diff --git a/notebook/agentchat_teachability_summarizer.ipynb b/notebook/agentchat_teachability_summarizer.ipynb index a6b6feb56..54600e682 100644 --- a/notebook/agentchat_teachability_summarizer.ipynb +++ b/notebook/agentchat_teachability_summarizer.ipynb @@ -659,6 +659,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ + "# New Chat Session\n", "Let's end our first chat here. The following function needs to be called at the end of each chat, so that `TeachableAgent` can store what the user has taught it." ] }, @@ -676,93 +677,6 @@ "Find title and abstracts of 10 arxiv papers on explainable AI\n", "\n", "--------------------------------------------------------------------------------\n", - "\u001b[93m\n", - "LOOK FOR RELEVANT MEMOS, AS QUESTION-ANSWER PAIRS\u001b[0m\n", - "\u001b[92m\n", - "INPUT-OUTPUT PAIR RETRIEVED FROM VECTOR DATABASE:\n", - " INPUT1\n", - " The task described is to create concise summaries of papers, highlighting their main elements.\n", - " OUTPUT\n", - " For a similar but different task, use the advice: \"Summaries should contain one sentence for title, innovation, and main result.\"\n", - " DISTANCE\n", - " 1.0016729331312506\u001b[0m\n", - "\u001b[92m\n", - "INPUT-OUTPUT PAIR RETRIEVED FROM VECTOR DATABASE:\n", - " INPUT1\n", - " How should I summarize each paper, including a sentence for title, innovation, and main result?\n", - " OUTPUT\n", - " Summarize each paper. I like summaries to contain one sentence for title, innovation, and main result.\n", - " DISTANCE\n", - " 1.0553857122321069\u001b[0m\n", - "\u001b[92m\n", - "INPUT-OUTPUT PAIR RETRIEVED FROM VECTOR DATABASE:\n", - " INPUT1\n", - " What information are you looking for in the provided TEXT?\n", - " OUTPUT\n", - " 1. Title: Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness\n", - "2. Title: Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making\n", - "3. Title: Trust Explanations to Do What They Say\n", - "4. Title: A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective\n", - "5. Title: Trust Calibration and Trust Respect: A Method for Building Team Cohesion in Human Robot Teams\n", - "6. Title: Trust Considerations for Explainable Robots: A Human Factors Perspective\n", - "7. Title: Experimental Investigation of Trust in Anthropomorphic Agents as Task Partners\n", - "8. Title: Uncalibrated Models Can Improve Human-AI Collaboration\n", - "9. Title: Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems\n", - "10. Title: A Turing Test for Transparency\n", - " DISTANCE\n", - " 1.4706147803115148\u001b[0m\n", - "\u001b[93m\n", - "LOOK FOR RELEVANT MEMOS, AS TASK-ADVICE PAIRS\u001b[0m\n", - "\u001b[92m\n", - "INPUT-OUTPUT PAIR RETRIEVED FROM VECTOR DATABASE:\n", - " INPUT1\n", - " The task described is to create concise summaries of papers, highlighting their main elements.\n", - " OUTPUT\n", - " For a similar but different task, use the advice: \"Summaries should contain one sentence for title, innovation, and main result.\"\n", - " DISTANCE\n", - " 0.6954076895033864\u001b[0m\n", - "\u001b[92m\n", - "INPUT-OUTPUT PAIR RETRIEVED FROM VECTOR DATABASE:\n", - " INPUT1\n", - " How should I summarize each paper, including a sentence for title, innovation, and main result?\n", - " OUTPUT\n", - " Summarize each paper. I like summaries to contain one sentence for title, innovation, and main result.\n", - " DISTANCE\n", - " 0.822614638614859\u001b[0m\n", - "\u001b[92m\n", - "INPUT-OUTPUT PAIR RETRIEVED FROM VECTOR DATABASE:\n", - " INPUT1\n", - " What information are you looking for in the provided TEXT?\n", - " OUTPUT\n", - " 1. Title: Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness\n", - "2. Title: Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making\n", - "3. Title: Trust Explanations to Do What They Say\n", - "4. Title: A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective\n", - "5. Title: Trust Calibration and Trust Respect: A Method for Building Team Cohesion in Human Robot Teams\n", - "6. Title: Trust Considerations for Explainable Robots: A Human Factors Perspective\n", - "7. Title: Experimental Investigation of Trust in Anthropomorphic Agents as Task Partners\n", - "8. Title: Uncalibrated Models Can Improve Human-AI Collaboration\n", - "9. Title: Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems\n", - "10. Title: A Turing Test for Transparency\n", - " DISTANCE\n", - " 1.347382467078216\u001b[0m\n", - "\u001b[93m\n", - "MEMOS APPENDED TO LAST USER MESSAGE...\n", - "\n", - "# Memories that might help\n", - "- 1. Title: Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness\n", - "2. Title: Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making\n", - "3. Title: Trust Explanations to Do What They Say\n", - "4. Title: A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective\n", - "5. Title: Trust Calibration and Trust Respect: A Method for Building Team Cohesion in Human Robot Teams\n", - "6. Title: Trust Considerations for Explainable Robots: A Human Factors Perspective\n", - "7. Title: Experimental Investigation of Trust in Anthropomorphic Agents as Task Partners\n", - "8. Title: Uncalibrated Models Can Improve Human-AI Collaboration\n", - "9. Title: Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems\n", - "10. Title: A Turing Test for Transparency\n", - "- Summarize each paper. I like summaries to contain one sentence for title, innovation, and main result.