{ "cells": [ { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "\u001b[1m> Entering new LLMBashChain chain...\u001b[0m\n", "找出当前目录下，文件名中包含serp的文件\u001b[32;1m\u001b[1;3m\n", "\n", "```bash\n", "ls\n", "grep -r \"serp\" *\n", "```\u001b[0m\n", "Code: \u001b[33;1m\u001b[1;3m['ls', 'grep -r \"serp\" *']\u001b[0m\n", "Answer: \u001b[33;1m\u001b[1;3mREADME.md\n", "\u001b[34m__pycache__\u001b[m\u001b[m\n", "anthropic_simple.ipynb\n", "app.py\n", "chain_api.ipynb\n", "chain_bash.ipynb\n", "chain_checker.ipynb\n", "chain_constitutional.ipynb\n", "chain_constitutional_prompts_cn.py\n", "chain_input_tool_schema.ipynb\n", "chain_load_json.ipynb\n", "chain_math.ipynb\n", "chain_moderation.ipynb\n", "chain_pal.ipynb\n", "chain_request_html.ipynb\n", "chain_save_json.ipynb\n", "chain_summarize_map_reduce.ipynb\n", "chain_transform.ipynb\n", "data_map_0.txt\n", "faiss.index\n", "\u001b[34mflagged\u001b[m\u001b[m\n", "index_bilibili.ipynb\n", "index_csv_loader.ipynb\n", "index_huggingface_datasets.ipynb\n", "index_image_caption.ipynb\n", "index_start.ipynb\n", "index_url_loader.ipynb\n", "index_web_base.ipynb\n", "index_youtube.ipynb\n", "\u001b[34mindexes\u001b[m\u001b[m\n", "llms_asyncio.py\n", "llms_cache.py\n", "llms_cache_gpt.py\n", "llms_cache_gpt_similarity.py\n", "llms_cache_option.ipynb\n", "llms_cache_option.py\n", "llms_cache_option_chain.ipynb\n", "llms_fake.py\n", "llms_openai.py\n", "llms_prompt_layer.ipynb\n", "llms_semantic_similarity.ipynb\n", "llms_sequential_chain.ipynb\n", "llms_serialization.ipynb\n", "llms_streaming.ipynb\n", "memory_kg.ipynb\n", "memory_predict_with_history.ipynb\n", "memory_start.ipynb\n", "memory_summary_buffer.ipynb\n", "openai_agent.py\n", "openai_chat\n", "openai_chat_agent.py\n", "openai_chat_prompt_template.py\n", "openai_conversation_chain.py\n", "openai_prompt_template.py\n", "openai_simple.py\n", "openai_track_usage.ipynb\n", "parser_fix_output.ipynb\n", "parser_list_output.ipynb\n", "parser_pydantic_output.ipynb\n", "parser_reponse_schema.ipynb\n", "prompt_custom_example_selector.ipynb\n", "prompt_load.ipynb\n", "prompt_partial_template.ipynb.ipynb\n", "\u001b[34mprompts\u001b[m\u001b[m\n", "prompts_relevance_example_selector.ipynb\n", "requirements.txt\n", "retriever_chatgpt.ipynb\n", "socket_client.py\n", "socket_server.py\n", "sqlite.db\n", "test.py\n", "\u001b[34mtxt\u001b[m\u001b[m\n", "llms_serialization.ipynb: \"tools = load_tools([\\\"serpapi\\\", \\\"llm-math\\\"], llm=llm)\\n\",\n", "openai_agent.py:tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm)\n", "openai_chat_agent.py:tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm)\n", "\u001b[0m\n", "\u001b[1m> Finished chain.\u001b[0m\n" ] }, { "data": { "text/plain": [ "'README.md\\n\\x1b[34m__pycache__\\x1b[m\\x1b[m\\nanthropic_simple.ipynb\\napp.py\\nchain_api.ipynb\\nchain_bash.ipynb\\nchain_checker.ipynb\\nchain_constitutional.ipynb\\nchain_constitutional_prompts_cn.py\\nchain_input_tool_schema.ipynb\\nchain_load_json.ipynb\\nchain_math.ipynb\\nchain_moderation.ipynb\\nchain_pal.ipynb\\nchain_request_html.ipynb\\nchain_save_json.ipynb\\nchain_summarize_map_reduce.ipynb\\nchain_transform.ipynb\\ndata_map_0.txt\\nfaiss.index\\n\\x1b[34mflagged\\x1b[m\\x1b[m\\nindex_bilibili.ipynb\\nindex_csv_loader.ipynb\\nindex_huggingface_datasets.ipynb\\nindex_image_caption.ipynb\\nindex_start.ipynb\\nindex_url_loader.ipynb\\nindex_web_base.ipynb\\nindex_youtube.ipynb\\n\\x1b[34mindexes\\x1b[m\\x1b[m\\nllms_asyncio.py\\nllms_cache.py\\nllms_cache_gpt.py\\nllms_cache_gpt_similarity.py\\nllms_cache_option.ipynb\\nllms_cache_option.py\\nllms_cache_option_chain.ipynb\\nllms_fake.py\\nllms_openai.py\\nllms_prompt_layer.ipynb\\nllms_semantic_similarity.ipynb\\nllms_sequential_chain.ipynb\\nllms_serialization.ipynb\\nllms_streaming.ipynb\\nmemory_kg.ipynb\\nmemory_predict_with_history.ipynb\\nmemory_start.ipynb\\nmemory_summary_buffer.ipynb\\nopenai_agent.py\\nopenai_chat\\nopenai_chat_agent.py\\nopenai_chat_prompt_template.py\\nopenai_conversation_chain.py\\nopenai_prompt_template.py\\nopenai_simple.py\\nopenai_track_usage.ipynb\\nparser_fix_output.ipynb\\nparser_list_output.ipynb\\nparser_pydantic_output.ipynb\\nparser_reponse_schema.ipynb\\nprompt_custom_example_selector.ipynb\\nprompt_load.ipynb\\nprompt_partial_template.ipynb.ipynb\\n\\x1b[34mprompts\\x1b[m\\x1b[m\\nprompts_relevance_example_selector.ipynb\\nrequirements.txt\\nretriever_chatgpt.ipynb\\nsocket_client.py\\nsocket_server.py\\nsqlite.db\\ntest.py\\n\\x1b[34mtxt\\x1b[m\\x1b[m\\nllms_serialization.ipynb: \"tools = load_tools([\\\\\"serpapi\\\\\", \\\\\"llm-math\\\\\"], llm=llm)\\\\n\",\\nopenai_agent.py:tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm)\\nopenai_chat_agent.py:tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm)\\n'" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from langchain.chains import LLMBashChain\n", "from langchain.llms import OpenAI\n", "\n", "llm = OpenAI(temperature=0)\n", "\n", "# text = \"查看当前目录下的文件列表，过滤出以chain开头的文件\"\n", "# text = \"重命名，把chain_bash.ipynb重命名为chain_bash_auto.ipynb\"\n", "# text = \"找出当前目录下，文件名中包含html的文件\"\n", "text = \"找出当前目录下，文件名中包含serp的文件\"\n", "\n", "bash_chain = LLMBashChain.from_llm(llm, verbose=True)\n", "\n", "bash_chain.run(text)" ] } ], "metadata": { "kernelspec": { "display_name": "base", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.10" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }