Fixed skill library
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@ -1,5 +0,0 @@
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import sys
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def explore_functions():
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"""None"""
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import sys
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def fibonacci():
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"""None"""
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fib = [0, 1]
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@ -0,0 +1,25 @@
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def openAbleton():
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"""open ableton"""
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import os
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os.system("open /Applications/Ableton\ Live\ 10\ Suite.app")
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import os
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# Search can be slow if there are many files
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# This will search in the Applications folder only
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applications = "/Applications/"
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# walk function will generate the file names in a directory tree
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# We will look for any application that contains "Ableton" in its name
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for foldername, subfolders, filenames in os.walk(applications):
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for filename in filenames:
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if "Ableton" in filename:
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ableton_path = os.path.join(foldername, filename)
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break
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ableton_path
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os.system("open /Applications/Ableton\ Live\ 11\ Intro.app")
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import time
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def schedule_fixed():
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"""None"""
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time.sleep(delay)
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@ -172,7 +172,7 @@ finally:
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# SKILLS
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You may use the following functions (assume they're imported) to complete your goals whenever possible:
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Try to use the following functions (assume they're imported) to complete your goals whenever possible:
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{{
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import sys
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@ -186,9 +186,9 @@ interpreter.model = "gpt-3.5"
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combined_messages = "\\n".join(json.dumps(x) for x in messages[-3:])
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#query_msg = interpreter.chat(f"This is the conversation so far: {combined_messages}. What is a <10 words query that could be used to find functions that would help answer the user's question?")
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query_msg = combined_messages
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query = query_msg[0]['content']
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interpreter.computer.skills.path = OI_SKILLS_DIR
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#query = query_msg[0]['content']
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query = combined_messages
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interpreter.computer.skills.path = '''OI_SKILLS_DIR'''
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skills = interpreter.computer.skills.search(query)
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lowercase_skills = [skill[0].lower() + skill[1:] for skill in skills]
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@ -87,6 +87,7 @@ def teach():
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interpreter.computer.languages = [l for l in interpreter.computer.languages if l.name.lower() == "python"]
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interpreter.force_task_completion = True
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for chunk in interpreter.chat(step, stream=True, display=False):
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print(chunk)
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if chunk["role"] == "computer" and "start" not in chunk and "end" not in chunk:
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chunk_type = chunk["type"]
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chunk_content = chunk["content"]
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