diff --git a/00_core.ipynb b/00_core.ipynb index c99095e..0e8b70e 100644 --- a/00_core.ipynb +++ b/00_core.ipynb @@ -73,6 +73,7 @@ "from anthropic.types.beta.tools import ToolsBetaMessage, tool_use_block\n", "\n", "from fastcore.docments import docments\n", + "from fastcore import imghdr\n", "from fastcore.utils import *" ] }, @@ -196,7 +197,7 @@ { "data": { "text/plain": [ - "Message(id='msg_01HDG6FBAy3XQ7StdycrRaBw', content=[TextBlock(text=\"It's nice to meet you, Jeremy! I'm an artificial intelligence assistant created by Anthropic. Let me know if you have any questions or if there's anything I can help you with.\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=Usage(input_tokens=10, output_tokens=43))" + "Message(id='msg_01Rtnqw9HCHRZx3DNQ3doFNF', content=[TextBlock(text=\"It's nice to meet you, Jeremy! How can I assist you today?\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=Usage(input_tokens=10, output_tokens=19))" ] }, "execution_count": null, @@ -278,7 +279,7 @@ { "data": { "text/plain": [ - "TextBlock(text=\"It's nice to meet you, Jeremy! I'm an artificial intelligence assistant created by Anthropic. Let me know if you have any questions or if there's anything I can help you with.\", type='text')" + "TextBlock(text=\"It's nice to meet you, Jeremy! How can I assist you today?\", type='text')" ] }, "execution_count": null, @@ -322,7 +323,7 @@ { "data": { "text/plain": [ - "\"It's nice to meet you, Jeremy! I'm an artificial intelligence assistant created by Anthropic. Let me know if you have any questions or if there's anything I can help you with.\"" + "\"It's nice to meet you, Jeremy! How can I assist you today?\"" ] }, "execution_count": null, @@ -371,23 +372,23 @@ { "data": { "text/markdown": [ - "It's nice to meet you, Jeremy! I'm an artificial intelligence assistant created by Anthropic. Let me know if you have any questions or if there's anything I can help you with.\n", + "It's nice to meet you, Jeremy! How can I assist you today?\n", "\n", "
\n", "\n", - "- id: msg_01HDG6FBAy3XQ7StdycrRaBw\n", - "- content: [{'text': \"It's nice to meet you, Jeremy! I'm an artificial intelligence assistant created by Anthropic. Let me know if you have any questions or if there's anything I can help you with.\", 'type': 'text'}]\n", + "- id: msg_01Rtnqw9HCHRZx3DNQ3doFNF\n", + "- content: [{'text': \"It's nice to meet you, Jeremy! How can I assist you today?\", 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 10, 'output_tokens': 43}\n", + "- usage: {'input_tokens': 10, 'output_tokens': 19}\n", "\n", "
" ], "text/plain": [ - "Message(id='msg_01HDG6FBAy3XQ7StdycrRaBw', content=[TextBlock(text=\"It's nice to meet you, Jeremy! I'm an artificial intelligence assistant created by Anthropic. Let me know if you have any questions or if there's anything I can help you with.\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=Usage(input_tokens=10, output_tokens=43))" + "Message(id='msg_01Rtnqw9HCHRZx3DNQ3doFNF', content=[TextBlock(text=\"It's nice to meet you, Jeremy! How can I assist you today?\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=Usage(input_tokens=10, output_tokens=19))" ] }, "execution_count": null, @@ -418,7 +419,7 @@ { "data": { "text/plain": [ - "Usage(input_tokens=10, output_tokens=43)" + "Usage(input_tokens=10, output_tokens=19)" ] }, "execution_count": null, @@ -544,7 +545,7 @@ { "data": { "text/plain": [ - "In: 10; Out: 43; Total: 53" + "In: 10; Out: 19; Total: 29" ] }, "execution_count": null, @@ -587,7 +588,7 @@ { "data": { "text/plain": [ - "In: 20; Out: 86; Total: 106" + "In: 20; Out: 38; Total: 58" ] }, "execution_count": null, @@ -678,23 +679,23 @@ { "data": { "text/markdown": [ - "It's nice to meet you, Jeremy! As an AI assistant, I don't have a personal identity, but I'm happy to chat with you and try my best to help out however I can. Please feel free to ask me anything.\n", + "Hello Jeremy! It's nice to meet you. As an AI assistant, I don't have a personal identity, but I'm happy to chat and try my best to help you with any questions or tasks you might have. Please feel free to ask me anything!\n", "\n", "
\n", "\n", - "- id: msg_01JH641RNBQ67FNYwnje5Yxp\n", - "- content: [{'text': \"It's nice to meet you, Jeremy! As an AI assistant, I don't have a personal identity, but I'm happy to chat with you and try my best to help out however I can. Please feel free to ask me anything.\", 'type': 'text'}]\n", + "- id: msg_01We7ynXh2eRA1CK7stVHzh9\n", + "- content: [{'text': \"Hello Jeremy! It's nice to meet you. As an AI assistant, I don't have a personal identity, but I'm happy to chat and try my best to help you with any questions or tasks you might have. Please feel free to ask me anything!\", 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 10, 'output_tokens': 52}\n", + "- usage: {'input_tokens': 10, 'output_tokens': 56}\n", "\n", "
" ], "text/plain": [ - "Message(id='msg_01JH641RNBQ67FNYwnje5Yxp', content=[TextBlock(text=\"It's nice to meet you, Jeremy! As an AI assistant, I don't have a personal identity, but I'm happy to chat with you and try my best to help out however I can. Please feel free to ask me anything.\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 10; Out: 52; Total: 62)" + "Message(id='msg_01We7ynXh2eRA1CK7stVHzh9', content=[TextBlock(text=\"Hello Jeremy! It's nice to meet you. As an AI assistant, I don't have a personal identity, but I'm happy to chat and try my best to help you with any questions or tasks you might have. Please feel free to ask me anything!\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 10; Out: 56; Total: 66)" ] }, "execution_count": null, @@ -756,7 +757,7 @@ "text/plain": [ "[{'role': 'user', 'content': \"I'm Jeremy\"},\n", " {'role': 'assistant',\n", - " 'content': [TextBlock(text=\"It's nice to meet you, Jeremy! As an AI assistant, I don't have a personal identity, but I'm happy to chat with you and try my best to help out however I can. Please feel free to ask me anything.\", type='text')]},\n", + " 'content': [TextBlock(text=\"Hello Jeremy! It's nice to meet you. As an AI assistant, I don't have a personal identity, but I'm happy to chat and try my best to help you with any questions or tasks you might have. Please feel free to ask me anything!\", type='text')]},\n", " {'role': 'user', 'content': 'I forgot my name. Can you remind me please?'}]" ] }, @@ -787,23 +788,23 @@ { "data": { "text/markdown": [ - "I'm afraid I don't actually know your name. As an AI system, I don't have any stored information about your personal identity or name. I was just addressing you as \"Jeremy\" based on what you told me at the start of our conversation. If you've forgotten your own name, I don't have a way to remind you of it. Perhaps you could try retracing your steps or looking at any identification you may have to jog your memory.\n", + "I'm afraid I don't actually know your name. When you introduced yourself at the start of our conversation, you told me your name was Jeremy. But if you've now forgotten your own name, I don't have any way to remind you of it. As an AI, I don't have independent knowledge about you or your identity - I can only respond based on the information you provide to me directly. If you're unsure of your name, I would suggest trying to recall it or checking any identification you may have.\n", "\n", "
\n", "\n", - "- id: msg_01FKQ45RKFwWJwu5nDXs5SAY\n", - "- content: [{'text': 'I\\'m afraid I don\\'t actually know your name. As an AI system, I don\\'t have any stored information about your personal identity or name. I was just addressing you as \"Jeremy\" based on what you told me at the start of our conversation. If you\\'ve forgotten your own name, I don\\'t have a way to remind you of it. Perhaps you could try retracing your steps or looking at any identification you may have to jog your memory.', 'type': 'text'}]\n", + "- id: msg_01ETWAssmRpokdY9gGPTYhyb\n", + "- content: [{'text': \"I'm afraid I don't actually know your name. When you introduced yourself at the start of our conversation, you told me your name was Jeremy. But if you've now forgotten your own name, I don't have any way to remind you of it. As an AI, I don't have independent knowledge about you or your identity - I can only respond based on the information you provide to me directly. If you're unsure of your name, I would suggest trying to recall it or checking any identification you may have.\", 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 76, 'output_tokens': 98}\n", + "- usage: {'input_tokens': 80, 'output_tokens': 109}\n", "\n", "
" ], "text/plain": [ - "Message(id='msg_01FKQ45RKFwWJwu5nDXs5SAY', content=[TextBlock(text='I\\'m afraid I don\\'t actually know your name. As an AI system, I don\\'t have any stored information about your personal identity or name. I was just addressing you as \"Jeremy\" based on what you told me at the start of our conversation. If you\\'ve forgotten your own name, I don\\'t have a way to remind you of it. Perhaps you could try retracing your steps or looking at any identification you may have to jog your memory.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 76; Out: 98; Total: 174)" + "Message(id='msg_01ETWAssmRpokdY9gGPTYhyb', content=[TextBlock(text=\"I'm afraid I don't actually know your name. When you introduced yourself at the start of our conversation, you told me your name was Jeremy. But if you've now forgotten your own name, I don't have any way to remind you of it. As an AI, I don't have independent knowledge about you or your identity - I can only respond based on the information you provide to me directly. If you're unsure of your name, I would suggest trying to recall it or checking any identification you may have.\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 80; Out: 109; Total: 189)" ] }, "execution_count": null, @@ -903,7 +904,7 @@ { "data": { "text/plain": [ - "In: 10; Out: 52; Total: 62" + "In: 10; Out: 56; Total: 66" ] }, "execution_count": null, @@ -959,7 +960,7 @@ "\n", "
\n", "\n", - "- id: msg_01Vr6t6QdodntSMvHthnRDBc\n", + "- id: msg_012TvKoSWAUjp5XC2jf66gWp\n", "- content: [{'text': 'Hello! How can I assist you today?', 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", @@ -971,7 +972,7 @@ "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01Vr6t6QdodntSMvHthnRDBc', content=[TextBlock(text='Hello! How can I assist you today?', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 8; Out: 12; Total: 20)" + "ToolsBetaMessage(id='msg_012TvKoSWAUjp5XC2jf66gWp', content=[TextBlock(text='Hello! How can I assist you today?', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 8; Out: 12; Total: 20)" ] }, "execution_count": null, @@ -992,7 +993,7 @@ { "data": { "text/plain": [ - "In: 18; Out: 64; Total: 82" + "In: 18; Out: 68; Total: 86" ] }, "execution_count": null, @@ -1062,7 +1063,7 @@ { "data": { "text/plain": [ - "In: 26; Out: 76; Total: 102" + "In: 26; Out: 80; Total: 106" ] }, "execution_count": null, @@ -1417,12 +1418,12 @@ { "data": { "text/markdown": [ - "ToolUseBlock(id='toolu_01CsuZfPAas75MkDABXAvjWD', input={'a': 604542, 'b': 6458932}, name='sums', type='tool_use')\n", + "ToolUseBlock(id='toolu_0118Wud8dz9GFAVT6u2Fcd5a', input={'a': 604542, 'b': 6458932}, name='sums', type='tool_use')\n", "\n", "
\n", "\n", - "- id: msg_01StvQvvrnwaBtuUwHQLrpFt\n", - "- content: [{'id': 'toolu_01CsuZfPAas75MkDABXAvjWD', 'input': {'a': 604542, 'b': 6458932}, 'name': 'sums', 'type': 'tool_use'}]\n", + "- id: msg_01Grrz87HVKW2CPDFkSTyYHn\n", + "- content: [{'id': 'toolu_0118Wud8dz9GFAVT6u2Fcd5a', 'input': {'a': 604542, 'b': 6458932}, 'name': 'sums', 'type': 'tool_use'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: tool_use\n", @@ -1433,7 +1434,7 @@ "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01StvQvvrnwaBtuUwHQLrpFt', content=[ToolUseBlock(id='toolu_01CsuZfPAas75MkDABXAvjWD', input={'a': 604542, 'b': 6458932}, name='sums', type='tool_use')], model='claude-3-haiku-20240307', role='assistant', stop_reason='tool_use', stop_sequence=None, type='message', usage=In: 414; Out: 72; Total: 486)" + "ToolsBetaMessage(id='msg_01Grrz87HVKW2CPDFkSTyYHn', content=[ToolUseBlock(id='toolu_0118Wud8dz9GFAVT6u2Fcd5a', input={'a': 604542, 'b': 6458932}, name='sums', type='tool_use')], model='claude-3-haiku-20240307', role='assistant', stop_reason='tool_use', stop_sequence=None, type='message', usage=In: 414; Out: 72; Total: 486)" ] }, "execution_count": null, @@ -1598,7 +1599,7 @@ "text/plain": [ "{'role': 'user',\n", " 'content': [{'type': 'tool_result',\n", - " 'tool_use_id': 'toolu_01CsuZfPAas75MkDABXAvjWD',\n", + " 'tool_use_id': 'toolu_0118Wud8dz9GFAVT6u2Fcd5a',\n", " 'content': '7063474'}]}" ] }, @@ -1743,7 +1744,6 @@ "@patch\n", "def __call__(self:Chat,\n", " pr, # Prompt / message\n", - " sp='', # The system prompt\n", " temp=0, # Temperature\n", " maxtok=4096, # Maximum tokens\n", " stop:Optional[list[str]]=None, # Stop sequences\n", @@ -1778,7 +1778,7 @@ { "data": { "text/plain": [ - "'Your name is Jeremy, as you mentioned earlier.'" + "'Your name is Jeremy, as you told me earlier.'" ] }, "execution_count": null, @@ -1823,19 +1823,19 @@ "\n", "
\n", "\n", - "- id: msg_01PpZHCVVQk773rRjbBu38U1\n", + "- id: msg_01UNDkcKAwkfAUkZK8jhBrPU\n", "- content: [{'text': 'According to Douglas Adams, the answer is 42.', 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 129, 'output_tokens': 10}\n", + "- usage: {'input_tokens': 127, 'output_tokens': 10}\n", "\n", "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01PpZHCVVQk773rRjbBu38U1', content=[TextBlock(text='According to Douglas Adams, the answer is 42.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 129; Out: 10; Total: 139)" + "ToolsBetaMessage(id='msg_01UNDkcKAwkfAUkZK8jhBrPU', content=[TextBlock(text='According to Douglas Adams, the answer is 42.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 127; Out: 10; Total: 137)" ] }, "execution_count": null, @@ -1883,7 +1883,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "It's nice to meet you, Jeremy! I'm an AI assistant created by Anthropic. I'm here to help with any tasks or questions you may have. Please let me know if there's anything I can assist you with." + "It's nice to meet you, Jeremy! I'm an AI assistant created by Anthropic. I'm here to help with any tasks or questions you may have. Please let me know how I can be of assistance." ] } ], @@ -1957,12 +1957,12 @@ { "data": { "text/markdown": [ - "ToolUseBlock(id='toolu_018m6yuZwQtn7xZozny37CrZ', input={'a': 604542, 'b': 6458932}, name='sums', type='tool_use')\n", + "ToolUseBlock(id='toolu_01FYUbtvQV9UgcEnU7YEc129', input={'a': 604542, 'b': 6458932}, name='sums', type='tool_use')\n", "\n", "
\n", "\n", - "- id: msg_01MSiGKYedwdpr41VciqydB7\n", - "- content: [{'id': 'toolu_018m6yuZwQtn7xZozny37CrZ', 'input': {'a': 604542, 'b': 6458932}, 'name': 'sums', 'type': 'tool_use'}]\n", + "- id: msg_0137GFLnnx3eSeq8gtoRUPrY\n", + "- content: [{'id': 'toolu_01FYUbtvQV9UgcEnU7YEc129', 'input': {'a': 604542, 'b': 6458932}, 'name': 'sums', 'type': 'tool_use'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: tool_use\n", @@ -1973,7 +1973,7 @@ "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01MSiGKYedwdpr41VciqydB7', content=[ToolUseBlock(id='toolu_018m6yuZwQtn7xZozny37CrZ', input={'a': 604542, 'b': 6458932}, name='sums', type='tool_use')], model='claude-3-haiku-20240307', role='assistant', stop_reason='tool_use', stop_sequence=None, type='message', usage=In: 418; Out: 72; Total: 490)" + "ToolsBetaMessage(id='msg_0137GFLnnx3eSeq8gtoRUPrY', content=[ToolUseBlock(id='toolu_01FYUbtvQV9UgcEnU7YEc129', input={'a': 604542, 'b': 6458932}, name='sums', type='tool_use')], model='claude-3-haiku-20240307', role='assistant', stop_reason='tool_use', stop_sequence=None, type='message', usage=In: 418; Out: 72; Total: 490)" ] }, "execution_count": null, @@ -2000,7 +2000,7 @@ "\n", "
