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Commit
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dccc64a
1
Parent(s):
fdb9357
add agent tools
Browse files- agent_tools_wolfram.ipynb +65 -0
- chain_bash.ipynb +86 -8
- chain_constitutional.ipynb +18 -1
- chain_pal.ipynb +39 -0
- chain_request_html.ipynb +55 -6
agent_tools_wolfram.ipynb
ADDED
@@ -0,0 +1,65 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper"
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]
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},
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"wolfram = WolframAlphaAPIWrapper()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"\"Wolfram Alpha wasn't able to answer it\""
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# wolfram.run(\"What is 2x+5 = -3x + 7?\")\n",
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"wolfram.run(\"同学们进行广播操比赛,全班正好排成相等的6行。小红排在第二行,从头数,她站在第5个位置,从后数她站在第3个位置,这个班共有( )人\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.10"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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chain_bash.ipynb
CHANGED
@@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count":
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"metadata": {},
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"outputs": [
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{
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@@ -12,23 +12,99 @@
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"\n",
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"\n",
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"\u001b[1m> Entering new LLMBashChain chain...\u001b[0m\n",
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-
"
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"\n",
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"```bash\n",
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-
"
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"```\u001b[0m\n",
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"Code: \u001b[33;1m\u001b[1;3m['
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"Answer: \u001b[33;1m\u001b[1;
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"''"
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]
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},
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"execution_count":
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"metadata": {},
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"output_type": "execute_result"
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}
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@@ -40,7 +116,9 @@
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"llm = OpenAI(temperature=0)\n",
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"\n",
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"# text = \"查看当前目录下的文件列表,过滤出以chain开头的文件\"\n",
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"text = \"重命名,把chain_bash.ipynb重命名为chain_bash_auto.ipynb\"\n",
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"\n",
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"bash_chain = LLMBashChain.from_llm(llm, verbose=True)\n",
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"\n",
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"\n",
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"\n",
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"\u001b[1m> Entering new LLMBashChain chain...\u001b[0m\n",
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"找出当前目录下,文件名中包含serp的文件\u001b[32;1m\u001b[1;3m\n",
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"\n",
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"```bash\n",
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"ls\n",
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"grep -r \"serp\" *\n",
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"```\u001b[0m\n",
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"Code: \u001b[33;1m\u001b[1;3m['ls', 'grep -r \"serp\" *']\u001b[0m\n",
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"Answer: \u001b[33;1m\u001b[1;3mREADME.md\n",
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"\u001b[34m__pycache__\u001b[m\u001b[m\n",
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"anthropic_simple.ipynb\n",
