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Merge pull request #33 from aurelio-labs/luca/fix-on-embeddings-check
Fix for embeddings
2 parents 45ce599 + 8011844 commit bfbf10b

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5 files changed

+70
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‎.gitignore

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@@ -17,3 +17,4 @@ mac.env
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.coverage
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.coverage.*
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.pytest_cache
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test.py

‎docs/examples/function_calling.ipynb

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},
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{
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"cell_type": "code",
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"execution_count": 213,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%reload_ext dotenv\n",
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"%dotenv"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# OpenAI\n",
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"import os\n",
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"import openai\n",
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"from semantic_router.utils.logger import logger\n",
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"\n",
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},
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{
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"cell_type": "code",
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"execution_count": 214,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import requests\n",
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"\n",
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"# Docs https://huggingface.co/docs/transformers/main_classes/text_generation\n",
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"HF_API_TOKEN = os.environ[\"HF_API_TOKEN\"]\n",
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"HF_API_TOKEN = os.getenv(\"HF_API_TOKEN\")\n",
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"\n",
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"\n",
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"def llm_mistral(prompt: str) -> str:\n",
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},
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{
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"cell_type": "code",
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"execution_count": 217,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"Set up the routing layer"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"from semantic_router.schema import Route\n",
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"from semantic_router.encoders import CohereEncoder, OpenAIEncoder\n",
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"from semantic_router.layer import RouteLayer\n",
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"from semantic_router.utils.logger import logger\n",
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"\n",
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"\n",
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"def create_router(routes: list[dict]) -> RouteLayer:\n",
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" logger.info(\"Creating route layer...\")\n",
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" encoder = OpenAIEncoder"
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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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"\n",
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"def create_router(routes: list[dict]) -> RouteLayer:\n",
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" logger.info(\"Creating route layer...\")\n",
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" encoder = CohereEncoder()\n",
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" encoder = OpenAIEncoder()\n",
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"\n",
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" route_list: list[Route] = []\n",
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" for route in routes:\n",
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},
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{
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"cell_type": "code",
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"execution_count": 219,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "code",
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"execution_count": 220,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"def get_time(location: str) -> str:\n",
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" \"\"\"Useful to get the time in a specific location\"\"\"\n",
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" print(f\"Calling `get_time` function with location: {location}\")\n",
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" return \"get_time\"\n",
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"\n",
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"\n",
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"def get_news(category: str, country: str) -> str:\n",
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" \"\"\"Useful to get the news in a specific country\"\"\"\n",
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" print(\n",
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" f\"Calling `get_news` function with category: {category} and country: {country}\"\n",
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" )\n",
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" return \"get_news\"\n",
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"\n",
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"\n",
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"# Registering functions to the router\n",
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"route_get_time = generate_route(get_time)\n",
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"route_get_news = generate_route(get_news)\n",
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"\n",
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"routes = [route_get_time, route_get_news]\n",
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"router = create_router(routes)\n",
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"\n",
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"# Tools\n",
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"tools = [get_time, get_news]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[32m2023-12-15 11:41:54 INFO semantic_router.utils.logger Extracting parameters...\u001b[0m\n",
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"\u001b[32m2023-12-15 11:41:54 INFO semantic_router.utils.logger Calling Mistral model\u001b[0m\n",
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"\u001b[32m2023-12-15 11:41:55 INFO semantic_router.utils.logger AI message: \n",
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" {\n",
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" 'location': 'Stockholm'\n",
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" }\u001b[0m\n",
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"\u001b[32m2023-12-15 11:41:55 INFO semantic_router.utils.logger Extracted parameters: {'location': 'Stockholm'}\u001b[0m\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"parameters: {'location': 'Stockholm'}\n",
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"Calling `get_time` function with location: Stockholm\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[32m2023-12-15 11:41:55 INFO semantic_router.utils.logger Extracting parameters...\u001b[0m\n",
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"\u001b[32m2023-12-15 11:41:55 INFO semantic_router.utils.logger Calling Mistral model\u001b[0m\n",
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"\u001b[32m2023-12-15 11:41:56 INFO semantic_router.utils.logger AI message: \n",
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" {\n",
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" 'category': 'tech',\n",
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" 'country': 'Lithuania'\n",
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" }\u001b[0m\n",
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"\u001b[32m2023-12-15 11:41:56 INFO semantic_router.utils.logger Extracted parameters: {'category': 'tech', 'country': 'Lithuania'}\u001b[0m\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"parameters: {'category': 'tech', 'country': 'Lithuania'}\n",
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"Calling `get_news` function with category: tech and country: Lithuania\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[33m2023-12-15 11:41:57 WARNING semantic_router.utils.logger No function found\u001b[0m\n",
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"\u001b[32m2023-12-15 11:41:57 INFO semantic_router.utils.logger Calling Mistral model\u001b[0m\n",
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"\u001b[32m2023-12-15 11:41:57 INFO semantic_router.utils.logger AI message: How can I help you today?\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"' How can I help you today?'"
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]
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},
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"execution_count": 220,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"call(query=\"What is the time in Stockholm?\", functions=tools, router=router)\n",
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"call(query=\"What is the tech news in the Lithuania?\", functions=tools, router=router)\n",
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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": "3.11.3"
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"version": "3.11.5"
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}
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},
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"nbformat": 4,

‎pyproject.toml

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[tool.poetry]
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name = "semantic-router"
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version = "0.0.9"
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version = "0.0.10"
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description = "Super fast semantic router for AI decision making"
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authors = [
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"James Briggs <james@aurelio.ai>",

‎semantic_router/encoders/openai.py

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@@ -36,7 +36,7 @@ def __call__(self, docs: list[str]) -> list[list[float]]:
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try:
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logger.info(f"Encoding {len(docs)} documents...")
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embeds = self.client.embeddings.create(input=docs, model=self.name)
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if isinstance(embeds, dict) and "data" in embeds:
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if "data" in embeds:
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break
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except OpenAIError as e:
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sleep(2**j)

‎tests/unit/encoders/test_openai.py

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with pytest.raises(ValueError) as e:
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openai_encoder(["test document"])
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assert "OpenAI API call failed. Error: Non-OpenAIError" in str(e.value)
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def test_openai_encoder_call_successful_retry(self, openai_encoder, mocker):

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