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update openai functions docs (#9278)

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Bagatur 1 year ago committed by GitHub
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103
docs/extras/modules/chains/how_to/openai_functions.ipynb
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@ -83,10 +83,8 @@
"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
"Prompt after formatting:\n",
"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for extracting information in structured formats.\n",
"Human: Use the given format to extract information from the following input:\n",
"Human: Sally is 13\n",
"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
" {'function_call': {'name': '_OutputFormatter', 'arguments': '{\\n \"output\": {\\n \"name\": \"Sally\",\\n \"age\": 13,\\n \"fav_food\": \"Unknown\"\\n }\\n}'}}\n",
"Human: Use the given format to extract information from the following input: Sally is 13\n",
"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
@ -105,18 +103,13 @@
"source": [
"# If we pass in a model explicitly, we need to make sure it supports the OpenAI function-calling API.\n",
"llm = ChatOpenAI(model=\"gpt-4\", temperature=0)\n",
"\n",
"prompt_msgs = [\n",
" SystemMessage(\n",
" content=\"You are a world class algorithm for extracting information in structured formats.\"\n",
" ),\n",
" HumanMessage(\n",
" content=\"Use the given format to extract information from the following input:\"\n",
" ),\n",
" HumanMessagePromptTemplate.from_template(\"{input}\"),\n",
" HumanMessage(content=\"Tips: Make sure to answer in the correct format\"),\n",
"]\n",
"prompt = ChatPromptTemplate(messages=prompt_msgs)\n",
"prompt = ChatPromptTemplate.from_messages(\n",
" [\n",
" (\"system\", \"You are a world class algorithm for extracting information in structured formats.\"),\n",
" (\"human\", \"Use the given format to extract information from the following input: {input}\"),\n",
" (\"human\", \"Tip: Make sure to answer in the correct format\"),\n",
" ]\n",
")\n",
"\n",
"chain = create_structured_output_chain(Person, llm, prompt, verbose=True)\n",
"chain.run(\"Sally is 13\")"
@ -132,7 +125,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 5,
"id": "4d8ea815",
"metadata": {},
"outputs": [
@ -145,10 +138,8 @@
"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
"Prompt after formatting:\n",
"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for extracting information in structured formats.\n",
"Human: Use the given format to extract information from the following input:\n",
"Human: Sally is 13, Joey just turned 12 and loves spinach. Caroline is 10 years older than Sally, so she's 23.\n",
"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
" {'function_call': {'name': '_OutputFormatter', 'arguments': '{\\n \"output\": {\\n \"people\": [\\n {\\n \"name\": \"Sally\",\\n \"age\": 13,\\n \"fav_food\": \"\"\\n },\\n {\\n \"name\": \"Joey\",\\n \"age\": 12,\\n \"fav_food\": \"spinach\"\\n },\\n {\\n \"name\": \"Caroline\",\\n \"age\": 23,\\n \"fav_food\": \"\"\\n }\\n ]\\n }\\n}'}}\n",
"Human: Use the given format to extract information from the following input: Sally is 13, Joey just turned 12 and loves spinach. Caroline is 10 years older than Sally.\n",
"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
@ -159,7 +150,7 @@
"People(people=[Person(name='Sally', age=13, fav_food=''), Person(name='Joey', age=12, fav_food='spinach'), Person(name='Caroline', age=23, fav_food='')])"
]
},
"execution_count": 4,
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
@ -176,7 +167,7 @@
"\n",
"chain = create_structured_output_chain(People, llm, prompt, verbose=True)\n",
"chain.run(\n",
" \"Sally is 13, Joey just turned 12 and loves spinach. Caroline is 10 years older than Sally, so she's 23.\"\n",
" \"Sally is 13, Joey just turned 12 and loves spinach. Caroline is 10 years older than Sally.\"\n",
")"
]
},
@ -229,10 +220,8 @@
"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
"Prompt after formatting:\n",
"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for extracting information in structured formats.\n",
"Human: Use the given format to extract information from the following input:\n",
