29 lines
1.2 KiB
Python
29 lines
1.2 KiB
Python
from typing import Any, Dict
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from ollama import Client
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from langchain_core.runnables.base import Runnable
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from langchain.prompts.base import StringPromptValue
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class OllamaWrapper(Runnable):
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def __init__(self, host: str):
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self.client = Client(host=host)
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def invoke(self, prompt: Any, config: Dict[str, Any] = None, **kwargs: Any) -> str:
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if isinstance(prompt, StringPromptValue):
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prompt = prompt.to_string()
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model_name = kwargs.get("model", "llama3")
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options = {
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"temperature": kwargs.get("temperature"),
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"top_p": kwargs.get("top_p"),
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"max_tokens": kwargs.get("max_tokens"),
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}
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messages = [{"role": "user", "content": prompt}]
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response = self.client.chat(model=model_name, messages=messages, options=options)
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if response and "message" in response and "content" in response["message"]:
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return response["message"]["content"]
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else:
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raise ValueError("Invalid response structure from model")
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async def ainvoke(self, prompt: Any, config: Dict[str, Any] = None, **kwargs: Any) -> str:
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return self.invoke(prompt, config, **kwargs)
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