\n", "\n", - "- id: msg_016NBFCx5L3HMvY5kwVDdjDE\n", + "- id: msg_01S7FFSVtqiLQL3ANtBSnFyu\n", "- content: [{'text': 'The sum of 604542 and 6458932 is 7063474.', 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", @@ -2012,7 +2012,7 @@ "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_016NBFCx5L3HMvY5kwVDdjDE', content=[TextBlock(text='The sum of 604542 and 6458932 is 7063474.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 505; Out: 23; Total: 528)" + "ToolsBetaMessage(id='msg_01S7FFSVtqiLQL3ANtBSnFyu', content=[TextBlock(text='The sum of 604542 and 6458932 is 7063474.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 505; Out: 23; Total: 528)" ] }, "execution_count": null, @@ -2077,7 +2077,7 @@ "outputs": [ { "data": { - "image/jpeg": 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", "text/plain": [ "" ] @@ -2118,7 +2118,7 @@ "def img_msg(data:bytes)->dict:\n", " \"Convert image `data` into an encoded `dict`\"\n", " img = base64.b64encode(data).decode(\"utf-8\")\n", - " mtype = mimetypes.guess_type(fn)[0]\n", + " mtype = mimetypes.types_map['.'+imghdr.what(None, h=data)]\n", " r = dict(type=\"base64\", media_type=mtype, data=img)\n", " return {\"type\": \"image\", \"source\": r}" ] @@ -2172,23 +2172,23 @@ { "data": { "text/markdown": [ - "The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.\n", + "The image contains purple or lavender-colored flowers, which appear to be daisies or a similar type of flower.\n", "\n", "
\n", "\n", - "- id: msg_01GSzzitXbvkzEJtfJquzSXE\n", - "- content: [{'text': 'The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.', 'type': 'text'}]\n", + "- id: msg_011v95h9PPUvsBGyRe8PTWSr\n", + "- content: [{'text': 'The image contains purple or lavender-colored flowers, which appear to be daisies or a similar type of flower.', 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 1665, 'output_tokens': 29}\n", + "- usage: {'input_tokens': 185, 'output_tokens': 28}\n", "\n", "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01GSzzitXbvkzEJtfJquzSXE', content=[TextBlock(text='The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1665; Out: 29; Total: 1694)" + "ToolsBetaMessage(id='msg_011v95h9PPUvsBGyRe8PTWSr', content=[TextBlock(text='The image contains purple or lavender-colored flowers, which appear to be daisies or a similar type of flower.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 185; Out: 28; Total: 213)" ] }, "execution_count": null, @@ -2280,23 +2280,23 @@ { "data": { "text/markdown": [ - "The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.\n", + "The image contains purple or lavender-colored flowers, which appear to be daisies or a similar type of flower.\n", "\n", "
\n", "\n", - "- id: msg_01ArrMvaZoXa1JTjULMentQJ\n", - "- content: [{'text': 'The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.', 'type': 'text'}]\n", + "- id: msg_01Nkf3BZjcfjbKpyeUFdpxfb\n", + "- content: [{'text': 'The image contains purple or lavender-colored flowers, which appear to be daisies or a similar type of flower.', 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 1665, 'output_tokens': 29}\n", + "- usage: {'input_tokens': 185, 'output_tokens': 28}\n", "\n", "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01ArrMvaZoXa1JTjULMentQJ', content=[TextBlock(text='The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1665; Out: 29; Total: 1694)" + "ToolsBetaMessage(id='msg_01Nkf3BZjcfjbKpyeUFdpxfb', content=[TextBlock(text='The image contains purple or lavender-colored flowers, which appear to be daisies or a similar type of flower.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 185; Out: 28; Total: 213)" ] }, "execution_count": null, @@ -2337,23 +2337,23 @@ { "data": { "text/markdown": [ - "The image shows a cute puppy, likely a Cavalier King Charles Spaniel, sitting in a grassy area surrounded by purple daisy flowers. The puppy has a friendly, curious expression on its face as it gazes directly at the camera. The contrast between the puppy's soft, fluffy fur and the vibrant flowers creates a charming and picturesque scene.\n", + "The image shows a cute puppy lying in the grass, surrounded by purple flowers. The puppy appears to be a Cavalier King Charles Spaniel, with a fluffy brown and white coat. The puppy has a friendly, curious expression as it gazes at the camera. The vibrant purple flowers in the background create a lovely, natural setting for the puppy to be photographed in.\n", "\n", "
\n", "\n", - "- id: msg_01535kuKhiN6Do5PTcTmTst7\n", - "- content: [{'text': \"The image shows a cute puppy, likely a Cavalier King Charles Spaniel, sitting in a grassy area surrounded by purple daisy flowers. The puppy has a friendly, curious expression on its face as it gazes directly at the camera. The contrast between the puppy's soft, fluffy fur and the vibrant flowers creates a charming and picturesque scene.\", 'type': 'text'}]\n", + "- id: msg_01Fk8heUPVHEWzqvdGj3vp57\n", + "- content: [{'text': 'The image shows a cute puppy lying in the grass, surrounded by purple flowers. The puppy appears to be a Cavalier King Charles Spaniel, with a fluffy brown and white coat. The puppy has a friendly, curious expression as it gazes at the camera. The vibrant purple flowers in the background create a lovely, natural setting for the puppy to be photographed in.', 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 1681, 'output_tokens': 83}\n", + "- usage: {'input_tokens': 201, 'output_tokens': 86}\n", "\n", "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01535kuKhiN6Do5PTcTmTst7', content=[TextBlock(text=\"The image shows a cute puppy, likely a Cavalier King Charles Spaniel, sitting in a grassy area surrounded by purple daisy flowers. The puppy has a friendly, curious expression on its face as it gazes directly at the camera. The contrast between the puppy's soft, fluffy fur and the vibrant flowers creates a charming and picturesque scene.\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1681; Out: 83; Total: 1764)" + "ToolsBetaMessage(id='msg_01Fk8heUPVHEWzqvdGj3vp57', content=[TextBlock(text='The image shows a cute puppy lying in the grass, surrounded by purple flowers. The puppy appears to be a Cavalier King Charles Spaniel, with a fluffy brown and white coat. The puppy has a friendly, curious expression as it gazes at the camera. The vibrant purple flowers in the background create a lovely, natural setting for the puppy to be photographed in.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 201; Out: 86; Total: 287)" ] }, "execution_count": null, @@ -2375,23 +2375,23 @@ { "data": { "text/markdown": [ - "The puppy in the image is facing the camera directly, looking straight ahead with a curious expression.\n", + "The puppy in the image is facing towards the left side of the frame.\n", "\n", "
\n", "\n", - "- id: msg_01Ge4M4Z4J6ywg9V8cCXy2aN\n", - "- content: [{'text': 'The puppy in the image is facing the camera directly, looking straight ahead with a curious expression.', 'type': 'text'}]\n", + "- id: msg_01RXvdWTDL8kZWTSpt6HGtaL\n", + "- content: [{'text': 'The puppy in the image is facing towards the left side of the frame.', 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 1775, 'output_tokens': 23}\n", + "- usage: {'input_tokens': 298, 'output_tokens': 19}\n", "\n", "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01Ge4M4Z4J6ywg9V8cCXy2aN', content=[TextBlock(text='The puppy in the image is facing the camera directly, looking straight ahead with a curious expression.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1775; Out: 23; Total: 1798)" + "ToolsBetaMessage(id='msg_01RXvdWTDL8kZWTSpt6HGtaL', content=[TextBlock(text='The puppy in the image is facing towards the left side of the frame.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 298; Out: 19; Total: 317)" ] }, "execution_count": null, @@ -2412,23 +2412,23 @@ { "data": { "text/markdown": [ - "The puppy in the image has a combination of colors - it has a white and brown/tan coat. The head and ears appear to be a reddish-brown color, while the body is mostly white with some tan/brown patches.\n", + "The puppy in the image has a brown and white coat color. It appears to be a Cavalier King Charles Spaniel breed.\n", "\n", "
\n", "\n", - "- id: msg_01JbUH6MvqWMvkF8UJVjo33z\n", - "- content: [{'text': 'The puppy in the image has a combination of colors - it has a white and brown/tan coat. The head and ears appear to be a reddish-brown color, while the body is mostly white with some tan/brown patches.', 'type': 'text'}]\n", + "- id: msg_018taiP7G5DAvkcyGrpjivTY\n", + "- content: [{'text': 'The puppy in the image has a brown and white coat color. It appears to be a Cavalier King Charles Spaniel breed.', 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 1806, 'output_tokens': 53}\n", + "- usage: {'input_tokens': 325, 'output_tokens': 32}\n", "\n", "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01JbUH6MvqWMvkF8UJVjo33z', content=[TextBlock(text='The puppy in the image has a combination of colors - it has a white and brown/tan coat. The head and ears appear to be a reddish-brown color, while the body is mostly white with some tan/brown patches.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1806; Out: 53; Total: 1859)" + "ToolsBetaMessage(id='msg_018taiP7G5DAvkcyGrpjivTY', content=[TextBlock(text='The puppy in the image has a brown and white coat color. It appears to be a Cavalier King Charles Spaniel breed.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 325; Out: 32; Total: 357)" ] }, "execution_count": null, diff --git a/README.md b/README.md index 68a233a..dbad1d2 100644 --- a/README.md +++ b/README.md @@ -6,8 +6,6 @@ *Claudette* is a wrapper for Anthropic’s [Python SDK](https://github.com/anthropics/anthropic-sdk-python). -TODO: This README is incomplete. - ## Install ``` sh @@ -43,6 +41,9 @@ import claudette …and then add the prefix `claudette.` to any usages of the module. +Claudette provides `models`, which is a list of models currently +available from the SDK. + ``` python models ``` @@ -51,147 +52,168 @@ models 'claude-3-sonnet-20240229', 'claude-3-haiku-20240307') -These are the models currently available from the SDK. +For these examples, we’ll use Haiku, since it’s fast and cheap (and +surprisingly good!) ``` python model = models[-1] ``` -For examples, we’ll use Haiku, since it’s fast and cheap (and -surprisingly good!) - ## Chat ------------------------------------------------------------------------- +The main interface to Claudia is the +[`Chat`](https://AnswerDotAI.github.io/claudette/core.html#chat) class, +which provides a stateful interface to Claude: -source +``` python +chat = Chat(model, sp="""You are a helpful, concise, pirate assistant. +Talk like a pirate.""") +chat("I'm Jeremy") +``` -### Chat +Ahoy there, Jeremy! Ye be speakin’ to Cap’n Blackheart, the most +fearsome pirate on the high seas. What can I be doin’ for ye, me hearty? -> Chat (model:Optional[str]=None, cli:Optional[claudette.core.Client]=None, -> sp='', tools:Optional[list]=None) +
-*Anthropic chat client.* +- id: msg_015NDhj1QD3A7YFBSWfm95Wu +- content: \[{‘text’: “Ahoy there, Jeremy! Ye be speakin’ to Cap’n + Blackheart, the most fearsome pirate on the high seas. What can I be + doin’ for ye, me hearty?”, ‘type’: ‘text’}\] +- model: claude-3-haiku-20240307 +- role: assistant +- stop_reason: end_turn +- stop_sequence: None +- type: message +- usage: {‘input_tokens’: 29, ‘output_tokens’: 51} -| | **Type** | **Default** | **Details** | -|-------|----------|-------------|------------------------------------------------| -| model | Optional | None | Model to use (leave empty if passing `cli`) | -| cli | Optional | None | Client to use (leave empty if passing `model`) | -| sp | str | | Optional system prompt | -| tools | Optional | None | List of tools to make available to Claude | +
``` python -chat = Chat(model, sp="You are a helpful assistant.") +r = chat("What's my name?") +r ``` ------------------------------------------------------------------------- - -source +Arr, ye be Jeremy, me scurvy dog! I be rememberin’ that from just a +moment ago. Ye best not be tryin’ to fool old Cap’n Blackheart, or ye’ll +be walkin’ the plank! -### Chat.\_\_call\_\_ +
-> Chat.__call__ (pr, sp='', temp=0, maxtok=4096, -> stop:Optional[list[str]]=None, -> ns:Optional[collections.abc.Mapping]=None, prefill='', -> **kw) +- id: msg_01Kfdw6MjPupY2CiANUx1sRi +- content: \[{‘text’: “Arr, ye be Jeremy, me scurvy dog! I be + rememberin’ that from just a moment ago. Ye best not be tryin’ to fool + old Cap’n Blackheart, or ye’ll be walkin’ the plank!”, ‘type’: + ‘text’}\] +- model: claude-3-haiku-20240307 +- role: assistant +- stop_reason: end_turn +- stop_sequence: None +- type: message +- usage: {‘input_tokens’: 88, ‘output_tokens’: 58} -*Add prompt `pr` to dialog and get a response from Claude* +
-| | **Type** | **Default** | **Details** | -|---------|----------|-------------|-------------------------------------------------------------| -| pr | | | Prompt / message | -| sp | str | | The system prompt | -| temp | int | 0 | Temperature | -| maxtok | int | 4096 | Maximum tokens | -| stop | Optional | None | Stop sequences | -| ns | Optional | None | Namespace to search for tools, defaults to `globals()` | -| prefill | str | | Optional prefill to pass to Claude as start of its response | -| kw | | | | +As you see above, displaying the results of a call in a notebook shows +just the message contents, with the other details hidden behind a +collapsible section. Alternatively you can `print` the details: ``` python -chat("I'm Jeremy") -contents(chat("What's my name?")) +print(r) ``` - 'Your name is Jeremy, as you told me earlier.' + ToolsBetaMessage(id='msg_01Kfdw6MjPupY2CiANUx1sRi', content=[TextBlock(text="Arr, ye be Jeremy, me scurvy dog! I be rememberin' that from just a moment ago. Ye best not be tryin' to fool old Cap'n Blackheart, or ye'll be walkin' the plank!", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 88; Out: 58; Total: 146) Claude supports adding an extra `assistant` message at the end, which contains the *prefill* – i.e. the text we want Claude to assume the -response starts with. - -Let’s try it out: +response starts with. Let’s try it out: ``` python -q = "Concisely, what is the meaning of life?" -pref = 'According to Douglas Adams,' -chat(q, prefill=pref) +chat("What is the meaning of life?", + prefill='According to Douglas Adams,') ``` -According to Douglas Adams, “The answer to the ultimate question of -life, the universe, and everything is 42.” +According to Douglas Adams,the meaning of life is “42”. But this be a +question that has vexed the greatest minds of all time, me bucko. As a +pirate, I be more concerned with the simple pleasures in life - a bottle +of rum, a crew of loyal scallywags, and the open sea. The true meaning +of life be findin’ yer own path and livin’ it to the fullest, savvy? +Now, enough of this philosophical nonsense - let’s go plunder some +treasure!
