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dbf9986d44
Replacement for PR #30191 (@ccurme) **Description**: currently, ChatOllama [will raise a value error if a ChatMessage is passed to it](https://github.com/langchain-ai/langchain/blob/master/libs/partners/ollama/langchain_ollama/chat_models.py#L514), as described https://github.com/langchain-ai/langchain/pull/30147#issuecomment-2708932481. Furthermore, ollama-python is removing the limitations on valid roles that can be passed through chat messages to a model in ollama - https://github.com/ollama/ollama-python/pull/462#event-16917810634. This PR removes the role limitations imposed by langchain and enables passing langchain ChatMessages with arbitrary 'role' values through the langchain ChatOllama class to the underlying ollama-python Client. As this PR relies on [merged but unreleased functionality in ollama-python]( https://github.com/ollama/ollama-python/pull/462#event-16917810634), I have temporarily pointed the ollama package source to the main branch of the ollama-python github repo. Format, lint, and tests of new functionality passing. Need to resolve issue with recently added ChatOllama tests. (Now resolved) **Issue**: resolves #30122 (related to ollama issue https://github.com/ollama/ollama/issues/8955) **Dependencies**: no new dependencies [x] PR title [x] PR message [x] Lint and test: format, lint, and test all running successfully and passing --------- Co-authored-by: Ryan Stewart <ryanstewart@Ryans-MacBook-Pro.local> Co-authored-by: Chester Curme <chester.curme@gmail.com>
langchain-ollama
This package contains the LangChain integration with Ollama
Installation
pip install -U langchain-ollama
You will also need to run the Ollama server locally. You can download it here.
Chat Models
ChatOllama class exposes chat models from Ollama.
from langchain_ollama import ChatOllama
llm = ChatOllama(model="llama3-groq-tool-use")
llm.invoke("Sing a ballad of LangChain.")
Embeddings
OllamaEmbeddings class exposes embeddings from Ollama.
from langchain_ollama import OllamaEmbeddings
embeddings = OllamaEmbeddings(model="llama3")
embeddings.embed_query("What is the meaning of life?")
LLMs
OllamaLLM class exposes LLMs from Ollama.
from langchain_ollama import OllamaLLM
llm = OllamaLLM(model="llama3")
llm.invoke("The meaning of life is")