mirror of https://github.com/hwchase17/langchain
docs: `integrations/providers/` update (#14315)
- added missed provider files (from `integrations/Callbacks` - updated notebooks: added links; updated into consistent formatspull/14626/head
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# Context
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>[Context](https://context.ai/) provides user analytics for LLM-powered products and features.
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## Installation and Setup
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We need to install the `context-python` Python package:
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```bash
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pip install context-python
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```
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## Callbacks
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See a [usage example](/docs/integrations/callbacks/context).
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```python
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from langchain.callbacks import ContextCallbackHandler
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```
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# Label Studio
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>[Label Studio](https://labelstud.io/guide/get_started) is an open-source data labeling platform that provides LangChain with flexibility when it comes to labeling data for fine-tuning large language models (LLMs). It also enables the preparation of custom training data and the collection and evaluation of responses through human feedback.
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## Installation and Setup
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See the [Label Studio installation guide](https://labelstud.io/guide/install) for installation options.
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We need to install the `label-studio` and `label-studio-sdk-python` Python packages:
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```bash
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pip install label-studio label-studio-sdk
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```
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## Callbacks
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See a [usage example](/docs/integrations/callbacks/labelstudio).
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```python
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from langchain.callbacks import LabelStudioCallbackHandler
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```
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# LLMonitor
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>[LLMonitor](https://llmonitor.com?utm_source=langchain&utm_medium=py&utm_campaign=docs) is an open-source observability platform that provides cost and usage analytics, user tracking, tracing and evaluation tools.
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## Installation and Setup
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Create an account on [llmonitor.com](https://llmonitor.com?utm_source=langchain&utm_medium=py&utm_campaign=docs), then copy your new app's `tracking id`.
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Once you have it, set it as an environment variable by running:
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```bash
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export LLMONITOR_APP_ID="..."
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```
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## Callbacks
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See a [usage example](/docs/integrations/callbacks/llmonitor).
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```python
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from langchain.callbacks import LLMonitorCallbackHandler
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```
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# Trubrics
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>[Trubrics](https://trubrics.com) is an LLM user analytics platform that lets you collect, analyse and manage user
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prompts & feedback on AI models.
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>
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>Check out [Trubrics repo](https://github.com/trubrics/trubrics-sdk) for more information on `Trubrics`.
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## Installation and Setup
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We need to install the `trubrics` Python package:
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```bash
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pip install trubrics
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```
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## Callbacks
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See a [usage example](/docs/integrations/callbacks/trubrics).
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```python
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from langchain.callbacks import TrubricsCallbackHandler
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```
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