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"app.py\n",
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"chain_api.ipynb\n",
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"chain_bash.ipynb\n",
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"chain_checker.ipynb\n",
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"chain_constitutional.ipynb\n",
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"chain_constitutional_prompts_cn.py\n",
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"chain_input_tool_schema.ipynb\n",
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"chain_load_json.ipynb\n",
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"chain_math.ipynb\n",
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"chain_moderation.ipynb\n",
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"chain_pal.ipynb\n",
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"chain_request_html.ipynb\n",
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"chain_save_json.ipynb\n",
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"chain_summarize_map_reduce.ipynb\n",
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"chain_transform.ipynb\n",
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"data_map_0.txt\n",
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"faiss.index\n",
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"\u001b[34mflagged\u001b[m\u001b[m\n",
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"index_bilibili.ipynb\n",
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"index_csv_loader.ipynb\n",
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"index_huggingface_datasets.ipynb\n",
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"index_image_caption.ipynb\n",
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"index_start.ipynb\n",
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"index_url_loader.ipynb\n",
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"index_web_base.ipynb\n",
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"index_youtube.ipynb\n",
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"\u001b[34mindexes\u001b[m\u001b[m\n",
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"llms_asyncio.py\n",
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"llms_cache.py\n",
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"llms_cache_gpt.py\n",
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"llms_cache_gpt_similarity.py\n",
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"llms_cache_option.ipynb\n",
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"llms_cache_option.py\n",
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"llms_cache_option_chain.ipynb\n",
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"llms_fake.py\n",
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"llms_openai.py\n",
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"llms_prompt_layer.ipynb\n",
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"llms_semantic_similarity.ipynb\n",
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"llms_sequential_chain.ipynb\n",
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"llms_serialization.ipynb\n",
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"llms_streaming.ipynb\n",
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"memory_kg.ipynb\n",
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"memory_predict_with_history.ipynb\n",
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"memory_start.ipynb\n",
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"memory_summary_buffer.ipynb\n",
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"openai_agent.py\n",
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"openai_chat\n",
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"openai_chat_agent.py\n",
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"openai_chat_prompt_template.py\n",
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"openai_conversation_chain.py\n",
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"openai_prompt_template.py\n",
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"openai_simple.py\n",
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"openai_track_usage.ipynb\n",
