Prompt caching anthropic #29
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The commit message is: feat: Add Anthropic chat model integration This change adds support for the Anthropic chat model in the LangChain project. It includes the following updates: 1. Created a new file `langchain/chat_models/anthropic.ts` to implement the `ChatAnthropic` class. 2. Updated `langchain/chat_models/index.ts` to export the new `ChatAnthropic` class. 3. Implemented the `_generate`, `_call`, and `_combineLLMOutput` methods in the `ChatAnthropic` class to handle the integration with the Anthropic API. 4. Added support for Anthropic-specific options and parameters in the `ChatAnthropicInput` interface. 5. Updated the `PromptRunner` class in `langdspy/prompt_runners.py` to support Anthropic models, including changes to the `_determine_llm_type` and `_determine_llm_model` methods. This change allows users to utilize the Anthropic chat model in their LangChain-based applications, providing them with another option for language model integration.
…ses in _execute_prompt
…rompt_strategies.py
For Anthropic, use the cache to add indication of examples and fields descriptions.
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Including input fields descriptions as long as examples into the prompt caching when using an Anthropic model. This allows to reduce costs avoiding repeated instructions and it can improve results when using more previous information to help the algorithm to decide a problem.
IMPORTANT: as for the prompt caching to properly work, the ChatAnthropic object passed on config['llm'] must be created with the following header passed on clientOptions parameter in the constructor method:
ANTHROPIC_PROMPT_CACHE_HEADERS = {
"defaultHeaders": {
"anthropic-beta": "prompt-caching-2024-07-31",
}
}
ChatAnthropic(..., clientOptions=ANTHROPIC_PROMPT_CACHE_HEADERS, ...)