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Update fallback cases (#14164)
### Description The `RateLimitError` initialization method has changed after openai v1, and the usage of `patch` needs to be changed. ### Twitter handle [lin_bob57617](https://twitter.com/lin_bob57617)
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@ -26,7 +26,7 @@
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 1,
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"id": "d3e893bf",
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"metadata": {},
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"outputs": [],
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@ -44,19 +44,24 @@
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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": 2,
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"id": "dfdd8bf5",
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"metadata": {},
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"outputs": [],
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"source": [
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"from unittest.mock import patch\n",
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"\n",
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"from openai.error import RateLimitError"
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"import httpx\n",
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"from openai import RateLimitError\n",
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"\n",
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"request = httpx.Request(\"GET\", \"/\")\n",
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"response = httpx.Response(200, request=request)\n",
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"error = RateLimitError(\"rate limit\", response=response, body=\"\")"
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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": 5,
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"execution_count": 3,
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"id": "e6fdffc1",
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"metadata": {},
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"outputs": [],
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@ -69,7 +74,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"execution_count": 4,
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"id": "584461ab",
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"metadata": {},
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"outputs": [
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@ -83,7 +88,7 @@
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],
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"source": [
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"# Let's use just the OpenAI LLm first, to show that we run into an error\n",
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"with patch(\"openai.ChatCompletion.create\", side_effect=RateLimitError()):\n",
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"with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
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" try:\n",
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" print(openai_llm.invoke(\"Why did the chicken cross the road?\"))\n",
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" except:\n",
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@ -106,7 +111,7 @@
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],
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"source": [
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"# Now let's try with fallbacks to Anthropic\n",
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"with patch(\"openai.ChatCompletion.create\", side_effect=RateLimitError()):\n",
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"with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
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" try:\n",
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" print(llm.invoke(\"Why did the chicken cross the road?\"))\n",
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" except:\n",
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@ -148,7 +153,7 @@
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" ]\n",
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")\n",
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"chain = prompt | llm\n",
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"with patch(\"openai.ChatCompletion.create\", side_effect=RateLimitError()):\n",
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"with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
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" try:\n",
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" print(chain.invoke({\"animal\": \"kangaroo\"}))\n",
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" except:\n",
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@ -286,7 +291,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.1"
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"version": "3.11.5"
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}
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},
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"nbformat": 4,
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@ -28,7 +28,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"execution_count": 1,
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"id": "d3e893bf",
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"metadata": {},
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"outputs": [],
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@ -46,19 +46,24 @@
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"execution_count": 2,
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"id": "dfdd8bf5",
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"metadata": {},
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"outputs": [],
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"source": [
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"from unittest.mock import patch\n",
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"\n",
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"from openai.error import RateLimitError"
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"import httpx\n",
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"from openai import RateLimitError\n",
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"\n",
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"request = httpx.Request(\"GET\", \"/\")\n",
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"response = httpx.Response(200, request=request)\n",
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"error = RateLimitError(\"rate limit\", response=response, body=\"\")"
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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": 24,
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"execution_count": 3,
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"id": "e6fdffc1",
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"metadata": {},
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"outputs": [],
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@ -71,7 +76,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"execution_count": 4,
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"id": "584461ab",
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"metadata": {},
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"outputs": [
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@ -85,7 +90,7 @@
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],
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"source": [
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"# Let's use just the OpenAI LLm first, to show that we run into an error\n",
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"with patch(\"openai.ChatCompletion.create\", side_effect=RateLimitError()):\n",
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"with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
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" try:\n",
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" print(openai_llm.invoke(\"Why did the chicken cross the road?\"))\n",
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" except:\n",
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@ -108,7 +113,7 @@
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],
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"source": [
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"# Now let's try with fallbacks to Anthropic\n",
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"with patch(\"openai.ChatCompletion.create\", side_effect=RateLimitError()):\n",
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"with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
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" try:\n",
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" print(llm.invoke(\"Why did the chicken cross the road?\"))\n",
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" except:\n",
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@ -150,7 +155,7 @@
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" ]\n",
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")\n",
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"chain = prompt | llm\n",
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"with patch(\"openai.ChatCompletion.create\", side_effect=RateLimitError()):\n",
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"with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
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" try:\n",
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" print(chain.invoke({\"animal\": \"kangaroo\"}))\n",
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" except:\n",
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@ -431,7 +436,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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"version": "3.11.5"
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}
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},
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"nbformat": 4,
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