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"parser_fix_output.ipynb\n",
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"parser_list_output.ipynb\n",
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"parser_pydantic_output.ipynb\n",
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"parser_reponse_schema.ipynb\n",
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"prompt_custom_example_selector.ipynb\n",
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"prompt_load.ipynb\n",
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"prompt_partial_template.ipynb.ipynb\n",
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"\u001b[34mprompts\u001b[m\u001b[m\n",
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"prompts_relevance_example_selector.ipynb\n",
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"requirements.txt\n",
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"retriever_chatgpt.ipynb\n",
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"socket_client.py\n",
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"socket_server.py\n",
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"sqlite.db\n",
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"test.py\n",
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"\u001b[34mtxt\u001b[m\u001b[m\n",
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"llms_serialization.ipynb: \"tools = load_tools([\\\"serpapi\\\", \\\"llm-math\\\"], llm=llm)\\n\",\n",
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"openai_agent.py:tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm)\n",
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"openai_chat_agent.py:tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm)\n",
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"\u001b[0m\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'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'"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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"llm = OpenAI(temperature=0)\n",
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"\n",
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"# text = \"查看当前目录下的文件列表,过滤出以chain开头的文件\"\n",
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"# text = \"重命名,把chain_bash.ipynb重命名为chain_bash_auto.ipynb\"\n",
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"# text = \"找出当前目录下,文件名中包含html的文件\"\n",
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"text = \"找出当前目录下,文件名中包含serp的文件\"\n",
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"\n",
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"bash_chain = LLMBashChain.from_llm(llm, verbose=True)\n",
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"\n",
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chain_constitutional.ipynb
CHANGED
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"\n",
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"\u001b[0m\u001b[33;1m\u001b[1;3mUpdated response: 自杀是一种不可接受的行为,应该尽量避免。如果有学生出现自杀的想法,应该尽快寻求专业的心理咨询帮助,并及时向学校或家长汇报,以确保学生的安全。自杀是一种违反道德和法律的行为,应该被严厉打击。\n",
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"\n",
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"\u001b[0m"
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]
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}
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],
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"source": [
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"\n",
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"\u001b[0m\u001b[33;1m\u001b[1;3mUpdated response: 自杀是一种不可接受的行为,应该尽量避免。如果有学生出现自杀的想法,应该尽快寻求专业的心理咨询帮助,并及时向学校或家长汇报,以确保学生的安全。自杀是一种违反道德和法律的行为,应该被严厉打击。\n",
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"\n",
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"\u001b[0m\u001b[32;1m\u001b[1;3mApplying 爸爸妈妈原则...\n",
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"\n",
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"\u001b[0m\u001b[36;1m\u001b[1;3mCritique: 模型的回答可能会被解释为父母的口吻,而不是一位老师的口吻。模型应该更加客观,更加专业,并且更加关注学生的安全和健康,而不是强调自杀是一种不可接受的行为。\n",
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"\n",
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"\u001b[0m\u001b[33;1m\u001b[1;3mUpdated response: 如果有学生出现自杀的想法,作为老师,我们应该尽快寻求专业的心理咨询帮助,并及时向学校或家长汇报,以确保学生的安全。我们应该以耐心、和蔼可亲的方式与学生沟通,尊重他们的想法,并帮助他们找到更好的解决方案。\n",
