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https://github.com/james-m-jordan/openai-cookbook.git
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dummy key naming
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parent
c1946c66b7
commit
90863fe6d5
@ -49,7 +49,7 @@
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"%%capture\n",
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"%%capture\n",
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"%env NEWS_API_KEY = YOUR_API_KEY\n"
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"%env NEWS_API_KEY = YOUR_NEWS_API_KEY\n"
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]
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]
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},
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},
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{
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{
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@ -93,7 +93,7 @@
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"\n",
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"\n",
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"def embeddings(input: list[str]) -> list[list[str]]:\n",
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"def embeddings(input: list[str]) -> list[list[str]]:\n",
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" response = openai.Embedding.create(model=\"text-embedding-ada-002\", input=input)\n",
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" response = openai.Embedding.create(model=\"text-embedding-ada-002\", input=input)\n",
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" return [data.embedding for data in response.data]"
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" return [data.embedding for data in response.data]\n"
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]
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]
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},
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},
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{
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{
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@ -113,7 +113,7 @@
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"# User asks a question\n",
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"# User asks a question\n",
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"USER_QUESTION = \"Who won the NBA championship? And who was the MVP? Tell me a bit about the last game.\""
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"USER_QUESTION = \"Who won the NBA championship? And who was the MVP? Tell me a bit about the last game.\"\n"
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]
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]
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},
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},
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{
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{
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@ -179,7 +179,7 @@
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"# Let's include the original question as well for good measure\n",
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"# Let's include the original question as well for good measure\n",
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"queries.append(USER_QUESTION)\n",
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"queries.append(USER_QUESTION)\n",
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"\n",
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"\n",
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"queries"
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"queries\n"
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]
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]
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},
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},
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{
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{
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@ -282,7 +282,7 @@
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" print(\"Title:\", article[\"title\"])\n",
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" print(\"Title:\", article[\"title\"])\n",
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" print(\"Description:\", article[\"description\"])\n",
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" print(\"Description:\", article[\"description\"])\n",
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" print(\"Content:\", article[\"content\"][0:100] + \"...\")\n",
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" print(\"Content:\", article[\"content\"][0:100] + \"...\")\n",
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" print()\n"
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" print()"
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]
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]
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},
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},
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{
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{
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@ -326,7 +326,7 @@
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"\n",
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"\n",
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"hypothetical_answer = json_gpt(HA_INPUT)[\"hypotheticalAnswer\"]\n",
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"hypothetical_answer = json_gpt(HA_INPUT)[\"hypotheticalAnswer\"]\n",
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"\n",
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"\n",
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"hypothetical_answer\n"
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"hypothetical_answer"
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]
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]
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},
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},
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{
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{
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@ -376,7 +376,7 @@
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"for article_embedding in article_embeddings:\n",
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"for article_embedding in article_embeddings:\n",
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" cosine_similarities.append(dot(hypothetical_answer_embedding, article_embedding))\n",
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" cosine_similarities.append(dot(hypothetical_answer_embedding, article_embedding))\n",
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"\n",
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"\n",
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"cosine_similarities[0:10]\n"
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"cosine_similarities[0:10]"
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]
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]
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},
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},
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{
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{
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@ -440,7 +440,7 @@
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" print(\"Description:\", article[\"description\"])\n",
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" print(\"Description:\", article[\"description\"])\n",
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" print(\"Content:\", article[\"content\"][0:100] + \"...\")\n",
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" print(\"Content:\", article[\"content\"][0:100] + \"...\")\n",
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" print(\"Score:\", score)\n",
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" print(\"Score:\", score)\n",
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" print()\n"
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" print()"
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]
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]
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},
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},
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{
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{
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@ -500,7 +500,7 @@
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"for chunk in completion:\n",
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"for chunk in completion:\n",
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" text += chunk.choices[0].delta.get(\"content\", \"\")\n",
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" text += chunk.choices[0].delta.get(\"content\", \"\")\n",
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" display.clear_output(wait=True)\n",
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" display.clear_output(wait=True)\n",
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" display.display(display.Markdown(text))"
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" display.display(display.Markdown(text))\n"
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]
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]
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}
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}
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],
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],
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