前言
本文是 Harrison Chase （LangChain 创建者）和吴恩达（Andrew Ng）的视频课程《LangChain for LLM Application Development》（使用 LangChain 进行大模型应用开发）的学习笔记。由于原课程为全英文视频课程，国内访问较慢，同时我整理和替换了部分内容以便于国内学习。阅读本文可快速学习课程内容。
课程介绍
本课程介绍了强大且易于扩展的 LangChain 框架，LangChain 框架是一款用于开发大语言模型（LLM）应用的开源框架，其使用提示词、记忆、链、代理等简化了大语言模型应用的开发工作。由于 LangChain 仍处于快速发展期，部分 API 还不稳定，课程中的部分代码已过时，我使用了目前最新的 v0.2 版本进行讲解，所有代码均可在 v0.2 版本下执行。另外，课程使用的 OpenAI 在国内难以访问，我替换为国内的 Kimi 大模型及开源自建的 Ollama，对于学习没有影响。
参考这篇文章来获取 Kimi 的 API 令牌。
参考这篇文章来用 Ollama 部署自己的大模型。
课程分为五个部分：
第四部分
评估
构建问答应用
当构建一个复杂的 LLM 应用时，比较重要但又困难的是如何去评价应用的效果。又或者，当我们切换不同的 LLM 模型时，如何去评价模型的优劣。再者，当我们使用不同的向量数据库或参数时，对结果是变好了还是变坏了。接下来，我们将介绍如何来评估 LLM 应用的结果是否正确。
首先，我们创建一条之前使用的问答链。
python
from langchain.chains import RetrievalQA
from langchain_ollama import ChatOllama
from langchain_community.document_loaders import CSVLoader
from langchain_community.embeddings import OllamaEmbeddings
from langchain_community.vectorstores import DocArrayInMemorySearch
from langchain.indexes import VectorstoreIndexCreator
from langchain.evaluation.qa import QAGenerateChain
# Ollama 服务地址
base_url = 'http://localhost:11434'
# 模型名称
llm_model = 'qwen2'
# 测试文件
file_path = 'product.csv'
# 创建模型
llm = ChatOllama(base_url=base_url, model=llm_model)
# 载入测试数据
loader = CSVLoader(file_path=file_path)
data = loader.load()
# 创建嵌入
embeddings = OllamaEmbeddings(base_url=base_url, model=llm_model)
# 创建向量索引
index = VectorstoreIndexCreator(
vectorstore_cls=DocArrayInMemorySearch,
embedding=embeddings
).from_loaders([loader])
# 创建问答链
qa = RetrievalQA.from_chain_type(
llm=llm,
chain_type="stuff",
retriever=index.vectorstore.as_retriever(),
verbose=True,
chain_type_kwargs={
"document_separator": "<<<<>>>>>"
}
)添加测试数据
我们可以添加一些测试数据，从 product.csv 中选取几条数据，例如第 11 和 12 条是下面这样：
11,高清投影仪,"高亮度，高对比度，支持高清视频播放，适合家庭影院和商务演示。"
12,智能手环,"监测心率、计步、睡眠，智能提醒，是健康生活的好伴侣。"
由于数据由 LLM 自动生成，数据可能都不相同。
我们设置问题并提供答案。这是一个字典 list，每个字典包含 query 和 answer。
python
examples = [
{
"query": "高清投影仪支持高清视频播放吗？",
"answer": "是"
},
{
"query": "哪一款产品能监测心率？",
"answer": "智能手环"
}
]我们这里创建了两条测试数据，但还不够，手动创建比较费时间，有没有更自动的方式呢？我们可以让大语言模型自己来生成。在 LangChain 中我们可以使用 QAGenerateChain 来让 LLM 自动对每条数据生成测试问题和答案。
python
# 创建测试集生成链
example_gen_chain = QAGenerateChain.from_llm(llm)
# 生成并解析结果（由于需要调用 LLM，我们这里只取前 5 条）
new_examples = example_gen_chain.apply_and_parse(
[{"doc": t} for t in data[:5]]
)
print(new_examples[0])我们查看第一条生成的测试数据，大概像这个样子。我们可以检查每一条生成的测试数据，看是否正确、合适。
{'qa_pairs': {'query': 'What features does the high-definition smart television have?', 'answer': 'The high-definition smart television has a 4K ultra-high definition resolution, an integrated intelligent system, and supports voice control. It provides a rich entertainment experience.'}}
另外，我们可以打开调试模式，看看它是如何运作的。
python
import langchain
langchain.debug = True将上述代码放到前面，然后重新运行代码。下面的输出比较长，查看前面主要的部分，我们可以看到 QAGenerateChain 链对每一条数据启动了子链，并生成了提示词，要求 LLM 作为老师，根据下面的数据生成提问和答案。最后按特定的格式输出，然后 LangChain 就可以解析到字典中。
[chain/start] [chain:QAGenerateChain] Entering Chain run with input:
[inputs]
[llm/start] [chain:QAGenerateChain > llm:ChatOllama] Entering LLM run with input:
{
"prompts": [
"Human: You are a teacher coming up with questions to ask on a quiz. \nGiven the following document, please generate a question and answer based on that document.\n\nExample Format:\n<Begin Document>\n...\n<End Document>\nQUESTION: question here\nANSWER: answer here\n\nThese questions should be detailed and be based explicitly on information in the document. Begin!\n\n<Begin Document>\npage_content='no: 1\nname: 高清智能电视\ndescription: 这款高清智能电视拥有4K超高清分辨率，内置智能系统，支持语音控制，提供丰富的娱乐体验。' metadata={'source': 'product.csv', 'row': 0}\n<End Document>"
]
}
[llm/start] [chain:QAGenerateChain > llm:ChatOllama] Entering LLM run with input:
{
"prompts": [
"Human: You are a teacher coming up with questions to ask on a quiz. \nGiven the following document, please generate a question and answer based on that document.\n\nExample Format:\n<Begin Document>\n...\n<End Document>\nQUESTION: question here\nANSWER: answer here\n\nThese questions should be detailed and be based explicitly on information in the document. Begin!\n\n<Begin Document>\npage_content='no: 2\nname: 多功能料理机\ndescription: 集搅拌、打蛋、榨汁等多种功能于一身，操作简便，是厨房里的得力助手。' metadata={'source': 'product.csv', 'row': 1}\n<End Document>"