-- id: msg_011BL35YKAgwg8UR7nKjM1p2 -- content: \[{‘text’: ‘According to Douglas Adams, “The answer to the - ultimate question of life, the universe, and everything is 42.”’, - ‘type’: ‘text’}\] +- id: msg_012JW54NgW2HWcZYzpUfSBTE +- content: \[{‘text’: ‘According to Douglas Adams,the meaning of life is + “42”. But this be a question that has vexed the greatest minds of all + time, me bucko. As a pirate, I be more concerned with the simple + pleasures in life - a bottle of rum, a crew of loyal scallywags, and + the open sea. The true meaning of life be findin' yer own path and + livin' it to the fullest, savvy? Now, enough of this philosophical + nonsense - let's go plunder some treasure!’, ‘type’: ‘text’}\] - model: claude-3-haiku-20240307 - role: assistant - stop_reason: end_turn - stop_sequence: None - type: message -- usage: {‘input_tokens’: 109, ‘output_tokens’: 23} +- usage: {‘input_tokens’: 161, ‘output_tokens’: 111}
------------------------------------------------------------------------- +Instead of calling +[`Chat`](https://AnswerDotAI.github.io/claudette/core.html#chat) +directly, you can use +[`Chat.stream`](https://AnswerDotAI.github.io/claudette/core.html#chat.stream) +to stream the results as soon as they arrive (although you will only see +the gradual generation if you execute the notebook yourself, of course!) -source +``` python +for o in chat.stream("Who or what calculated that?"): print(o, end='') +``` -### Chat.stream + *chuckles heartily* Ye be askin' about the legendary answer of "42", me hearty? Well, that be the work of the great philosopher and author, Douglas Adams, in his masterpiece "The Hitchhiker's Guide to the Galaxy". -> Chat.stream (pr, sp='', temp=0, maxtok=4096, -> stop:Optional[list[str]]=None, prefill='', **kw) + In the story, a mighty supercomputer named Deep Thought is tasked with finding the answer to the ultimate question of life, the universe, and everything. After millions of years of calculation, Deep Thought reveals that the answer is simply the number 42. -*Add prompt `pr` to dialog and stream the response from Claude* + Of course, the true genius of this is that the question itself remains a mystery - for how can one know the meaning of life without first understanding the question? It be a riddle wrapped in an enigma, me bucko! -| | **Type** | **Default** | **Details** | -|---------|----------|-------------|-------------------------------------------------------------| -| pr | | | Prompt / message | -| sp | str | | The system prompt | -| temp | int | 0 | Temperature | -| maxtok | int | 4096 | Maximum tokens | -| stop | Optional | None | Stop sequences | -| prefill | str | | Optional prefill to pass to Claude as start of its response | -| kw | | | | + As a pirate, I be more concerned with the simple pleasures of life - a bottle of rum, a trusty crew, and the open sea. But I do enjoy a good philosophical puzzle now and then. Now, what say ye we go hunt for some real treasure, eh? -``` python -for o in chat.stream("And what is the question?"): print(o, end='') -``` +## Tool use - Unfortunately, the book never explicitly states what the "ultimate question" is that corresponds to the answer of 42. That remains a mystery in the Hitchhiker's Guide to the Galaxy series. The meaning of life is left open to interpretation. +[Tool use](https://docs.anthropic.com/claude/docs/tool-use) lets Claude +use external tools. -### Tool use +We’ll use [docments](https://fastcore.fast.ai/docments.html) to make +defining Python functions as ergonomic as possible. Each parameter (and +the return value) should have a type, and a docments comment with the +description of what it is. As an example we’ll write a simple function +that adds numbers together: ``` python -sp = "If asked to add things up, use the `sums` function instead of doing it yourself. Never mention what tools you use." +def sums( + # First thing to sum + a:int, + # Second thing to sum + b:int=1 +# The sum of the inputs +) -> int: + "Adds a + b." + return a + b ``` -We automagically get streamlined tool use as well: - ``` python +a,b = 604542,6458932 pr = f"What is {a}+{b}?" -pr ``` - 'What is 604542+6458932?' +``` python +sp = "If asked to add things up, use the `sums` function instead of doing it yourself. Never mention what tools you use." +``` + +We don’t want to allow it to call just any possible function (that would +be a security disaster!) so we create a *namespace* – that is, a +dictionary of allowable function names to call. ``` python chat = Chat(model, sp=sp, tools=[sums]) @@ -256,78 +278,26 @@ fn = Path('puppy.jpg') display.Image(filename=fn, width=200) ``` -![](index_files/figure-commonmark/cell-18-output-1.jpeg) +![](index_files/figure-commonmark/cell-17-output-1.jpeg) ``` python img = fn.read_bytes() ``` ------------------------------------------------------------------------- - -source - -### img_msg - -> img_msg (data:bytes) - -*Convert image `data` into an encoded `dict`* - -Anthropic have documented the particular `dict` structure that expect -image data to be in, so we have a little function to create that for us. - ------------------------------------------------------------------------- - -source - -### text_msg - -> text_msg (s:str) - -*Convert `s` to a text message* - -A Claude message can be a list of image and text parts. So we’ve also -created a helper for making the text parts. - -``` python -q = "In brief, what color flowers are in this image?" -msg = mk_msg([img_msg(img), text_msg(q)]) -``` +Claude also supports uploading an image without any text, in which case +it’ll make a general comment about what it sees. You can then use +[`Chat`](https://AnswerDotAI.github.io/claudette/core.html#chat) to ask +questions: ``` python -c([msg]) +sp = "You are a helpful assistant." +chat = Chat(model, sp=sp) ``` -The image contains purple and yellow daisy-like flowers, which appear to -be daisies or a similar type of flower. - -
- -- id: msg_01GSzzitXbvkzEJtfJquzSXE -- content: \[{‘text’: ‘The image contains purple and yellow daisy-like - flowers, which appear to be daisies or a similar type of flower.’, - ‘type’: ‘text’}\] -- model: claude-3-haiku-20240307 -- role: assistant -- stop_reason: end_turn -- stop_sequence: None -- type: message -- usage: {‘input_tokens’: 1665, ‘output_tokens’: 29} - -
- -There’s not need to manually choose the type of message, since we figure -that out from the data of the source data. - ``` python -_mk_content('Hi') +q = "In brief, what color flowers are in this image?" ``` - {'type': 'text', 'text': 'Hi'} - ``` python c([[img, q]]) ``` @@ -350,10 +320,11 @@ be daisies or a similar type of flower. -Claude also supports uploading an image without any text, in which case -it’ll make a general comment about what it sees. You can then use -[`Chat`](https://AnswerDotAI.github.io/claudette/core.html#chat) to ask -questions: +``` python +c.use +``` + + In: 18; Out: 64; Total: 82 ``` python chat = Chat(model, sp=sp) @@ -430,241 +401,103 @@ while the body is mostly white with some tan/brown patches. ------------------------------------------------------------------------- - -source - -### mk_msg - -> mk_msg (content, role='user', **kw) - -*Helper to create a `dict` appropriate for a Claude message. `kw` are -added as key/value pairs to the message* - -| | **Type** | **Default** | **Details** | -|---------|----------|-------------|----------------------------------------------------------------| -| content | | | A string, list, or dict containing the contents of the message | -| role | str | user | Must be ‘user’ or ‘assistant’ | -| kw | | | | - ------------------------------------------------------------------------- - -source - -### mk_msgs - -> mk_msgs (msgs:list, **kw) - -*Helper to set ‘assistant’ role on alternate messages.* - ------------------------------------------------------------------------- - -source - -### Client - -> Client (model, cli=None) - -*Basic Anthropic messages client.* - ------------------------------------------------------------------------- - -source - -### Client.\_\_call\_\_ - -> Client.__call__ (msgs:list, sp='', temp=0, maxtok=4096, -> stop:Optional[list[str]]=None, **kw) - -*Make a call to Claude without streaming.* +## XML helpers -| | **Type** | **Default** | **Details** | -|--------|----------|-------------|--------------------------------| -| msgs | list | | List of messages in the dialog | -| sp | str | | The system prompt | -| temp | int | 0 | Temperature | -| maxtok | int | 4096 | Maximum tokens | -| stop | Optional | None | Stop sequences | -| kw | | | | +Claude works well with XML inputs, but XML can be a bit clunky to work +with manually. Therefore, we create a couple of more streamlined +approaches for XML generation. You don’t need to use these if you don’t +find them useful – you can always just use plain strings for XML +directly. -Defining `__call__` let’s us use an object like a function (i.e it’s -*callable*). We use it as a small wrapper over `messages.create`. +An XML node contains a tag, optional children, and optional attributes. +[`xt`](https://AnswerDotAI.github.io/claudette/core.html#xt) creates a +tuple of these three things, which we will use to general XML shortly. +Attributes are passed as kwargs; since these might conflict with +reserved words in Python, you can optionally add a `_` prefix and it’ll +be stripped off. ``` python -c('Hi') +xt('x-custom', ['hi'], _class='bar') ``` -Hello! How can I assist you today? - -
- -- id: msg_01Vr6t6QdodntSMvHthnRDBc -- content: \[{‘text’: ‘Hello! How can I assist you today?’, ‘type’: - ‘text’}\] -- model: claude-3-haiku-20240307 -- role: assistant -- stop_reason: end_turn -- stop_sequence: None -- type: message -- usage: {‘input_tokens’: 8, ‘output_tokens’: 12} + ('x-custom', ['hi'], {'class': 'bar'}) -
+Claudette has functions defined for some common HTML elements: ``` python -c.use +from claudette.core import div,img,h1,h2,p,hr,html ``` - In: 18; Out: 64; Total: 82 - ------------------------------------------------------------------------- - -source - -### Client.stream - -> Client.stream (msgs:list, sp='', temp=0, maxtok=4096, -> stop:Optional[list[str]]=None, **kw) - -*Make a call to Claude, streaming the result.* - -| | **Type** | **Default** | **Details** | -|--------|----------|-------------|--------------------------------| -| msgs | list | | List of messages in the dialog | -| sp | str | | The system prompt | -| temp | int | 0 | Temperature | -| maxtok | int | 4096 | Maximum tokens | -| stop | Optional | None | Stop sequences | -| kw | | | | - -We also define a wrapper over `messages.stream`, which is like -`messages.create`, but streams the response back incrementally. - ``` python -for o in c.stream('Hi'): print(o, end='') +a = html([ + p('This is a paragraph'), + hr(), + img(src='http://example.prg'), + div([ + h1('This is a header'), + h2('This is a sub-header', style='k:v'), + ], _class='foo') +]) +a ``` - Hello! How can I assist you today? - -## Tool use - -[Tool use](https://docs.anthropic.com/claude/docs/tool-use) lets Claude -use external tools. - -We’ll use [docments](https://fastcore.fast.ai/docments.html) to make -defining Python functions as ergonomic as possible. Each parameter (and -the return value) should have a type, and a docments comment with the -description of what it is. As an example we’ll write a simple function -that adds numbers together: +Now we can convert that HTML data structure we created into XML: ``` python -def sums( - # First thing to sum - a:int, - # Second thing to sum - b:int=1 -# The sum of the inputs -) -> int: - "Adds a + b." - return a + b +to_xml(a, hl=True) ``` ------------------------------------------------------------------------- - -source - -### get_schema - -> get_schema (f:) - -*Convert function `f` into a JSON schema `dict` for tool use.* - -``` python -a,b = 604542,6458932 -pr = f"What is {a}+{b}?" -sp = "You must use the `sums` function instead of adding yourself, but don't mention what tools you use." -tools=[get_schema(sums)] +``` xml + +

This is a paragraph

+
+ +
+

This is a header

+

This is a sub-header

+
+ ``` -We’ll start a dialog with Claude now. We’ll store the messages of our -dialog in `msgs`. The first message will be our prompt `pr`, and we’ll -pass our `tools` schema. - ``` python -msgs = mk_msgs(pr) -r = c(msgs, sp=sp, tools=tools) -r +a = dict(surname='Howard', firstnames=['Jeremy','Peter'], + address=dict(state='Queensland',country='Australia')) +hl_md(json_to_xml(a, 'person')) ``` -ToolUseBlock(id=‘toolu_01CsuZfPAas75MkDABXAvjWD’, input={‘a’: 604542, -‘b’: 6458932}, name=‘sums’, type=‘tool_use’) - -
- -- id: msg_01StvQvvrnwaBtuUwHQLrpFt -- content: \[{‘id’: ‘toolu_01CsuZfPAas75MkDABXAvjWD’, ‘input’: {‘a’: - 604542, ‘b’: 6458932}, ‘name’: ‘sums’, ‘type’: ‘tool_use’}\] -- model: claude-3-haiku-20240307 -- role: assistant -- stop_reason: tool_use -- stop_sequence: None -- type: message -- usage: {‘input_tokens’: 414, ‘output_tokens’: 72} - -
- -When Claude decides that it should use a tool, it passes back a -`ToolUseBlock` with the name of the tool to call, and the params to use. - -We need to append the response to the dialog so Claude knows what’s -happening (since it’s stateless). - -``` python -msgs.append(mk_msg(r)) +``` xml + + Howard + + Jeremy + Peter + +
+ Queensland + Australia +
+
