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https://github.com/hwchase17/langchain.git
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8461934c2b
supports following UX
```python
class SubTool(TypedDict):
"""Subtool docstring"""
args: Annotated[Dict[str, Any], {}, "this does bar"]
class Tool(TypedDict):
"""Docstring
Args:
arg1: foo
"""
arg1: str
arg2: Union[int, str]
arg3: Optional[List[SubTool]]
arg4: Annotated[Literal["bar", "baz"], ..., "this does foo"]
arg5: Annotated[Optional[float], None]
```
- can parse google style docstring
- can use Annotated to specify default value (second arg)
- can use Annotated to specify arg description (third arg)
- can have nested complex types
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")