 COPY requirements.txt requirements.txt
 RUN ["python", "-m", "pip", "install", "-r", "requirements.txt"]

services/bot/bot/custom/conditions.py

@@ -1,4 +1,4 @@
-from dff.script import Context
+from chatsky.script import Context
 
 
 def is_upper_case(ctx: Context, pipeline):

services/bot/bot/pipeline.py

@@ -1,8 +1,8 @@
 import os
 
-from dff.pipeline import Pipeline
-from dff.context_storages import context_storage_factory
-from dff.messengers.telegram import PollingTelegramInterface
+from chatsky.pipeline import Pipeline
+from chatsky.context_storages import context_storage_factory
+from chatsky.messengers.telegram import LongpollingInterface
 
 from . import script
 
@@ -24,7 +24,7 @@ def get_variable(var_name: str):
 messenger_interface = None
 
 if TG_BOT_TOKEN is not None:
-    messenger_interface = PollingTelegramInterface(token=TG_BOT_TOKEN)
+    messenger_interface = LongpollingInterface(token=TG_BOT_TOKEN)
 
 
 pipeline = Pipeline.from_script(

services/bot/bot/script.py

@@ -1,6 +1,6 @@
-from dff.script import Message
-from dff.script import RESPONSE, TRANSITIONS, LOCAL
-from dff.script.conditions import exact_match, true
+from chatsky.script import Message
+from chatsky.script import RESPONSE, TRANSITIONS, LOCAL
+from chatsky.script.conditions import exact_match, true
 
 from .custom.conditions import is_upper_case
 from .custom.services import pre_service, post_service
@@ -11,7 +11,7 @@
     "technical_flow": {
         "start_node": {
             TRANSITIONS: {
-                ("main_flow", "greeting_node"): exact_match(Message("/start")),
+                ("main_flow", "greeting_node"): exact_match("/start"),
             },
         },
         "fallback": {

services/bot/requirements.txt

@@ -1,2 +1,2 @@
-dff[telegram,sqlite]~=0.7
+chatsky[telegram,sqlite]~=0.8
 pytest

services/bot/test.py

@@ -1,8 +1,7 @@
 from json import load
 from pathlib import Path
 
-from dff.utils.testing import check_happy_path
-from dff.script import Message
+from chatsky.utils.testing import check_happy_path
 import pytest
 
 from .bot.pipeline import pipeline
@@ -22,4 +21,4 @@
     "happy_path", TEST_CASES
 )
 def test_happy_paths(happy_path: str):
-    check_happy_path(pipeline, tuple(map(lambda l: (Message(text=l[0]), Message(text=l[1])), TEST_DATA[happy_path])))
+    check_happy_path(pipeline, TEST_DATA[happy_path])