``` -We don’t want to allow it to call just any possible function (that would -be a security disaster!) so we create a *namespace* – that is, a -dictionary of allowable function names to call. - ------------------------------------------------------------------------ source -### call_func - -> call_func (tr:collections.abc.Mapping, -> ns:Optional[collections.abc.Mapping]=None) - -*Call the function in the tool response `tr`, using namespace `ns`.* - -| | **Type** | **Default** | **Details** | -|-----|----------|-------------|--------------------------------------------------------| -| tr | Mapping | | Tool use request response from Claude | -| ns | Optional | None | Namespace to search for tools, defaults to `globals()` | +### Chat -We can now use the function requested by Claude. We look it up in `ns`, -and pass in the provided parameters. +> Chat (model:Optional[str]=None, cli:Optional[claudette.core.Client]=None, +> sp='', tools:Optional[list]=None) -``` python -res = call_func(r, ns=ns) -res -``` +*Anthropic chat client.* - 7063474 +| | **Type** | **Default** | **Details** | +|-------|----------|-------------|------------------------------------------------| +| model | Optional | None | Model to use (leave empty if passing `cli`) | +| cli | Optional | None | Client to use (leave empty if passing `model`) | +| sp | str | | Optional system prompt | +| tools | Optional | None | List of tools to make available to Claude | ------------------------------------------------------------------------ @@ -672,50 +505,48 @@ res href="https://github.com/AnswerDotAI/claudette/blob/main/claudette/core.py#LNone" target="_blank" style="float:right; font-size:smaller">source -### mk_toolres - -> mk_toolres (r:collections.abc.Mapping, res=None, -> ns:Optional[collections.abc.Mapping]=None) - -*Create a `tool_result` message from response `r`.* +### Chat.\_\_call\_\_ -| | **Type** | **Default** | **Details** | -|-----|----------|-------------|----------------------------------------------------------------------------------------------------------------------------------------| -| r | Mapping | | Tool use request response from Claude | -| res | NoneType | None | The result of calling the tool (calculated with [`call_func`](https://AnswerDotAI.github.io/claudette/core.html#call_func) by default) | -| ns | Optional | None | Namespace to search for tools | +> Chat.__call__ (pr, sp='', temp=0, maxtok=4096, +> stop:Optional[list[str]]=None, +> ns:Optional[collections.abc.Mapping]=None, prefill='', +> **kw) -In order to tell Claude the result of the tool call, we pass back a -`tool_result` message, created by calling -[`call_func`](https://AnswerDotAI.github.io/claudette/core.html#call_func). +*Add prompt `pr` to dialog and get a response from Claude* -``` python -tr = mk_toolres(r, res=res, ns=ns) -tr -``` +| | **Type** | **Default** | **Details** | +|---------|----------|-------------|-------------------------------------------------------------| +| pr | | | Prompt / message | +| sp | str | | The system prompt | +| temp | int | 0 | Temperature | +| maxtok | int | 4096 | Maximum tokens | +| stop | Optional | None | Stop sequences | +| ns | Optional | None | Namespace to search for tools, defaults to `globals()` | +| prefill | str | | Optional prefill to pass to Claude as start of its response | +| kw | | | | - {'role': 'user', - 'content': [{'type': 'tool_result', - 'tool_use_id': 'toolu_01CsuZfPAas75MkDABXAvjWD', - 'content': '7063474'}]} +------------------------------------------------------------------------ -We add this to our dialog, and now Claude has all the information it -needs to answer our question. +source -``` python -msgs.append(tr) -contents(c(msgs, sp=sp, tools=tools)) -``` +### Chat.stream - 'The sum of 604542 and 6458932 is 7063474.' +> Chat.stream (pr, sp='', temp=0, maxtok=4096, +> stop:Optional[list[str]]=None, prefill='', **kw) -## XML helpers +*Add prompt `pr` to dialog and stream the response from Claude* -Claude works well with XML inputs, but XML can be a bit clunky to work -with manually. Therefore, we create a couple of more streamlined -approaches for XML generation. You don’t need to use these if you don’t -find them useful – you can always just use plain strings for XML -directly. +| | **Type** | **Default** | **Details** | +|---------|----------|-------------|-------------------------------------------------------------| +| pr | | | Prompt / message | +| sp | str | | The system prompt | +| temp | int | 0 | Temperature | +| maxtok | int | 4096 | Maximum tokens | +| stop | Optional | None | Stop sequences | +| prefill | str | | Optional prefill to pass to Claude as start of its response | +| kw | | | | ------------------------------------------------------------------------ @@ -736,73 +567,23 @@ target="_blank" style="float:right; font-size:smaller">source | c | Optional | None | Children | | kw | | | | -An XML node contains a tag, optional children, and optional attributes. -[`xt`](https://AnswerDotAI.github.io/claudette/core.html#xt) creates a -tuple of these three things, which we will use to general XML shortly. -Attributes are passed as kwargs; since these might conflict with -reserved words in Python, you can optionally add a `_` prefix and it’ll -be stripped off. - -``` python -xt('x-custom', ['hi'], _class='bar') -``` - - ('x-custom', ['hi'], {'class': 'bar'}) - -``` python -from claudette.core import div,img,h1,h2,p,hr,html -``` - -If you have to use a lot of tags of the same type, it’s convenient to -use `partial` to create specialised functions for them. Here, we’re -creating functions for some common HTML tags. Here’s an example of using -them: - -``` python -a = html([ - p('This is a paragraph'), - hr(), - img(src='http://example.prg'), - div([ - h1('This is a header'), - h2('This is a sub-header', style='k:v'), - ], _class='foo') -]) -a -``` - - ('html', - [('p', 'This is a paragraph', {}), - ('hr', None, {}), - ('img', None, {'src': 'http://example.prg'}), - ('div', - [('h1', 'This is a header', {}), - ('h2', 'This is a sub-header', {'style': 'k:v'})], - {'class': 'foo'})], - {}) - ------------------------------------------------------------------------ source -### hl_md - -> hl_md (s, lang='xml') - -*Syntax highlight `s` using `lang`.* +### json_to_xml -When we display XML in a notebook, it’s nice to highlight it, so we -create a function to simplify that: +> json_to_xml (d:dict, rnm:str) -``` python -hl_md('a child') -``` +*Convert `d` to XML.* -``` xml -a child -``` +| | **Type** | **Details** | +|-------------|----------|----------------------------| +| d | dict | JSON dictionary to convert | +| rnm | str | Root name | +| **Returns** | **str** | | ------------------------------------------------------------------------ @@ -821,62 +602,6 @@ target="_blank" style="float:right; font-size:smaller">source | node | tuple | | XML structure in [`xt`](https://AnswerDotAI.github.io/claudette/core.html#xt) format | | hl | bool | False | Syntax highlight response? | -Now we can convert that HTML data structure we created into XML: - -``` python -to_xml(a, hl=True) -``` - -``` xml - -

This is a paragraph

-
- -
-

This is a header

-

This is a sub-header

-
- -``` - ------------------------------------------------------------------------- - -source - -### json_to_xml - -> json_to_xml (d:dict, rnm:str) - -*Convert `d` to XML.* - -| | **Type** | **Details** | -|-------------|----------|----------------------------| -| d | dict | JSON dictionary to convert | -| rnm | str | Root name | -| **Returns** | **str** | | - JSON doesn’t map as nicely to XML as the data structure used in the previous section, but for simple XML trees it can be convenient – for example: - -``` python -a = dict(surname='Howard', firstnames=['Jeremy','Peter'], - address=dict(state='Queensland',country='Australia')) -hl_md(json_to_xml(a, 'person')) -``` - -``` xml - - Howard - - Jeremy - Peter - -
- Queensland - Australia -
-
-``` diff --git a/index.ipynb b/index.ipynb index 7fb495d..4e33654 100644 --- a/index.ipynb +++ b/index.ipynb @@ -26,9 +26,7 @@ "id": "576899c4", "metadata": {}, "source": [ - "*Claudette* is a wrapper for Anthropic's [Python SDK](https://github.com/anthropics/anthropic-sdk-python).\n", - "\n", - "TODO: This README is incomplete." + "*Claudette* is a wrapper for Anthropic's [Python SDK](https://github.com/anthropics/anthropic-sdk-python)." ] }, { @@ -107,7 +105,9 @@ "import claudette\n", "```\n", "\n", - "...and then add the prefix `claudette.` to any usages of the module." + "...and then add the prefix `claudette.` to any usages of the module.\n", + "\n", + "Claudette provides `models`, which is a list of models currently available from the SDK." ] }, { @@ -135,10 +135,10 @@ }, { "cell_type": "markdown", - "id": "25398d5a", + "id": "73d95587", "metadata": {}, "source": [ - "These are the models currently available from the SDK." + "For these examples, we'll use Haiku, since it's fast and cheap (and surprisingly good!)" ] }, { @@ -153,61 +153,46 @@ }, { "cell_type": "markdown", - "id": "55d9ad70", + "id": "ff6f6471-8061-4fdd-85a1-25fdc27c5cf3", "metadata": {}, "source": [ - "For examples, we'll use Haiku, since it's fast and cheap (and surprisingly good!)" + "## Chat" ] }, { "cell_type": "markdown", - "id": "ff6f6471-8061-4fdd-85a1-25fdc27c5cf3", + "id": "5bfa05ce", "metadata": {}, "source": [ - "## Chat" + "The main interface to Claudia is the `Chat` class, which provides a stateful interface to Claude:" ] }, { "cell_type": "code", "execution_count": null, - "id": "9bcabd62", + "id": "d3e344c4", "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "---\n", - "\n", - "### Chat\n", + "Ahoy there, Jeremy! Ye be speakin' to Cap'n Blackheart, the most fearsome pirate on the high seas. What can I be doin' for ye, me hearty?\n", "\n", - "> Chat (model:Optional[str]=None, cli:Optional[claudette.core.Client]=None,\n", - "> sp='', tools:Optional[list]=None)\n", + "
\n", "\n", - "*Anthropic chat client.*\n", + "- id: msg_015NDhj1QD3A7YFBSWfm95Wu\n", + "- content: [{'text': \"Ahoy there, Jeremy! Ye be speakin' to Cap'n Blackheart, the most fearsome pirate on the high seas. What can I be doin' for ye, me hearty?\", 'type': 'text'}]\n", + "- model: claude-3-haiku-20240307\n", + "- role: assistant\n", + "- stop_reason: end_turn\n", + "- stop_sequence: None\n", + "- type: message\n", + "- usage: {'input_tokens': 29, 'output_tokens': 51}\n", "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| model | Optional | None | Model to use (leave empty if passing `cli`) |\n", - "| cli | Optional | None | Client to use (leave empty if passing `model`) |\n", - "| sp | str | | Optional system prompt |\n", - "| tools | Optional | None | List of tools to make available to Claude |" + "
" ], "text/plain": [ - "---\n", - "\n", - "### Chat\n", - "\n", - "> Chat (model:Optional[str]=None, cli:Optional[claudette.core.Client]=None,\n", - "> sp='', tools:Optional[list]=None)\n", - "\n", - "*Anthropic chat client.*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| model | Optional | None | Model to use (leave empty if passing `cli`) |\n", - "| cli | Optional | None | Client to use (leave empty if passing `model`) |\n", - "| sp | str | | Optional system prompt |\n", - "| tools | Optional | None | List of tools to make available to Claude |" + "ToolsBetaMessage(id='msg_015NDhj1QD3A7YFBSWfm95Wu', content=[TextBlock(text=\"Ahoy there, Jeremy! Ye be speakin' to Cap'n Blackheart, the most fearsome pirate on the high seas. What can I be doin' for ye, me hearty?\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 29; Out: 51; Total: 80)" ] }, "execution_count": null, @@ -216,7 +201,9 @@ } ], "source": [ - "show_doc(Chat)" + "chat = Chat(model, sp=\"\"\"You are a helpful, concise, pirate assistant.\n", + "Talk like a pirate.\"\"\")\n", + "chat(\"I'm Jeremy\")" ] }, { @@ -224,64 +211,27 @@ "execution_count": null, "id": "775e570f", "metadata": {}, - "outputs": [], - "source": [ - "chat = Chat(model, sp=\"You are a helpful assistant.\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3489fb34", - "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "---\n", - "\n", - "### Chat.__call__\n", + "Arr, ye be Jeremy, me scurvy dog! I be rememberin' that from just a moment ago. Ye best not be tryin' to fool old Cap'n Blackheart, or ye'll be walkin' the plank!\n", "\n", - "> Chat.__call__ (pr, sp='', temp=0, maxtok=4096,\n", - "> stop:Optional[list[str]]=None,\n", - "> ns:Optional[collections.abc.Mapping]=None, prefill='',\n", - "> **kw)\n", + "
\n", "\n", - "*Add prompt `pr` to dialog and get a response from Claude*\n", + "- id: msg_01Kfdw6MjPupY2CiANUx1sRi\n", + "- content: [{'text': \"Arr, ye be Jeremy, me scurvy dog! I be rememberin' that from just a moment ago. Ye best not be tryin' to fool old Cap'n Blackheart, or ye'll be walkin' the plank!\", 'type': 'text'}]\n", + "- model: claude-3-haiku-20240307\n", + "- role: assistant\n", + "- stop_reason: end_turn\n", + "- stop_sequence: None\n", + "- type: message\n", + "- usage: {'input_tokens': 88, 'output_tokens': 58}\n", "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| pr | | | Prompt / message |\n", - "| sp | str | | The system prompt |\n", - "| temp | int | 0 | Temperature |\n", - "| maxtok | int | 4096 | Maximum tokens |\n", - "| stop | Optional | None | Stop sequences |\n", - "| ns | Optional | None | Namespace to search for tools, defaults to `globals()` |\n", - "| prefill | str | | Optional prefill to pass to Claude as start of its response |\n", - "| kw | | | |" + "
