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community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463)
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
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234
libs/community/langchain_community/llms/rwkv.py
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234
libs/community/langchain_community/llms/rwkv.py
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"""RWKV models.
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Based on https://github.com/saharNooby/rwkv.cpp/blob/master/rwkv/chat_with_bot.py
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https://github.com/BlinkDL/ChatRWKV/blob/main/v2/chat.py
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"""
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from typing import Any, Dict, List, Mapping, Optional, Set
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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 BaseModel, Extra, root_validator
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from langchain_community.llms.utils import enforce_stop_tokens
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class RWKV(LLM, BaseModel):
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"""RWKV language models.
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To use, you should have the ``rwkv`` python package installed, the
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pre-trained model file, and the model's config information.
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Example:
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.. code-block:: python
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from langchain_community.llms import RWKV
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model = RWKV(model="./models/rwkv-3b-fp16.bin", strategy="cpu fp32")
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# Simplest invocation
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response = model("Once upon a time, ")
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"""
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model: str
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"""Path to the pre-trained RWKV model file."""
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tokens_path: str
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"""Path to the RWKV tokens file."""
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strategy: str = "cpu fp32"
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"""Token context window."""
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rwkv_verbose: bool = True
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"""Print debug information."""
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temperature: float = 1.0
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"""The temperature to use for sampling."""
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top_p: float = 0.5
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"""The top-p value to use for sampling."""
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penalty_alpha_frequency: float = 0.4
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"""Positive values penalize new tokens based on their existing frequency
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in the text so far, decreasing the model's likelihood to repeat the same
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line verbatim.."""
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penalty_alpha_presence: float = 0.4
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"""Positive values penalize new tokens based on whether they appear
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in the text so far, increasing the model's likelihood to talk about
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new topics.."""
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CHUNK_LEN: int = 256
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"""Batch size for prompt processing."""
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max_tokens_per_generation: int = 256
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"""Maximum number of tokens to generate."""
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client: Any = None #: :meta private:
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tokenizer: Any = None #: :meta private:
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pipeline: Any = None #: :meta private:
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model_tokens: Any = None #: :meta private:
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model_state: Any = None #: :meta private:
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class Config:
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"""Configuration for this pydantic object."""
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extra = Extra.forbid
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@property
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def _default_params(self) -> Dict[str, Any]:
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"""Get the identifying parameters."""
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return {
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"verbose": self.verbose,
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"top_p": self.top_p,
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"temperature": self.temperature,
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"penalty_alpha_frequency": self.penalty_alpha_frequency,
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"penalty_alpha_presence": self.penalty_alpha_presence,
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"CHUNK_LEN": self.CHUNK_LEN,
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"max_tokens_per_generation": self.max_tokens_per_generation,
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}
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@staticmethod
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def _rwkv_param_names() -> Set[str]:
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"""Get the identifying parameters."""
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return {
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"verbose",
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}
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@root_validator()
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that the python package exists in the environment."""
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try:
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import tokenizers
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except ImportError:
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raise ImportError(
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"Could not import tokenizers python package. "
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"Please install it with `pip install tokenizers`."
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)
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try:
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from rwkv.model import RWKV as RWKVMODEL
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from rwkv.utils import PIPELINE
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values["tokenizer"] = tokenizers.Tokenizer.from_file(values["tokens_path"])
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rwkv_keys = cls._rwkv_param_names()
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model_kwargs = {k: v for k, v in values.items() if k in rwkv_keys}
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model_kwargs["verbose"] = values["rwkv_verbose"]
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values["client"] = RWKVMODEL(
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values["model"], strategy=values["strategy"], **model_kwargs
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)
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values["pipeline"] = PIPELINE(values["client"], values["tokens_path"])
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except ImportError:
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raise ImportError(
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"Could not import rwkv python package. "
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"Please install it with `pip install rwkv`."
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)
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return values
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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 {
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"model": self.model,
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**self._default_params,
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**{k: v for k, v in self.__dict__.items() if k in RWKV._rwkv_param_names()},
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}
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@property
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def _llm_type(self) -> str:
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"""Return the type of llm."""
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return "rwkv"
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def run_rnn(self, _tokens: List[str], newline_adj: int = 0) -> Any:
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AVOID_REPEAT_TOKENS = []
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AVOID_REPEAT = "，：？！"
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for i in AVOID_REPEAT:
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dd = self.pipeline.encode(i)
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assert len(dd) == 1
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AVOID_REPEAT_TOKENS += dd
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tokens = [int(x) for x in _tokens]
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self.model_tokens += tokens
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out: Any = None
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while len(tokens) > 0:
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out, self.model_state = self.client.forward(
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tokens[: self.CHUNK_LEN], self.model_state
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)
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tokens = tokens[self.CHUNK_LEN :]
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END_OF_LINE = 187
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out[END_OF_LINE] += newline_adj # adjust \n probability
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if self.model_tokens[-1] in AVOID_REPEAT_TOKENS:
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out[self.model_tokens[-1]] = -999999999
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return out
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def rwkv_generate(self, prompt: str) -> str:
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self.model_state = None
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self.model_tokens = []
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logits = self.run_rnn(self.tokenizer.encode(prompt).ids)
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begin = len(self.model_tokens)
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out_last = begin
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occurrence: Dict = {}
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decoded = ""
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for i in range(self.max_tokens_per_generation):
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for n in occurrence:
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logits[n] -= (
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self.penalty_alpha_presence
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+ occurrence[n] * self.penalty_alpha_frequency
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)
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token = self.pipeline.sample_logits(
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logits, temperature=self.temperature, top_p=self.top_p
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)
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END_OF_TEXT = 0
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if token == END_OF_TEXT:
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break
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if token not in occurrence:
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occurrence[token] = 1
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else:
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occurrence[token] += 1
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logits = self.run_rnn([token])
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xxx = self.tokenizer.decode(self.model_tokens[out_last:])
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if "\ufffd" not in xxx: # avoid utf-8 display issues
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decoded += xxx
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out_last = begin + i + 1
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if i >= self.max_tokens_per_generation - 100:
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break
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return decoded
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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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r"""RWKV generation
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Args:
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prompt: The prompt to pass into the model.
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stop: A list of strings to stop generation when encountered.
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Returns:
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The string generated by the model.
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Example:
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.. code-block:: python
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prompt = "Once upon a time, "
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response = model(prompt, n_predict=55)
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"""
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text = self.rwkv_generate(prompt)
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if stop is not None:
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text = enforce_stop_tokens(text, stop)
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return text
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