Implementing python processors.

.editorconfig

@@ -4,7 +4,8 @@ root = true
 [*]
 charset = utf-8
 indent_style = space
-indent_size = 2
+indent_size = 
+
 insert_final_newline = true
 trim_trailing_whitespace = true
 

.gitignore

@@ -38,4 +38,7 @@ testem.log
 .DS_Store
 Thumbs.db
 
-.nx/cache
+.nx/cache
+
+.cache
+unittests/

apps/backend/tests/test_hello.py

@@ -1,7 +1,18 @@
 """Hello unit test module."""
-
+import pytest
 from libs.py_core.py_core.hello import hello
+from libs.py_core.py_core.system.processor import ChildCardRecommendationGenerator
+
 
 def test_hello():
     """Test the hello function."""
     assert hello() == "Hello aacesstalk-backend"
+
+
+@pytest.mark.asyncio
+async def test_processor():
+    child_card_recommender = ChildCardRecommendationGenerator()
+
+    card_recommendation_result = await child_card_recommender.generate()
+
+    print(card_recommendation_result)

libs/py_core/py_core/system/model.py

@@ -0,0 +1,47 @@
+from enum import StrEnum
+from typing import Literal, TypeAlias
+from nanoid import generate
+
+from pydantic import BaseModel, ConfigDict, TypeAdapter, Field
+
+
+class ChildCardRecommendationResult(BaseModel):
+    model_config = ConfigDict(frozen=True)
+
+    nouns: list[str]
+    emotions: list[str]
+    actions: list[str]
+
+
+class ParentGuidanceElement(BaseModel):
+    model_config = ConfigDict(frozen=True)
+
+    example: str
+    guidance: str
+
+
+class ParentRecommendationResult(BaseModel):
+    model_config = ConfigDict(frozen=True)
+
+    recommendations: list[ParentGuidanceElement]
+
+
+class DialogueRole(StrEnum):
+    model_config = ConfigDict(frozen=True)
+
+    Parent = "parent"
+    Child = "child"
+
+
+class DialogueMessage(BaseModel):
+    model_config = ConfigDict(frozen=True)
+
+    id: str = Field(default_factory=lambda: generate(size=20))
+    speaker: Literal["parent", "child"]
+    content: str | list[str]
+    recommendation_id: str
+
+
+Dialogue: TypeAlias = list[DialogueMessage]
+
+DialogueTypeAdapter = TypeAdapter(Dialogue)

libs/py_core/py_core/system/processor.py

@@ -0,0 +1,37 @@
+from typing import Any
+
+from chatlib.tool.versatile_mapper import ChatCompletionFewShotMapper, ChatCompletionFewShotMapperParams
+from chatlib.tool.converter import generate_pydantic_converter
+from chatlib.llm.integration.openai_api import GPTChatCompletionAPI, ChatGPTModel
+
+from libs.py_core.py_core.system.model import ChildCardRecommendationResult, Dialogue, DialogueMessage, DialogueRole
+
+
+class ChildCardRecommendationGenerator:
+
+    def __init__(self):
+        str_output_converter, output_str_converter = generate_pydantic_converter(ChildCardRecommendationResult)
+
+        self.__mapper: ChatCompletionFewShotMapper[Dialogue, ChildCardRecommendationResult, Any] = (
+            ChatCompletionFewShotMapper(GPTChatCompletionAPI(),
+                                        instruction_generator=f"""
+                                        You are a helpful assistant that serves as an Alternative Augmented Communication tool.
+Suppose that you are helping a communication with a child and parents in Korean. The autistic child has the language proficiency of a 6 to 8-year-old in Korean, so recommendations should consider their cognitive level.
+Given the last message of the parents, suggest a list of keywords that can help the child pick to create a sentence as an answer.
+Proceed in the following order.
+1. [nouns] : Provide nouns that reflect detailed context based on your parents' questions.
+2. [actions] : Provide words for the action that can be matched with the nouns suggested in [nouns].
+3. [emotions] : Suggest emotions that the child might want to express in the situation, including both positive and negative emotions and needs.
+Note that the output must be JSON, formatted like the following:
+{ChildCardRecommendationResult.schema_json()}
+The result should be in Korean and please provide up to four options for each element.
+                                        """,
+                                        input_str_converter=lambda dialogue, params: dialogue.json(),
+                                        output_str_converter=output_str_converter,
+                                        str_output_converter=str_output_converter
+                                        ))
+
+    async def generate(self) -> ChildCardRecommendationResult:
+        return await self.__mapper.run(None, input=[DialogueMessage(speaker=DialogueRole.Parent, content="오늘 학교에서 뭐 했어?")],
+                                       params=ChatCompletionFewShotMapperParams(model = ChatGPTModel.GPT_4_0125, api_params={}))
+

libs/py_core/pyproject.toml

@@ -23,7 +23,8 @@ readme = 'README.md'
   [tool.poetry.dependencies]
   python = ">=3.11.8,<3.12"
   pendulum = "^3.0.0"
-  chatlib = {git = "https://github.com/yghokim/chatlib.git", tag="0.6.8"}
+  chatlib = {git = "https://github.com/yghokim/chatlib.git", tag="0.7.0"}
+  pydantic = "^2.6.4"
 
   [tool.poetry.group.dev.dependencies]
   autopep8 = "2.0.2"

libs/py_core/test.py

@@ -0,0 +1,15 @@
+from chatlib.llm.integration.openai_api import GPTChatCompletionAPI
+
+from libs.py_core.py_core.system.processor import ChildCardRecommendationGenerator
+
+
+async def test_processor():
+
+    GPTChatCompletionAPI.authorize()
+
+    child_card_recommender = ChildCardRecommendationGenerator()
+
+    card_recommendation_result = await child_card_recommender.generate()
+
+    print(card_recommendation_result)
+

libs/py_core/tests/test_hello.py

@@ -1,8 +1,11 @@
 """Hello unit test module."""
 
+import pytest
 from libs.py_core.py_core.hello import hello
+from libs.py_core.py_core.system.processor import ChildCardRecommendationGenerator
 
 
 def test_hello():
     """Test the hello function."""
     assert hello() == "Hello py-core"
+