mirror of
https://github.com/hwchase17/langchain
synced 2024-11-02 09:40:22 +00:00
ed58eeb9c5
Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
153 lines
5.2 KiB
Python
153 lines
5.2 KiB
Python
import logging
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from typing import Any, Dict, List, Mapping, Optional
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from langchain_core.callbacks import CallbackManagerForLLMRun
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from langchain_core.language_models.llms import LLM
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from langchain_core.pydantic_v1 import Extra, Field, SecretStr, root_validator
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from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
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logger = logging.getLogger(__name__)
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class GooseAI(LLM):
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"""GooseAI large language models.
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To use, you should have the ``openai`` python package installed, and the
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environment variable ``GOOSEAI_API_KEY`` set with your API key.
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Any parameters that are valid to be passed to the openai.create call can be passed
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in, even if not explicitly saved on this class.
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Example:
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.. code-block:: python
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from langchain_community.llms import GooseAI
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gooseai = GooseAI(model_name="gpt-neo-20b")
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"""
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client: Any
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model_name: str = "gpt-neo-20b"
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"""Model name to use"""
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temperature: float = 0.7
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"""What sampling temperature to use"""
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max_tokens: int = 256
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"""The maximum number of tokens to generate in the completion.
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-1 returns as many tokens as possible given the prompt and
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the models maximal context size."""
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top_p: float = 1
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"""Total probability mass of tokens to consider at each step."""
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min_tokens: int = 1
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"""The minimum number of tokens to generate in the completion."""
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frequency_penalty: float = 0
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"""Penalizes repeated tokens according to frequency."""
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presence_penalty: float = 0
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"""Penalizes repeated tokens."""
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n: int = 1
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"""How many completions to generate for each prompt."""
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model_kwargs: Dict[str, Any] = Field(default_factory=dict)
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"""Holds any model parameters valid for `create` call not explicitly specified."""
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logit_bias: Optional[Dict[str, float]] = Field(default_factory=dict)
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"""Adjust the probability of specific tokens being generated."""
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gooseai_api_key: Optional[SecretStr] = None
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class Config:
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"""Configuration for this pydantic config."""
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extra = Extra.ignore
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@root_validator(pre=True)
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def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
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"""Build extra kwargs from additional params that were passed in."""
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all_required_field_names = {field.alias for field in cls.__fields__.values()}
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extra = values.get("model_kwargs", {})
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for field_name in list(values):
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if field_name not in all_required_field_names:
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if field_name in extra:
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raise ValueError(f"Found {field_name} supplied twice.")
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logger.warning(
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f"""WARNING! {field_name} is not default parameter.
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{field_name} was transferred to model_kwargs.
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Please confirm that {field_name} is what you intended."""
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)
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extra[field_name] = values.pop(field_name)
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values["model_kwargs"] = extra
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return values
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@root_validator()
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that api key and python package exists in environment."""
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gooseai_api_key = convert_to_secret_str(
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get_from_dict_or_env(values, "gooseai_api_key", "GOOSEAI_API_KEY")
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)
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values["gooseai_api_key"] = gooseai_api_key
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try:
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import openai
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openai.api_key = gooseai_api_key.get_secret_value()
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openai.api_base = "https://api.goose.ai/v1"
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values["client"] = openai.Completion
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except ImportError:
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raise ImportError(
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"Could not import openai python package. "
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"Please install it with `pip install openai`."
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)
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return values
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@property
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def _default_params(self) -> Dict[str, Any]:
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"""Get the default parameters for calling GooseAI API."""
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normal_params = {
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"temperature": self.temperature,
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"max_tokens": self.max_tokens,
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"top_p": self.top_p,
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"min_tokens": self.min_tokens,
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"frequency_penalty": self.frequency_penalty,
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"presence_penalty": self.presence_penalty,
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"n": self.n,
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"logit_bias": self.logit_bias,
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}
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return {**normal_params, **self.model_kwargs}
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@property
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def _identifying_params(self) -> Mapping[str, Any]:
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"""Get the identifying parameters."""
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return {**{"model_name": self.model_name}, **self._default_params}
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@property
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def _llm_type(self) -> str:
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"""Return type of llm."""
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return "gooseai"
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def _call(
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self,
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prompt: str,
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stop: Optional[List[str]] = None,
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run_manager: Optional[CallbackManagerForLLMRun] = None,
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**kwargs: Any,
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) -> str:
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"""Call the GooseAI API."""
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params = self._default_params
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if stop is not None:
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if "stop" in params:
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raise ValueError("`stop` found in both the input and default params.")
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params["stop"] = stop
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params = {**params, **kwargs}
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response = self.client.create(engine=self.model_name, prompt=prompt, **params)
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text = response.choices[0].text
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return text
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