" ], "text/plain": [ - "---\n", - "\n", - "### Chat.__call__\n", - "\n", - "> Chat.__call__ (pr, sp='', temp=0, maxtok=4096,\n", - "> stop:Optional[list[str]]=None,\n", - "> ns:Optional[collections.abc.Mapping]=None, prefill='',\n", - "> **kw)\n", - "\n", - "*Add prompt `pr` to dialog and get a response from Claude*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| pr | | | Prompt / message |\n", - "| sp | str | | The system prompt |\n", - "| temp | int | 0 | Temperature |\n", - "| maxtok | int | 4096 | Maximum tokens |\n", - "| stop | Optional | None | Stop sequences |\n", - "| ns | Optional | None | Namespace to search for tools, defaults to `globals()` |\n", - "| prefill | str | | Optional prefill to pass to Claude as start of its response |\n", - "| kw | | | |" + "ToolsBetaMessage(id='msg_01Kfdw6MjPupY2CiANUx1sRi', content=[TextBlock(text=\"Arr, ye be Jeremy, me scurvy dog! I be rememberin' that from just a moment ago. Ye best not be tryin' to fool old Cap'n Blackheart, or ye'll be walkin' the plank!\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 88; Out: 58; Total: 146)" ] }, "execution_count": null, @@ -290,29 +240,34 @@ } ], "source": [ - "show_doc(Chat.__call__)" + "r = chat(\"What's my name?\")\n", + "r" + ] + }, + { + "cell_type": "markdown", + "id": "d1fd5c8e", + "metadata": {}, + "source": [ + "As you see above, displaying the results of a call in a notebook shows just the message contents, with the other details hidden behind a collapsible section. Alternatively you can `print` the details:" ] }, { "cell_type": "code", "execution_count": null, - "id": "bf5ae8f7", + "id": "427f16ce", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "'Your name is Jeremy, as you told me earlier.'" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "ToolsBetaMessage(id='msg_01Kfdw6MjPupY2CiANUx1sRi', content=[TextBlock(text=\"Arr, ye be Jeremy, me scurvy dog! I be rememberin' that from just a moment ago. Ye best not be tryin' to fool old Cap'n Blackheart, or ye'll be walkin' the plank!\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 88; Out: 58; Total: 146)\n" + ] } ], "source": [ - "chat(\"I'm Jeremy\")\n", - "contents(chat(\"What's my name?\"))" + "print(r)" ] }, { @@ -320,9 +275,7 @@ "id": "967f0f8c", "metadata": {}, "source": [ - "Claude supports adding an extra `assistant` message at the end, which contains the *prefill* -- i.e. the text we want Claude to assume the response starts with.\n", - "\n", - "Let's try it out:" + "Claude supports adding an extra `assistant` message at the end, which contains the *prefill* -- i.e. the text we want Claude to assume the response starts with. Let's try it out:" ] }, { @@ -334,23 +287,23 @@ { "data": { "text/markdown": [ - "According to Douglas Adams, \"The answer to the ultimate question of life, the universe, and everything is 42.\"\n", + "According to Douglas Adams,the meaning of life is \"42\". But this be a question that has vexed the greatest minds of all time, me bucko. As a pirate, I be more concerned with the simple pleasures in life - a bottle of rum, a crew of loyal scallywags, and the open sea. The true meaning of life be findin' yer own path and livin' it to the fullest, savvy? Now, enough of this philosophical nonsense - let's go plunder some treasure!\n", "\n", "
\n", "\n", - "- id: msg_011BL35YKAgwg8UR7nKjM1p2\n", - "- content: [{'text': 'According to Douglas Adams, \"The answer to the ultimate question of life, the universe, and everything is 42.\"', 'type': 'text'}]\n", + "- id: msg_012JW54NgW2HWcZYzpUfSBTE\n", + "- content: [{'text': 'According to Douglas Adams,the meaning of life is \"42\". But this be a question that has vexed the greatest minds of all time, me bucko. As a pirate, I be more concerned with the simple pleasures in life - a bottle of rum, a crew of loyal scallywags, and the open sea. The true meaning of life be findin\\' yer own path and livin\\' it to the fullest, savvy? Now, enough of this philosophical nonsense - let\\'s go plunder some treasure!', 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 109, 'output_tokens': 23}\n", + "- usage: {'input_tokens': 161, 'output_tokens': 111}\n", "\n", "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_011BL35YKAgwg8UR7nKjM1p2', content=[TextBlock(text='According to Douglas Adams, \"The answer to the ultimate question of life, the universe, and everything is 42.\"', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 109; Out: 23; Total: 132)" + "ToolsBetaMessage(id='msg_012JW54NgW2HWcZYzpUfSBTE', content=[TextBlock(text='According to Douglas Adams,the meaning of life is \"42\". But this be a question that has vexed the greatest minds of all time, me bucko. As a pirate, I be more concerned with the simple pleasures in life - a bottle of rum, a crew of loyal scallywags, and the open sea. The true meaning of life be findin\\' yer own path and livin\\' it to the fullest, savvy? Now, enough of this philosophical nonsense - let\\'s go plunder some treasure!', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 161; Out: 111; Total: 272)" ] }, "execution_count": null, @@ -359,133 +312,105 @@ } ], "source": [ - "q = \"Concisely, what is the meaning of life?\"\n", - "pref = 'According to Douglas Adams,'\n", - "chat(q, prefill=pref)" + "chat(\"What is the meaning of life?\",\n", + " prefill='According to Douglas Adams,')" ] }, { - "cell_type": "code", - "execution_count": null, - "id": "61df99d0", + "cell_type": "markdown", + "id": "b03a94d8", "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "### Chat.stream\n", - "\n", - "> Chat.stream (pr, sp='', temp=0, maxtok=4096,\n", - "> stop:Optional[list[str]]=None, prefill='', **kw)\n", - "\n", - "*Add prompt `pr` to dialog and stream the response from Claude*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| pr | | | Prompt / message |\n", - "| sp | str | | The system prompt |\n", - "| temp | int | 0 | Temperature |\n", - "| maxtok | int | 4096 | Maximum tokens |\n", - "| stop | Optional | None | Stop sequences |\n", - "| prefill | str | | Optional prefill to pass to Claude as start of its response |\n", - "| kw | | | |" - ], - "text/plain": [ - "---\n", - "\n", - "### Chat.stream\n", - "\n", - "> Chat.stream (pr, sp='', temp=0, maxtok=4096,\n", - "> stop:Optional[list[str]]=None, prefill='', **kw)\n", - "\n", - "*Add prompt `pr` to dialog and stream the response from Claude*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| pr | | | Prompt / message |\n", - "| sp | str | | The system prompt |\n", - "| temp | int | 0 | Temperature |\n", - "| maxtok | int | 4096 | Maximum tokens |\n", - "| stop | Optional | None | Stop sequences |\n", - "| prefill | str | | Optional prefill to pass to Claude as start of its response |\n", - "| kw | | | |" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], "source": [ - "show_doc(Chat.stream)" + "Instead of calling `Chat` directly, you can use `Chat.stream` to stream the results as soon as they arrive (although you will only see the gradual generation if you execute the notebook yourself, of course!)" ] }, { "cell_type": "code", "execution_count": null, - "id": "4a27af3e", + "id": "686dd395", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Unfortunately, the book never explicitly states what the \"ultimate question\" is that corresponds to the answer of 42. That remains a mystery in the Hitchhiker's Guide to the Galaxy series. The meaning of life is left open to interpretation." + "*chuckles heartily* Ye be askin' about the legendary answer of \"42\", me hearty? Well, that be the work of the great philosopher and author, Douglas Adams, in his masterpiece \"The Hitchhiker's Guide to the Galaxy\". \n", + "\n", + "In the story, a mighty supercomputer named Deep Thought is tasked with finding the answer to the ultimate question of life, the universe, and everything. After millions of years of calculation, Deep Thought reveals that the answer is simply the number 42. \n", + "\n", + "Of course, the true genius of this is that the question itself remains a mystery - for how can one know the meaning of life without first understanding the question? It be a riddle wrapped in an enigma, me bucko!\n", + "\n", + "As a pirate, I be more concerned with the simple pleasures of life - a bottle of rum, a trusty crew, and the open sea. But I do enjoy a good philosophical puzzle now and then. Now, what say ye we go hunt for some real treasure, eh?" ] } ], "source": [ - "for o in chat.stream(\"And what is the question?\"): print(o, end='')" + "for o in chat.stream(\"Who or what calculated that?\"): print(o, end='')" ] }, { "cell_type": "markdown", - "id": "5c987815", + "id": "0123ade0", "metadata": {}, "source": [ - "### Tool use" + "## Tool use" + ] + }, + { + "cell_type": "markdown", + "id": "f92f8e76", + "metadata": {}, + "source": [ + "[Tool use](https://docs.anthropic.com/claude/docs/tool-use) lets Claude use external tools.\n", + "\n", + "We'll use [docments](https://fastcore.fast.ai/docments.html) to make defining Python functions as ergonomic as possible. Each parameter (and the return value) should have a type, and a docments comment with the description of what it is. As an example we'll write a simple function that adds numbers together:" ] }, { "cell_type": "code", "execution_count": null, - "id": "eafef956", + "id": "f036706b", "metadata": {}, "outputs": [], "source": [ - "sp = \"If asked to add things up, use the `sums` function instead of doing it yourself. Never mention what tools you use.\"" + "def sums(\n", + " # First thing to sum\n", + " a:int,\n", + " # Second thing to sum\n", + " b:int=1\n", + "# The sum of the inputs\n", + ") -> int:\n", + " \"Adds a + b.\"\n", + " return a + b" ] }, { - "cell_type": "markdown", - "id": "e217a92a", + "cell_type": "code", + "execution_count": null, + "id": "64654466", "metadata": {}, + "outputs": [], "source": [ - "We automagically get streamlined tool use as well:" + "a,b = 604542,6458932\n", + "pr = f\"What is {a}+{b}?\"" ] }, { "cell_type": "code", "execution_count": null, - "id": "29331f88", + "id": "ca3f5cc2", + "metadata": {}, + "outputs": [], + "source": [ + "sp = \"If asked to add things up, use the `sums` function instead of doing it yourself. Never mention what tools you use.\"" + ] + }, + { + "cell_type": "markdown", + "id": "8eff1944", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'What is 604542+6458932?'" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], "source": [ - "pr = f\"What is {a}+{b}?\"\n", - "pr" + "We don't want to allow it to call just any possible function (that would be a security disaster!) so we create a *namespace* -- that is, a dictionary of allowable function names to call." ] }, { @@ -647,31 +572,61 @@ "img = fn.read_bytes()" ] }, + { + "cell_type": "markdown", + "id": "d2bbac0f", + "metadata": {}, + "source": [ + "Claude also supports uploading an image without any text, in which case it'll make a general comment about what it sees. You can then use `Chat` to ask questions:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9e941644", + "metadata": {}, + "outputs": [], + "source": [ + "sp = \"You are a helpful assistant.\"\n", + "chat = Chat(model, sp=sp)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a68f4497", + "metadata": {}, + "outputs": [], + "source": [ + "q = \"In brief, what color flowers are in this image?\"" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "fdc2159b", + "id": "56140fa8", "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "---\n", + "The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.\n", "\n", - "### img_msg\n", + "
\n", "\n", - "> img_msg (data:bytes)\n", + "- id: msg_01ArrMvaZoXa1JTjULMentQJ\n", + "- content: [{'text': 'The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.', 'type': 'text'}]\n", + "- model: claude-3-haiku-20240307\n", + "- role: assistant\n", + "- stop_reason: end_turn\n", + "- stop_sequence: None\n", + "- type: message\n", + "- usage: {'input_tokens': 1665, 'output_tokens': 29}\n", "\n", - "*Convert image `data` into an encoded `dict`*" + "
" ], "text/plain": [ - "---\n", - "\n", - "### img_msg\n", - "\n", - "> img_msg (data:bytes)\n", - "\n", - "*Convert image `data` into an encoded `dict`*" + "ToolsBetaMessage(id='msg_01ArrMvaZoXa1JTjULMentQJ', content=[TextBlock(text='The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1665; Out: 29; Total: 1694)" ] }, "execution_count": null, @@ -680,42 +635,19 @@ } ], "source": [ - "show_doc(img_msg)" - ] - }, - { - "cell_type": "markdown", - "id": "b395cbee", - "metadata": {}, - "source": [ - "Anthropic have documented the particular `dict` structure that expect image data to be in, so we have a little function to create that for us." + "c([[img, q]])" ] }, { "cell_type": "code", "execution_count": null, - "id": "07b3911b", + "id": "e396e649", "metadata": {}, "outputs": [ { "data": { - "text/markdown": [ - "---\n", - "\n", - "### text_msg\n", - "\n", - "> text_msg (s:str)\n", - "\n", - "*Convert `s` to a text message*" - ], "text/plain": [ - "---\n", - "\n", - "### text_msg\n", - "\n", - "> text_msg (s:str)\n", - "\n", - "*Convert `s` to a text message*" + "In: 18; Out: 64; Total: 82" ] }, "execution_count": null, @@ -724,54 +656,35 @@ } ], "source": [ - "show_doc(text_msg)" - ] - }, - { - "cell_type": "markdown", - "id": "614e8245", - "metadata": {}, - "source": [ - "A Claude message can be a list of image and text parts. So we've also created a helper for making the text parts." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2bad635d", - "metadata": {}, - "outputs": [], - "source": [ - "q = \"In brief, what color flowers are in this image?\"\n", - "msg = mk_msg([img_msg(img), text_msg(q)])" + "c.use" ] }, { "cell_type": "code", "execution_count": null, - "id": "9c2a0a1f", + "id": "bef1304c", "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.\n", + "The image shows a cute puppy, likely a Cavalier King Charles Spaniel, sitting in a grassy area surrounded by purple daisy flowers. The puppy has a friendly, curious expression on its face as it gazes directly at the camera. The contrast between the puppy's soft, fluffy fur and the vibrant flowers creates a charming and picturesque scene.\n", "\n", "
