fix: update old hybrid example

e8f00a38 · jamescalam · e365910a · e8f00a38
Commit e8f00a38 authored 4 months ago by jamescalam
--- a/docs/examples/hybrid-layer.ipynb
+++ b/docs/examples/hybrid-layer.ipynb
@@ -11,7 +11,9 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "The Hybrid Layer in the Semantic Router library can improve making performance particularly for niche use-cases that contain specific terminology, such as finance or medical. It helps us provide more importance to making based on the keywords contained in our utterances and user queries.\n"
+    "The `HybridRouter` in the Semantic Router library can improve making performance particularly for niche use-cases that contain specific terminology, such as finance or medical.\n",
+    "\n",
+    "It helps us provide more importance to making based on the keywords contained in our utterances and user queries."
   ]
  },
  {
@@ -34,7 +36,7 @@
   "metadata": {},
   "outputs": [],
   "source": [
-    "#!pip install -qU semantic-router==0.0.11"
+    "#!pip install -qU semantic-router==0.1.0.dev2"
   ]
  },
  {
@@ -46,14 +48,14 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
-      "c:\\Users\\Siraj\\Documents\\Personal\\Work\\Aurelio\\Virtual Environments\\semantic_router_3\\Lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "/Users/jamesbriggs/Library/Caches/pypoetry/virtualenvs/semantic-router-C1zr4a78-py3.12/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
@@ -83,28 +85,10 @@
  },
  {
   "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
-    "chitchat = Route(\n",
-    "    name=\"chitchat\",\n",
-    "    utterances=[\n",
-    "        \"how's the weather today?\",\n",
-    "        \"how are things going?\",\n",
-    "        \"lovely weather today\",\n",
-    "        \"the weather is horrendous\",\n",
-    "        \"let's go to the chippy\",\n",
-    "    ],\n",
-    ")\n",
-    "\n",
    "chitchat = Route(\n",
    "    name=\"chitchat\",\n",
    "    utterances=[\n",
@@ -133,14 +117,14 @@
   "outputs": [],
   "source": [
    "import os\n",
-    "from semantic_router.encoders import CohereEncoder, BM25Encoder, TfidfEncoder\n",
+    "from semantic_router.encoders import OpenAIEncoder, TfidfEncoder\n",
    "from getpass import getpass\n",
    "\n",
-    "os.environ[\"COHERE_API_KEY\"] = os.environ[\"COHERE_API_KEY\"] or getpass(\n",
+    "os.environ[\"OPENAI_API_KEY\"] = os.getenv(\"OPENAI_API_KEY\") or getpass(\n",
-    "    \"Enter Cohere API Key: \"\n",
+    "    \"Enter OpenAI API Key: \"\n",
    ")\n",
    "\n",
-    "dense_encoder = CohereEncoder()\n",
+    "dense_encoder = OpenAIEncoder()\n",
    "# sparse_encoder = BM25Encoder()\n",
    "sparse_encoder = TfidfEncoder()"
   ]
@@ -154,63 +138,67 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
-      "\u001b[32m2024-05-07 21:15:31 INFO semantic_router.utils.logger Creating embeddings for all routes...\u001b[0m\n"
+      "\u001b[32m2024-11-24 00:37:14 INFO semantic_router.utils.logger Downloading and initializing default sBM25 model parameters.\u001b[0m\n",
+      "\u001b[32m2024-11-24 00:37:22 INFO semantic_router.utils.logger Encoding route politics\u001b[0m\n",
+      "\u001b[32m2024-11-24 00:37:23 INFO semantic_router.utils.logger Encoding route chitchat\u001b[0m\n"
     ]
    }
   ],
   "source": [
-    "from semantic_router.hybrid_layer import HybridRouteLayer\n",
+    "from semantic_router.routers import HybridRouter\n",
    "\n",
-    "dl = HybridRouteLayer(\n",
+    "router = HybridRouter(\n",
-    "    encoder=dense_encoder, sparse_encoder=sparse_encoder, routes=routes\n",
+    "    encoder=dense_encoder,\n",
+    "    sparse_encoder=sparse_encoder,\n",
+    "    routes=routes\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
-       "'politics'"
+       "RouteChoice(name='politics', function_call=None, similarity_score=1.1909239963848142)"
      ]
     },
-     "execution_count": 7,
+     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
-    "dl(\"don't you love politics?\")"
+    "router(\"don't you love politics?\")"
   ]
  },
  {
   "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
-       "'chitchat'"
+       "RouteChoice(name='chitchat', function_call=None, similarity_score=2.0)"
      ]
     },
-     "execution_count": 8,
+     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
-    "dl(\"how's the weather today?\")"
+    "router(\"how's the weather today?\")"
   ]
  },
  {
@@ -237,7 +225,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.12.7"
  }
 },
 "nbformat": 4,

 %% Cell type:markdown id: tags:
 # Semantic Router: Hybrid Layer
 %% Cell type:markdown id: tags:
-The Hybrid Layer in the Semantic Router library can improve making performance particularly for niche use-cases that contain specific terminology, such as finance or medical. It helps us provide more importance to making based on the keywords contained in our utterances and user queries.
