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update oai cookbooks (#13135)

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Bagatur
2023-11-09 08:04:51 -08:00
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parent f04cc4b7e1
commit 150d58304d
2 changed files with 62 additions and 17 deletions
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23
cookbook/extraction_openai_tools.ipynb
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@@ -5,7 +5,7 @@
"id": "2def22ea",
"metadata": {},
"source": [
"# Extration with OpenAI Tools\n",
"# Extraction with OpenAI Tools\n",
"\n",
"Performing extraction has never been easier! OpenAI's tool calling ability is the perfect thing to use as it allows for extracting multiple different elements from text that are different types. \n",
"\n",
@@ -144,14 +144,16 @@
"metadata": {},
"source": [
"```python\n",
"from langchain.output_parsers import PydanticToolsParser\n",
"from langchain.utils.openai_functions import convert_pydantic_to_openai_function\n",
"from langchain.schema.runnable import Runnable\n",
"from typing import Union, List, Type, Optional\n",
"\n",
"from langchain.output_parsers.openai_tools import PydanticToolsParser\n",
"from langchain.utils.openai_functions import convert_pydantic_to_openai_tool\n",
"from langchain.schema.runnable import Runnable\n",
"from langchain.pydantic_v1 import BaseModel\n",
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain.schema.messages import SystemMessage\n",
"from langchain.schema.language_model import BaseLanguageModel\n",
"\n",
"_EXTRACTION_TEMPLATE = \"\"\"Extract and save the relevant entities mentioned \\\n",
"in the following passage together with their properties.\n",
"\n",
@@ -161,16 +163,15 @@
"def create_extraction_chain_pydantic(\n",
" pydantic_schemas: Union[List[Type[BaseModel]], Type[BaseModel]],\n",
" llm: BaseLanguageModel,\n",
" system_message: Optional[str] = _EXTRACTION_TEMPLATE,\n",
" system_message: str = _EXTRACTION_TEMPLATE,\n",
") -> Runnable:\n",
" if not isinstance(pydantic_schemas, list):\n",
" pydantic_schemas = [pydantic_schemas]\n",
" prompt = ChatPromptTemplate.from_messages({\n",
" (\"system\", _EXTRACTION_TEMPLATE),\n",
" prompt = ChatPromptTemplate.from_messages([\n",
" (\"system\", system_message),\n",
" (\"user\", \"{input}\")\n",
" })\n",
" functions = [convert_pydantic_to_openai_function(p) for p in pydantic_schemas]\n",
" tools = [{\"type\": \"function\", \"function\": d} for d in functiMons]\n",
" ])\n",
" tools = [convert_pydantic_to_openai_tool(p) for p in pydantic_schemas]\n",
" model = llm.bind(tools=tools)\n",
" chain = prompt | model | PydanticToolsParser(tools=pydantic_schemas)\n",
" return chain\n",
@@ -202,7 +203,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.1"
"version": "3.9.1"
}
},
"nbformat": 4,