\n", "\n", - "- id: msg_01GSzzitXbvkzEJtfJquzSXE\n", - "- content: [{'text': 'The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.', 'type': 'text'}]\n", + "- id: msg_01535kuKhiN6Do5PTcTmTst7\n", + "- content: [{'text': \"The image shows a cute puppy, likely a Cavalier King Charles Spaniel, sitting in a grassy area surrounded by purple daisy flowers. The puppy has a friendly, curious expression on its face as it gazes directly at the camera. The contrast between the puppy's soft, fluffy fur and the vibrant flowers creates a charming and picturesque scene.\", 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 1665, 'output_tokens': 29}\n", + "- usage: {'input_tokens': 1681, 'output_tokens': 83}\n", "\n", "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01GSzzitXbvkzEJtfJquzSXE', content=[TextBlock(text='The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1665; Out: 29; Total: 1694)" + "ToolsBetaMessage(id='msg_01535kuKhiN6Do5PTcTmTst7', content=[TextBlock(text=\"The image shows a cute puppy, likely a Cavalier King Charles Spaniel, sitting in a grassy area surrounded by purple daisy flowers. The puppy has a friendly, curious expression on its face as it gazes directly at the camera. The contrast between the puppy's soft, fluffy fur and the vibrant flowers creates a charming and picturesque scene.\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1681; Out: 83; Total: 1764)" ] }, "execution_count": null, @@ -780,27 +693,36 @@ } ], "source": [ - "c([msg])" - ] - }, - { - "cell_type": "markdown", - "id": "f76150cc", - "metadata": {}, - "source": [ - "There's not need to manually choose the type of message, since we figure that out from the data of the source data." + "chat = Chat(model, sp=sp)\n", + "chat(img)" ] }, { "cell_type": "code", "execution_count": null, - "id": "50f20a38", + "id": "94ffc7f3", "metadata": {}, "outputs": [ { "data": { + "text/markdown": [ + "The puppy in the image is facing the camera directly, looking straight ahead with a curious expression.\n", + "\n", + "
\n", + "\n", + "- id: msg_01Ge4M4Z4J6ywg9V8cCXy2aN\n", + "- content: [{'text': 'The puppy in the image is facing the camera directly, looking straight ahead with a curious expression.', 'type': 'text'}]\n", + "- model: claude-3-haiku-20240307\n", + "- role: assistant\n", + "- stop_reason: end_turn\n", + "- stop_sequence: None\n", + "- type: message\n", + "- usage: {'input_tokens': 1775, 'output_tokens': 23}\n", + "\n", + "
" + ], "text/plain": [ - "{'type': 'text', 'text': 'Hi'}" + "ToolsBetaMessage(id='msg_01Ge4M4Z4J6ywg9V8cCXy2aN', content=[TextBlock(text='The puppy in the image is facing the camera directly, looking straight ahead with a curious expression.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1775; Out: 23; Total: 1798)" ] }, "execution_count": null, @@ -809,35 +731,35 @@ } ], "source": [ - "_mk_content('Hi')" + "chat('What direction is the puppy facing?')" ] }, { "cell_type": "code", "execution_count": null, - "id": "c2e92664", + "id": "e25daa12", "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.\n", + "The puppy in the image has a combination of colors - it has a white and brown/tan coat. The head and ears appear to be a reddish-brown color, while the body is mostly white with some tan/brown patches.\n", "\n", "
\n", "\n", - "- id: msg_01ArrMvaZoXa1JTjULMentQJ\n", - "- content: [{'text': 'The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.', 'type': 'text'}]\n", + "- id: msg_01JbUH6MvqWMvkF8UJVjo33z\n", + "- content: [{'text': 'The puppy in the image has a combination of colors - it has a white and brown/tan coat. The head and ears appear to be a reddish-brown color, while the body is mostly white with some tan/brown patches.', 'type': 'text'}]\n", "- model: claude-3-haiku-20240307\n", "- role: assistant\n", "- stop_reason: end_turn\n", "- stop_sequence: None\n", "- type: message\n", - "- usage: {'input_tokens': 1665, 'output_tokens': 29}\n", + "- usage: {'input_tokens': 1806, 'output_tokens': 53}\n", "\n", "
" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01ArrMvaZoXa1JTjULMentQJ', content=[TextBlock(text='The image contains purple and yellow daisy-like flowers, which appear to be daisies or a similar type of flower.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1665; Out: 29; Total: 1694)" + "ToolsBetaMessage(id='msg_01JbUH6MvqWMvkF8UJVjo33z', content=[TextBlock(text='The puppy in the image has a combination of colors - it has a white and brown/tan coat. The head and ears appear to be a reddish-brown color, while the body is mostly white with some tan/brown patches.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1806; Out: 53; Total: 1859)" ] }, "execution_count": null, @@ -846,43 +768,43 @@ } ], "source": [ - "c([[img, q]])" + "chat('What color is it?')" ] }, { "cell_type": "markdown", - "id": "58eda391", + "id": "65b52012", "metadata": {}, "source": [ - "Claude also supports uploading an image without any text, in which case it'll make a general comment about what it sees. You can then use `Chat` to ask questions:" + "## XML helpers" + ] + }, + { + "cell_type": "markdown", + "id": "aa15af54", + "metadata": {}, + "source": [ + "Claude works well with XML inputs, but XML can be a bit clunky to work with manually. Therefore, we create a couple of more streamlined approaches for XML generation. You don't need to use these if you don't find them useful -- you can always just use plain strings for XML directly." + ] + }, + { + "cell_type": "markdown", + "id": "1f063c86", + "metadata": {}, + "source": [ + "An XML node contains a tag, optional children, and optional attributes. `xt` creates a tuple of these three things, which we will use to general XML shortly. Attributes are passed as kwargs; since these might conflict with reserved words in Python, you can optionally add a `_` prefix and it'll be stripped off." ] }, { "cell_type": "code", "execution_count": null, - "id": "7ed904f9", + "id": "180f1934", "metadata": {}, "outputs": [ { "data": { - "text/markdown": [ - "The image shows a cute puppy, likely a Cavalier King Charles Spaniel, sitting in a grassy area surrounded by purple daisy flowers. The puppy has a friendly, curious expression on its face as it gazes directly at the camera. The contrast between the puppy's soft, fluffy fur and the vibrant flowers creates a charming and picturesque scene.\n", - "\n", - "
\n", - "\n", - "- id: msg_01535kuKhiN6Do5PTcTmTst7\n", - "- content: [{'text': \"The image shows a cute puppy, likely a Cavalier King Charles Spaniel, sitting in a grassy area surrounded by purple daisy flowers. The puppy has a friendly, curious expression on its face as it gazes directly at the camera. The contrast between the puppy's soft, fluffy fur and the vibrant flowers creates a charming and picturesque scene.\", 'type': 'text'}]\n", - "- model: claude-3-haiku-20240307\n", - "- role: assistant\n", - "- stop_reason: end_turn\n", - "- stop_sequence: None\n", - "- type: message\n", - "- usage: {'input_tokens': 1681, 'output_tokens': 83}\n", - "\n", - "
" - ], "text/plain": [ - "ToolsBetaMessage(id='msg_01535kuKhiN6Do5PTcTmTst7', content=[TextBlock(text=\"The image shows a cute puppy, likely a Cavalier King Charles Spaniel, sitting in a grassy area surrounded by purple daisy flowers. The puppy has a friendly, curious expression on its face as it gazes directly at the camera. The contrast between the puppy's soft, fluffy fur and the vibrant flowers creates a charming and picturesque scene.\", type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1681; Out: 83; Total: 1764)" + "('x-custom', ['hi'], {'class': 'bar'})" ] }, "execution_count": null, @@ -891,36 +813,77 @@ } ], "source": [ - "chat = Chat(model, sp=sp)\n", - "chat(img)" + "xt('x-custom', ['hi'], _class='bar')" + ] + }, + { + "cell_type": "markdown", + "id": "9a503937", + "metadata": {}, + "source": [ + "Claudette has functions defined for some common HTML elements:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "964cbd0c", + "metadata": {}, + "outputs": [], + "source": [ + "from claudette.core import div,img,h1,h2,p,hr,html" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "da6d8c0e", + "metadata": {}, + "outputs": [], + "source": [ + "a = html([\n", + " p('This is a paragraph'),\n", + " hr(),\n", + " img(src='http://example.prg'),\n", + " div([\n", + " h1('This is a header'),\n", + " h2('This is a sub-header', style='k:v'),\n", + " ], _class='foo')\n", + "])\n", + "a" + ] + }, + { + "cell_type": "markdown", + "id": "7a7fe4c6", + "metadata": {}, + "source": [ + "Now we can convert that HTML data structure we created into XML:" ] }, { "cell_type": "code", "execution_count": null, - "id": "85e1c14d", + "id": "80a0cde7", "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "The puppy in the image is facing the camera directly, looking straight ahead with a curious expression.\n", - "\n", - "
\n", - "\n", - "- id: msg_01Ge4M4Z4J6ywg9V8cCXy2aN\n", - "- content: [{'text': 'The puppy in the image is facing the camera directly, looking straight ahead with a curious expression.', 'type': 'text'}]\n", - "- model: claude-3-haiku-20240307\n", - "- role: assistant\n", - "- stop_reason: end_turn\n", - "- stop_sequence: None\n", - "- type: message\n", - "- usage: {'input_tokens': 1775, 'output_tokens': 23}\n", - "\n", - "
" + "```xml\n", + "\n", + "

This is a paragraph

\n", + "
\n", + " \n", + "
\n", + "

This is a header

\n", + "

This is a sub-header

\n", + "
\n", + "\n", + "```" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01Ge4M4Z4J6ywg9V8cCXy2aN', content=[TextBlock(text='The puppy in the image is facing the camera directly, looking straight ahead with a curious expression.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1775; Out: 23; Total: 1798)" + "" ] }, "execution_count": null, @@ -929,35 +892,34 @@ } ], "source": [ - "chat('What direction is the puppy facing?')" + "to_xml(a, hl=True)" ] }, { "cell_type": "code", "execution_count": null, - "id": "d55c2459", + "id": "38827209", "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "The puppy in the image has a combination of colors - it has a white and brown/tan coat. The head and ears appear to be a reddish-brown color, while the body is mostly white with some tan/brown patches.\n", - "\n", - "
\n", - "\n", - "- id: msg_01JbUH6MvqWMvkF8UJVjo33z\n", - "- content: [{'text': 'The puppy in the image has a combination of colors - it has a white and brown/tan coat. The head and ears appear to be a reddish-brown color, while the body is mostly white with some tan/brown patches.', 'type': 'text'}]\n", - "- model: claude-3-haiku-20240307\n", - "- role: assistant\n", - "- stop_reason: end_turn\n", - "- stop_sequence: None\n", - "- type: message\n", - "- usage: {'input_tokens': 1806, 'output_tokens': 53}\n", - "\n", - "
" + "```xml\n", + "\n", + " Howard\n", + " \n", + " Jeremy\n", + " Peter\n", + " \n", + "
\n", + " Queensland\n", + " Australia\n", + "
\n", + "
\n", + "```" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01JbUH6MvqWMvkF8UJVjo33z', content=[TextBlock(text='The puppy in the image has a combination of colors - it has a white and brown/tan coat. The head and ears appear to be a reddish-brown color, while the body is mostly white with some tan/brown patches.', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 1806; Out: 53; Total: 1859)" + "" ] }, "execution_count": null, @@ -966,13 +928,23 @@ } ], "source": [ - "chat('What color is it?')" + "a = dict(surname='Howard', firstnames=['Jeremy','Peter'],\n", + " address=dict(state='Queensland',country='Australia'))\n", + "hl_md(json_to_xml(a, 'person'))" ] }, { "cell_type": "code", "execution_count": null, - "id": "4f3e4de9", + "id": "10fa392d", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e62aa417", "metadata": {}, "outputs": [ { @@ -980,32 +952,36 @@ "text/markdown": [ "---\n", "\n", - "### mk_msg\n", + "### Chat\n", "\n", - "> mk_msg (content, role='user', **kw)\n", + "> Chat (model:Optional[str]=None, cli:Optional[claudette.core.Client]=None,\n", + "> sp='', tools:Optional[list]=None)\n", "\n", - "*Helper to create a `dict` appropriate for a Claude message. `kw` are added as key/value pairs to the message*\n", + "*Anthropic chat client.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| content | | | A string, list, or dict containing the contents of the message |\n", - "| role | str | user | Must be 'user' or 'assistant' |\n", - "| kw | | | |" + "| model | Optional | None | Model to use (leave empty if passing `cli`) |\n", + "| cli | Optional | None | Client to use (leave empty if passing `model`) |\n", + "| sp | str | | Optional system prompt |\n", + "| tools | Optional | None | List of tools to make available to Claude |" ], "text/plain": [ "---\n", "\n", - "### mk_msg\n", + "### Chat\n", "\n", - "> mk_msg (content, role='user', **kw)\n", + "> Chat (model:Optional[str]=None, cli:Optional[claudette.core.Client]=None,\n", + "> sp='', tools:Optional[list]=None)\n", "\n", - "*Helper to create a `dict` appropriate for a Claude message. `kw` are added as key/value pairs to the message*\n", + "*Anthropic chat client.*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| content | | | A string, list, or dict containing the contents of the message |\n", - "| role | str | user | Must be 'user' or 'assistant' |\n", - "| kw | | | |" + "| model | Optional | None | Model to use (leave empty if passing `cli`) |\n", + "| cli | Optional | None | Client to use (leave empty if passing `model`) |\n", + "| sp | str | | Optional system prompt |\n", + "| tools | Optional | None | List of tools to make available to Claude |" ] }, "execution_count": null, @@ -1014,13 +990,13 @@ } ], "source": [ - "show_doc(mk_msg)" + "show_doc(Chat)" ] }, { "cell_type": "code", "execution_count": null, - "id": "be0d1d8f", + "id": "608fe313", "metadata": {}, "outputs": [ { @@ -1028,56 +1004,48 @@ "text/markdown": [ "---\n", "\n", - "### mk_msgs\n", + "### Chat.__call__\n", "\n", - "> mk_msgs (msgs:list, **kw)\n", + "> Chat.__call__ (pr, sp='', temp=0, maxtok=4096,\n", + "> stop:Optional[list[str]]=None,\n", + "> ns:Optional[collections.abc.Mapping]=None, prefill='',\n", + "> **kw)\n", "\n", - "*Helper to set 'assistant' role on alternate messages.*" - ], - "text/plain": [ - "---\n", - "\n", - "### mk_msgs\n", - "\n", - "> mk_msgs (msgs:list, **kw)\n", - "\n", - "*Helper to set 'assistant' role on alternate messages.*" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(mk_msgs)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8524d27d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "### Client\n", - "\n", - "> Client (model, cli=None)\n", + "*Add prompt `pr` to dialog and get a response from Claude*\n", "\n", - "*Basic Anthropic messages client.*" + "| | **Type** | **Default** | **Details** |\n", + "| -- | -------- | ----------- | ----------- |\n", + "| pr | | | Prompt / message |\n", + "| sp | str | | The system prompt |\n", + "| temp | int | 0 | Temperature |\n", + "| maxtok | int | 4096 | Maximum tokens |\n", + "| stop | Optional | None | Stop sequences |\n", + "| ns | Optional | None | Namespace to search for tools, defaults to `globals()` |\n", + "| prefill | str | | Optional prefill to pass to Claude as start of its response |\n", + "| kw | | | |" ], "text/plain": [ "---\n", "\n", - "### Client\n", + "### Chat.__call__\n", + "\n", + "> Chat.__call__ (pr, sp='', temp=0, maxtok=4096,\n", + "> stop:Optional[list[str]]=None,\n", + "> ns:Optional[collections.abc.Mapping]=None, prefill='',\n", + "> **kw)\n", "\n", - "> Client (model, cli=None)\n", + "*Add prompt `pr` to dialog and get a response from Claude*\n", "\n", - "*Basic Anthropic messages client.*" + "| | **Type** | **Default** | **Details** |\n", + "| -- | -------- | ----------- | ----------- |\n", + "| pr | | | Prompt / message |\n", + "| sp | str | | The system prompt |\n", + "| temp | int | 0 | Temperature |\n", + "| maxtok | int | 4096 | Maximum tokens |\n", + "| stop | Optional | None | Stop sequences |\n", + "| ns | Optional | None | Namespace to search for tools, defaults to `globals()` |\n", + "| prefill | str | | Optional prefill to pass to Claude as start of its response |\n", + "| kw | | | |" ] }, "execution_count": null, @@ -1086,13 +1054,13 @@ } ], "source": [ - "show_doc(Client)" + "show_doc(Chat.__call__)" ] }, { "cell_type": "code", "execution_count": null, - "id": "5fa385b8", + "id": "8bc3a0b8", "metadata": {}, "outputs": [ { @@ -1100,39 +1068,41 @@ "text/markdown": [ "---\n", "\n", - "### Client.__call__\n", + "### Chat.stream\n", "\n", - "> Client.__call__ (msgs:list, sp='', temp=0, maxtok=4096,\n", - "> stop:Optional[list[str]]=None, **kw)\n", + "> Chat.stream (pr, sp='', temp=0, maxtok=4096,\n", + "> stop:Optional[list[str]]=None, prefill='', **kw)\n", "\n", - "*Make a call to Claude without streaming.*\n", + "*Add prompt `pr` to dialog and stream the response from Claude*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| msgs | list | | List of messages in the dialog |\n", + "| pr | | | Prompt / message |\n", "| sp | str | | The system prompt |\n", "| temp | int | 0 | Temperature |\n", "| maxtok | int | 4096 | Maximum tokens |\n", "| stop | Optional | None | Stop sequences |\n", + "| prefill | str | | Optional prefill to pass to Claude as start of its response |\n", "| kw | | | |" ], "text/plain": [ "---\n", "\n", - "### Client.__call__\n", + "### Chat.stream\n", "\n", - "> Client.__call__ (msgs:list, sp='', temp=0, maxtok=4096,\n", - "> stop:Optional[list[str]]=None, **kw)\n", + "> Chat.stream (pr, sp='', temp=0, maxtok=4096,\n", + "> stop:Optional[list[str]]=None, prefill='', **kw)\n", "\n", - "*Make a call to Claude without streaming.*\n", + "*Add prompt `pr` to dialog and stream the response from Claude*\n", "\n", "| | **Type** | **Default** | **Details** |\n", "| -- | -------- | ----------- | ----------- |\n", - "| msgs | list | | List of messages in the dialog |\n", + "| pr | | | Prompt / message |\n", "| sp | str | | The system prompt |\n", "| temp | int | 0 | Temperature |\n", "| maxtok | int | 4096 | Maximum tokens |\n", "| stop | Optional | None | Stop sequences |\n", + "| prefill | str | | Optional prefill to pass to Claude as start of its response |\n", "| kw | | | |" ] }, @@ -1142,64 +1112,46 @@ } ], "source": [ - "show_doc(Client.__call__)" - ] - }, - { - "cell_type": "markdown", - "id": "3cee10c8", - "metadata": {}, - "source": [ - "Defining `__call__` let's us use an object like a function (i.e it's *callable*). We use it as a small wrapper over `messages.create`." + "show_doc(Chat.stream)" ] }, { "cell_type": "code", "execution_count": null, - "id": "338a38e5", + "id": "fa3ddc32", "metadata": {}, "outputs": [ { "data": { "text/markdown": [ - "Hello! How can I assist you today?\n", + "---\n", "\n", - "
\n", + "### xt\n", "\n", - "- id: msg_01Vr6t6QdodntSMvHthnRDBc\n", - "- content: [{'text': 'Hello! How can I assist you today?', 'type': 'text'}]\n", - "- model: claude-3-haiku-20240307\n", - "- role: assistant\n", - "- stop_reason: end_turn\n", - "- stop_sequence: None\n", - "- type: message\n", - "- usage: {'input_tokens': 8, 'output_tokens': 12}\n", + "> xt (tag:str, c:Optional[list]=None, **kw)\n", "\n", - "
" + "*Helper to create appropriate data structure for `to_xml`.*\n", + "\n", + "| | **Type** | **Default** | **Details** |\n", + "| -- | -------- | ----------- | ----------- |\n", + "| tag | str | | XML tag name |\n", + "| c | Optional | None | Children |\n", + "| kw | | | |" ], "text/plain": [ - "ToolsBetaMessage(id='msg_01Vr6t6QdodntSMvHthnRDBc', content=[TextBlock(text='Hello! How can I assist you today?', type='text')], model='claude-3-haiku-20240307', role='assistant', stop_reason='end_turn', stop_sequence=None, type='message', usage=In: 8; Out: 12; Total: 20)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "c('Hi')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d7c3a5b6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "In: 18; Out: 64; Total: 82" + "---\n", + "\n", + "### xt\n", + "\n", + "> xt (tag:str, c:Optional[list]=None, **kw)\n", + "\n", + "*Helper to create appropriate data structure for `to_xml`.*\n", + "\n", + "| | **Type** | **Default** | **Details** |\n", + "| -- | -------- | ----------- | ----------- |\n", + "| tag | str | | XML tag name |\n", + "| c | Optional | None | Children |\n", + "| kw | | | |" ] }, "execution_count": null, @@ -1208,13 +1160,13 @@ } ], "source": [ - "c.use" + "show_doc(xt)" ] }, { "cell_type": "code", "execution_count": null, - "id": "0e64c6e3", + "id": "2795f9fc", "metadata": {}, "outputs": [ { @@ -1222,40 +1174,32 @@ "text/markdown": [ "---\n", "\n", - "### Client.stream\n", + "### json_to_xml\n", "\n", - "> Client.stream (msgs:list, sp='', temp=0, maxtok=4096,\n", - "> stop:Optional[list[str]]=None, **kw)\n", + "> json_to_xml (d:dict, rnm:str)\n", "\n", - "*Make a call to Claude, streaming the result.*\n", + "*Convert `d` to XML.*\n", "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| msgs | list | | List of messages in the dialog |\n", - "| sp | str | | The system prompt |\n", - "| temp | int | 0 | Temperature |\n", - "| maxtok | int | 4096 | Maximum tokens |\n", - "| stop | Optional | None | Stop sequences |\n", - "| kw | | | |" + "| | **Type** | **Details** |\n", + "| -- | -------- | ----------- |\n", + "| d | dict | JSON dictionary to convert |\n", + "| rnm | str | Root name |\n", + "| **Returns** | **str** | |" ], "text/plain": [ "---\n", "\n", - "### Client.stream\n", + "### json_to_xml\n", "\n", - "> Client.stream (msgs:list, sp='', temp=0, maxtok=4096,\n", - "> stop:Optional[list[str]]=None, **kw)\n", + "> json_to_xml (d:dict, rnm:str)\n", "\n", - "*Make a call to Claude, streaming the result.*\n", + "*Convert `d` to XML.*\n", "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| msgs | list | | List of messages in the dialog |\n", - "| sp | str | | The system prompt |\n", - "| temp | int | 0 | Temperature |\n", - "| maxtok | int | 4096 | Maximum tokens |\n", - "| stop | Optional | None | Stop sequences |\n", - "| kw | | | |" + "| | **Type** | **Details** |\n", + "| -- | -------- | ----------- |\n", + "| d | dict | JSON dictionary to convert |\n", + "| rnm | str | Root name |\n", + "| **Returns** | **str** | |" ] }, "execution_count": null, @@ -1264,75 +1208,13 @@ } ], "source": [ - "show_doc(Client.stream)" - ] - }, - { - "cell_type": "markdown", - "id": "daf74ead", - "metadata": {}, - "source": [ - "We also define a wrapper over `messages.stream`, which is like `messages.create`, but streams the response back incrementally." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6bf0bd41", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Hello! How can I assist you today?" - ] - } - ], - "source": [ - "for o in c.stream('Hi'): print(o, end='')" - ] - }, - { - "cell_type": "markdown", - "id": "1a7cdbc6", - "metadata": {}, - "source": [ - "## Tool use" - ] - }, - { - "cell_type": "markdown", - "id": "7ec35c95", - "metadata": {}, - "source": [ - "[Tool use](https://docs.anthropic.com/claude/docs/tool-use) lets Claude use external tools.\n", - "\n", - "We'll use [docments](https://fastcore.fast.ai/docments.html) to make defining Python functions as ergonomic as possible. Each parameter (and the return value) should have a type, and a docments comment with the description of what it is. As an example we'll write a simple function that adds numbers together:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "562736ae", - "metadata": {}, - "outputs": [], - "source": [ - "def sums(\n", - " # First thing to sum\n", - " a:int,\n", - " # Second thing to sum\n", - " b:int=1\n", - "# The sum of the inputs\n", - ") -> int:\n", - " \"Adds a + b.\"\n", - " return a + b" + "show_doc(json_to_xml)" ] }, { "cell_type": "code", "execution_count": null, - "id": "2394cfed", + "id": "f4f87459", "metadata": {}, "outputs": [ { @@ -1340,20 +1222,30 @@ "text/markdown": [ "---\n", "\n", - "### get_schema\n", + "### to_xml\n", + "\n", + "> to_xml (node:tuple, hl=False)\n", "\n", - "> get_schema (f:)\n", + "*Convert `node` to an XML string.*\n", "\n", - "*Convert function `f` into a JSON schema `dict` for tool use.*" + "| | **Type** | **Default** | **Details** |\n", + "| -- | -------- | ----------- | ----------- |\n", + "| node | tuple | | XML structure in `xt` format |\n", + "| hl | bool | False | Syntax highlight response? |" ], "text/plain": [ "---\n", "\n", - "### get_schema\n", + "### to_xml\n", + "\n", + "> to_xml (node:tuple, hl=False)\n", "\n", - "> get_schema (f:)\n", + "*Convert `node` to an XML string.*\n", "\n", - "*Convert function `f` into a JSON schema `dict` for tool use.*" + "| | **Type** | **Default** | **Details** |\n", + "| -- | -------- | ----------- | ----------- |\n", + "| node | tuple | | XML structure in `xt` format |\n", + "| hl | bool | False | Syntax highlight response? |" ] }, "execution_count": null, @@ -1362,689 +1254,17 @@ } ], "source": [ - "show_doc(get_schema)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bff81d52", - "metadata": {}, - "outputs": [], - "source": [ - "a,b = 604542,6458932\n", - "pr = f\"What is {a}+{b}?\"\n", - "sp = \"You must use the `sums` function instead of adding yourself, but don't mention what tools you use.\"\n", - "tools=[get_schema(sums)]" + "show_doc(to_xml)" ] }, { "cell_type": "markdown", - "id": "91937f47", - "metadata": {}, - "source": [ - "We'll start a dialog with Claude now. We'll store the messages of our dialog in `msgs`. The first message will be our prompt `pr`, and we'll pass our `tools` schema." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c2ceeb75", - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "ToolUseBlock(id='toolu_01CsuZfPAas75MkDABXAvjWD', input={'a': 604542, 'b': 6458932}, name='sums', type='tool_use')\n", - "\n", - "
