objc[49534]: Class GGMLMetalClass is implemented in both /Users/rlm/miniforge3/envs/llama2/lib/python3.9/site-packages/gpt4all/llmodel_DO_NOT_MODIFY/build/libreplit-mainline-metal.dylib (0x131614208) and /Users/rlm/miniforge3/envs/llama2/lib/python3.9/site-packages/gpt4all/llmodel_DO_NOT_MODIFY/build/libllamamodel-mainline-metal.dylib (0x131988208). One of the two will be used. Which one is undefined.Test similarity search is working with our local embeddings.question = "What are the approaches to Task Decomposition?"docs = vectorstore.similarity_search(question)len(docs)    4docs[0]    Document(page_content='Task decomposition can be done (1) by LLM with simple prompting like "Steps for XYZ.\\n1.", "What are the subgoals for achieving XYZ?", (2) by using task-specific instructions; e.g. "Write a story outline." for writing a novel, or (3) with human inputs.', metadata={'description': 'Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver.\nAgent System Overview In a LLM-powered autonomous agent system, LLM functions as the agent‚Äôs brain, complemented by several key components:', 'language': 'en', 'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'title': "LLM Powered Autonomous Agents | Lil'Log"})Model‚ÄãLLaMA2‚ÄãNote: new versions of llama-cpp-python use GGUF model files (see here).If you have an existing GGML model, see here for instructions for conversion for GGUF. And / or, you can download a GGUF converted model (e.g., here).Finally, as noted in detail here install llama-cpp-pythonpip install llama-cpp-pythonTo enable use of GPU on Apple Silicon, follow the steps here to use the Python binding with Metal support.In particular, ensure that conda is
The popularity of projects like PrivateGPT, llama.cpp, and GPT4All underscore the importance of running LLMs locally.
The popularity of projects like PrivateGPT, llama.cpp, and GPT4All underscore the importance of running LLMs locally. ->: objc[49534]: Class GGMLMetalClass is implemented in both /Users/rlm/miniforge3/envs/llama2/lib/python3.9/site-packages/gpt4all/llmodel_DO_NOT_MODIFY/build/libreplit-mainline-metal.dylib (0x131614208) and /Users/rlm/miniforge3/envs/llama2/lib/python3.9/site-packages/gpt4all/llmodel_DO_NOT_MODIFY/build/libllamamodel-mainline-metal.dylib (0x131988208). One of the two will be used. Which one is undefined.Test similarity search is working with our local embeddings.question = "What are the approaches to Task Decomposition?"docs = vectorstore.similarity_search(question)len(docs)    4docs[0]    Document(page_content='Task decomposition can be done (1) by LLM with simple prompting like "Steps for XYZ.\\n1.", "What are the subgoals for achieving XYZ?", (2) by using task-specific instructions; e.g. "Write a story outline." for writing a novel, or (3) with human inputs.', metadata={'description': 'Building agents with LLM (large language model) as its core controller is a cool concept. Several proof-of-concepts demos, such as AutoGPT, GPT-Engineer and BabyAGI, serve as inspiring examples. The potentiality of LLM extends beyond generating well-written copies, stories, essays and programs; it can be framed as a powerful general problem solver.\nAgent System Overview In a LLM-powered autonomous agent system, LLM functions as the agent‚Äôs brain, complemented by several key components:', 'language': 'en', 'source': 'https://lilianweng.github.io/posts/2023-06-23-agent/', 'title': "LLM Powered Autonomous Agents | Lil'Log"})Model‚ÄãLLaMA2‚ÄãNote: new versions of llama-cpp-python use GGUF model files (see here).If you have an existing GGML model, see here for instructions for conversion for GGUF. And / or, you can download a GGUF converted model (e.g., here).Finally, as noted in detail here install llama-cpp-pythonpip install llama-cpp-pythonTo enable use of GPU on Apple Silicon, follow the steps here to use the Python binding with Metal support.In particular, ensure that conda is