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- Fixed a broken link in the `integrations/providers/infino.mdx` - Fixed a title in the `integration/collbacks/infino.ipynb` example - Updated text format in this example.
36 lines
1.2 KiB
Plaintext
36 lines
1.2 KiB
Plaintext
# Infino
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>[Infino](https://github.com/infinohq/infino) is an open-source observability platform that stores both metrics and application logs together.
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Key features of `Infino` include:
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- **Metrics Tracking**: Capture time taken by LLM model to handle request, errors, number of tokens, and costing indication for the particular LLM.
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- **Data Tracking**: Log and store prompt, request, and response data for each LangChain interaction.
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- **Graph Visualization**: Generate basic graphs over time, depicting metrics such as request duration, error occurrences, token count, and cost.
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## Installation and Setup
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First, you'll need to install the `infinopy` Python package as follows:
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```bash
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pip install infinopy
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```
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If you already have an `Infino Server` running, then you're good to go; but if
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you don't, follow the next steps to start it:
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- Make sure you have Docker installed
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- Run the following in your terminal:
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```
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docker run --rm --detach --name infino-example -p 3000:3000 infinohq/infino:latest
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```
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## Using Infino
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See a [usage example of `InfinoCallbackHandler`](/docs/integrations/callbacks/infino.html).
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```python
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from langchain.callbacks import InfinoCallbackHandler
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```
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