\n", - "- For a similar but different task, use the advice: \"Summaries should contain one sentence for title, innovation, and main result.\"\n", - "\n", "\u001b[0m\n", "\u001b[33magent\u001b[0m (to user):\n", "\n", @@ -801,28 +715,6 @@ "\n", "\n", "--------------------------------------------------------------------------------\n", - "\u001b[93m\n", - "LOOK FOR RELEVANT MEMOS, AS QUESTION-ANSWER PAIRS\u001b[0m\n", - "\u001b[93m\n", - "THE CLOSEST MEMO IS BEYOND THE THRESHOLD:\u001b[0m\n", - "\u001b[92m\n", - "INPUT-OUTPUT PAIR RETRIEVED FROM VECTOR DATABASE:\n", - " INPUT1\n", - " What information are you looking for in the provided TEXT?\n", - " OUTPUT\n", - " 1. Title: Who Should I Trust: AI or Myself? Leveraging Human and AI Correctness\n", - "2. Title: Effect of Confidence and Explanation on Accuracy and Trust Calibration in AI-Assisted Decision Making\n", - "3. Title: Trust Explanations to Do What They Say\n", - "4. Title: A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective\n", - "5. Title: Trust Calibration and Trust Respect: A Method for Building Team Cohesion in Human Robot Teams\n", - "6. Title: Trust Considerations for Explainable Robots: A Human Factors Perspective\n", - "7. Title: Experimental Investigation of Trust in Anthropomorphic Agents as Task Partners\n", - "8. Title: Uncalibrated Models Can Improve Human-AI Collaboration\n", - "9. Title: Knowing About Knowing: An Illusion of Human Competence Can Hinder Appropriate Reliance on AI Systems\n", - "10. Title: A Turing Test for Transparency\n", - " DISTANCE\n", - " 1.8120591440810037\u001b[0m\n", - "\n", "\u001b[33magent\u001b[0m (to user):\n", "\n", "I apologize for the oversight. It seems you don't have the 'requests' library installed in your Python environment. We will need to switch to a web scraper that uses the standard Python libraries. Let's use `urllib` and `html.parser` instead. Please run the following code:\n", @@ -912,19 +804,6 @@ "\n", "\n", "--------------------------------------------------------------------------------\n", - "\u001b[93m\n", - "LOOK FOR RELEVANT MEMOS, AS QUESTION-ANSWER PAIRS\u001b[0m\n", - "\u001b[93m\n", - "THE CLOSEST MEMO IS BEYOND THE THRESHOLD:\u001b[0m\n", - "\u001b[92m\n", - "INPUT-OUTPUT PAIR RETRIEVED FROM VECTOR DATABASE:\n", - " INPUT1\n", - " The task described is to create concise summaries of papers, highlighting their main elements.\n", - " OUTPUT\n", - " For a similar but different task, use the advice: \"Summaries should contain one sentence for title, innovation, and main result.\"\n", - " DISTANCE\n", - " 1.6159366969592213\u001b[0m\n", - "\n", "\u001b[33magent\u001b[0m (to user):\n", "\n", "It seems that there was an issue with parsing the webpage properly, leading to incomplete titles and abstracts. However, I will summarize the ones with proper information. \n", @@ -953,19 +832,6 @@ "\n", "\n", "--------------------------------------------------------------------------------\n", - "\u001b[93m\n", - "LOOK FOR RELEVANT MEMOS, AS QUESTION-ANSWER PAIRS\u001b[0m\n", - "\u001b[93m\n", - "THE CLOSEST MEMO IS BEYOND THE THRESHOLD:\u001b[0m\n", - "\u001b[92m\n", - "INPUT-OUTPUT PAIR RETRIEVED FROM VECTOR DATABASE:\n", - " INPUT1\n", - " The task described is to create concise summaries of papers, highlighting their main elements.\n", - " OUTPUT\n", - " For a similar but different task, use the advice: \"Summaries should contain one sentence for title, innovation, and main result.\"\n", - " DISTANCE\n", - " 1.8468207628521356\u001b[0m\n", - "\n", "\u001b[33magent\u001b[0m (to user):\n", "\n", "I apologize for the inconvenience caused earlier and thank you for understanding. If you need any further assistance or help with other tasks, please feel free to ask.\n", @@ -1059,19 +925,6 @@ "\n", "\n", "--------------------------------------------------------------------------------\n", - "\u001b[93m\n", - "LOOK FOR RELEVANT MEMOS, AS QUESTION-ANSWER PAIRS\u001b[0m\n", - "\u001b[93m\n", - "THE CLOSEST MEMO IS BEYOND THE THRESHOLD:\u001b[0m\n", - "\u001b[92m\n", - "INPUT-OUTPUT PAIR RETRIEVED FROM VECTOR DATABASE:\n", - " INPUT1\n", - " The task described is to create concise summaries of papers, highlighting their main elements.\n", - " OUTPUT\n", - " For a similar but different task, use the advice: \"Summaries should contain one sentence for title, innovation, and main result.\"\n", - " DISTANCE\n", - " 1.8468207628521356\u001b[0m\n", - "\n", "\u001b[33magent\u001b[0m (to user):\n", "\n", "TERMINATE\n",