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Willem van den Ende 2025-04-30 15:23:29 +01:00
parent 7fa0c78298
commit acfd344f88
1 changed files with 17 additions and 16 deletions
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agentic_search.py
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@ -1,4 +1,5 @@
import json # Import the json module import json # Import the json module
from qwen_agent.agents import Assistant from qwen_agent.agents import Assistant
# Define LLM # Define LLM
@ -24,44 +25,44 @@ llm_cfg = {
# Define Tools # Define Tools
tools = [ tools = [
{'mcpServers': { # You can specify the MCP configuration file {'mcpServers': { # You can specify the MCP configuration file
'time': { 'time': {
'command': 'uvx', 'command': 'uvx',
'args': ['mcp-server-time', '--local-timezone=Asia/Shanghai'] 'args': ['mcp-server-time', '--local-timezone=Asia/Shanghai']
}, },
"fetch": { "fetch": {
"command": "uvx", "command": "uvx",
"args": ["mcp-server-fetch"] "args": ["mcp-server-fetch"]
}, },
"ddg-search": { "ddg-search": {
"command": "uvx", "command": "uvx",
"args": ["duckduckgo-mcp-server"] "args": ["duckduckgo-mcp-server"]
}
} }
}
}, },
'code_interpreter', # Built-in tools 'code_interpreter', # Built-in tools
] ]
# Define Agent # Define Agent
bot = Assistant(llm=llm_cfg, function_list=tools) bot = Assistant(llm=llm_cfg, function_list=tools)
# Streaming generation # Streaming generation
messages = [{'role': 'user', 'content': 'Write a 500 word blog post about the latest qwen 3 model. Use the search tool, and fetch the top 3 articles before you write the post. Write in a casual, but factual style - no hyperbole. Provide references to the webpages in the output.'}] messages = [{'role': 'user',
'content': 'Write a 500 word blog post about the latest qwen 3 model. Use the search tool, and fetch the top 3 articles before you write the post. Write in a casual, but factual style - no hyperbole. Provide references to the webpages in the output.'}]
final_responses = None final_responses = None
# Consider adding error handling around bot.run # Consider adding error handling around bot.run
try: try:
for responses in bot.run(messages=messages, enable_thinking=True, max_tokens=30000): for responses in bot.run(messages=messages, enable_thinking=True, max_tokens=30000):
print(".",end="", flush=True) print(".", end="", flush=True)
final_responses = responses.pop() final_responses = responses.pop()
except Exception as e: except Exception as e:
print(f"An error occurred during agent execution: {e}") print(f"An error occurred during agent execution: {e}")
# Pretty-print the final response object # Pretty-print the final response object
if final_responses: if final_responses:
print("--- Full Response Object ---") print("--- Full Response Object ---")
print(json.dumps(final_responses, indent=2)) # Use indent=2 (or 4) for pretty printing print(json.dumps(final_responses, indent=2)) # Use indent=2 (or 4) for pretty printing
print("\n--- Extracted Content ---") print("\n--- Extracted Content ---")
print(final_responses.get('content', 'No content found in response.')) # Use .get for safer access print(final_responses.get('content', 'No content found in response.')) # Use .get for safer access
else: else:
print("No final response received from the agent.") print("No final response received from the agent.")