Merge pull request #9 from dosaboy/fix-pkg

Changes for packaging and unit-tests

.dockerignore

@@ -0,0 +1 @@
+.tox

pyproject.toml

@@ -25,6 +25,9 @@ dependencies = [
   "transformers",
 ]
 
+[tool.flit.module]
+name = "support_ai"
+
 [project.scripts]
 ai-bot = "support_ai.ai_bot:main"
 ds-updater = "support_ai.ds_updater:main"

src/support_ai/ai_bot.py → support_ai/ai_bot.py

@@ -5,8 +5,8 @@
 import argparse
 import uuid
 
-from .lib.chain import Chain
-from .utils import get_config
+from support_ai.lib.chain import Chain
+from support_ai.utils import get_config
 
 
 def parse_args():

src/support_ai/api_server.py → support_ai/api_server.py

@@ -1,16 +1,13 @@
 """
 Support-AI API Server
 """
-
 import argparse
 
 from flask import Blueprint, Flask, jsonify, request, Response
 from flask_restful import Api, Resource
-
-from .lib import const
-from .lib.chain import Chain
-from .utils import get_config
-
+from support_ai.lib import const
+from support_ai.lib.chain import Chain
+from support_ai.utils import get_config
 
 app = Flask(__name__)
 chain = None  # pylint: disable=invalid-name

src/support_ai/ds_updater.py → support_ai/ds_updater.py

@@ -7,8 +7,8 @@
 import sys
 import time
 
-from .lib.datasources.ds_updater import DSUpdater
-from .utils import get_config
+from support_ai.lib.datasources.ds_updater import DSUpdater
+from support_ai.utils import get_config
 
 
 def parse_args():

src/support_ai/lib/chain.py → support_ai/lib/chain.py

@@ -2,10 +2,10 @@
 Chain Module for Processing Queries with Context and Memory
 """
 
-from . import const
-from .context import BaseContext
-from .datasources.ds_querier import DSQuerier
-from .memory import Memory
+from support_ai.lib import const
+from support_ai.lib.context import BaseContext
+from support_ai.lib.datasources.ds_querier import DSQuerier
+from support_ai.lib.memory import Memory
 
 
 class Chain(BaseContext):

src/support_ai/lib/context.py → support_ai/lib/context.py

@@ -4,7 +4,7 @@
 a ModelManager instance.
 """
 
-from .model_manager.model_manager import ModelManager
+from support_ai.lib.model_manager.model_manager import ModelManager
 
 
 class BaseContext:  # pylint: disable=too-few-public-methods

src/support_ai/lib/datasources/ds_querier.py → support_ai/lib/datasources/ds_querier.py

@@ -3,15 +3,13 @@
 querying different data sources based on the provided configuration
 and user queries.
 """
-
 from langchain_core.prompts import PromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.runnables import RunnablePassthrough
-
-from .. import const
-from ..context import BaseContext
-from ..vectorstore import VectorStore
-from .utils import get_datasources
+from support_ai.lib import const
+from support_ai.lib.context import BaseContext
+from support_ai.lib.vectorstore import VectorStore
+from support_ai.lib.datasources.utils import get_datasources
 
 
 CLASSIFICATION_PROMPT = """

src/support_ai/lib/datasources/ds_updater.py → support_ai/lib/datasources/ds_updater.py

@@ -7,10 +7,10 @@
 import threading
 from datetime import datetime, timedelta
 
-from ..const import META_DIR
-from ..context import BaseContext
-from ..vectorstore import VectorStore
-from .utils import get_datasources
+from support_ai.lib.const import META_DIR
+from support_ai.lib.context import BaseContext
+from support_ai.lib.vectorstore import VectorStore
+from support_ai.lib.datasources.utils import get_datasources
 
 
 UPDATE_TIME = META_DIR + 'update_time'

src/support_ai/lib/datasources/kb.py → support_ai/lib/datasources/kb.py

@@ -2,19 +2,17 @@
 This module provides functionality for interacting with a Salesforce
 Knowledge Base,
 """
-
 from html.parser import HTMLParser
 from io import StringIO
 
 import simple_salesforce
 from langchain_core.prompts import PromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.runnables import RunnablePassthrough
-
-from .. import const
-from ..context import BaseContext
-from ..utils.lru import timed_lru_cache
-from .ds import Data, Content, Datasource
+from support_ai.lib import const
+from support_ai.lib.context import BaseContext
+from support_ai.lib.utils.lru import timed_lru_cache
+from support_ai.lib.datasources.ds import Data, Content, Datasource
 
