106 lines
3.4 KiB
Python
106 lines
3.4 KiB
Python
import json # Import the json module
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from qwen_agent.agents import Assistant
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# Define LLM
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llm_cfg = {
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'model': 'qwen3:0.6B',
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# Use the endpoint provided by Alibaba Model Studio:
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# 'model_type': 'qwen_dashscope',
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# 'api_key': os.getenv('DASHSCOPE_API_KEY'),
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# Use a custom endpoint compatible with OpenAI API:
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'model_server': 'http://localhost:11434/v1', # api_base
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'api_key': 'EMPTY',
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# Other parameters:
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# 'generate_cfg': {
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# # Add: When the response content is `<think>this is the thought</think>this is the answer;
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# # Do not add: When the response has been separated by reasoning_content and content.
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# 'thought_in_content': True,
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# },
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}
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# Define Tools
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tools = [
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{'mcpServers': { # You can specify the MCP configuration file
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'time': {
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'command': 'uvx',
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'args': ['mcp-server-time', '--local-timezone=Asia/Shanghai']
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},
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"fetch": {
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"command": "uvx",
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"args": ["mcp-server-fetch"]
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},
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"ddg-search": {
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"command": "npx",
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"args": ["-y", "@oevortex/ddg_search"]
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},
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}
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},
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'code_interpreter', # Built-in tools
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]
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# Define Agent
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bot = Assistant(llm=llm_cfg, function_list=tools)
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# Streaming generation
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messages = [{'role': 'user',
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'content':
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""""
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Write a 500 word blog post about the latest qwen 3 model.
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Use the search tool, and fetch the top 3 articles before you write the post.
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Write in a casual, but factual style - no hyperbole.
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Provide urls to the webpages in the output."""}]
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final_responses = None
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# Add comprehensive error handling around bot.run
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try:
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timeout = 300 # 5 minute timeout
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final_responses = None
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partial_responses = []
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for responses in bot.run(messages=messages, enable_thinking=True, max_tokens=30000, timeout=timeout):
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print(".", end="", flush=True)
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partial_responses.append(responses)
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final_responses = responses.pop()
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except TimeoutError:
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print("\nRequest timed out after {} seconds".format(timeout))
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except ConnectionError as ce:
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print(f"\nConnection error occurred: {ce}")
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except ValueError as ve:
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print(f"\nInvalid input or response format: {ve}")
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except Exception as e:
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print(f"\nAn unexpected error occurred: {e}")
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finally:
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if partial_responses and not final_responses:
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try:
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final_responses = partial_responses[-1].pop()
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except (IndexError, AttributeError):
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print("\nFailed to recover partial response")
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# Pretty-print the final response object with validation
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if final_responses:
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print("\n--- Full Response Object ---")
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try:
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if isinstance(final_responses, dict):
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print(json.dumps(final_responses, indent=2))
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else:
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print("Response is not in expected format:", type(final_responses))
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print("\n--- Extracted Content ---")
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if isinstance(final_responses, dict):
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content = final_responses.get('content')
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if content:
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print(content)
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else:
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print("No content field found in response")
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else:
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print("Cannot extract content from invalid response format")
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except json.JSONDecodeError as je:
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print(f"Failed to format response: {je}")
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else:
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print("\nNo final response received from the agent.")
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