[feat] add GH Action testing mongo class

.github/workflows/python-app.yml

@@ -5,7 +5,7 @@ name: Python application
 
 on:
   push:
-    branches: [ "main" ]
+    branches: [ "main", "dev" ]
   pull_request:
     branches: [ "main" ]
 
@@ -26,14 +26,10 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
+        pip install poetry
+        poetry lock
+        poetry install
         pip install flake8 pytest
-        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
-    - name: Lint with flake8
-      run: |
-        # stop the build if there are Python syntax errors or undefined names
-        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
-        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
-        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
     - name: Test with pytest
       run: |
-        pytest
+        poetry run pytest

src/api/controllers/__init__.py

@@ -0,0 +1,3 @@
+from .chat import new_message as chat_new_message
+
+__all__ = ["chat_new_message"]

src/api/controllers/chat.py

@@ -0,0 +1,23 @@
+from src.infrastructure.database import MongoDB, get_service_details
+from src.infrastructure.config import LLM
+from src.services import CustomChat
+
+
+async def new_message(
+    db: MongoDB,
+    model: LLM,
+    message: str,
+    service_name: str,
+) -> str:
+
+    if service_details := get_service_details(service_name, db):
+        prompt = service_details["prompt"]
+    else:
+        prompt = "You are a helpful assistant. Be kind!"
+
+    chat = CustomChat(
+        model=model,
+        sys_prompt=prompt
+    )
+    response = await chat(message)
+    return response

src/api/models/__init__.py

@@ -0,0 +1,3 @@
+from .api import APIResponse, APIRequest
+
+__all__ = ["APIResponse", "APIRequest"]

src/api/models/api.py

@@ -0,0 +1,14 @@
+from typing import Optional
+from pydantic import BaseModel
+
+
+class APIResponse(BaseModel):
+    status_code: int
+    status_message: Optional[str] = None
+    response: Optional[dict] = None
+
+
+class APIRequest(BaseModel):
+    message: str
+    user_id: str
+    service_name: Optional[str] = None

src/api/routes/chat.py

@@ -0,0 +1,44 @@
+from fastapi import APIRouter, status, Request, Depends
+
+from src.api.models import APIResponse, APIRequest
+from src.api.controllers import chat_new_message
+
+
+router = APIRouter(
+    prefix="/chat",
+    tags=["chat"],
+    # dependencies=[Depends(validate_user)]
+)
+
+
+@router.get("/", status_code=status.HTTP_200_OK)
+async def router_test() -> APIResponse:
+    return APIResponse(
+        status_code=200,
+        status_message="-- CHAT ROUTER WORKING! --"
+    )
+
+
+@router.post("/new_message", status_code=status.HTTP_200_OK)
+async def new_message(api_request: APIRequest, req: Request) -> APIResponse:
+    try:
+        response = await chat_new_message(
+            req.app.database,
+            req.app.llm,
+            api_request.message,
+            api_request.service_name
+        )
+
+        return APIResponse(
+            status_code=200,
+            response={
+                "user": api_request.message,
+                "ai": response
+            }
+        )
+
+    except Exception as e:
+        return APIResponse(
+            status_code=500,
+            status_message=f"Error: {e}"
+        )

src/infrastructure/config/__init__.py

@@ -0,0 +1,4 @@
+from .settings import settings
+from .llm import LLM
+
+__all__ = ["settings", "LLM"]

src/infrastructure/config/llm.py

@@ -0,0 +1,31 @@
+from .settings import settings
+
+from langchain_ollama.llms import OllamaLLM
+from langchain_openai import ChatOpenAI
+
+
+class LLM:
+    def __new__(cls, model_name: str):
+        try:
+            if model_name == "ollama":
+                return OllamaLLM(
+                    model=settings.MODEL_NAME,
+                    base_url=settings.MODEL_URL,
+                    temperature=settings.MODEL_TEMPERATURE
+                )
+
+            elif model_name == "openai":
+                return ChatOpenAI(
+                    model=settings.MODEL_NAME,
+                    base_url=settings.MODEL_URL,
+                    temperature=settings.MODEL_TEMPERATURE,
+                    api_key=settings.MODEL_API_KEY
+                )
+            # More models can be added here
+
+            raise ValueError(f"Model {model_name} not supported")
+
+        except Exception as e:
+            raise ValueError(
+                f"Problem instantiating the model {model_name}: {e}"
+            )

src/infrastructure/config/settings.py

@@ -0,0 +1,33 @@
+from pydantic_settings import BaseSettings
+
+
+class Settings(BaseSettings):
+
+    # MongoDB
+    MONGO_USER: str
+    MONGO_PASSWORD: str
+    MONGO_HOST: str = "localhost"
+    MONGO_PORT: str = "27017"
+    MONGO_DB: str
+
+    # ChromaDB
+    CHROMA_HOST: str = "localhost"
+    CHROMA_PORT: str = "8000"
+    CHROMA_DB: str
+
+    # General Settings
+    TIMEZONE: str = "America/Sao_Paulo"
+
+    # LLM
+    MODEL: str = "ollama"
+    MODEL_NAME: str = "llama3"
+    MODEL_URL: str = "http://localhost:11434"
+    MODEL_TEMPERATURE: float = 0.2
+    MODEL_API_KEY: str = ''
+
+    class Config:
+        env_file = ".env"
+        extra = "ignore"
+
+
+settings = Settings()

src/services/__init__.py

@@ -0,0 +1,3 @@
+from .custom_chat.chat import CustomChat
+
+__all__ = ["CustomChat"]

src/services/custom_chat/chat.py

@@ -0,0 +1,23 @@
+from src.infrastructure.config import LLM
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.tools import BaseTool
+from typing import List
+
+
+class CustomChat:
+    def __init__(self, model: LLM, sys_prompt: str):
+        self.model = model
+        self.sys_prompt = sys_prompt
+        self._prompt_template = ChatPromptTemplate.from_messages([
+            ("system", self.sys_prompt),
+            ("user", "{input}")
+        ])
+
+    async def __call__(self, user_input: str):
+        # TO DO: add bind_tools
+        self.chain = self._prompt_template | self.model
+        response = self.chain.invoke({"input": user_input})
+        return response
+
+    def add_tools(self, tools: List[BaseTool]):
+        pass

src/services/custom_chat/tools.py

@@ -0,0 +1,4 @@
+"""
+TO DO:
+    - Pode-se adicionar tools para dar um bind_tools no modelo.
+"""