]
}
[llm/start] [chain:QAGenerateChain > llm:ChatOllama] Entering LLM run with input:
{
"prompts": [
"Human: You are a teacher coming up with questions to ask on a quiz. \nGiven the following document, please generate a question and answer based on that document.\n\nExample Format:\n<Begin Document>\n...\n<End Document>\nQUESTION: question here\nANSWER: answer here\n\nThese questions should be detailed and be based explicitly on information in the document. Begin!\n\n<Begin Document>\npage_content='no: 3\nname: 无线蓝牙耳机\ndescription: 轻巧舒适，音质清晰，支持长时间续航，适合运动和日常使用。' metadata={'source': 'product.csv', 'row': 2}\n<End Document>"
]
}
[llm/start] [chain:QAGenerateChain > llm:ChatOllama] Entering LLM run with input:
{
"prompts": [
"Human: You are a teacher coming up with questions to ask on a quiz. \nGiven the following document, please generate a question and answer based on that document.\n\nExample Format:\n<Begin Document>\n...\n<End Document>\nQUESTION: question here\nANSWER: answer here\n\nThese questions should be detailed and be based explicitly on information in the document. Begin!\n\n<Begin Document>\npage_content='no: 4\nname: 智能扫地机器人\ndescription: 自动规划清扫路线，智能避障，解放双手，保持家中清洁。' metadata={'source': 'product.csv', 'row': 3}\n<End Document>"
]
}
[llm/start] [chain:QAGenerateChain > llm:ChatOllama] Entering LLM run with input:
{
"prompts": [
"Human: You are a teacher coming up with questions to ask on a quiz. \nGiven the following document, please generate a question and answer based on that document.\n\nExample Format:\n<Begin Document>\n...\n<End Document>\nQUESTION: question here\nANSWER: answer here\n\nThese questions should be detailed and be based explicitly on information in the document. Begin!\n\n<Begin Document>\npage_content='no: 5\nname: 便携式榨汁机\ndescription: 小巧便携，操作简便，快速榨汁，适合健康生活需求。' metadata={'source': 'product.csv', 'row': 4}\n<End Document>"
]
}
[llm/end] [chain:QAGenerateChain > llm:ChatOllama] [75.50s] Exiting LLM run with output:
{
"generations": [
[
{
"text": "QUESTION: What features does the high-definition smart television have?\nANSWER: The high-definition smart television has a 4K ultra-high definition resolution, an integrated intelligent system, and supports voice control. It provides a rich entertainment experience.",
"generation_info": {
"model": "qwen2",
"created_at": "2024-09-12T02:27:28.132404919Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 15075322258,
"load_duration": 4068642657,
"prompt_eval_count": 146,
"prompt_eval_duration": 3419985000,
"eval_count": 48,
"eval_duration": 7545190000
},
"type": "ChatGeneration",
"message": {
"lc": 1,
"type": "constructor",
"id": [
"langchain",
"schema",
"messages",
"AIMessage"
],
"kwargs": {
"content": "QUESTION: What features does the high-definition smart television have?\nANSWER: The high-definition smart television has a 4K ultra-high definition resolution, an integrated intelligent system, and supports voice control. It provides a rich entertainment experience.",
"response_metadata": {
"model": "qwen2",
"created_at": "2024-09-12T02:27:28.132404919Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 15075322258,
"load_duration": 4068642657,
"prompt_eval_count": 146,
"prompt_eval_duration": 3419985000,
"eval_count": 48,
"eval_duration": 7545190000
},
"type": "ai",
"id": "run-e2282df6-a2bb-4b75-bd94-c6ee8338b339-0",
"usage_metadata": {
"input_tokens": 146,
"output_tokens": 48,
"total_tokens": 194
},
"tool_calls": [],
"invalid_tool_calls": []
}
}
}
]
],
"llm_output": null,
"run": null
}
[llm/end] [chain:QAGenerateChain > llm:ChatOllama] [75.51s] Exiting LLM run with output:
{
"generations": [
[
{
"text": "QUESTION: What is the multifunctional kitchen appliance mentioned in the document capable of doing?\nANSWER: The multifunctional kitchen appliance, known as '多功能料理机', can perform various tasks such as blending, whisking eggs, and juicing. It's designed for ease of operation and serves as a helpful tool in the kitchen.",