 
 QUESTIONS_PROMPT = """

src/support_ai/lib/datasources/salesforce.py → support_ai/lib/datasources/salesforce.py

@@ -10,13 +10,15 @@
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.runnables import RunnablePassthrough
 from langchain_text_splitters import RecursiveCharacterTextSplitter
-
-from .. import const
-from ..context import BaseContext
-from ..utils.docs_chain import docs_refine
-from ..utils.lru import timed_lru_cache
-from ..utils.parallel_executor import run_fn_in_parallel, run_in_parallel
-from .ds import Data, Content, Datasource
+from support_ai.lib import const
+from support_ai.lib.context import BaseContext
+from support_ai.lib.utils.docs_chain import docs_refine
+from support_ai.lib.utils.lru import timed_lru_cache
+from support_ai.lib.utils.parallel_executor import (
+  run_fn_in_parallel,
+  run_in_parallel,
+)
+from support_ai.lib.datasources.ds import Data, Content, Datasource
 
 
 SYMPTOM_INITIAL_PROMPT = """Summarize symptom of the following content:

src/support_ai/lib/datasources/utils.py → support_ai/lib/datasources/utils.py

@@ -2,10 +2,9 @@
 This module provides functionality to retrieve and instantiate data sources
 based on the configuration provided.
 """
-
-from .. import const
-from .kb import KnowledgeBaseSource
-from .salesforce import SalesforceSource
+from support_ai.lib import const
+from support_ai.lib.datasources.kb import KnowledgeBaseSource
+from support_ai.lib.datasources.salesforce import SalesforceSource
 
 _ds_mapping: dict = {
     const.CONFIG_SF: SalesforceSource,

src/support_ai/lib/memory.py → support_ai/lib/memory.py

@@ -2,7 +2,6 @@
 This module provides a memory management class that stores and retrieves
 conversation history in a MongoDB database.
 """
-
 from operator import itemgetter
 from threading import Lock
 
@@ -13,8 +12,7 @@
 from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.runnables import RunnableLambda, RunnablePassthrough
-
-from . import const
+from support_ai.lib import const
 
 
 class Memory:

src/support_ai/lib/model_manager/huggingface_factory.py → support_ai/lib/model_manager/huggingface_factory.py

@@ -2,12 +2,10 @@
 This module provides a factory for creating Hugging Face-based
 language models and embeddings.
 """
-
 from langchain_community.llms import HuggingFacePipeline
 from langchain_community.embeddings import HuggingFaceEmbeddings
-
-from .. import const
-from .model_factory import ModelFactory
+from support_ai.lib import const
+from support_ai.lib.model_manager.model_factory import ModelFactory
 
 
 class HuggingFaceFactory(ModelFactory):

src/support_ai/lib/model_manager/llamacpp_factory.py → support_ai/lib/model_manager/llamacpp_factory.py

@@ -3,12 +3,10 @@
 This module provides a factory for creating LlamaCpp-based language models
 and embeddings.
 """
-
 from langchain_community.llms import LlamaCpp
 from langchain_community.embeddings import LlamaCppEmbeddings
-
-from .. import const
-from .model_factory import ModelFactory
+from support_ai.lib import const
+from support_ai.lib.model_manager.model_factory import ModelFactory
 
 
 class LlamaCppFactory(ModelFactory):

src/support_ai/lib/model_manager/model_manager.py → support_ai/lib/model_manager/model_manager.py

@@ -2,18 +2,16 @@
 This module defines functionality for managing language models and
 embeddings configurations.
 """
-
 from dataclasses import dataclass
 
 from langchain_core.embeddings import Embeddings
 from langchain_core.language_models.llms import BaseLLM
-
-from .. import const
-from .huggingface_factory import HuggingFaceFactory
-from .llamacpp_factory import LlamaCppFactory
-from .ollama_factory import OllamaFactory
-from .openai_factory import OpenAIFactory
-from .remote_factory import RemoteFactory
+from support_ai.lib import const
+from support_ai.lib.model_manager.huggingface_factory import HuggingFaceFactory
+from support_ai.lib.model_manager.llamacpp_factory import LlamaCppFactory
+from support_ai.lib.model_manager.ollama_factory import OllamaFactory
+from support_ai.lib.model_manager.openai_factory import OpenAIFactory
+from support_ai.lib.model_manager.remote_factory import RemoteFactory
 
