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update openai functions docs (#9278)

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Bagatur
2023-08-15 17:00:56 -07:00
committed by GitHub
parent 9abf60acb6
commit afba2be3dc
2 changed files with 62 additions and 85 deletions
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44
libs/langchain/langchain/chains/openai_functions/base.py
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@@ -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")