Refactor project into layered prototype structure

README.md

@@ -11,3 +11,14 @@ license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+## Repository layout
+
+The prototype is now organized into lightweight layers to keep responsibilities clear even in a demo setting:
+
+- `application/` – orchestration services that combine prompts with infrastructure adapters.
+- `infrastructure/` – clients for external APIs and market data providers (Featherless, Coinlore, etc.).
+- `presentation/` – Gradio components, dashboards, and CSS themes displayed in the Space UI.
+- `domain/` – placeholder for future data models specific to the investment analytics domain.
+
+`app.py` wires these pieces together to expose the multi-tab Gradio experience on Hugging Face Spaces.

app.py

@@ -1,11 +1,17 @@
 import gradio as gr
-from services.llm_client import llm_service
-from core.analyzer import PortfolioAnalyzer
-from core.comparer import PortfolioComparer
-from core.chat import ChatAssistant
-from core.metrics import show_metrics_table
-from core.crypto_dashboard import build_crypto_dashboard  # Plotly dashboard + KPI-line
-from core.visual_comparison import build_price_chart, build_volatility_chart  # Interactive pair comparison
+
+from application.chat_assistant import ChatAssistant
+from application.metrics_table import show_metrics_table
+from application.portfolio_analyzer import PortfolioAnalyzer
+from application.portfolio_comparer import PortfolioComparer
+from infrastructure.llm_client import llm_service
+from presentation.components.crypto_dashboard import (
+    build_crypto_dashboard,
+)  # Plotly dashboard + KPI-line
+from presentation.components.visual_comparison import (
+    build_price_chart,
+    build_volatility_chart,
+)  # Interactive pair comparison
 
 # === CSS loader ===
 def load_css(path: str) -> str:
@@ -13,8 +19,8 @@ def load_css(path: str) -> str:
         return f.read()
 
 # === Styles ===
-base_css   = load_css("core/styles/base.css")
-crypto_css = load_css("core/styles/crypto_dashboard.css")
+base_css = load_css("presentation/styles/themes/base.css")
+crypto_css = load_css("presentation/styles/themes/crypto_dashboard.css")
 
 # === Model setup ===
 MODEL_NAME = "meta-llama/Meta-Llama-3.1-8B-Instruct"
@@ -44,7 +50,7 @@ with gr.Blocks(css=base_css) as demo:
 
         # --- Comparison Table ---
         with gr.TabItem("Comparison Table"):
-            from core.comparison_table import show_comparison_table
+            from presentation.components.comparison_table import show_comparison_table
             pid_a = gr.Textbox(label="Portfolio A", value="3852a354-e66e-4bc5-97e9-55124e31e687")
             pid_b = gr.Textbox(label="Portfolio B", value="b1ef37aa-5b9a-41b4-8823f2de36bb")
             compare_btn = gr.Button("Load Comparison", variant="primary")

application/__init__.py

@@ -0,0 +1,13 @@
+"""Application layer services orchestrating domain and infrastructure."""
+
+from .chat_assistant import ChatAssistant
+from .metrics_table import show_metrics_table
+from .portfolio_analyzer import PortfolioAnalyzer
+from .portfolio_comparer import PortfolioComparer
+
+__all__ = [
+    "ChatAssistant",
+    "PortfolioAnalyzer",
+    "PortfolioComparer",
+    "show_metrics_table",
+]

core/chat.py → application/chat_assistant.py

@@ -7,7 +7,8 @@ Purpose: General chat interface for user questions about investments or portfoli
 """
 
 from typing import Generator
-from services.llm_client import llm_service
+
+from infrastructure.llm_client import llm_service
 from prompts.system_prompts import GENERAL_CONTEXT
 
 

core/metrics.py → application/metrics_table.py

@@ -6,9 +6,11 @@ Purpose: Provides async utilities to fetch and display portfolio metrics as a Da
 Назначение: предоставляет асинхронные функции для получения и отображения метрик портфеля в виде DataFrame.
 """
 
-import pandas as pd
 import asyncio
-from services.output_api import extract_portfolio_id, fetch_metrics_async
+
+import pandas as pd
+
+from infrastructure.output_api import extract_portfolio_id, fetch_metrics_async
 
 
 def show_metrics_table(portfolio_input: str):

core/analyzer.py → application/portfolio_analyzer.py

@@ -8,8 +8,9 @@ Purpose: Handles single-portfolio analysis using LLM. Fetches metrics, builds pr
 
 import asyncio
 from typing import Generator
-from services.output_api import extract_portfolio_id, fetch_metrics_async
-from services.llm_client import llm_service
+
+from infrastructure.output_api import extract_portfolio_id, fetch_metrics_async
+from infrastructure.llm_client import llm_service
 from prompts.system_prompts import ANALYSIS_SYSTEM_PROMPT
 from prompts.reference_templates import REFERENCE_PROMPT
 

core/comparer.py → application/portfolio_comparer.py

@@ -8,8 +8,9 @@ Purpose: Compares two portfolios using LLM. Fetches metrics for both and builds
 
 import asyncio
 from typing import Generator
-from services.output_api import extract_portfolio_id, fetch_metrics_async
-from services.llm_client import llm_service
+
+from infrastructure.output_api import extract_portfolio_id, fetch_metrics_async
+from infrastructure.llm_client import llm_service
 from prompts.system_prompts import COMPARISON_SYSTEM_PROMPT
 from prompts.reference_templates import REFERENCE_COMPARISON_PROMPT
 

core/__init__.py

@@ -1,2 +1,13 @@
-# __init__.py
-# Marks this directory as a Python package.
+"""Legacy compatibility layer bridging old imports to the new structure."""
+
+from application.chat_assistant import ChatAssistant
+from application.metrics_table import show_metrics_table
+from application.portfolio_analyzer import PortfolioAnalyzer
+from application.portfolio_comparer import PortfolioComparer
+
+__all__ = [
+    "ChatAssistant",
+    "PortfolioAnalyzer",
+    "PortfolioComparer",
+    "show_metrics_table",
+]

domain/__init__.py

@@ -0,0 +1,3 @@
+"""Domain layer placeholder for future data models in the prototype."""
+
+__all__: list[str] = []

infrastructure/__init__.py

@@ -0,0 +1,18 @@
+"""Infrastructure adapters for external services and data providers."""
+
+from . import market_data
+from .llm_client import FeatherlessLLM, llm_service
+from .output_api import (
+    extract_portfolio_id,
+    fetch_absolute_pnl_async,
+    fetch_metrics_async,
+)
+
+__all__ = [
+    "FeatherlessLLM",
+    "llm_service",
+    "extract_portfolio_id",
+    "fetch_absolute_pnl_async",
+    "fetch_metrics_async",
+    "market_data",
+]

infrastructure/market_data/__init__.py

@@ -0,0 +1,5 @@
+"""Market data providers used across the prototype."""
+
+from . import binance, coinlore, yfinance
+
+__all__ = ["binance", "coinlore", "yfinance"]

presentation/__init__.py

@@ -0,0 +1,5 @@
+"""Presentation layer: UI components, charts, and styles."""
+
+from . import components, styles
+
+__all__ = ["components", "styles"]

presentation/components/__init__.py

@@ -0,0 +1,12 @@
+"""Individual UI components used by the Gradio interface."""
+
+from .comparison_table import show_comparison_table
+from .crypto_dashboard import build_crypto_dashboard
+from .visual_comparison import build_price_chart, build_volatility_chart
+
+__all__ = [
+    "show_comparison_table",
+    "build_crypto_dashboard",
+    "build_price_chart",
+    "build_volatility_chart",
+]

{core → presentation/components}/comparison_table.py

@@ -6,10 +6,12 @@ Purpose: Generates comparative DataFrame for two portfolios and an LLM commentar
 Назначение: создаёт сравнительную таблицу метрик двух портфелей и комментарий LLM.
 """
 
-import pandas as pd
 import asyncio
-from services.output_api import fetch_metrics_async, extract_portfolio_id
-from services.llm_client import llm_service
+
+import pandas as pd
+
+from infrastructure.llm_client import llm_service
+from infrastructure.output_api import extract_portfolio_id, fetch_metrics_async
 from prompts.system_prompts import COMPARISON_SYSTEM_PROMPT
 
 

{core → presentation/components}/crypto_dashboard.py

@@ -5,9 +5,11 @@ Crypto Dashboard — Plotly Edition (clean layout)
 • без глобального Markdown-заголовка
 """
 import requests
+
 import pandas as pd
 import plotly.express as px
-from services.llm_client import llm_service
+
+from infrastructure.llm_client import llm_service
 
 
 def fetch_coinlore_data(limit=100):

presentation/styles/__init__.py

@@ -0,0 +1,5 @@
+"""Static style assets for the presentation layer."""
+
+__all__ = [
+    "themes",
+]

presentation/styles/themes/__init__.py

@@ -0,0 +1,3 @@
+"""Theme CSS assets for the presentation layer."""
+
+__all__: list[str] = []

services/__init__.py

@@ -1,2 +0,0 @@
-# __init__.py
-# Marks this directory as a Python package.