mirror of
https://github.com/hwchase17/langchain.git
synced 2025-05-30 11:39:03 +00:00
2ddac9a7c3
Implemented bind_tools for OllamaFunctions. Made OllamaFunctions sub class of ChatOllama. Implemented with_structured_output for OllamaFunctions. integration unit test has been updated. notebook has been updated. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
84 lines
2.8 KiB
Python
84 lines
2.8 KiB
Python
"""Test OllamaFunctions"""
|
|
|
|
import unittest
|
|
|
|
from langchain_core.messages import AIMessage
|
|
from langchain_core.pydantic_v1 import BaseModel, Field
|
|
|
|
from langchain_experimental.llms.ollama_functions import (
|
|
OllamaFunctions,
|
|
convert_to_ollama_tool,
|
|
)
|
|
|
|
|
|
class Joke(BaseModel):
|
|
setup: str = Field(description="The setup of the joke")
|
|
punchline: str = Field(description="The punchline to the joke")
|
|
|
|
|
|
class TestOllamaFunctions(unittest.TestCase):
|
|
"""
|
|
Test OllamaFunctions
|
|
"""
|
|
|
|
def test_default_ollama_functions(self) -> None:
|
|
base_model = OllamaFunctions(model="llama3", format="json")
|
|
|
|
# bind functions
|
|
model = base_model.bind_tools(
|
|
tools=[
|
|
{
|
|
"name": "get_current_weather",
|
|
"description": "Get the current weather in a given location",
|
|
"parameters": {
|
|
"type": "object",
|
|
"properties": {
|
|
"location": {
|
|
"type": "string",
|
|
"description": "The city and state, "
|
|
"e.g. San Francisco, CA",
|
|
},
|
|
"unit": {
|
|
"type": "string",
|
|
"enum": ["celsius", "fahrenheit"],
|
|
},
|
|
},
|
|
"required": ["location"],
|
|
},
|
|
}
|
|
],
|
|
function_call={"name": "get_current_weather"},
|
|
)
|
|
|
|
res = model.invoke("What's the weather in San Francisco?")
|
|
|
|
function_call = res.additional_kwargs.get("function_call")
|
|
assert function_call
|
|
self.assertEqual(function_call.get("name"), "get_current_weather")
|
|
|
|
def test_ollama_structured_output(self) -> None:
|
|
model = OllamaFunctions(model="phi3")
|
|
structured_llm = model.with_structured_output(Joke, include_raw=False)
|
|
|
|
res = structured_llm.invoke("Tell me a joke about cats")
|
|
assert isinstance(res, Joke)
|
|
|
|
def test_ollama_structured_output_with_json(self) -> None:
|
|
model = OllamaFunctions(model="phi3")
|
|
joke_schema = convert_to_ollama_tool(Joke)
|
|
structured_llm = model.with_structured_output(joke_schema, include_raw=False)
|
|
|
|
res = structured_llm.invoke("Tell me a joke about cats")
|
|
assert "setup" in res
|
|
assert "punchline" in res
|
|
|
|
def test_ollama_structured_output_raw(self) -> None:
|
|
model = OllamaFunctions(model="phi3")
|
|
structured_llm = model.with_structured_output(Joke, include_raw=True)
|
|
|
|
res = structured_llm.invoke("Tell me a joke about cars")
|
|
assert "raw" in res
|
|
assert "parsed" in res
|
|
assert isinstance(res["raw"], AIMessage)
|
|
assert isinstance(res["parsed"], Joke)
|