"generation_info": {
"model": "qwen2",
"created_at": "2024-09-12T02:27:40.655928024Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 12512086251,
"load_duration": 62599702,
"prompt_eval_count": 145,
"prompt_eval_duration": 1594234000,
"eval_count": 69,
"eval_duration": 10853358000
},
"type": "ChatGeneration",
"message": {
"lc": 1,
"type": "constructor",
"id": [
"langchain",
"schema",
"messages",
"AIMessage"
],
"kwargs": {
"content": "QUESTION: What is the multifunctional kitchen appliance mentioned in the document capable of doing?\nANSWER: The multifunctional kitchen appliance, known as '多功能料理机', can perform various tasks such as blending, whisking eggs, and juicing. It's designed for ease of operation and serves as a helpful tool in the kitchen.",
"response_metadata": {
"model": "qwen2",
"created_at": "2024-09-12T02:27:40.655928024Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 12512086251,
"load_duration": 62599702,
"prompt_eval_count": 145,
"prompt_eval_duration": 1594234000,
"eval_count": 69,
"eval_duration": 10853358000
},
"type": "ai",
"id": "run-db59bd5a-e8c5-4ce4-be93-477b1f7beeeb-0",
"usage_metadata": {
"input_tokens": 145,
"output_tokens": 69,
"total_tokens": 214
},
"tool_calls": [],
"invalid_tool_calls": []
}
}
}
]
],
"llm_output": null,
"run": null
}
[llm/end] [chain:QAGenerateChain > llm:ChatOllama] [75.51s] Exiting LLM run with output:
{
"generations": [
[
{
"text": "QUESTION: What are the features of the product with the name \"无线蓝牙耳机\" (Wireless Bluetooth Earphones)?\n\nANSWER: The product named \"无线蓝牙耳机\" offers several features including:\n1. **Lightweight and Comfortable**: The earphones are designed to be lightweight, ensuring comfort during use.\n2. **Crystal Clear Sound Quality**: It provides clear sound quality for an enjoyable listening experience.\n3. **Long Battery Life**: The headphones support a long duration of battery usage, making them suitable for both sports activities and everyday use.\n4. **Versatile Use**: They can be used while exercising or in daily routines without any issues due to their versatile design and functionality.\n\nThese features highlight the product's suitability for users who value convenience, comfort, and audio quality in their listening devices.",
"generation_info": {
"model": "qwen2",
"created_at": "2024-09-12T02:28:06.427487738Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 25761127075,
"load_duration": 63109381,
"prompt_eval_count": 139,
"prompt_eval_duration": 1397453000,
"eval_count": 162,
"eval_duration": 24259968000
},
"type": "ChatGeneration",
"message": {
"lc": 1,
"type": "constructor",
"id": [
"langchain",
"schema",
"messages",
"AIMessage"
],
"kwargs": {
"content": "QUESTION: What are the features of the product with the name \"无线蓝牙耳机\" (Wireless Bluetooth Earphones)?\n\nANSWER: The product named \"无线蓝牙耳机\" offers several features including:\n1. **Lightweight and Comfortable**: The earphones are designed to be lightweight, ensuring comfort during use.\n2. **Crystal Clear Sound Quality**: It provides clear sound quality for an enjoyable listening experience.\n3. **Long Battery Life**: The headphones support a long duration of battery usage, making them suitable for both sports activities and everyday use.\n4. **Versatile Use**: They can be used while exercising or in daily routines without any issues due to their versatile design and functionality.\n\nThese features highlight the product's suitability for users who value convenience, comfort, and audio quality in their listening devices.",
"response_metadata": {
"model": "qwen2",
"created_at": "2024-09-12T02:28:06.427487738Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 25761127075,
"load_duration": 63109381,
"prompt_eval_count": 139,
"prompt_eval_duration": 1397453000,
"eval_count": 162,
"eval_duration": 24259968000
},
"type": "ai",
"id": "run-3dc06185-da4e-4b56-b615-dcf831157fb2-0",
