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
66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
"""Util that calls SceneXplain.
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In order to set this up, you need API key for the SceneXplain API.
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You can obtain a key by following the steps below.
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- Sign up for a free account at https://scenex.jina.ai/.
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- Navigate to the API Access page (https://scenex.jina.ai/api) and create a new API key.
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"""
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from typing import Dict
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import requests
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from langchain_core.pydantic_v1 import BaseModel, BaseSettings, Field, root_validator
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from langchain_core.utils import get_from_dict_or_env
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class SceneXplainAPIWrapper(BaseSettings, BaseModel):
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"""Wrapper for SceneXplain API.
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In order to set this up, you need API key for the SceneXplain API.
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You can obtain a key by following the steps below.
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- Sign up for a free account at https://scenex.jina.ai/.
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- Navigate to the API Access page (https://scenex.jina.ai/api)
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and create a new API key.
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"""
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scenex_api_key: str = Field(..., env="SCENEX_API_KEY")
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scenex_api_url: str = "https://api.scenex.jina.ai/v1/describe"
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def _describe_image(self, image: str) -> str:
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headers = {
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"x-api-key": f"token {self.scenex_api_key}",
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"content-type": "application/json",
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}
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payload = {
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"data": [
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{
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"image": image,
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"algorithm": "Ember",
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"languages": ["en"],
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}
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]
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}
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response = requests.post(self.scenex_api_url, headers=headers, json=payload)
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response.raise_for_status()
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result = response.json().get("result", [])
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img = result[0] if result else {}
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return img.get("text", "")
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@root_validator(pre=True)
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def validate_environment(cls, values: Dict) -> Dict:
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"""Validate that api key exists in environment."""
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scenex_api_key = get_from_dict_or_env(
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values, "scenex_api_key", "SCENEX_API_KEY"
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)
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values["scenex_api_key"] = scenex_api_key
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return values
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def run(self, image: str) -> str:
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"""Run SceneXplain image explainer."""
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description = self._describe_image(image)
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if not description:
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return "No description found."
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return description
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