"Human: Sally is 13\n",
"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
" {'function_call': {'name': 'output_formatter', 'arguments': '{\\n \"name\": \"Sally\",\\n \"age\": 13\\n}'}}\n",
"Human: Use the given format to extract information from the following input: Sally is 13\n",
"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
@ -279,7 +268,7 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 9,
"id": "17f52508",
"metadata": {},
"outputs": [],
@ -302,7 +291,7 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 10,
"id": "a4658ad8",
"metadata": {},
"outputs": [
@ -314,11 +303,9 @@
"\n",
"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
"Prompt after formatting:\n",
"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities\n",
"Human: Make calls to the relevant function to record the entities in the following input:\n",
"Human: Harry was a chubby brown beagle who loved chicken\n",
"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
" {'function_call': {'name': 'RecordDog', 'arguments': '{\\n \"name\": \"Harry\",\\n \"color\": \"brown\",\\n \"fav_food\": \"chicken\"\\n}'}}\n",
"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities.\n",
"Human: Make calls to the relevant function to record the entities in the following input: Harry was a chubby brown beagle who loved chicken\n",
"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
@ -329,21 +316,19 @@
"RecordDog(name='Harry', color='brown', fav_food='chicken')"
]
},
"execution_count": 9,
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"prompt_msgs = [\n",
" SystemMessage(content=\"You are a world class algorithm for recording entities\"),\n",
" HumanMessage(\n",
" content=\"Make calls to the relevant function to record the entities in the following input:\"\n",
" ),\n",
" HumanMessagePromptTemplate.from_template(\"{input}\"),\n",
" HumanMessage(content=\"Tips: Make sure to answer in the correct format\"),\n",
"]\n",
"prompt = ChatPromptTemplate(messages=prompt_msgs)\n",
"prompt = ChatPromptTemplate.from_messages(\n",
" [\n",
" (\"system\", \"You are a world class algorithm for recording entities.\"),\n",
" (\"human\", \"Make calls to the relevant function to record the entities in the following input: {input}\"),\n",
" (\"human\", \"Tip: Make sure to answer in the correct format\"),\n",
" ]\n",
")\n",
"\n",
"chain = create_openai_fn_chain([RecordPerson, RecordDog], llm, prompt, verbose=True)\n",
"chain.run(\"Harry was a chubby brown beagle who loved chicken\")"
@ -362,7 +347,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 11,
"id": "95ac5825",
"metadata": {},
"outputs": [
@ -374,11 +359,9 @@
"\n",
"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
"Prompt after formatting:\n",
"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities\n",
"Human: Make calls to the relevant function to record the entities in the following input:\n",
"Human: The most important thing to remember about Tommy, my 12 year old, is that he'll do anything for apple pie.\n",
"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
" {'function_call': {'name': 'record_person', 'arguments': '{\\n \"name\": \"Tommy\",\\n \"age\": 12,\\n \"fav_food\": {\\n \"food\": \"apple pie\"\\n }\\n}'}}\n",
"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities.\n",
"Human: Make calls to the relevant function to record the entities in the following input: The most important thing to remember about Tommy, my 12 year old, is that he'll do anything for apple pie.\n",
"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
@ -389,7 +372,7 @@
"{'name': 'Tommy', 'age': 12, 'fav_food': {'food': 'apple pie'}}"
]
},
"execution_count": 10,
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
@ -434,7 +417,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 12,
"id": "8b0d11de",
"metadata": {},
"outputs": [
@ -446,11 +429,9 @@
"\n",
"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
"Prompt after formatting:\n",
"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities\n",
"Human: Make calls to the relevant function to record the entities in the following input:\n",
"Human: I can't find my dog Henry anywhere, he's a small brown beagle. Could you send a message about him?\n",