"usage_metadata": {
"input_tokens": 139,
"output_tokens": 162,
"total_tokens": 301
},
"tool_calls": [],
"invalid_tool_calls": []
}
}
}
]
],
"llm_output": null,
"run": null
}
[llm/end] [chain:QAGenerateChain > llm:ChatOllama] [75.51s] Exiting LLM run with output:
{
"generations": [
[
{
"text": "QUESTION: What is the product being described and what are its main features?\n\nANSWER: The product being described is a \"智能扫地机器人\" (intelligent floor sweeping robot). Its main features include automatic planning of cleaning routes, intelligent obstacle avoidance, freeing up hands, and maintaining home cleanliness.",
"generation_info": {
"model": "qwen2",
"created_at": "2024-09-12T02:28:17.028896159Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 10589442660,
"load_duration": 26054599,
"prompt_eval_count": 139,
"prompt_eval_duration": 1401741000,
"eval_count": 61,
"eval_duration": 9159878000
},
"type": "ChatGeneration",
"message": {
"lc": 1,
"type": "constructor",
"id": [
"langchain",
"schema",
"messages",
"AIMessage"
],
"kwargs": {
"content": "QUESTION: What is the product being described and what are its main features?\n\nANSWER: The product being described is a \"智能扫地机器人\" (intelligent floor sweeping robot). Its main features include automatic planning of cleaning routes, intelligent obstacle avoidance, freeing up hands, and maintaining home cleanliness.",
"response_metadata": {
"model": "qwen2",
"created_at": "2024-09-12T02:28:17.028896159Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 10589442660,
"load_duration": 26054599,
"prompt_eval_count": 139,
"prompt_eval_duration": 1401741000,
"eval_count": 61,
"eval_duration": 9159878000
},
"type": "ai",
"id": "run-a489b5fe-7798-41f0-8380-e9bde0e8a889-0",
"usage_metadata": {
"input_tokens": 139,
"output_tokens": 61,
"total_tokens": 200
},
"tool_calls": [],
"invalid_tool_calls": []
}
}
}
]
],
"llm_output": null,
"run": null
}
[llm/end] [chain:QAGenerateChain > llm:ChatOllama] [75.51s] Exiting LLM run with output:
{
"generations": [
[
{
"text": "QUESTION: What is the product described in this document?\nANSWER: The product described in this document is a portable juicer named \"便携式榨汁机\" (portable juice extractor). It's characterized as compact, easy to operate, and capable of quickly extracting juice, making it suitable for needs related to health living.",
"generation_info": {
"model": "qwen2",
"created_at": "2024-09-12T02:28:28.529352164Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 11484086566,
"load_duration": 62195060,
"prompt_eval_count": 140,
"prompt_eval_duration": 1362653000,
"eval_count": 68,
"eval_duration": 10018610000
},
"type": "ChatGeneration",
"message": {
"lc": 1,
"type": "constructor",
"id": [
"langchain",
"schema",
"messages",
"AIMessage"
],
"kwargs": {
"content": "QUESTION: What is the product described in this document?\nANSWER: The product described in this document is a portable juicer named \"便携式榨汁机\" (portable juice extractor). It's characterized as compact, easy to operate, and capable of quickly extracting juice, making it suitable for needs related to health living.",
"response_metadata": {
"model": "qwen2",
"created_at": "2024-09-12T02:28:28.529352164Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 11484086566,
"load_duration": 62195060,
"prompt_eval_count": 140,
"prompt_eval_duration": 1362653000,
"eval_count": 68,
"eval_duration": 10018610000
},
"type": "ai",
"id": "run-5709894f-ab18-4a1e-9e7b-0b8acd1eeb6a-0",
"usage_metadata": {
"input_tokens": 140,
"output_tokens": 68,
"total_tokens": 208
},
"tool_calls": [],
"invalid_tool_calls": []
}
}
}
]
],
"llm_output": null,
"run": null
}
[chain/end] [chain:QAGenerateChain] [75.51s] Exiting Chain run with output:
{
"outputs": [
{
"qa_pairs": {
"query": "What features does the high-definition smart television have?",
"answer": "The high-definition smart television has a 4K ultra-high definition resolution, an integrated intelligent system, and supports voice control. It provides a rich entertainment experience."
