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Update all URLs to langchain docunotebooks (#1745)

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Eugene Yurtsev
2024-09-17 15:01:22 -04:00
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parent 36c757e758
commit b11552a10a
22 changed files with 44 additions and 44 deletions
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docs/docs/tutorials/rag/langgraph_agentic_rag.ipynb
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"source": [
"# Agentic RAG\n",
"\n",
"[Retrieval Agents](https://python.langchain.com/v0.2/docs/tutorials/qa_chat_history/#agents) are useful when we want to make decisions about whether to retrieve from an index.\n",
"[Retrieval Agents](https://python.langchain.com/docs/tutorials/qa_chat_history/#agents) are useful when we want to make decisions about whether to retrieve from an index.\n",
"\n",
"To implement a retrieval agent, we simple need to give an LLM access to a retriever tool.\n",
"\n",
docs/docs/tutorials/rag/langgraph_crag.ipynb
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"\n",
"* Let's skip the knowledge refinement phase as a first pass. This can be added back as a node, if desired. \n",
"* If *any* documents are irrelevant, let's opt to supplement retrieval with web search. \n",
"* We'll use [Tavily Search](https://python.langchain.com/v0.2/docs/integrations/tools/tavily_search/) for web search.\n",
"* We'll use [Tavily Search](https://python.langchain.com/docs/integrations/tools/tavily_search/) for web search.\n",
"* Let's use query re-writing to optimize the query for web search.\n",
"\n",
"![Screenshot 2024-04-01 at 9.28.30 AM.png](attachment:683fae34-980f-43f0-a9c2-9894bebd9157.png)"
docs/docs/tutorials/rag/langgraph_crag_local.ipynb
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@@ -26,7 +26,7 @@
"\n",
"* If *any* documents are irrelevant, we'll supplement retrieval with web search. \n",
"* We'll skip the knowledge refinement, but this can be added back as a node if desired. \n",
"* We'll use [Tavily Search](https://python.langchain.com/v0.2/docs/integrations/tools/tavily_search/) for web search.\n",
"* We'll use [Tavily Search](https://python.langchain.com/docs/integrations/tools/tavily_search/) for web search.\n",
"\n",
"![Screenshot 2024-06-24 at 3.03.16 PM.png](attachment:b77a7d3b-b28a-4dcf-9f1a-861f2f2c5f6c.png)"
]
@@ -43,7 +43,7 @@
"* Download [Ollama app](https://ollama.ai/).\n",
"* Pull your model of choice, e.g.: `ollama pull llama3`\n",
"\n",
"We'll use [Tavily](https://python.langchain.com/v0.2/docs/integrations/tools/tavily_search/) for web search.\n",
"We'll use [Tavily](https://python.langchain.com/docs/integrations/tools/tavily_search/) for web search.\n",
"\n",
"We'll use a vectorstore with [Nomic local embeddings](https://blog.nomic.ai/posts/nomic-embed-text-v1) or, optionally, OpenAI embeddings.\n",
"\n",