"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
" {'function_call': {'name': 'record_dog', 'arguments': '{\\n \"name\": \"Henry\",\\n \"color\": \"brown\",\\n \"fav_food\": {\\n \"food\": null\\n }\\n}'}}\n",
"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities.\n",
"Human: Make calls to the relevant function to record the entities in the following input: I can't find my dog Henry anywhere, he's a small brown beagle. Could you send a message about him?\n",
"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
@ -462,7 +443,7 @@
" 'arguments': {'name': 'Henry', 'color': 'brown', 'fav_food': {'food': None}}}"
]
},
"execution_count": 11,
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
@ -502,9 +483,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "venv",
"display_name": "poetry-venv",
"language": "python",
"name": "venv"
"name": "poetry-venv"
},
"language_info": {
"codemirror_mode": {
@ -516,7 +497,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
"version": "3.9.1"
}
},
"nbformat": 4,

44
libs/langchain/langchain/chains/openai_functions/base.py
Unescape Escape View File

@ -226,9 +226,9 @@ def create_openai_fn_chain(
from langchain.chains.openai_functions import create_openai_fn_chain
from langchain.chat_models import ChatOpenAI
from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate
from langchain.prompts import ChatPromptTemplate
from pydantic_v1 import BaseModel, Field
from pydantic import BaseModel, Field
class RecordPerson(BaseModel):
@ -247,17 +247,15 @@ def create_openai_fn_chain(
fav_food: Optional[str] = Field(None, description="The dog's favorite food")
llm = ChatOpenAI(model="gpt-3.5-turbo-0613", temperature=0)
prompt_msgs = [
SystemMessage(
content="You are a world class algorithm for recording entities"
),
HumanMessage(content="Make calls to the relevant function to record the entities in the following input:"),
HumanMessagePromptTemplate.from_template("{input}"),
HumanMessage(content="Tips: Make sure to answer in the correct format"),
]
prompt = ChatPromptTemplate(messages=prompt_msgs)
chain = create_openai_fn_chain([RecordPerson, RecordDog])
llm = ChatOpenAI(model="gpt-4", temperature=0)
prompt = ChatPromptTemplate.from_messages(
[
("system", "You are a world class algorithm for recording entities."),
("human", "Make calls to the relevant function to record the entities in the following input: {input}"),
("human", "Tip: Make sure to answer in the correct format"),
]
)
chain = create_openai_fn_chain([RecordPerson, RecordDog], llm, prompt)
chain.run("Harry was a chubby brown beagle who loved chicken")
# -> RecordDog(name="Harry", color="brown", fav_food="chicken")
""" # noqa: E501
@ -312,9 +310,9 @@ def create_structured_output_chain(
from langchain.chains.openai_functions import create_structured_output_chain
from langchain.chat_models import ChatOpenAI
from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate
from langchain.prompts import ChatPromptTemplate
from pydantic_v1 import BaseModel, Field
from pydantic import BaseModel, Field
class Dog(BaseModel):
\"\"\"Identifying information about a dog.\"\"\"
@ -324,15 +322,13 @@ def create_structured_output_chain(
fav_food: Optional[str] = Field(None, description="The dog's favorite food")
llm = ChatOpenAI(model="gpt-3.5-turbo-0613", temperature=0)
prompt_msgs = [
SystemMessage(
content="You are a world class algorithm for extracting information in structured formats."
),
HumanMessage(content="Use the given format to extract information from the following input:"),
HumanMessagePromptTemplate.from_template("{input}"),
HumanMessage(content="Tips: Make sure to answer in the correct format"),
]
prompt = ChatPromptTemplate(messages=prompt_msgs)
prompt = ChatPromptTemplate.from_messages(
[
("system", "You are a world class algorithm for extracting information in structured formats."),
("human", "Use the given format to extract information from the following input: {input}"),
("human", "Tip: Make sure to answer in the correct format"),
]
)
chain = create_structured_output_chain(Dog, llm, prompt)
chain.run("Harry was a chubby brown beagle who loved chicken")
# -> Dog(name="Harry", color="brown", fav_food="chicken")

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