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…tch]: import models from community ran ```bash git grep -l 'from langchain\.chat_models' | xargs -L 1 sed -i '' "s/from\ langchain\.chat_models/from\ langchain_community.chat_models/g" git grep -l 'from langchain\.llms' | xargs -L 1 sed -i '' "s/from\ langchain\.llms/from\ langchain_community.llms/g" git grep -l 'from langchain\.embeddings' | xargs -L 1 sed -i '' "s/from\ langchain\.embeddings/from\ langchain_community.embeddings/g" git checkout master libs/langchain/tests/unit_tests/llms git checkout master libs/langchain/tests/unit_tests/chat_models git checkout master libs/langchain/tests/unit_tests/embeddings/test_imports.py make format cd libs/langchain; make format cd ../experimental; make format cd ../core; make format ```
50 lines
1.2 KiB
Plaintext
50 lines
1.2 KiB
Plaintext
# PromptLayer
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>[PromptLayer](https://docs.promptlayer.com/introduction) is a platform for prompt engineering.
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> It also helps with the LLM observability to visualize requests, version prompts, and track usage.
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>
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>While `PromptLayer` does have LLMs that integrate directly with LangChain (e.g.
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> [`PromptLayerOpenAI`](https://docs.promptlayer.com/languages/langchain)),
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> using a callback is the recommended way to integrate `PromptLayer` with LangChain.
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## Installation and Setup
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To work with `PromptLayer`, we have to:
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- Create a `PromptLayer` account
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- Create an api token and set it as an environment variable (`PROMPTLAYER_API_KEY`)
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Install a Python package:
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```bash
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pip install promptlayer
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```
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## Callback
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See a [usage example](/docs/integrations/callbacks/promptlayer).
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```python
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import promptlayer # Don't forget this import!
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from langchain.callbacks import PromptLayerCallbackHandler
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```
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## LLM
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See a [usage example](/docs/integrations/llms/promptlayer_openai).
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```python
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from langchain_community.llms import PromptLayerOpenAI
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```
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## Chat Models
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See a [usage example](/docs/integrations/chat/promptlayer_chatopenai).
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```python
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from langchain_community.chat_models import PromptLayerChatOpenAI
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```
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