mirror of
https://github.com/hwchase17/langchain
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c42ec58578
- **Updating Together.ai Endpoint**: "langchain_together: Updated Deprecated endpoint for partner package" - Description: The inference API of together is deprecates, do replaced with completions and made corresponding changes. - Twitter handle: @dev_yashmathur --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com> |
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langchain_together | ||
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poetry.lock | ||
pyproject.toml | ||
README.md |
langchain-together
This package contains the LangChain integration for Together's generative models.
Installation
pip install -U langchain-together
Embeddings
You can use Together's embedding models through TogetherEmbeddings
class.
from langchain_together import TogetherEmbeddings
embeddings = TogetherEmbeddings(
model='togethercomputer/m2-bert-80M-8k-retrieval'
)
embeddings.embed_query("What is a large language model?")
LLMs
You can use Together's generative AI models as Langchain LLMs:
from langchain_together import Together
from langchain_core.prompts import PromptTemplate
llm = Together(
model="togethercomputer/RedPajama-INCITE-7B-Base",
temperature=0.7,
max_tokens=64,
top_k=1,
# together_api_key="..."
)
template = """Question: {question}
Answer: """
prompt = PromptTemplate.from_template(template)
chain = prompt | llm
question = "Who was the president in the year Justin Beiber was born?"
print(chain.invoke({"question": question}))