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feat: standard content, IDs, translators, & normalization (#32569)
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‎docs/docs/how_to/multimodal_inputs.ipynb‎

Lines changed: 17 additions & 17 deletions
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@@ -58,7 +58,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": null,
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"id": "1fcf7b27-1cc3-420a-b920-0420b5892e20",
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"metadata": {},
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"outputs": [
@@ -102,7 +102,7 @@
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" ],\n",
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"}\n",
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"response = llm.invoke([message])\n",
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"print(response.text())"
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"print(response.text)"
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]
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},
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{
@@ -133,7 +133,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": null,
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"id": "99d27f8f-ae78-48bc-9bf2-3cef35213ec7",
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"metadata": {},
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"outputs": [
@@ -163,7 +163,7 @@
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" ],\n",
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"}\n",
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"response = llm.invoke([message])\n",
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"print(response.text())"
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"print(response.text)"
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]
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},
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{
@@ -176,7 +176,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": null,
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"id": "325fb4ca",
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"metadata": {},
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"outputs": [
@@ -198,7 +198,7 @@
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" ],\n",
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"}\n",
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"response = llm.invoke([message])\n",
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"print(response.text())"
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"print(response.text)"
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]
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},
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{
@@ -234,7 +234,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": null,
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"id": "6c1455a9-699a-4702-a7e0-7f6eaec76a21",
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"metadata": {},
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"outputs": [
@@ -284,7 +284,7 @@
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" ],\n",
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"}\n",
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"response = llm.invoke([message])\n",
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"print(response.text())"
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"print(response.text)"
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]
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},
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{
@@ -312,7 +312,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": null,
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"id": "55e1d937-3b22-4deb-b9f0-9e688f0609dc",
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"metadata": {},
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"outputs": [
@@ -342,7 +342,7 @@
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" ],\n",
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"}\n",
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"response = llm.invoke([message])\n",
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"print(response.text())"
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"print(response.text)"
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]
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},
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{
@@ -417,7 +417,7 @@
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" ],\n",
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"}\n",
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"response = llm.invoke([message])\n",
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"print(response.text())"
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"print(response.text)"
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]
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},
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{
@@ -443,7 +443,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": null,
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"id": "83593b9d-a8d3-4c99-9dac-64e0a9d397cb",
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"metadata": {},
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"outputs": [
@@ -488,13 +488,13 @@
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" ],\n",
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"}\n",
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"response = llm.invoke([message])\n",
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"print(response.text())\n",
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"print(response.text)\n",
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"response.usage_metadata"
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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": 3,
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"execution_count": null,
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"id": "9bbf578e-794a-4dc0-a469-78c876ccd4a3",
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"metadata": {},
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"outputs": [
@@ -530,7 +530,7 @@
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" ],\n",
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"}\n",
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"response = llm.invoke([message, response, next_message])\n",
533-
"print(response.text())\n",
533+
"print(response.text)\n",
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"response.usage_metadata"
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]
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},
@@ -600,7 +600,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": null,
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"id": "ae076c9b-ff8f-461d-9349-250f396c9a25",
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"metadata": {},
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"outputs": [
@@ -641,7 +641,7 @@
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" ],\n",
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"}\n",
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"response = llm.invoke([message])\n",
644-
"print(response.text())"
644+
"print(response.text)"
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]
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},
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{

‎docs/docs/how_to/multimodal_prompts.ipynb‎

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@@ -54,7 +54,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": null,
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"id": "5df2e558-321d-4cf7-994e-2815ac37e704",
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"metadata": {},
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"outputs": [
@@ -75,7 +75,7 @@
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"\n",
7676
"chain = prompt | llm\n",
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"response = chain.invoke({\"image_url\": url})\n",
78-
"print(response.text())"
78+
"print(response.text)"
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]
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},
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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": 4,
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"execution_count": null,
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"id": "25e4829e-0073-49a8-9669-9f43e5778383",
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"metadata": {},
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"outputs": [
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" \"cache_type\": \"ephemeral\",\n",
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" }\n",
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")\n",
147-
"print(response.text())"
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"print(response.text)"
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]
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},
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{