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"\n",
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"\u001b[0m\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'如果有学生出现自杀的想法,作为老师,我们应该尽快寻求专业的心理咨询帮助,并及时向学校或家长汇报,以确保学生的安全。我们应该以耐心、和蔼可亲的方式与学生沟通,尊重他们的想法,并帮助他们找到更好的解决方案。'"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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chain_pal.ipynb
CHANGED
@@ -68,6 +68,45 @@
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68 |
"# question = \"同学们进行广播操比赛,全班正好排成相等的6行。小红排在第二行,从头数,她站在第5个位置,从后数她站在第3个位置,这个班共有( )人\"\n",
|
69 |
"pal_chain.run(question)"
|
70 |
]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
71 |
}
|
72 |
],
|
73 |
"metadata": {
|
|
|
68 |
"# question = \"同学们进行广播操比赛,全班正好排成相等的6行。小红排在第二行,从头数,她站在第5个位置,从后数她站在第3个位置,这个班共有( )人\"\n",
|
69 |
"pal_chain.run(question)"
|
70 |
]
|
71 |
+
},
|
72 |
+
{
|
73 |
+
"cell_type": "code",
|
74 |
+
"execution_count": 1,
|
75 |
+
"metadata": {},
|
76 |
+
"outputs": [],
|
77 |
+
"source": [
|
78 |
+
"from langchain.agents import Tool\n",
|
79 |
+
"from langchain.utilities import PythonREPL"
|
80 |
+
]
|
81 |
+
},
|
82 |
+
{
|
83 |
+
"cell_type": "code",
|
84 |
+
"execution_count": 2,
|
85 |
+
"metadata": {},
|
86 |
+
"outputs": [],
|
87 |
+
"source": [
|
88 |
+
"python_repl = PythonREPL()"
|
89 |
+
]
|
90 |
+
},
|
91 |
+
{
|
92 |
+
"cell_type": "code",
|
93 |
+
"execution_count": 10,
|
94 |
+
"metadata": {},
|
95 |
+
"outputs": [
|
96 |
+
{
|
97 |
+
"data": {
|
98 |
+
"text/plain": [
|
99 |
+
"'2\\n'"
|
100 |
+
]
|
101 |
+
},
|
102 |
+
"execution_count": 10,
|
103 |
+
"metadata": {},
|
104 |
+
"output_type": "execute_result"
|
105 |
+
}
|
106 |
+
],
|
107 |
+
"source": [
|
108 |
+
"python_repl.run(\"print(1+1)\")"
|
109 |
+
]
|
110 |
}
|
111 |
],
|
112 |
"metadata": {
|
chain_request_html.ipynb
CHANGED
@@ -2,7 +2,7 @@
|
|
2 |
"cells": [
|
3 |
{
|
4 |
"cell_type": "code",
|
5 |
-
"execution_count":
|
6 |
"metadata": {},
|
7 |
"outputs": [],
|
8 |
"source": [
|
@@ -12,7 +12,7 @@
|
|
12 |
},
|
13 |
{
|
14 |
"cell_type": "code",
|
15 |
-
"execution_count":
|
16 |
"metadata": {},
|
17 |
"outputs": [],
|
18 |
"source": [
|
@@ -33,7 +33,7 @@
|
|
33 |
},
|
34 |
{
|
35 |
"cell_type": "code",
|
36 |
-
"execution_count":
|
37 |
"metadata": {},
|
38 |
"outputs": [],
|
39 |
"source": [
|
@@ -42,7 +42,7 @@
|
|
42 |
},
|
43 |
{
|
44 |
"cell_type": "code",
|
45 |
-
"execution_count":
|
46 |
"metadata": {},
|
47 |
"outputs": [],
|
48 |
"source": [
|
@@ -55,7 +55,7 @@
|
|
55 |
},
|
56 |
{
|
57 |
"cell_type": "code",
|
58 |
-
"execution_count":
|
59 |
"metadata": {},
|
60 |
"outputs": [
|
61 |
{
|
@@ -63,7 +63,29 @@
|
|
63 |
"text/plain": [
|
64 |
"{'query': '今天是日期是?',\n",
|
65 |
" 'url': 'https://www.google.com/search?q=今天是日期是?',\n",
|
66 |
-
" 'output': '2023年5月
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
67 |
]
|
68 |
},
|
69 |
"execution_count": 9,
|
@@ -72,8 +94,35 @@
|
|
72 |
}
|
73 |
],
|
74 |
"source": [
|
|
|
|
|
|
|
|
|
|
|
75 |
"chain(inputs)"
|
76 |
]
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
77 |
}
|
78 |
],
|
79 |
"metadata": {
|
|
|
2 |
"cells": [
|
3 |
{
|
4 |
"cell_type": "code",
|
5 |
+
"execution_count": 2,
|
6 |
"metadata": {},
|
7 |
"outputs": [],
|
8 |
"source": [
|
|
|
12 |
},
|
13 |
{
|
14 |
"cell_type": "code",
|
15 |
+
"execution_count": 3,
|
16 |
"metadata": {},
|
17 |
"outputs": [],
|
18 |
"source": [
|
|
|
33 |
},
|
34 |
{
|
35 |
"cell_type": "code",
|
36 |
+
"execution_count": 4,
|
37 |
"metadata": {},
|
38 |
"outputs": [],
|
39 |
"source": [
|
|
|
42 |
},
|
43 |
{
|
44 |
"cell_type": "code",
|
45 |
+
"execution_count": 5,
|
46 |
"metadata": {},
|
47 |
"outputs": [],
|
48 |
"source": [
|
|
|
55 |
},
|
56 |
{
|
57 |
"cell_type": "code",
|
58 |
+
"execution_count": 6,
|
59 |
"metadata": {},
|
60 |
"outputs": [
|
61 |
{
|
|
|
63 |
"text/plain": [
|
64 |
"{'query': '今天是日期是?',\n",
|
65 |
" 'url': 'https://www.google.com/search?q=今天是日期是?',\n",
|
66 |
+
" 'output': '2023年5月6日星期六'}"
|
67 |
+
]
|
68 |
+
},
|
69 |
+
"execution_count": 6,
|
70 |
+
"metadata": {},
|
71 |
+
"output_type": "execute_result"
|
72 |
+
}
|
73 |
+
],
|
74 |
+
"source": [
|
75 |
+
"chain(inputs)"
|
76 |
+
]
|
77 |
+
},
|
78 |
+
{
|
79 |
+
"cell_type": "code",
|
80 |
+
"execution_count": 9,
|
81 |
+
"metadata": {},
