Change and Modify Pr 753 finance

examples/assistant_finance_bot.py

@@ -0,0 +1,158 @@
+# Copyright 2023 The Qwen team, Alibaba Group. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Example: Finance Assistant Bot using yfinance tool.
+
+This example demonstrates how to use the Finance tool to build a stock analysis assistant.
+
+Prerequisites:
+    pip install yfinance
+
+Usage:
+    python assistant_finance_bot.py
+
+You can ask questions like:
+    - "What's the current price of AAPL?"
+    - "Show me Tesla's stock history for the past 3 months"
+    - "Give me financial information about Microsoft"
+    - "Compare the PE ratios of GOOGL and META"
+    - "What's Alibaba's market cap? (use 9988.HK or BABA)"
+    - "What's Toyota's market info? (use 7203.T)"
+"""
+
+from qwen_agent.agents import Assistant
+from qwen_agent.utils.output_beautify import typewriter_print
+from qwen_agent.gui import WebUI
+
+def main():
+    # Step 1: Configure the LLM
+    llm_cfg = {
+        # Use DashScope model service:
+        #'model': 'qwen-max-latest',
+        #'model_type': 'qwen_dashscope',
+        # 'api_key': 'YOUR_DASHSCOPE_API_KEY',  # Uses DASHSCOPE_API_KEY env var if not set
+
+        # Or use OpenAI-compatible API (e.g., vLLM, Ollama):
+        'model': 'Qwen3-Next-80B-A3B',
+        'model_server': 'http://localhost:8080/', # local llama server
+        'api_key': 'EMPTY',
+
+        'generate_cfg': {
+            'top_p': 0.8,
+        }
+    }
+
+    # Step 2: Define the system message for the finance assistant
+    system_message = '''You are a professional financial analyst assistant. You have access to real-time stock market data through the finance tool.
+
+When users ask about stocks or financial data:
+1. Use the finance tool to retrieve accurate, up-to-date information
+2. Present the data in a clear, organized manner
+3. Provide brief analysis or context when appropriate
+4. If comparing multiple stocks, present the data in a comparable format
+
+For stock symbols:
+- US stocks: Use standard tickers (AAPL, GOOGL, MSFT, TSLA, etc.)
+- Hong Kong stocks: Add .HK suffix (9988.HK for Alibaba HK)
+- Chinese A-shares: Use .SS for Shanghai (600519.SS) or .SZ for Shenzhen (000001.SZ)
+- Tokyo stocks: Add .T suffix (7203.T for Toyota Motor Japan)
+
+Available actions for the finance tool:
+- "price": Get current stock price and trading info
+- "history": Get historical price data (specify period like "1mo", "3mo", "1y")
+- "info": Get detailed company information
+- "financials": Get financial statements summary
+
+Always be helpful and explain financial terms when needed.'''
+
+    # Step 3: Create the assistant with the finance tool
+    tools = ['finance']
+    bot = Assistant(
+        llm=llm_cfg,
+        system_message=system_message,
+        function_list=tools,
+    )
+
+    # Step 4: Run the chatbot
+    messages = []
+    print('=' * 60)
+    print('Finance Assistant Bot')
+    print('=' * 60)
+    print('Ask me about stocks, prices, company info, or financials!')
+    print('Examples:')
+    print('  - "What is Apple\'s current stock price?"')
+    print('  - "Show me TSLA history for the past month"')
+    print('  - "Tell me about Microsoft\'s financials"')
+    print('Type "exit" to quit.')
+    print('=' * 60)
+
+    while True:
+        query = input('\nYou: ').strip()
+        if not query:
+            continue
+        if query.lower() in ['exit', 'quit', 'bye']:
+            print('Goodbye!')
+            break
+
+        messages.append({'role': 'user', 'content': query})
+        response = []
+        response_plain_text = ''
+        print('\nAssistant: ', end='', flush=True)
+        for response in bot.run(messages=messages):
+            response_plain_text = typewriter_print(response, response_plain_text)
+        messages.extend(response)
+        print()
+
+def app_gui():
+    llm_cfg = {
+        # Use DashScope model service:
+        #'model': 'qwen-max-latest',
+        #'model_type': 'qwen_dashscope',
+        # 'api_key': 'YOUR_DASHSCOPE_API_KEY',  # Uses DASHSCOPE_API_KEY env var if not set
+
+        # Or use OpenAI-compatible API (e.g., vLLM, Ollama):
+        'model': 'Qwen3-Next-80B-A3B',
+        'model_server': 'http://localhost:8080/', # local llama server
+        'api_key': 'EMPTY',
+
+        'generate_cfg': {
+            'top_p': 0.8,
+        }
+    }
+    # Define the agent
+    tools = ['finance']
+    bot = Assistant(
+        llm=llm_cfg,
+    #    system_message=system_message,
+        function_list=tools,
+        name='Qwen3 finance Demo',
+        description="I'm a demo using the Qwen3 tool finance",
+    )
+
+    chatbot_config = {
+        'prompt.suggestions': [
+            'What is Apple\'s current stock price?',
+            'Show me TSLA history for the past month',
+            'Tell me about Microsoft\'s financials',
+            'トヨタ自動車の配当について教えてください。'
+        ]
+    }
+    WebUI(
+        bot,
+        chatbot_config=chatbot_config,
+    ).run()
+
+if __name__ == '__main__':
+    #main()
+    app_gui()

qwen_agent/tools/__init__.py

@@ -14,6 +14,7 @@
 
 from .amap_weather import AmapWeather
 from .base import TOOL_REGISTRY, BaseTool
+from .finance import Finance
 from .code_interpreter import CodeInterpreter
 from .doc_parser import DocParser
 from .extract_doc_vocabulary import ExtractDocVocabulary
@@ -34,6 +35,7 @@
     'CodeInterpreter',
     'ImageGen',
     'AmapWeather',
+    'Finance',
     'TOOL_REGISTRY',
     'DocParser',
     'KeywordSearch',