New stcructure v1.2

.idea/TradeLinkAI.iml

@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module version="4">
+  <component name="PyDocumentationSettings">
+    <option name="format" value="PLAIN" />
+    <option name="myDocStringFormat" value="Plain" />
+  </component>
+</module>

app.py

@@ -3,82 +3,51 @@ from services.llm_client import llm_service
 from core.analyzer import PortfolioAnalyzer
 from core.comparer import PortfolioComparer
 from core.chat import ChatAssistant
-from core.visualization import build_alpha_chart
 from core.metrics import show_metrics_table
+from core.visualization import build_alpha_chart
 
 # === Model setup ===
-MODEL_NAME = "mistralai/Mixtral-8x7B-Instruct"
+MODEL_NAME = "meta-llama/Meta-Llama-3.1-8B-Instruct"
 
 # === Use case classes ===
 analyzer = PortfolioAnalyzer(llm_service, MODEL_NAME)
 comparer = PortfolioComparer(llm_service, MODEL_NAME)
 chatbot = ChatAssistant(llm_service, MODEL_NAME)
 
-
 # === Gradio Interface ===
-with gr.Blocks() as demo:
-    gr.Markdown("## 🧠 TradeLink AI Analyzer — Portfolio Intelligence")
-
-    # --- Tab: Single Portfolio Analysis ---
-    with gr.Tab("📊 Portfolio Analysis"):
-        portfolio_input = gr.Textbox(label="Enter portfolioId or link")
-        analyze_button = gr.Button("🔍 Analyze")
-        analyze_output = gr.Textbox(label="Analysis Result", lines=15)
-
-        analyze_button.click(
-            fn=analyzer.run,
-            inputs=portfolio_input,
-            outputs=analyze_output,
-        )
-
-    # --- Tab: Comparison ---
-    with gr.Tab("⚖️ Portfolio Comparison"):
-        compare_input_1 = gr.Textbox(label="Portfolio A")
-        compare_input_2 = gr.Textbox(label="Portfolio B")
-        compare_button = gr.Button("📈 Compare")
-        compare_output = gr.Textbox(label="Comparison Result", lines=20)
-
-        compare_button.click(
-            fn=comparer.run,
-            inputs=[compare_input_1, compare_input_2],
-            outputs=compare_output,
-        )
-
-    # --- Tab: Chat Assistant ---
-    with gr.Tab("💬 Chat Assistant"):
-        chat_input = gr.Textbox(label="Ask about TradeLink")
-        chat_button = gr.Button("Send")
-        chat_output = gr.Textbox(label="Response", lines=10)
-
-        chat_button.click(
-            fn=chatbot.run,
-            inputs=chat_input,
-            outputs=chat_output,
-        )
-
-    # --- Tab: Metrics Table ---
-    with gr.Tab("📋 Metrics Table"):
-        metrics_input = gr.Textbox(label="Enter portfolioId")
-        metrics_button = gr.Button("Show Metrics")
-        metrics_output = gr.Dataframe(label="Portfolio Metrics")
-
-        metrics_button.click(
-            fn=show_metrics_table,
-            inputs=metrics_input,
-            outputs=metrics_output,
-        )
-
-    # --- Tab: AlphaBTC Chart ---
-    with gr.Tab("📈 AlphaBTC Chart"):
-        chart_input = gr.Textbox(label="Portfolio ID", value="3852a354-e66e-4bc5-97e9-55124e31e687")
-        chart_button = gr.Button("Plot Chart")
-        chart_output = gr.Plot(label="Alpha vs BTC")
-
-        chart_button.click(
-            fn=build_alpha_chart,
-            inputs=chart_input,
-            outputs=chart_output,
-        )
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("## 🧠 Анализ и сравнение инвестиционных портфелей **TradeLink**")
+
+    with gr.Tab("📊 Анализ"):
+        portfolio_input = gr.Textbox(label="Введите ссылку или portfolioId", placeholder="ea856c1b-...")
+        analyze_button = gr.Button("🔍 Проанализировать")
+        analyze_output = gr.Textbox(label="📈 Результат анализа", lines=15)
+        analyze_button.click(fn=analyzer.run, inputs=portfolio_input, outputs=analyze_output)
+
+    with gr.Tab("⚖️ Сравнение"):
+        compare_input_1 = gr.Textbox(label="Портфель 1", placeholder="ea856c1b-...")
+        compare_input_2 = gr.Textbox(label="Портфель 2", placeholder="d52f55cc-...")
+        compare_button = gr.Button("📊 Сравнить")
+        compare_output = gr.Textbox(label="📉 Результат сравнения", lines=20)
+        compare_button.click(fn=comparer.run, inputs=[compare_input_1, compare_input_2], outputs=compare_output)
+
+    with gr.Tab("💬 Диалог"):
+        chat_input = gr.Textbox(label="Ваш вопрос", placeholder="Что такое TradeLink Passport?")
+        chat_button = gr.Button("Отправить")
+        chat_output = gr.Textbox(label="Ответ", lines=8)
+        chat_button.click(fn=chatbot.run, inputs=chat_input, outputs=chat_output)
+
+    with gr.Tab("📋 Таблица метрик"):
+        metrics_input = gr.Textbox(label="Введите portfolioId", placeholder="ea856c1b-...")
+        metrics_button = gr.Button("📥 Показать метрики")
+        metrics_output = gr.Dataframe(label="📊 Метрики портфеля", wrap=True)
+        metrics_button.click(fn=show_metrics_table, inputs=metrics_input, outputs=metrics_output)
+
+    with gr.Tab("📈 AlphaBTC график"):
+        chart_input = gr.Textbox(label="Введите portfolioId", value="3852a354-e66e-4bc5-97e9-55124e31e687")
+        chart_button = gr.Button("Построить график")
+        chart_output = gr.Plot(label="График Alpha к BTC")
+        chart_button.click(fn=build_alpha_chart, inputs=chart_input, outputs=chart_output)
 
 if __name__ == "__main__":
     demo.launch()

core/analyzer.py

@@ -9,7 +9,7 @@ Purpose: Handles single-portfolio analysis using LLM. Fetches metrics, builds pr
 import asyncio
 from typing import Generator
 from services.tradelink_api import extract_portfolio_id, fetch_metrics_async
-from services.llm_client import LLMAdapter
+from services.llm_client import llm_service  # Hugging Face client
 from prompts.system_prompts import ANALYSIS_SYSTEM_PROMPT
 from prompts.reference_templates import REFERENCE_PROMPT
 
@@ -17,7 +17,8 @@ from prompts.reference_templates import REFERENCE_PROMPT
 class PortfolioAnalyzer:
     """Main use-case class for analyzing a single portfolio."""
 
-    def __init__(self, llm: LLMAdapter, model_name: str):
+    def __init__(self, llm=llm_service, model_name: str = "mistralai/Mixtral-8x7B-Instruct"):
+        # llm must expose .stream_chat(messages=list[dict], model=str) -> Iterable[str]
         self.llm = llm
         self.model_name = model_name
 
@@ -39,7 +40,8 @@ class PortfolioAnalyzer:
             yield "❗ Unable to retrieve metrics from API."
             return
 
-        metrics_text = ", ".join([f"{k}: {v}" for k, v in metrics.items()])
+        # Build prompt text from metrics
+        metrics_text = ", ".join(f"{k}: {v}" for k, v in metrics.items())
         prompt = f"{REFERENCE_PROMPT}\n\nUse this data for analysis:\n{metrics_text}"
 
         try: