mirror of
https://github.com/hwchase17/langchain
synced 2024-11-08 07:10:35 +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
162 lines
5.1 KiB
Python
162 lines
5.1 KiB
Python
from typing import Any, Iterator, List, Mapping, Optional
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import requests
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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.outputs import GenerationChunk
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from requests.exceptions import ConnectionError
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from langchain_community.llms.utils import enforce_stop_tokens
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class TitanTakeoff(LLM):
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"""Wrapper around Titan Takeoff APIs."""
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base_url: str = "http://localhost:8000"
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"""Specifies the baseURL to use for the Titan Takeoff API.
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Default = http://localhost:8000.
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"""
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generate_max_length: int = 128
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"""Maximum generation length. Default = 128."""
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sampling_topk: int = 1
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"""Sample predictions from the top K most probable candidates. Default = 1."""
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sampling_topp: float = 1.0
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"""Sample from predictions whose cumulative probability exceeds this value.
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Default = 1.0.
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"""
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sampling_temperature: float = 1.0
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"""Sample with randomness. Bigger temperatures are associated with
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more randomness and 'creativity'. Default = 1.0.
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"""
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repetition_penalty: float = 1.0
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"""Penalise the generation of tokens that have been generated before.
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Set to > 1 to penalize. Default = 1 (no penalty).
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"""
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no_repeat_ngram_size: int = 0
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"""Prevent repetitions of ngrams of this size. Default = 0 (turned off)."""
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streaming: bool = False
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"""Whether to stream the output. Default = False."""
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@property
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def _default_params(self) -> Mapping[str, Any]:
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"""Get the default parameters for calling Titan Takeoff Server."""
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params = {
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"generate_max_length": self.generate_max_length,
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"sampling_topk": self.sampling_topk,
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"sampling_topp": self.sampling_topp,
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"sampling_temperature": self.sampling_temperature,
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"repetition_penalty": self.repetition_penalty,
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"no_repeat_ngram_size": self.no_repeat_ngram_size,
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}
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return 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 "titan_takeoff"
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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 out to Titan Takeoff generate endpoint.
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Args:
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prompt: The prompt to pass into the model.
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stop: Optional list of stop words to use when generating.
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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 = "What is the capital of the United Kingdom?"
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response = model(prompt)
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"""
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try:
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if self.streaming:
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text_output = ""
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for chunk in self._stream(
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prompt=prompt,
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stop=stop,
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run_manager=run_manager,
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):
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text_output += chunk.text
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return text_output
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url = f"{self.base_url}/generate"
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params = {"text": prompt, **self._default_params}
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response = requests.post(url, json=params)
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response.raise_for_status()
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response.encoding = "utf-8"
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text = ""
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if "message" in response.json():
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text = response.json()["message"]
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else:
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raise ValueError("Something went wrong.")
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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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except ConnectionError:
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raise ConnectionError(
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"Could not connect to Titan Takeoff server. \
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Please make sure that the server is running."
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)
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def _stream(
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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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) -> Iterator[GenerationChunk]:
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"""Call out to Titan Takeoff stream endpoint.
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Args:
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prompt: The prompt to pass into the model.
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stop: Optional list of stop words to use when generating.
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Returns:
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The string generated by the model.
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Yields:
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A dictionary like object containing a string token.
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Example:
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.. code-block:: python
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prompt = "What is the capital of the United Kingdom?"
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response = model(prompt)
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"""
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url = f"{self.base_url}/generate_stream"
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params = {"text": prompt, **self._default_params}
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response = requests.post(url, json=params, stream=True)
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response.encoding = "utf-8"
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for text in response.iter_content(chunk_size=1, decode_unicode=True):
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if text:
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chunk = GenerationChunk(text=text)
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yield chunk
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if run_manager:
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run_manager.on_llm_new_token(token=chunk.text)
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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 {"base_url": self.base_url, **{}, **self._default_params}
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