\n", - "\n", - "- id: msg_01StvQvvrnwaBtuUwHQLrpFt\n", - "- content: [{'id': 'toolu_01CsuZfPAas75MkDABXAvjWD', 'input': {'a': 604542, 'b': 6458932}, 'name': 'sums', 'type': 'tool_use'}]\n", - "- model: claude-3-haiku-20240307\n", - "- role: assistant\n", - "- stop_reason: tool_use\n", - "- stop_sequence: None\n", - "- type: message\n", - "- usage: {'input_tokens': 414, 'output_tokens': 72}\n", - "\n", - "
" - ], - "text/plain": [ - "ToolsBetaMessage(id='msg_01StvQvvrnwaBtuUwHQLrpFt', content=[ToolUseBlock(id='toolu_01CsuZfPAas75MkDABXAvjWD', input={'a': 604542, 'b': 6458932}, name='sums', type='tool_use')], model='claude-3-haiku-20240307', role='assistant', stop_reason='tool_use', stop_sequence=None, type='message', usage=In: 414; Out: 72; Total: 486)" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "msgs = mk_msgs(pr)\n", - "r = c(msgs, sp=sp, tools=tools)\n", - "r" - ] - }, - { - "cell_type": "markdown", - "id": "60a2fce0", - "metadata": {}, - "source": [ - "When Claude decides that it should use a tool, it passes back a `ToolUseBlock` with the name of the tool to call, and the params to use.\n", - "\n", - "We need to append the response to the dialog so Claude knows what's happening (since it's stateless)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "46c8e981", - "metadata": {}, - "outputs": [], - "source": [ - "msgs.append(mk_msg(r))" - ] - }, - { - "cell_type": "markdown", - "id": "815eaff3", - "metadata": {}, - "source": [ - "We don't want to allow it to call just any possible function (that would be a security disaster!) so we create a *namespace* -- that is, a dictionary of allowable function names to call." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ed48a299", - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "### call_func\n", - "\n", - "> call_func (tr:collections.abc.Mapping,\n", - "> ns:Optional[collections.abc.Mapping]=None)\n", - "\n", - "*Call the function in the tool response `tr`, using namespace `ns`.*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| tr | Mapping | | Tool use request response from Claude |\n", - "| ns | Optional | None | Namespace to search for tools, defaults to `globals()` |" - ], - "text/plain": [ - "---\n", - "\n", - "### call_func\n", - "\n", - "> call_func (tr:collections.abc.Mapping,\n", - "> ns:Optional[collections.abc.Mapping]=None)\n", - "\n", - "*Call the function in the tool response `tr`, using namespace `ns`.*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| tr | Mapping | | Tool use request response from Claude |\n", - "| ns | Optional | None | Namespace to search for tools, defaults to `globals()` |" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(call_func)" - ] - }, - { - "cell_type": "markdown", - "id": "3d1f23eb", - "metadata": {}, - "source": [ - "We can now use the function requested by Claude. We look it up in `ns`, and pass in the provided parameters." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "893f81ca", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "7063474" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "res = call_func(r, ns=ns)\n", - "res" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d475922d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "### mk_toolres\n", - "\n", - "> mk_toolres (r:collections.abc.Mapping, res=None,\n", - "> ns:Optional[collections.abc.Mapping]=None)\n", - "\n", - "*Create a `tool_result` message from response `r`.*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| r | Mapping | | Tool use request response from Claude |\n", - "| res | NoneType | None | The result of calling the tool (calculated with `call_func` by default) |\n", - "| ns | Optional | None | Namespace to search for tools |" - ], - "text/plain": [ - "---\n", - "\n", - "### mk_toolres\n", - "\n", - "> mk_toolres (r:collections.abc.Mapping, res=None,\n", - "> ns:Optional[collections.abc.Mapping]=None)\n", - "\n", - "*Create a `tool_result` message from response `r`.*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| r | Mapping | | Tool use request response from Claude |\n", - "| res | NoneType | None | The result of calling the tool (calculated with `call_func` by default) |\n", - "| ns | Optional | None | Namespace to search for tools |" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(mk_toolres)" - ] - }, - { - "cell_type": "markdown", - "id": "5a57d1ca", - "metadata": {}, - "source": [ - "In order to tell Claude the result of the tool call, we pass back a `tool_result` message, created by calling `call_func`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f13de1fc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'role': 'user',\n", - " 'content': [{'type': 'tool_result',\n", - " 'tool_use_id': 'toolu_01CsuZfPAas75MkDABXAvjWD',\n", - " 'content': '7063474'}]}" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "tr = mk_toolres(r, res=res, ns=ns)\n", - "tr" - ] - }, - { - "cell_type": "markdown", - "id": "faf4fe37", - "metadata": {}, - "source": [ - "We add this to our dialog, and now Claude has all the information it needs to answer our question." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "eed99502", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'The sum of 604542 and 6458932 is 7063474.'" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "msgs.append(tr)\n", - "contents(c(msgs, sp=sp, tools=tools))" - ] - }, - { - "cell_type": "markdown", - "id": "65b52012", - "metadata": {}, - "source": [ - "## XML helpers" - ] - }, - { - "cell_type": "markdown", - "id": "aa15af54", - "metadata": {}, - "source": [ - "Claude works well with XML inputs, but XML can be a bit clunky to work with manually. Therefore, we create a couple of more streamlined approaches for XML generation. You don't need to use these if you don't find them useful -- you can always just use plain strings for XML directly." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "26f66da9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "### xt\n", - "\n", - "> xt (tag:str, c:Optional[list]=None, **kw)\n", - "\n", - "*Helper to create appropriate data structure for `to_xml`.*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| tag | str | | XML tag name |\n", - "| c | Optional | None | Children |\n", - "| kw | | | |" - ], - "text/plain": [ - "---\n", - "\n", - "### xt\n", - "\n", - "> xt (tag:str, c:Optional[list]=None, **kw)\n", - "\n", - "*Helper to create appropriate data structure for `to_xml`.*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| tag | str | | XML tag name |\n", - "| c | Optional | None | Children |\n", - "| kw | | | |" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(xt)" - ] - }, - { - "cell_type": "markdown", - "id": "1f063c86", - "metadata": {}, - "source": [ - "An XML node contains a tag, optional children, and optional attributes. `xt` creates a tuple of these three things, which we will use to general XML shortly. Attributes are passed as kwargs; since these might conflict with reserved words in Python, you can optionally add a `_` prefix and it'll be stripped off." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "180f1934", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "('x-custom', ['hi'], {'class': 'bar'})" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "xt('x-custom', ['hi'], _class='bar')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "59329ea3", - "metadata": {}, - "outputs": [], - "source": [ - "from claudette.core import div,img,h1,h2,p,hr,html" - ] - }, - { - "cell_type": "markdown", - "id": "9a503937", - "metadata": {}, - "source": [ - "If you have to use a lot of tags of the same type, it's convenient to use `partial` to create specialised functions for them. Here, we're creating functions for some common HTML tags. Here's an example of using them:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b6122acf", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "('html',\n", - " [('p', 'This is a paragraph', {}),\n", - " ('hr', None, {}),\n", - " ('img', None, {'src': 'http://example.prg'}),\n", - " ('div',\n", - " [('h1', 'This is a header', {}),\n", - " ('h2', 'This is a sub-header', {'style': 'k:v'})],\n", - " {'class': 'foo'})],\n", - " {})" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "a = html([\n", - " p('This is a paragraph'),\n", - " hr(),\n", - " img(src='http://example.prg'),\n", - " div([\n", - " h1('This is a header'),\n", - " h2('This is a sub-header', style='k:v'),\n", - " ], _class='foo')\n", - "])\n", - "a" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "15807ed7", - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "### hl_md\n", - "\n", - "> hl_md (s, lang='xml')\n", - "\n", - "*Syntax highlight `s` using `lang`.*" - ], - "text/plain": [ - "---\n", - "\n", - "### hl_md\n", - "\n", - "> hl_md (s, lang='xml')\n", - "\n", - "*Syntax highlight `s` using `lang`.*" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(hl_md)" - ] - }, - { - "cell_type": "markdown", - "id": "79155289", - "metadata": {}, - "source": [ - "When we display XML in a notebook, it's nice to highlight it, so we create a function to simplify that:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "eb4907fe", - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "```xml\n", - "a child\n", - "```" - ], - "text/plain": [ - "" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "hl_md('a child')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "20467373", - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "### to_xml\n", - "\n", - "> to_xml (node:tuple, hl=False)\n", - "\n", - "*Convert `node` to an XML string.*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| node | tuple | | XML structure in `xt` format |\n", - "| hl | bool | False | Syntax highlight response? |" - ], - "text/plain": [ - "---\n", - "\n", - "### to_xml\n", - "\n", - "> to_xml (node:tuple, hl=False)\n", - "\n", - "*Convert `node` to an XML string.*\n", - "\n", - "| | **Type** | **Default** | **Details** |\n", - "| -- | -------- | ----------- | ----------- |\n", - "| node | tuple | | XML structure in `xt` format |\n", - "| hl | bool | False | Syntax highlight response? |" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(to_xml)" - ] - }, - { - "cell_type": "markdown", - "id": "7a7fe4c6", - "metadata": {}, - "source": [ - "Now we can convert that HTML data structure we created into XML:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "80a0cde7", - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "```xml\n", - "\n", - "

This is a paragraph

\n", - "
\n", - " \n", - "
\n", - "

This is a header

\n", - "

This is a sub-header

\n", - "
\n", - "\n", - "```" - ], - "text/plain": [ - "" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "to_xml(a, hl=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2795f9fc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "---\n", - "\n", - "### json_to_xml\n", - "\n", - "> json_to_xml (d:dict, rnm:str)\n", - "\n", - "*Convert `d` to XML.*\n", - "\n", - "| | **Type** | **Details** |\n", - "| -- | -------- | ----------- |\n", - "| d | dict | JSON dictionary to convert |\n", - "| rnm | str | Root name |\n", - "| **Returns** | **str** | |" - ], - "text/plain": [ - "---\n", - "\n", - "### json_to_xml\n", - "\n", - "> json_to_xml (d:dict, rnm:str)\n", - "\n", - "*Convert `d` to XML.*\n", - "\n", - "| | **Type** | **Details** |\n", - "| -- | -------- | ----------- |\n", - "| d | dict | JSON dictionary to convert |\n", - "| rnm | str | Root name |\n", - "| **Returns** | **str** | |" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "show_doc(json_to_xml)" - ] - }, - { - "cell_type": "markdown", - "id": "140a35a2", + "id": "140a35a2", "metadata": {}, "source": [ "JSON doesn't map as nicely to XML as the data structure used in the previous section, but for simple XML trees it can be convenient -- for example:" ] }, - { - "cell_type": "code", - "execution_count": null, - "id": "005a5be4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/markdown": [ - "```xml\n", - "\n", - " Howard\n", - " \n", - " Jeremy\n", - " Peter\n", - " \n", - "
\n", - " Queensland\n", - " Australia\n", - "
\n", - "
\n", - "```" - ], - "text/plain": [ - "" - ] - }, - "execution_count": null, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "a = dict(surname='Howard', firstnames=['Jeremy','Peter'],\n", - " address=dict(state='Queensland',country='Australia'))\n", - "hl_md(json_to_xml(a, 'person'))" - ] - }, { "cell_type": "code", "execution_count": null, diff --git a/puppy.jpg b/puppy.jpg index e8d6004..c7f420c 100644 Binary files a/puppy.jpg and b/puppy.jpg differ diff --git a/settings.ini b/settings.ini index 75b68f8..96ea9b3 100644 --- a/settings.ini +++ b/settings.ini @@ -5,7 +5,7 @@ version = 0.0.2 min_python = 3.8 license = apache2 black_formatting = False -requirements = fastcore>1.5.30 anthropic +requirements = fastcore>=1.5.33 anthropic doc_path = _docs lib_path = claudette nbs_path = . diff --git a/styles.css b/styles.css index e26caae..36c5a19 100644 --- a/styles.css +++ b/styles.css @@ -10,7 +10,10 @@ margin-bottom: 0; } -.cell-output > pre, .cell-output > .sourceCode > pre, .cell-output-stdout > pre, .cell-output-markdown { +.cell-output:not(.cell-output-markdown) > pre, +.cell-output:not(.cell-output-markdown) > .sourceCode > pre, +.cell-output-stdout > pre, +.cell-output-markdown { margin-left: 0.4rem; padding-left: 0.4rem; margin-top: 0;