👩🏻‍🍳 Haystack食谱

使用Haystack的示例笔记本集合👇

你可以将这些例子作为指南，了解如何在Haystack中使用不同的模型提供商、向量数据库、检索技术等。大多数例子展示了一个特定的小型演示。

要更深入地了解如何使用Haystack，请访问我们的文档和官方教程。

欲获取更多示例，你可能还会发现我们的博客很有用。

**注意：**除非标题中提到"(Haystack 1.x)"，否则所有这些示例都使用Haystack 2.0及以上版本。

名称	Colab
使用AssemblyAI进行说话人分离	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/using_speaker_diarization_with_assemblyai.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
Anthropic高级提示词定制	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/prompt_customization_for_Anthropic.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用TitanML Takeoff的本地LLM实现Techcrunch新闻摘要	<a href="https://colab.research.google.com/drive/10EralM_8pCJ5nXnGIZYr6atqefmi8r2z?usp=sharing" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
在Vertex AI中使用Gemini模型	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/vertexai-gemini-examples.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
用于RAG的Gradient AI嵌入器和生成器	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/gradient-embeders-and-generators-for-notion-rag.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Hugging Face TGI的Mixtral 8x7B进行网页问答	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/mixtral-8x7b-for-web-qa.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Amazon Bedrock和OpenSearch进行PDF问答	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/amazon_bedrock_for_documentation_qa.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Hugging Face的Zephyr 7B Beta进行RAG	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/zephyr-7b-beta-for-rag.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用自定义组件的Hacker News RAG	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/hackernews-custom-component-rag.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Chroma进行RAG和索引	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/chroma-indexing-and-rag-examples.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
在Haystack RAG管道中使用Jina-embeddings-v2-base-en模型进行法律文档分析	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/jina-embeddings-v2-legal-analysis-rag.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Whisper、Qdrant和Mistral从播客进行多语言RAG	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/multilingual_rag_podcast.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
通过嵌入有意义的元数据来改进检索	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/improve-retrieval-by-embedding-metadata.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
高级RAG：查询扩展	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/querey-expansion.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
通过LLMs进行信息提取（Gorilla OpenFunctions）	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/information-extraction-gorilla.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
通过LLMs进行信息提取（NexusRaven）	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/information_extraction_raven.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
在Haystack管道中使用AstraDB作为数据存储	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/astradb_haystack_integration.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
流式模型探索器：比较不同模型如何处理相同的提示	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/model_explorer_streaming.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用OpenAIChatGenerator进行函数调用	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/function_calling_with_OpenAIChatGenerator.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
在Haystack 2.x中使用vLLM推理引擎	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/vllm_inference_engine.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Google Gemma构建：聊天和RAG	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/gemma_chat_rag.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用HyDE优化检索	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/using_hyde_for_improved_retrieval.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用FastEmbed生成嵌入的RAG管道	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/rag_fastembed.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Qdrant和FastEmbed的稀疏嵌入检索	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/sparse_embedding_retrieval.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
混合检索：BM42 + 密集检索（使用Qdrant和FastEmbed）	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/hybrid_retrieval_bm42.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用NVIDIA NIMs的离线RAG管道	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/rag-with-nims.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Haystack-UpTrain集成评估RAG管道	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/rag_eval_uptrain.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Llama 3.1模型对奥斯卡进行RAG	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/llama3_rag.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
与SQL数据库聊天	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/chat_with_SQL_3_ways.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用DeepEval集成评估RAG管道	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/rag_eval_deep_eval.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Ragas集成评估RAG管道	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/rag_eval_ragas.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
从查询中提取元数据过滤器	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/extracting_metadata_filters_from_a_user_query.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
在自定义组件中并发运行任务	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/concurrent_tasks.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用DSPy进行提示优化	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/prompt_optimization_with_dspy.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Prometheus 2进行RAG评估	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/prometheus2_evaluation.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Character Codex和llamafile构建测验和冒险	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/charactercodex_llamafile.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用`OpenAPITool`调用API	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/openapitool.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
使用Apify提取和利用网站内容进行RAG	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/apify_haystack_rag.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
Cohere用于多语言问答（Haystack 1.x）	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/haystack-1.x/cohere-for-multilingual-qa.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
GPT-4和Weaviate用于自定义文档问答（Haystack 1.x）	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/haystack-1.x/gpt4-weaviate-custom-documentation-qa.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>
Whisper转录器和Weaviate用于YouTube视频问答（Haystack 1.x）	<a href="https://colab.research.google.com/github/deepset-ai/haystack-cookbook/blob/main/notebooks/haystack-1.x/whisper-and-weaviate-for-youtube-rag.ipynb" target="_parent"><img src="https://yellow-cdn.veclightyear.com/835a84d5/4196d3cf-8bbb-4b66-838a-e55893536019.svg" alt="在Colab中打开"/></a>