}
},
{
"qa_pairs": {
"query": "What is the multifunctional kitchen appliance mentioned in the document capable of doing?",
"answer": "The multifunctional kitchen appliance, known as '多功能料理机', can perform various tasks such as blending, whisking eggs, and juicing. It's designed for ease of operation and serves as a helpful tool in the kitchen."
}
},
{
"qa_pairs": {
"query": "What are the features of the product with the name \"无线蓝牙耳机\" (Wireless Bluetooth Earphones)?",
"answer": "The product named \"无线蓝牙耳机\" offers several features including:"
}
},
{
"qa_pairs": {
"query": "What is the product being described and what are its main features?",
"answer": "The product being described is a \"智能扫地机器人\" (intelligent floor sweeping robot). Its main features include automatic planning of cleaning routes, intelligent obstacle avoidance, freeing up hands, and maintaining home cleanliness."
}
},
{
"qa_pairs": {
"query": "What is the product described in this document?",
"answer": "The product described in this document is a portable juicer named \"便携式榨汁机\" (portable juice extractor). It's characterized as compact, easy to operate, and capable of quickly extracting juice, making it suitable for needs related to health living."
}
}
]
}
接着，我们将手动创建的测试数据和自动创建的合并。
python
all_examples = examples + [ex['qa_pairs'] for ex in new_examples]手动评估
我们让 LLM 来回答我们测试数据集中的问题，首先测试第一条手动添加的问题。
python
response = qa.run(examples[0]["query"])
print(response)调试模式下的输出类似下面这样。
[chain/start] [chain:RetrievalQA] Entering Chain run with input:
{
"query": "高清投影仪支持高清视频播放吗？"
}
[chain/start] [chain:RetrievalQA > chain:StuffDocumentsChain] Entering Chain run with input:
[inputs]
[chain/start] [chain:RetrievalQA > chain:StuffDocumentsChain > chain:LLMChain] Entering Chain run with input:
{
"question": "高清投影仪支持高清视频播放吗？",
"context": "no: 11\nname: 高清投影仪\ndescription: 高亮度，高对比度，支持高清视频播放，适合家庭影院和商务演示。<<<<>>>>>no: 22\nname: 智能跑步机\ndescription: 多种运动模式，智能记录运动数据，适合家庭健身。<<<<>>>>>no: 12\nname: 智能手环\ndescription: 监测心率、计步、睡眠，智能提醒，是健康生活的好伴侣。<<<<>>>>>no: 4\nname: 智能扫地机器人\ndescription: 自动规划清扫路线，智能避障，解放双手，保持家中清洁。"
}
[llm/start] [chain:RetrievalQA > chain:StuffDocumentsChain > chain:LLMChain > llm:ChatOllama] Entering LLM run with input:
{
"prompts": [
"System: Use the following pieces of context to answer the user's question. \nIf you don't know the answer, just say that you don't know, don't try to make up an answer.\n----------------\nno: 11\nname: 高清投影仪\ndescription: 高亮度，高对比度，支持高清视频播放，适合家庭影院和商务演示。<<<<>>>>>no: 22\nname: 智能跑步机\ndescription: 多种运动模式，智能记录运动数据，适合家庭健身。<<<<>>>>>no: 12\nname: 智能手环\ndescription: 监测心率、计步、睡眠，智能提醒，是健康生活的好伴侣。<<<<>>>>>no: 4\nname: 智能扫地机器人\ndescription: 自动规划清扫路线，智能避障，解放双手，保持家中清洁。\nHuman: 高清投影仪支持高清视频播放吗？"
]
}
