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docs: update pydantic comments -> callouts in tutorials (#1825)

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This commit is contained in:
Vadym Barda
2024-09-24 13:09:59 +00:00
committed by GitHub
parent bb5ff42bcd
commit 37948b3348
16 changed files with 218 additions and 19 deletions
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docs/docs/tutorials/rag/langgraph_adaptive_rag.ipynb
+15 -4
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@@ -8,9 +8,7 @@
},
"cell_type": "markdown",
"id": "5afcaed0-3d55-4e1f-95d3-c32c751c29d8",
"metadata": {
"jp-MarkdownHeadingCollapsed": true
},
"metadata": {},
"source": [
"# Adaptive RAG\n",
"\n",
@@ -148,6 +146,19 @@
"## LLMs"
]
},
{
"cell_type": "markdown",
"id": "d28baefd-a961-49b0-8394-c5478dadda1c",
"metadata": {},
"source": [
"<div class=\"admonition note\">\n",
" <p class=\"admonition-title\">Using Pydantic with LangChain</p>\n",
" <p>\n",
" This notebook uses Pydantic v2 <code>BaseModel</code>, which requires <code>langchain-core >= 0.3</code>. Using <code>langchain-core < 0.3</code> will result in errors due to mixing of Pydantic v1 and v2 <code>BaseModels</code>.\n",
" </p>\n",
"</div>"
]
},
{
"cell_type": "code",
"execution_count": 3,
@@ -170,7 +181,7 @@
"\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"# NOTE: you must use langchain-core >= 0.3 with Pydantic v2\n",
"\n",
"from pydantic import BaseModel, Field\n",
"\n",
"\n",
docs/docs/tutorials/rag/langgraph_agentic_rag.ipynb
+14 -1
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@@ -189,6 +189,19 @@
"![Screenshot 2024-02-14 at 3.43.58 PM.png](attachment:7ad1a116-28d7-473f-8cff-5f2efd0bf118.png)"
]
},
{
"cell_type": "markdown",
"id": "bd7a7843-2a4a-4de5-a211-ff2efe3aba47",
"metadata": {},
"source": [
"<div class=\"admonition note\">\n",
" <p class=\"admonition-title\">Using Pydantic with LangChain</p>\n",
" <p>\n",
" This notebook uses Pydantic v2 <code>BaseModel</code>, which requires <code>langchain-core >= 0.3</code>. Using <code>langchain-core < 0.3</code> will result in errors due to mixing of Pydantic v1 and v2 <code>BaseModels</code>.\n",
" </p>\n",
"</div>"
]
},
{
"cell_type": "code",
"execution_count": 3,
@@ -217,7 +230,7 @@
"from langchain_core.output_parsers import StrOutputParser\n",
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"# NOTE: you must use langchain-core >= 0.3 with Pydantic v2\n",
"\n",
"from pydantic import BaseModel, Field\n",
"\n",
"\n",
docs/docs/tutorials/rag/langgraph_crag.ipynb
+14 -1
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@@ -139,6 +139,19 @@
"## LLMs"
]
},
{
"cell_type": "markdown",
"id": "c1da8975-f2c4-4584-a0f9-bd5af88983a3",
"metadata": {},
"source": [
"<div class=\"admonition note\">\n",
" <p class=\"admonition-title\">Using Pydantic with LangChain</p>\n",
" <p>\n",
" This notebook uses Pydantic v2 <code>BaseModel</code>, which requires <code>langchain-core >= 0.3</code>. Using <code>langchain-core < 0.3</code> will result in errors due to mixing of Pydantic v1 and v2 <code>BaseModels</code>.\n",
" </p>\n",
"</div>"
]
},
{
"cell_type": "code",
"execution_count": 5,
@@ -158,7 +171,7 @@
"\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"# NOTE: you must use langchain-core >= 0.3 with Pydantic v2\n",
"\n",
"from pydantic import BaseModel, Field\n",
"\n",
"\n",
docs/docs/tutorials/rag/langgraph_self_rag.ipynb
+14 -1
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@@ -150,6 +150,19 @@
"## LLMs"
]
},
{
"cell_type": "markdown",
"id": "6cf1011b-213c-45fd-9608-328fc6eea677",
"metadata": {},
"source": [
"<div class=\"admonition note\">\n",
" <p class=\"admonition-title\">Using Pydantic with LangChain</p>\n",
" <p>\n",
" This notebook uses Pydantic v2 <code>BaseModel</code>, which requires <code>langchain-core >= 0.3</code>. Using <code>langchain-core < 0.3</code> will result in errors due to mixing of Pydantic v1 and v2 <code>BaseModels</code>.\n",
" </p>\n",
"</div>"
]
},
{
"cell_type": "code",
"execution_count": 5,
@@ -170,7 +183,7 @@
"\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"from langchain_openai import ChatOpenAI\n",
"# NOTE: you must use langchain-core >= 0.3 with Pydantic v2\n",
"\n",
"from pydantic import BaseModel, Field\n",
"\n",
"\n",