{
"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
}