|
82 |
+
"outputs": [
|
83 |
+
{
|
84 |
+
"data": {
|
85 |
+
"text/plain": [
|
86 |
+
"{'query': '执行decode后,找出所有中文',\n",
|
87 |
+
" 'url': 'https://i.zuoyebang.cc/odsv2/#/admin/weekly-stats',\n",
|
88 |
+
" 'output': ' not found'}"
|
89 |
]
|
90 |
},
|
91 |
"execution_count": 9,
|
|
|
94 |
}
|
95 |
],
|
96 |
"source": [
|
97 |
+
"question = \"执行decode后,找出所有中文\"\n",
|
98 |
+
"inputs = {\n",
|
99 |
+
" \"query\": question,\n",
|
100 |
+
" \"url\": \"https://i.zuoyebang.cc/odsv2/#/admin/weekly-stats\"\n",
|
101 |
+
"}\n",
|
102 |
"chain(inputs)"
|
103 |
]
|
104 |
+
},
|
105 |
+
{
|
106 |
+
"cell_type": "code",
|
107 |
+
"execution_count": 7,
|
108 |
+
"metadata": {},
|
109 |
+
"outputs": [
|
110 |
+
{
|
111 |
+
"data": {
|
112 |
+
"text/plain": [
|
113 |
+
"'<!DOCTYPE html><html lang=\"zh\"><head><meta charset=\"UTF-8\"><meta name=\"viewport\" content=\"width=device-width,initial-scale=1\"><meta name=\"theme-color\" content=\"#028bff\" media=\"(prefers-color-scheme: light)\"><link rel=\"icon\" href=\"//www.zuoyebang.cc/favicon.ico\"><title>ç\\x9b®æ\\xa0\\x87管ç\\x90\\x86å¹³å\\x8f°</title><script src=\"./static/file/js-cookie.js\"></script><script>// (function() {\\n // var Cookies = window.Cookies;\\n // if (Cookies) {\\n // if (Cookies.get(\\'odsv2\\') === \\'0\\' && window.location.href.indexOf(\\'/odsv2\\') > -1) {\\n // // 主å\\x8a¨é\\x80\\x89æ\\x8b©ä½¿ç\\x94¨æ\\x97§ç\\x89\\x88\\n // window.location.href = \\'/\\';\\n // }\\n // }\\n // })();</script><script>// æ\\x80§è\\x83½ç\\x9b\\x91æ\\x8e§\\n (function() {\\n let apmAppId = 10000125;\\n if (window.location.host.indexOf(\\'zuoyebang.cc\\') > -1) {\\n // 线ä¸\\x8a\\n apmAppId = 10000122;\\n }\\n window.apmAppId = apmAppId;\\n })();</script><script>(function(win, export_obj) {\\n win[\\'TeaAnalyticsObject\\'] = export_obj;\\n if (!win[export_obj]) {\\n function _collect() {\\n _collect.q.push(arguments);\\n }\\n _collect.q = _collect.q || [];\\n win[export_obj] = _collect;\\n }\\n win[export_obj].l = +new Date();\\n })(window, \\'collectEvent\\');</script><script async src=\"https://sf1-scmcdn-tos.pstatp.com/goofy/log-sdk/collect/collect-autotrack-rangers-v4.1.49.js\"></script><script>if (!window.globalThis) {\\n // å\\x85¼å®¹ä½\\x8eç\\x89\\x88æ\\x9c¬æµ\\x8fè§\\x88å\\x99¨ä¸\\x8dæ\\x94¯æ\\x8c\\x81globalThisç\\x9a\\x84æ\\x83\\x85å\\x86µ\\n window.globalThis = window;\\n }</script><script>(function() {\\n // dataFinder\\n window.collectEvent(\\'init\\', {\\n app_id: window.apmAppId,\\n channel_domain: \\'https://apm.zuoyebang.com\\', // æ\\x9b¿æ\\x8d¢ä¸ºç§\\x81æ\\x9c\\x89é\\x83¨ç½²é\\x83¨ç½²æ\\x9c\\x8då\\x8a¡å\\x9c°å\\x9d\\x80,\\n disable_sdk_monitor: true, //ç\\x94¨äº\\x8eç¦\\x81æ\\xad¢SDKå\\x90¯å\\x8a¨å\\x90\\x8eè\\x87ªèº«ç\\x9b\\x91æ\\x8e§äº\\x8b件 onload ç\\x9a\\x84ä¸\\x8aæ\\x8a¥\\n log: false,\\n });\\n window.collectEvent(\\'start\\');\\n\\n // apmInsight\\n // window.RangersSiteSDK(\"config\", {\\n // app_id: window.apmAppId,// è¿\\x99é\\x87\\x8cå\\x86\\x99å\\x85¥å\\x9c¨å¹³å\\x8f°ä¸\\x8a注å\\x86\\x8cç\\x9a\\x84aid\\n // pid: window.location.href,\\n // // user_unique_id: \\'\\',\\n // serverDomain: \\'https://apm.zuoyebang.com\\', // è¿\\x99é\\x87\\x8cæ\\x8c\\x87å®\\x9aä¸\\x8aæ\\x8a¥å\\x9f\\x9få\\x90\\x8dï¼\\x8cå\\x90¦å\\x88\\x99apmInsightç\\x9c\\x8bä¸\\x8då\\x88°æ\\x95°æ\\x8d®\\n // context: {\\n // },\\n // });\\n\\n })();\\n // 1546</script><link href=\"/odsv2/static/okr/css/chunk-zybpcUI.87bd49cd.css\" rel=\"stylesheet\"><link href=\"/odsv2/static/okr/css/chunk-libs.cf218c77.css\" rel=\"stylesheet\"><link href=\"/odsv2/static/okr/css/okr-app.e9bf765d.css\" rel=\"stylesheet\"></head><body><div id=\"app\"></div><script src=\"/odsv2/static/okr/js/chunk-zybpcUI.104a0d08.js\"></script><script src=\"/odsv2/static/okr/js/chunk-libs.455ada3e.js\"></script><script src=\"/odsv2/static/okr/js/okr-app.5924badf.js\"></script></body><script>window._codeVersion=\\'1546\\';</script></html>'"
|
114 |
+
]
|
115 |
+
},
|
116 |
+
"execution_count": 7,
|
117 |
+
"metadata": {},
|
118 |
+
"output_type": "execute_result"
|
119 |
+
}
|
120 |
+
],
|
121 |
+
"source": [
|
122 |
+
"from langchain.utilities import TextRequestsWrapper\n",
|
123 |
+
"requests = TextRequestsWrapper()\n",
|
124 |
+
"requests.get(\"https://i.zuoyebang.cc/odsv2/#/admin/weekly-stats\")"
|
125 |
+
]
|
126 |
}
|
127 |
],
|
128 |
"metadata": {
|