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Nov 22, 2023
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Add colab links #77

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eyurtsev Nov 22, 2023
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eyurtsev Nov 22, 2023
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rm links
hinthornw Nov 22, 2023
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hinthornw Nov 22, 2023
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10 changes: 9 additions & 1 deletion docs/source/conf.py
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html_theme = "sphinx_book_theme"

html_theme_options = {
"path_to_docs": "docs",
"path_to_docs": "docs/source",
"repository_url": "https://github.com/langchain-ai/langchain-benchmarks",
"home_page_in_toc": True,
"show_navbar_depth": 2,
"use_sidenotes": True,
"use_repository_button": True,
"use_issues_button": True,
"use_source_button": True,
"use_fullscreen_button": True,
"repository_branch": "main",
"launch_buttons": {
"notebook_interface": "jupyterlab",
"colab_url": "https://colab.research.google.com",
},
}

html_context = {
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2 changes: 1 addition & 1 deletion docs/source/notebooks/extraction/email.ipynb
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"metadata": {},
"source": [
"# Email Extraction\n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/extraction/email.ipynb)\n",
"\n",
"\n",
"Let's evaluate an LLM on its ability to extract structured information from email texts."
]
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2 changes: 1 addition & 1 deletion docs/source/notebooks/extraction/intro.ipynb
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"source": [
"# Introduction\n",
"\n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/extraction/intro.ipynb)\n",
"\n",
"\n",
"These tasks refer to an LLM's ability to extract structured output from an unstructured source, such as emails, websites, or other text. Below are a list of supported datasets.\n"
]
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2 changes: 1 addition & 1 deletion docs/source/notebooks/getting_started.ipynb
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"metadata": {},
"source": [
"# Getting Started\n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/getting_started.ipynb)\n",
"\n",
"\n",
"LLMs are powerful but can be hard to steer and prone to errors when deployed. At the same time, new models and techniques are being developed all the time. We want to make it easy for you to experiment with different techniques, understand their tradeoffs, and make informed decisions for your specific use case.\n",
"\n",
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2 changes: 1 addition & 1 deletion docs/source/notebooks/retrieval/comparing_techniques.ipynb
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"metadata": {},
"source": [
"# Evaluating RAG Architectures on Benchmark Tasks\n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/retrieval/comparing_techniques.ipynb)\n",
"\n",
"\n",
"\n",
"#### Introduction\n",
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2 changes: 1 addition & 1 deletion docs/source/notebooks/retrieval/intro.ipynb
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"source": [
"# Introduction\n",
"\n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/retrieval/intro.ipynb)\n",
"\n",
"\n",
"These tasks are meant to test retrieval-augmented generation (RAG) architectures on various datasets.\n",
"\n",
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2 changes: 1 addition & 1 deletion docs/source/notebooks/retrieval/langchain_docs_qa.ipynb
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"metadata": {},
"source": [
"# Q&A over LangChain Docs\n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/retrieval/langchain_docs_qa.ipynb)\n",
"\n",
"\n",
"Let's evaluate your architecture on a Q&A dataset for the LangChain python docs. For more examples of how to test different embeddings, indexing strategies, and architectures, see the [Evaluating RAG Architectures on Benchmark Tasks](./comparing_techniques.ipynb) notebook.\n",
"\n",
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2 changes: 1 addition & 1 deletion docs/source/notebooks/retrieval/semi_structured.ipynb
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"metadata": {},
"source": [
"# Semi-structured RAG\n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/retrieval/semi_structured.ipynb)\n",
"\n",
"\n",
"Let's evaluate your architecture on a small semi-structured Q&A dataset. This dataset is composed of QA pairs over pdfs that contain tables."
]
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2 changes: 1 addition & 1 deletion docs/source/notebooks/tool_usage/intro.ipynb
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"source": [
"# Introduction\n",
"\n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/tool_usage/intro.ipynb)\n",
"\n",
"\n",
"Tool Usage tasks are designed to evaluate how well an agent can use tools to accomplish an objective.\n",
"\n",
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2 changes: 1 addition & 1 deletion docs/source/notebooks/tool_usage/multiverse_math.ipynb
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},
"source": [
"# Multiverse Math\n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/tool_usage/multiverse_math.ipynb)\n",
"\n",
"\n",
"Let's see how to evaluate an agent's ability to use tools.\n",
"\n",
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2 changes: 1 addition & 1 deletion docs/source/notebooks/tool_usage/relational_data.ipynb
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"metadata": {},
"source": [
"# Relational Data \n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/tool_usage/relational_data.ipynb)\n",
"\n",
"\n",
"Let's see how to evaluate an agent's ability to use tools."
]
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2 changes: 1 addition & 1 deletion docs/source/notebooks/tool_usage/typewriter_1.ipynb
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},
"source": [
"# Typewriter: Single Tool\n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/tool_usage/typewriter_1.ipynb)\n",
"\n",
"\n",
"Let's see how to evaluate an agent's ability to use tools.\n",
"\n",
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2 changes: 1 addition & 1 deletion docs/source/notebooks/tool_usage/typewriter_26.ipynb
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},
"source": [
"# Typewriter: 26 Tools\n",
"[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/langchain-ai/langchain-benchmarks/blob/main/docs/source/notebooks/tool_usage/typewriter_26.ipynb)\n",
"\n",
"\n",
"Let's see how to evaluate an agent's ability to use tools.\n",
"\n",
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