[llm/end] [chain:RetrievalQA > chain:StuffDocumentsChain > chain:LLMChain > llm:ChatOllama] [6.70s] Exiting LLM run with output:
{
"generations": [
[
{
"text": "是的，高清投影仪支持高清视频播放。",
"generation_info": {
"model": "qwen2",
"created_at": "2024-09-12T02:45:31.841247748Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 6682410396,
"load_duration": 25734266,
"prompt_eval_count": 211,
"prompt_eval_duration": 5067573000,
"eval_count": 12,
"eval_duration": 1532113000
},
"type": "ChatGeneration",
"message": {
"lc": 1,
"type": "constructor",
"id": [
"langchain",
"schema",
"messages",
"AIMessage"
],
"kwargs": {
"content": "是的，高清投影仪支持高清视频播放。",
"response_metadata": {
"model": "qwen2",
"created_at": "2024-09-12T02:45:31.841247748Z",
"message": {
"role": "assistant",
"content": ""
},
"done_reason": "stop",
"done": true,
"total_duration": 6682410396,
"load_duration": 25734266,
"prompt_eval_count": 211,
"prompt_eval_duration": 5067573000,
"eval_count": 12,
"eval_duration": 1532113000
},
"type": "ai",
"id": "run-6ef3e8d8-425e-4f61-9c1d-9925a2277e8f-0",
"usage_metadata": {
"input_tokens": 211,
"output_tokens": 12,
"total_tokens": 223
},
"tool_calls": [],
"invalid_tool_calls": []
}
}
}
]
],
"llm_output": null,
"run": null
}
[chain/end] [chain:RetrievalQA > chain:StuffDocumentsChain > chain:LLMChain] [6.70s] Exiting Chain run with output:
{
"text": "是的，高清投影仪支持高清视频播放。"
}
[chain/end] [chain:RetrievalQA > chain:StuffDocumentsChain] [6.71s] Exiting Chain run with output:
{
"output_text": "是的，高清投影仪支持高清视频播放。"
}
[chain/end] [chain:RetrievalQA] [7.29s] Exiting Chain run with output:
{
"result": "是的，高清投影仪支持高清视频播放。"
}
是的，高清投影仪支持高清视频播放。
可以看到，这里使用 stuff 链并生成了提示词，将我们的数据也一并提交给了 LLM，LLM 给出的答案是：是的，高清投影仪支持高清视频播放。答案并不一模一样，但意思是一样的。
让 LLM 自我评估
那如果我们要对所有数据进行测试呢？也需要一条条比对吗？我们也可以让 LLM 来帮助我们做这些。LangChain 提供了 QAEvalChain 链来自动评估结果。
我们可以先关闭调试模式 langchain.debug = False，避免过多的内容输出。
python
from langchain.evaluation.qa import QAEvalChain
# 获得所有测试数据的预测结果
predictions = qa.apply(all_examples)
# 可以使用之前的 LLM 模型，也可以使用一个新的模型
llm = ChatOllama(base_url=base_url, model=llm_model)
# 创建评估链
eval_chain = QAEvalChain.from_llm(llm)
# 获得评估结果
graded_outputs = eval_chain.evaluate(all_examples, predictions)
# 遍历输出结果
for i, eg in enumerate(all_examples):
print(f"Example {i}:")
print("Question: " + predictions[i]['query'])
print("Real Answer: " + predictions[i]['answer'])
print("Predicted Answer: " + predictions[i]['result'])
print("Predicted Grade: " + graded_outputs[i]['results'])
print()输出类似如下所示。
Example 0:
Question: 高清投影仪支持高清视频播放吗？
Real Answer: 是
Predicted Answer: 是的，高清投影仪支持高清视频播放。
Predicted Grade: CORRECT
Example 1:
Question: 哪一款产品能监测心率？
Real Answer: 智能手环
Predicted Answer: 智能手环能监测心率。
Predicted Grade: CORRECT
Example 2:
Question: What features does the high-definition smart TV have according to the document?
Real Answer: The high-definition smart TV mentioned in the document has several notable features. It boasts a 4K ultra-high definition resolution, indicating an exceptionally clear picture quality. Additionally, it is equipped with an internal smart system which allows for various interactive functionalities. One of these capabilities includes voice control, suggesting users can operate or navigate through its features using their voice commands. Lastly, the TV offers a rich entertainment experience, implying that it may include access to streaming services, internet connectivity, and other multimedia content options to ensure users enjoy a varied range of programming.
Predicted Answer: I'm sorry, but I don't know the answer because the provided context doesn't mention a "high-definition smart TV". The context includes information about a high-definition projector, an automatic coffee machine, and an intelligent treadmill.
Predicted Grade: INCORRECT
Example 3:
Question: What is the product described in this document?
Real Answer: The product described in this document is a "multifunctional kitchen appliance" which combines various functions such as mixing, beating eggs and juicing. It's noted for its ease of use, making it a helpful tool in the kitchen.
Predicted Answer: The document describes several different products:
1. 高清投影仪 - A high-definition projector with high brightness and contrast, suitable for home cinema and business presentations.
2. 无线蓝牙耳机 - Wireless Bluetooth headphones that are lightweight, comfortable to wear, have clear sound quality, and offer long battery life, suitable for sports and daily use.
3. 全自动咖啡机 - An automated coffee machine that allows one-button operation and offers multiple coffee flavor choices, providing a professional coffee experience.
4. 智能跑步机 - A smart treadmill with various exercise modes and the ability to record workout data automatically, suitable for home fitness routines.
Each product has been characterized by its unique features and application scenarios as detailed in their descriptions.
Predicted Grade: INCORRECT
Example 4:
Question: What are the features of the product described in the document?
Real Answer: The product, named "wireless bluetooth headphones," is characterized by being lightweight and comfortable to wear. It offers clear sound quality and supports long-lasting battery life, making it suitable for both sports activities and everyday use.
Predicted Answer: The product described is an "高清投影仪" (High Definition Projector), which features high brightness, high contrast ratio, and support for high-definition video playback. It's suitable for both家庭影院 (home cinema) and 商务演示 (business presentations).
Another product mentioned is an "全自动咖啡机" (Fully Automatic Coffee Machine). This machine allows for one-touch operation with a variety of coffee taste choices, providing a professional coffee experience.
A third item highlighted is the "智能跑步机" (Smart Treadmill), which offers various exercise modes and can intelligently record workout data. It's ideal for家庭健身 (home fitness).
Lastly, there's an "智能扫地机器人" (Smart Vacuum Cleaning Robot) that autonomously plans its cleaning routes, has intelligent obstacle avoidance, frees up hands, and helps keep the home clean.
Predicted Grade: INCORRECT
Example 5:
Question: What is the description of the product "智能扫地机器人"?
Real Answer: The description of the product "智能扫地机器人" is that it automatically plans cleaning routes, has intelligent obstacle avoidance, frees up your hands, and keeps the house clean.
Predicted Answer: The description of the product "智能扫地机器人" is: 自动规划清扫路线，智能避障，解放双手，保持家中清洁。
Predicted Grade: CORRECT
Example 6:
Question: What is the description of the product '便携式榨汁机'?
Real Answer: The '便携式榨汁机' is described as being small, portable, easy to operate, fast at juicing and suitable for health living needs.
Predicted Answer: I don't know the answer to that question because there is no specific context provided for a '便携式榨汁机' (portable juicer).
Predicted Grade: CORRECT
从上面的输出我们看到，我们这里应该有 7 条测试数据，而每一条数据都输出了 Question（问题），Real Answer（真实回答），Predicted Answer（预测回答） 和 Predicted Grade（预测结果）四行。其中 Real Answer 是先前的 QAGenerateChain 创建的测试集中的答案，而 Predicted Answer 则是由 QAEvalChain 回答的答案，最后的 Predicted Grade 则是两者的匹配结果。上面生成的测试中，部分通过了测试，但是并没有全部通过。
由于两次回答是两条独立的链调用的，因此是互相没有影响的。而我们的问题往往是开放的，没有固定的答案，因此也需要 LLM 来帮助我们判断两次的答案是否是一致的。
这里我们学习了如何使用 LLM 来建立自动的测试链，自动生成测试数据，并自动评估答案。这样就可以方便地生成大批量的测试数据，并快速评估结果。
（未完待续）
下一篇：第五部分