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
152 lines
4.6 KiB
Python
152 lines
4.6 KiB
Python
from __future__ import annotations
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from typing import Any, Dict, List, Mapping, Optional
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from langchain_core.callbacks import (
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AsyncCallbackManagerForLLMRun,
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CallbackManagerForLLMRun,
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)
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from langchain_core.language_models.llms import LLM
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from langchain_core.pydantic_v1 import BaseModel, Extra
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# Ignoring type because below is valid pydantic code
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# Unexpected keyword argument "extra" for "__init_subclass__" of "object"
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class Params(BaseModel, extra=Extra.allow): # type: ignore[call-arg]
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"""Parameters for the Javelin AI Gateway LLM."""
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temperature: float = 0.0
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stop: Optional[List[str]] = None
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max_tokens: Optional[int] = None
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class JavelinAIGateway(LLM):
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"""Javelin AI Gateway LLMs.
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To use, you should have the ``javelin_sdk`` python package installed.
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For more information, see https://docs.getjavelin.io
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Example:
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.. code-block:: python
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from langchain_community.llms import JavelinAIGateway
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completions = JavelinAIGateway(
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gateway_uri="<your-javelin-ai-gateway-uri>",
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route="<your-javelin-ai-gateway-completions-route>",
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params={
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"temperature": 0.1
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}
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)
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"""
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route: str
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"""The route to use for the Javelin AI Gateway API."""
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client: Optional[Any] = None
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"""The Javelin AI Gateway client."""
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gateway_uri: Optional[str] = None
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"""The URI of the Javelin AI Gateway API."""
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params: Optional[Params] = None
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"""Parameters for the Javelin AI Gateway API."""
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javelin_api_key: Optional[str] = None
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"""The API key for the Javelin AI Gateway API."""
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def __init__(self, **kwargs: Any):
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try:
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from javelin_sdk import (
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JavelinClient,
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UnauthorizedError,
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)
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except ImportError:
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raise ImportError(
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"Could not import javelin_sdk python package. "
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"Please install it with `pip install javelin_sdk`."
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)
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super().__init__(**kwargs)
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if self.gateway_uri:
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try:
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self.client = JavelinClient(
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base_url=self.gateway_uri, api_key=self.javelin_api_key
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)
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except UnauthorizedError as e:
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raise ValueError("Javelin: Incorrect API Key.") from e
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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 Javelin AI Gateway API."""
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params: Dict[str, Any] = {
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"gateway_uri": self.gateway_uri,
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"route": self.route,
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"javelin_api_key": self.javelin_api_key,
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**(self.params.dict() if self.params else {}),
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}
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return params
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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 self._default_params
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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 Javelin AI Gateway API."""
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data: Dict[str, Any] = {
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"prompt": prompt,
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**(self.params.dict() if self.params else {}),
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}
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if s := (stop or (self.params.stop if self.params else None)):
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data["stop"] = s
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if self.client is not None:
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resp = self.client.query_route(self.route, query_body=data)
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else:
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raise ValueError("Javelin client is not initialized.")
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resp_dict = resp.dict()
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try:
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return resp_dict["llm_response"]["choices"][0]["text"]
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except KeyError:
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return ""
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async def _acall(
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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[AsyncCallbackManagerForLLMRun] = None,
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**kwargs: Any,
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) -> str:
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"""Call async the Javelin AI Gateway API."""
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data: Dict[str, Any] = {
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"prompt": prompt,
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**(self.params.dict() if self.params else {}),
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}
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if s := (stop or (self.params.stop if self.params else None)):
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data["stop"] = s
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if self.client is not None:
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resp = await self.client.aquery_route(self.route, query_body=data)
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else:
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raise ValueError("Javelin client is not initialized.")
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resp_dict = resp.dict()
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try:
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return resp_dict["llm_response"]["choices"][0]["text"]
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except KeyError:
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return ""
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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 "javelin-ai-gateway"
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