‎docs/docs/integrations/chat/anthropic.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": null,
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"id": "30a0af36-2327-4b1d-9ba5-e47cb72db0be",
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"metadata": {},
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"outputs": [
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"response = llm_with_tools.invoke(\n",
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" \"There's a syntax error in my primes.py file. Can you help me fix it?\"\n",
14951495
")\n",
1496-
"print(response.text())\n",
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"print(response.text)\n",
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"response.tool_calls"
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]
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},

‎docs/docs/integrations/chat/bedrock.ipynb‎

Lines changed: 3 additions & 3 deletions
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@@ -243,12 +243,12 @@
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"id": "0ef05abb-9c04-4dc3-995e-f857779644d5",
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"metadata": {},
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"source": [
246-
"You can filter to text using the [.text()](https://python.langchain.com/api_reference/core/messages/langchain_core.messages.ai.AIMessage.html#langchain_core.messages.ai.AIMessage.text) method on the output:"
246+
"You can filter to text using the [.text](https://python.langchain.com/api_reference/core/messages/langchain_core.messages.ai.AIMessage.html#langchain_core.messages.ai.AIMessage.text) property on the output:"
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]
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},
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{
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"cell_type": "code",
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"outputs": [
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],
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"source": [
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"for chunk in llm.stream(messages):\n",
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" print(chunk.text(), end=\"|\")"
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" print(chunk.text, end=\"|\")"
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]
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},
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{

‎docs/docs/integrations/chat/litellm.ipynb‎

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@@ -261,7 +261,7 @@
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},
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{
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"cell_type": "code",
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"id": "c5fac0e9-05a4-4fc1-a3b3-e5bbb24b971b",
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"metadata": {
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"colab": {
@@ -286,7 +286,7 @@
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],
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"source": [
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"async for token in llm.astream(\"Hello, please explain how antibiotics work\"):\n",
289-
" print(token.text(), end=\"\")"
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" print(token.text, end=\"\")"
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]
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},
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{

‎docs/docs/integrations/chat/openai.ipynb‎

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},
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{
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"cell_type": "code",
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"outputs": [
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"llm_with_tools = llm.bind_tools([tool])\n",
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"\n",
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"response = llm_with_tools.invoke(\"What is deep research by OpenAI?\")\n",
863-
"print(response.text())"
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"print(response.text)"
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},
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{
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"id": "073f6010-6b0e-4db6-b2d3-7427c8dec95b",
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}
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"source": [
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},
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{
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"cell_type": "code",
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"id": "b6da5bd6-a44a-4c64-970b-30da26b003d6",
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"metadata": {},
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}
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],
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"source": [
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},
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{
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"cell_type": "code",
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"id": "51d3e4d3-ea78-426c-9205-aecb0937fca7",
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"metadata": {},
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"outputs": [
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"messages = [{\"role\": \"user\", \"content\": first_query}]\n",
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"\n",
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"response = llm_with_tools.invoke(messages)\n",
1431-
"response_text = response.text()\n",
1431+
"response_text = response.text\n",
14321432
"print(f\"{response_text[:100]}... {response_text[-100:]}\")"
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]
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{
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"cell_type": "code",
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"id": "b248bedf-2050-4c17-a90e-3a26eeb1b055",
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"metadata": {},
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"outputs": [
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" ]\n",
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")\n",
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"second_response = llm_with_tools.invoke(messages)\n",
1463-
"print(second_response.text())"
1463+
"print(second_response.text)"
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]
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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": "009e541a-b372-410e-b9dd-608a8052ce09",
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"metadata": {},
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"outputs": [
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" output_version=\"responses/v1\",\n",
15031503
")\n",
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"response = llm.invoke(\"Hi, I'm Bob.\")\n",
1505-
"print(response.text())"
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"print(response.text)"
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]
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{
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"cell_type": "code",
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"id": "393a443a-4c5f-4a07-bc0e-c76e529b35e3",
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"metadata": {},
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"outputs": [
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" \"What is my name?\",\n",
15251525
" previous_response_id=response.response_metadata[\"id\"],\n",
15261526
")\n",
1527-
"print(second_response.text())"
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"print(second_response.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": "8d322f3a-0732-45ab-ac95-dfd4596e0d85",
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"metadata": {},
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"outputs": [
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"response = llm.invoke(\"What is 3^3?\")\n",
16171617
"\n",
16181618
"# Output\n",
1619-
"response.text()"
1619+
"response.text"
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]
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},
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{

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