51 lines
1.8 KiB
Python
51 lines
1.8 KiB
Python
import logging
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from collections.abc import Iterable
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from typing import Optional, Union
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from langchain.callbacks.manager import CallbackManager
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from langchain.callbacks.stdout import StdOutCallbackHandler
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from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
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from langchain_community.llms.ollama import Ollama
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from ollama import Client
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from embedchain.config import BaseLlmConfig
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from embedchain.helpers.json_serializable import register_deserializable
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from embedchain.llm.base import BaseLlm
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logger = logging.getLogger(__name__)
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@register_deserializable
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class OllamaLlm(BaseLlm):
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def __init__(self, config: Optional[BaseLlmConfig] = None):
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super().__init__(config=config)
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if self.config.model is None:
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self.config.model = "llama2"
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client = Client(host=config.base_url)
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local_models = client.list()["models"]
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if not any(model.get("name") == self.config.model for model in local_models):
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logger.info(f"Pulling {self.config.model} from Ollama!")
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client.pull(self.config.model)
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def get_llm_model_answer(self, prompt):
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return self._get_answer(prompt=prompt, config=self.config)
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@staticmethod
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def _get_answer(prompt: str, config: BaseLlmConfig) -> Union[str, Iterable]:
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if config.stream:
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callbacks = config.callbacks if config.callbacks else [StreamingStdOutCallbackHandler()]
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else:
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callbacks = [StdOutCallbackHandler()]
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llm = Ollama(
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model=config.model,
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system=config.system_prompt,
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temperature=config.temperature,
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top_p=config.top_p,
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callback_manager=CallbackManager(callbacks),
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base_url=config.base_url,
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)
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return llm.invoke(prompt)
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