 
 LLM_CONFIG = 'llm_config'

src/support_ai/lib/model_manager/ollama_factory.py → support_ai/lib/model_manager/ollama_factory.py

@@ -2,12 +2,10 @@
 This module provides a factory for creating Ollama-based chat models
 and embeddings.
 """
-
 from langchain_community.chat_models import ChatOllama
 from langchain_community.embeddings import OllamaEmbeddings
-
-from .. import const
-from .model_factory import ModelFactory
+from support_ai.lib import const
+from support_ai.lib.model_manager.model_factory import ModelFactory
 
 
 class OllamaFactory(ModelFactory):

src/support_ai/lib/model_manager/openai_factory.py → support_ai/lib/model_manager/openai_factory.py

@@ -2,12 +2,10 @@
 This module provides the OpenAIFactory class, which is a factory for creating
 OpenAI language models and embeddings based on configuration settings.
 """
-
 from langchain_community.llms import OpenAI
 from langchain_community.embeddings import OpenAIEmbeddings
-
-from .. import const
-from .model_factory import ModelFactory
+from support_ai.lib import const
+from support_ai.lib.model_manager.model_factory import ModelFactory
 
 
 class OpenAIFactory(ModelFactory):

src/support_ai/lib/model_manager/remote_factory.py → support_ai/lib/model_manager/remote_factory.py

@@ -2,7 +2,6 @@
 This module contains classes for interacting with remote language models and
 embeddings via HTTP requests.
 """
-
 import json
 from typing import Any, List, Mapping, Optional
 
@@ -11,9 +10,8 @@
 from langchain_core.embeddings import Embeddings
 from langchain_core.language_models.llms import LLM
 from pydantic import BaseModel
-
-from .. import const
-from .model_factory import ModelFactory
+from support_ai.lib import const
+from support_ai.lib.model_manager.model_factory import ModelFactory
 
 
 class RemoteLLM(LLM):

src/support_ai/lib/vectorstore.py → support_ai/lib/vectorstore.py

@@ -5,8 +5,7 @@
 import os
 
 from langchain_community.vectorstores import Chroma
-
-from . import const
+from support_ai.lib import const
 
 VECTORDB_DIR = const.META_DIR + 'vectordb'
 COLLECTION_METADATA = 'collection_metadata'

src/support_ai/utils.py → support_ai/utils.py

@@ -5,8 +5,7 @@
 import pkgutil
 
 import yaml
-
-from .lib import const
+from support_ai.lib import const
 
 
 def get_config(path):

tests/unit/test_supportai.py

@@ -1,16 +1,23 @@
 """ SupportAI Unit Tests """
 import unittest
+from unittest import mock
+
+from support_ai import ai_bot
+
+# pylint: disable=no-self-use
 
 
 class TestSupportAI(unittest.TestCase):
     """ Unit Tests for Support AI. """
-    def setUp(self) -> None:
-        pass
-
-    def tearDown(self):
-        pass
 
-    def test_ai_bot(self):
+    @mock.patch('support_ai.ai_bot.input')
+    @mock.patch.object(ai_bot, 'parse_args')
+    @mock.patch.object(ai_bot, 'get_config')
+    @mock.patch.object(ai_bot, 'Chain')
+    def test_ai_bot_quit(self, _mock_chain, _mock_get_config, _mock_parse_args,
+                         mock_input):
         """
-        THIS IS A PLACEHOLDER TEST UNTIL WE GET SOME REAL TESTS IMPLEMENTED.
+        Test api bot quit.
         """
+        mock_input.return_value = 'quit'
+        ai_bot.main()

tox.ini

@@ -20,7 +20,7 @@ import-order-style = pep8
 basepython = {env:TOX_PYTHON:python3}
 unit_tests = {toxinidir}/tests/unit/
 pyfiles =
-    {toxinidir}/src/support_ai {[testenv]unit_tests}
+    {toxinidir}/support_ai {[testenv]unit_tests}
 setenv = 
     PYTHONHASHSEED=0
 deps =