+The `HybridRouter` in the Semantic Router library can improve making performance particularly for niche use-cases that contain specific terminology, such as finance or medical.
+It helps us provide more importance to making based on the keywords contained in our utterances and user queries.
 %% Cell type:markdown id: tags:
 ## Getting Started
 %% Cell type:markdown id: tags:
 We start by installing the library:
 %% Cell type:code id: tags:
 ``` python
-#!pip install -qU semantic-router==0.0.11
+#!pip install -qU semantic-router==0.1.0.dev2
 ```
 %% Cell type:markdown id: tags:
 We start by defining a dictionary mapping s to example phrases that should trigger those s.
 %% Cell type:code id: tags:
 ``` python
 from semantic_router.route import Route
 politics = Route(
    name="politics",
    utterances=[
        "isn't politics the best thing ever",
        "why don't you tell me about your political opinions",
        "don't you just love the president",
        "don't you just hate the president",
        "they're going to destroy this country!",
        "they will save the country!",
    ],
 )
 ```
 %% Output
-    c:\Users\Siraj\Documents\Personal\Work\Aurelio\Virtual Environments\semantic_router_3\Lib\site-packages\tqdm\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
+    /Users/jamesbriggs/Library/Caches/pypoetry/virtualenvs/semantic-router-C1zr4a78-py3.12/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
      from .autonotebook import tqdm as notebook_tqdm
 %% Cell type:markdown id: tags:
 Let's define another for good measure:
 %% Cell type:code id: tags:
 ``` python
-```
-%% Cell type:code id: tags:
-``` python
-chitchat = Route(
-    name="chitchat",
-    utterances=[
-        "how's the weather today?",
-        "how are things going?",
-        "lovely weather today",
-        "the weather is horrendous",
-        "let's go to the chippy",
-    ],
-)
 chitchat = Route(
    name="chitchat",
    utterances=[
        "how's the weather today?",
        "how are things going?",
        "lovely weather today",
        "the weather is horrendous",
        "let's go to the chippy",
    ],
 )
 routes = [politics, chitchat]
 ```
 %% Cell type:markdown id: tags:
 Now we initialize our embedding model:
 %% Cell type:code id: tags:
 ``` python
 import os
-from semantic_router.encoders import CohereEncoder, BM25Encoder, TfidfEncoder
+from semantic_router.encoders import OpenAIEncoder, TfidfEncoder
 from getpass import getpass
-os.environ["COHERE_API_KEY"] = os.environ["COHERE_API_KEY"] or getpass(
+os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY") or getpass(
-    "Enter Cohere API Key: "
+    "Enter OpenAI API Key: "
 )
-dense_encoder = CohereEncoder()
+dense_encoder = OpenAIEncoder()
 # sparse_encoder = BM25Encoder()
 sparse_encoder = TfidfEncoder()
 ```
 %% Cell type:markdown id: tags:
 Now we define the `RouteLayer`. When called, the route layer will consume text (a query) and output the category (`Route`) it belongs to — to initialize a `RouteLayer` we need our `encoder` model and a list of `routes`.
 %% Cell type:code id: tags:
 ``` python
-from semantic_router.hybrid_layer import HybridRouteLayer
+from semantic_router.routers import HybridRouter
-dl = HybridRouteLayer(
+router = HybridRouter(
-    encoder=dense_encoder, sparse_encoder=sparse_encoder, routes=routes
+    encoder=dense_encoder,
+    sparse_encoder=sparse_encoder,
+    routes=routes
 )
 ```
 %% Output
-    [32m2024-05-07 21:15:31 INFO semantic_router.utils.logger Creating embeddings for all routes...[0m
+    [32m2024-11-24 00:37:14 INFO semantic_router.utils.logger Downloading and initializing default sBM25 model parameters.[0m
+    [32m2024-11-24 00:37:22 INFO semantic_router.utils.logger Encoding route politics[0m
+    [32m2024-11-24 00:37:23 INFO semantic_router.utils.logger Encoding route chitchat[0m
 %% Cell type:code id: tags:
 ``` python
-dl("don't you love politics?")
+router("don't you love politics?")
 ```
 %% Output
-    'politics'
+    RouteChoice(name='politics', function_call=None, similarity_score=1.1909239963848142)
 %% Cell type:code id: tags:
 ``` python
-dl("how's the weather today?")
+router("how's the weather today?")
 ```
 %% Output
-    'chitchat'
+    RouteChoice(name='chitchat', function_call=None, similarity_score=2.0)
 %% Cell type:markdown id: tags:
 ---