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docs: add tool calling example in Tongyi chat model integration. (#20925)
**Description:** add tool calling example in Tongyi chat model integration. **Issue:** None **Dependencies:** None
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@ -142,11 +142,70 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"cell_type": "markdown",
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"metadata": {},
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"outputs": [],
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"source": []
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"source": [
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"## Tool Calling\n",
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"ChatTongyi supports tool calling API that lets you describe tools and their arguments, and have the model return a JSON object with a tool to invoke and the inputs to that tool."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"AIMessage(content='', additional_kwargs={'tool_calls': [{'function': {'name': 'get_current_weather', 'arguments': '{\"location\": \"San Francisco\"}'}, 'id': '', 'type': 'function'}]}, response_metadata={'model_name': 'qwen-turbo', 'finish_reason': 'tool_calls', 'request_id': 'dae79197-8780-9b7e-8c15-6a83e2a53534', 'token_usage': {'input_tokens': 229, 'output_tokens': 19, 'total_tokens': 248}}, id='run-9e06f837-582b-473b-bb1f-5e99a68ecc10-0', tool_calls=[{'name': 'get_current_weather', 'args': {'location': 'San Francisco'}, 'id': ''}])"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from langchain_community.chat_models.tongyi import ChatTongyi\n",
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"from langchain_core.messages import HumanMessage, SystemMessage\n",
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"\n",
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"tools = [\n",
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" {\n",
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" \"type\": \"function\",\n",
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" \"function\": {\n",
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" \"name\": \"get_current_time\",\n",
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" \"description\": \"当你想知道现在的时间时非常有用。\",\n",
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" \"parameters\": {},\n",
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" },\n",
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" },\n",
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" {\n",
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" \"type\": \"function\",\n",
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" \"function\": {\n",
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" \"name\": \"get_current_weather\",\n",
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" \"description\": \"当你想查询指定城市的天气时非常有用。\",\n",
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" \"parameters\": {\n",
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" \"type\": \"object\",\n",
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" \"properties\": {\n",
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" \"location\": {\n",
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" \"type\": \"string\",\n",
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" \"description\": \"城市或县区,比如北京市、杭州市、余杭区等。\",\n",
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" }\n",
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" },\n",
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" },\n",
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" \"required\": [\"location\"],\n",
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" },\n",
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" },\n",
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"]\n",
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"\n",
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"messages = [\n",
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" SystemMessage(content=\"You are a helpful assistant.\"),\n",
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" HumanMessage(content=\"What is the weather like in San Francisco?\"),\n",
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"]\n",
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"chatLLM = ChatTongyi()\n",
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"llm_kwargs = {\"tools\": tools, \"result_format\": \"message\"}\n",
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"ai_message = chatLLM.bind(**llm_kwargs).invoke(messages)\n",
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"ai_message"
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]
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}
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],
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"metadata": {
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