Added community contribution of a 3 way with Gemini
This commit is contained in:
Edward Donner
178
week2/day1.ipynb
178
week2/day1.ipynb
@@ -438,188 +438,18 @@
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},
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{
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"cell_type": "markdown",
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"id": "392d2072-4e5d-424c-b4b4-098d7e3ead2d",
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"id": "3637910d-2c6f-4f19-b1fb-2f916d23f9ac",
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"metadata": {},
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"source": [
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"# And now for a 3 way convo including Gemini"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "eb0c319c-0226-4c6d-99bc-a9167fa86005",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Let's make a conversation between GPT-4o-mini and Claude-3-haiku\n",
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"# We're using cheap versions of models so the costs will be minimal\n",
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"# See the community-contributions folder\n",
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"\n",
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"gpt_model = \"gpt-4o-mini\"\n",
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"claude_model = \"claude-3-haiku-20240307\"\n",
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"\n",
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"gpt_system = \"You are a chatbot who is very argumentative; \\\n",
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"you disagree with anything in the conversation and you challenge everything, in a snarky way.\"\n",
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"\n",
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"claude_system = \"You are a very polite, courteous chatbot. You try to agree with \\\n",
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"everything the other people in the conversation say, or find common ground. If another person is argumentative, \\\n",
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"you try to calm them down and keep chatting.\"\n",
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"\n",
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"gemini_system = \"You are an extremely knowledgeable and know-it-all counselor chatbot. You try to help resolve disagreements, \\\n",
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"and if a person is either too argumentative or too polite, you cannot help but to use quotes from famous psychologists to teach \\\n",
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"your students to be kind yet maintain boundaries.\"\n",
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"\n",
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"gemini_instance = google.generativeai.GenerativeModel(\n",
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" model_name='gemini-1.5-flash',\n",
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" system_instruction=gemini_system\n",
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")"
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"For a great variation with a 3-way bringing Gemini into the conversation!"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "041b1596-a646-4321-a89a-9a51046d9b72",
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"metadata": {},
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"outputs": [],
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"source": [
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"gpt_messages = [\"Hi there\"]\n",
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"claude_messages = [\"Hi\"]\n",
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"gemini_messages = [\"How is everyone?\"]\n",
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"gpt_name = \"Bob\"\n",
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"claude_name = \"Larry\"\n",
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"gemini_name = \"Frank\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "fcd0a633-d506-4b68-8411-46f3fbe34752",
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"metadata": {},
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"outputs": [],
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"source": [
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"def construct_joined_user_msg(msg1, msg1_name, msg2, msg2_name):\n",
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" return msg1_name + ' said: ' + msg1 + '. \\n\\nThen ' + msg2_name + ' said: ' + msg2 + '.'"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4aef8ba5-1d93-4473-8c5f-707a12d8a1cf",
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"metadata": {},
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"outputs": [],
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"source": [
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"def call_gpt(return_msgs=False):\n",
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" messages = [{\"role\": \"system\", \"content\": gpt_system}]\n",
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" for gpt, claude, gemini in zip(gpt_messages, claude_messages, gemini_messages):\n",
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" messages.append({\"role\": \"assistant\", \"content\": gpt})\n",
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" messages.append({\"role\": \"user\", \"content\": construct_joined_user_msg(claude, claude_name, gemini, gemini_name)})\n",
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" if return_msgs: return messages\n",
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" completion = openai.chat.completions.create(\n",
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" model=gpt_model,\n",
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" messages=messages\n",
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" )\n",
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" return completion.choices[0].message.content"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "36365e7a-43b4-4a0d-a241-fff1440509d3",
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"metadata": {},
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"outputs": [],
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"source": [
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"call_gpt(return_msgs=False)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3ebebebe-8255-4ca5-9335-258f93e3181f",
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"metadata": {},
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"outputs": [],
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"source": [
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"def call_claude(return_msgs=False):\n",
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" messages = []\n",
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" for gpt, claude_msg, gemini in zip(gpt_messages, claude_messages, gemini_messages):\n",
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" messages.append({\"role\": \"user\", \"content\": construct_joined_user_msg(gemini, gemini_name, gpt, gpt_name)})\n",
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" messages.append({\"role\": \"assistant\", \"content\": claude_msg})\n",
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" messages.append({\"role\": \"user\", \"content\": gpt_name + \" said \" + gpt_messages[-1]})\n",
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" if return_msgs: return messages\n",
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" message = claude.messages.create(\n",
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" model=claude_model,\n",
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" system=claude_system,\n",
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" messages=messages,\n",
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" max_tokens=500\n",
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" )\n",
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" return message.content[0].text"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b2da7997-a1fe-43fe-9970-4014f665e501",
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"metadata": {},
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"outputs": [],
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"source": [
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"call_claude(return_msgs=False)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "94497894-8cb9-4da4-8671-edede74055f8",
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"metadata": {},
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"outputs": [],
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"source": [
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"def call_gemini(return_msgs=False):\n",
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" messages = []\n",
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" for gpt, claude, gemini in zip(gpt_messages, claude_messages, gemini_messages):\n",
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" messages.append({\"role\": \"user\", \"parts\": construct_joined_user_msg(gpt, gpt_name, claude, claude_name)})\n",
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" messages.append({\"role\": \"model\", \"parts\": gemini})\n",
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" messages.append({\"role\": \"user\", \"parts\": construct_joined_user_msg(gpt_messages[-1], gpt_name, claude_messages[-1], claude_name)})\n",
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" if return_msgs: return messages\n",
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" message = gemini_instance.generate_content(messages)\n",
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" return message.text"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "fddff0fc-0cc3-4473-9d55-effe445ef1ca",
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"metadata": {},
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"outputs": [],
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"source": [
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"call_gemini(return_msgs=False)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1988abf3-1986-40f0-b804-c02b54472b8c",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(f\"GPT:\\n{gpt_messages[0]}\\n\")\n",
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"print(f\"Claude:\\n{claude_messages[0]}\\n\")\n",
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"print(f\"Gemini:\\n{gemini_messages[0]}\\n\")\n",
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"\n",
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"for i in range(5):\n",
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" gpt_next = call_gpt()\n",
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" print(f\"GPT aka {gpt_name}:\\n{gpt_next}\\n\")\n",
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" gpt_messages.append(gpt_next)\n",
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" \n",
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" claude_next = call_claude()\n",
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" print(f\"Claude aka {claude_name}:\\n{claude_next}\\n\")\n",
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" claude_messages.append(claude_next)\n",
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"\n",
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" gemini_next = call_gemini()\n",
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" print(f\"Gemini aka {gemini_name}:\\n{gemini_next}\\n\")\n",
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" gemini_messages.append(gemini_next)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b72906b3-8c4a-4c15-8508-01118d33782a",
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"id": "0d86790a-3a6f-4b18-ab0a-bc6107945a27",
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"metadata": {},
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"outputs": [],
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"source": []
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