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Co-authored-by: Maxime Grenu <69890511+cluster2600@users.noreply.github.com> Co-authored-by: Claude <claude@anthropic.com> Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: jmaillefaud <jonathan.maillefaud@evooq.ch> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: tanwirahmad <tanwirahmad@users.noreply.github.com> Co-authored-by: Christophe Bornet <cbornet@hotmail.com> Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com> Co-authored-by: niceg <79145285+growmuye@users.noreply.github.com> Co-authored-by: Chaitanya varma <varmac301@gmail.com> Co-authored-by: dishaprakash <57954147+dishaprakash@users.noreply.github.com> Co-authored-by: Chester Curme <chester.curme@gmail.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Co-authored-by: Kanav Bansal <13186335+bansalkanav@users.noreply.github.com> Co-authored-by: Aleksandr Filippov <71711753+alex-feel@users.noreply.github.com> Co-authored-by: Alex Feel <afilippov@spotware.com>
44 lines
1.2 KiB
Markdown
44 lines
1.2 KiB
Markdown
# langchain-anthropic
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This package contains the LangChain integration for Anthropic's generative models.
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## Installation
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`pip install -U langchain-anthropic`
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## Chat Models
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Anthropic recommends using their chat models over text completions.
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You can see their recommended models [in the Anthropic docs](https://docs.anthropic.com/claude/docs/models-overview#model-recommendations).
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To use, you should have an Anthropic API key configured. Initialize the model as:
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```python
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from langchain_anthropic import ChatAnthropic
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from langchain_core.messages import AIMessage, HumanMessage
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model = ChatAnthropic(model="claude-3-opus-20240229", temperature=0, max_tokens=1024)
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```
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### Define the input message
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`message = HumanMessage(content="What is the capital of France?")`
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### Generate a response using the model
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`response = model.invoke([message])`
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For a more detailed walkthrough see [here](https://python.langchain.com/docs/integrations/chat/anthropic).
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## LLMs (Legacy)
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You can use the Claude 2 models for text completions.
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```python
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from langchain_anthropic import AnthropicLLM
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model = AnthropicLLM(model="claude-2.1", temperature=0, max_tokens=1024)
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response = model.invoke("The best restaurant in San Francisco is: ")
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```
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