Update output_parsing.ipynb

Author: bansalkanav

Module 9 - GenAI (LLMs and Prompt Engineering)/6. Building Apps Powered by GenAI using LangChain/1. Introduction to LangChain/4. Output Parsing/output_parsing.ipynb

@@ -43,7 +43,7 @@
  "source": [
  "from langchain_core.output_parsers import CommaSeparatedListOutputParser\n",
  "\n",
- "output_parser = CommaSeparatedListOutputParser()"
+ "csv_output_parser = CommaSeparatedListOutputParser()"
  ]
  },
  {
@@ -66,7 +66,7 @@
  "source": [
  "# As discussed above, lets experiment with get_format_instructions()\n",
  "\n",
- "output_parser.get_format_instructions()"
+ "csv_output_parser.get_format_instructions()"
  ]
  },
  {
@@ -90,23 +90,39 @@
  "example_input = \"Python, DA, SQL, ML, DL\"\n",
  "\n",
  "# using parse() method\n",
- "output_parser.parse(example_input)"
+ "csv_output_parser.parse(example_input)"
  ]
  },
  {
  "cell_type": "code",
- "execution_count": 17,
+ "execution_count": 4,
+ "id": "653b4ff2-bde5-408b-afd6-14fd804399d0",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from langchain_openai import ChatOpenAI\n",
+ "\n",
+ "# Read the API Key\n",
+ "f = open('keys/.openai_api_key.txt')\n",
+ "OPENAI_API_KEY = f.read()\n",
+ "\n",
+ "# Set the OpenAI Key and initialize a ChatModel\n",
+ "chat_model = ChatOpenAI(openai_api_key=OPENAI_API_KEY)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
  "id": "67f5242f-1517-4b77-bb01-2507894a6fbe",
  "metadata": {},
  "outputs": [
  {
  "data": {
  "text/plain": [
- "[SystemMessagePromptTemplate(prompt=PromptTemplate(input_variables=[], template='You are a helpful AI Chef.')),\n",
- " HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=['dish_name', 'output_format_instructions'], template='Give me the ingredients for cooking {dish_name}. {output_format_instructions}'))]"
+ "ChatPromptTemplate(input_variables=['dish_name', 'output_format_instructions'], messages=[SystemMessagePromptTemplate(prompt=PromptTemplate(input_variables=[], template='You are a helpful AI Chef.')), HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=['dish_name', 'output_format_instructions'], template='Give me the ingredients for cooking {dish_name}. {output_format_instructions}'))])"
  ]
  },
- "execution_count": 17,
+ "execution_count": 5,
  "metadata": {},
  "output_type": "execute_result"
  }
@@ -119,81 +135,124 @@
  " (\"human\", \"Give me the ingredients for cooking {dish_name}. {output_format_instructions}\"),\n",
  "])\n",
  "\n",
- "prompt_template.messages"
+ "prompt_template"
  ]
  },
  {
  "cell_type": "code",
- "execution_count": 18,
- "id": "653b4ff2-bde5-408b-afd6-14fd804399d0",
+ "execution_count": 6,
+ "id": "d5a6a423-ae97-4536-a898-ae9322478d22",
  "metadata": {},
  "outputs": [],
  "source": [
- "# Setup API Key\n",
- "\n",
- "f = open('keys/.openai_api_key.txt')\n",
+ "chain = prompt_template | chat_model | csv_output_parser"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "f7fe8e3d-f2b8-4008-ac02-bc00f6bff39d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "['paneer',\n",
+ " 'basmati rice',\n",
+ " 'onions',\n",
+ " 'tomatoes',\n",
+ " 'yogurt',\n",
+ " 'ginger',\n",
+ " 'garlic',\n",
+ " 'green chilies',\n",
+ " 'spices (such as cumin',\n",
+ " 'coriander',\n",
+ " 'turmeric',\n",
+ " 'garam masala)',\n",
+ " 'ghee',\n",
+ " 'vegetable oil',\n",
+ " 'fresh coriander leaves',\n",
+ " 'mint leaves',\n",
+ " 'saffron',\n",
+ " 'water']"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "input = {\"dish_name\": \"paneer biryani\", \"output_format_instructions\": csv_output_parser.get_format_instructions()}\n",
  "\n",
- "OPENAI_API_KEY = f.read()"
+ "chain.invoke(input)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "14516d5e-9cce-46aa-8c3d-5ba65d12f4ef",
+ "metadata": {},
+ "source": [
+ "## **JSONParser**"
  ]
  },
  {
  "cell_type": "code",
- "execution_count": 19,
- "id": "b734ae2c-bb0c-40a7-9e67-586eede34f7a",
+ "execution_count": 8,
+ "id": "f999b0d3-839b-4b60-ae6a-ebf8390008c7",
  "metadata": {},
  "outputs": [],
  "source": [
- "from langchain_openai import ChatOpenAI\n",
+ "from langchain_core.output_parsers import JsonOutputParser\n",
  "\n",
- "# Set the OpenAI Key and initialize a ChatModel\n",
- "chat_model = ChatOpenAI(openai_api_key=OPENAI_API_KEY)"
+ "json_output_parser = JsonOutputParser()"
  ]
  },
  {
  "cell_type": "code",
- "execution_count": 20,
- "id": "d5a6a423-ae97-4536-a898-ae9322478d22",
+ "execution_count": 9,
+ "id": "2c3e7a50-9db7-4941-9c94-da1ac833cda1",
  "metadata": {},
  "outputs": [],
  "source": [
- "chain = prompt_template | chat_model | output_parser"
+ "json_chain = chain = prompt_template | chat_model | json_output_parser"
  ]
  },
  {
  "cell_type": "code",
- "execution_count": 21,
- "id": "f7fe8e3d-f2b8-4008-ac02-bc00f6bff39d",
+ "execution_count": 10,
+ "id": "7ef84474-2fa0-42b4-88b7-990662dad134",
  "metadata": {},
  "outputs": [
  {
  "data": {
  "text/plain": [
- "['paneer',\n",
- " 'basmati rice',\n",
- " 'yogurt',\n",
- " 'onions',\n",
- " 'tomatoes',\n",
- " 'ginger',\n",
- " 'garlic',\n",
- " 'green chilies',\n",
- " 'biryani masala',\n",
- " 'ghee',\n",
- " 'mint leaves',\n",
- " 'coriander leaves',\n",
- " 'saffron',\n",
- " 'milk',\n",
- " 'salt',\n",
- " 'oil',\n",
- " 'spices']"
+ "{'paneerBiryani': {'ingredients': ['1 cup basmati rice',\n",
+ "  '200g paneer, cut into cubes',\n",
+ "  '1 onion, thinly sliced',\n",
+ "  '1 tomato, chopped',\n",
+ "  '1/2 cup yogurt',\n",
+ "  '1/2 cup fried onions',\n",
+ "  '1/4 cup chopped coriander leaves',\n",
+ "  '1/4 cup chopped mint leaves',\n",
+ "  '2 tablespoons biryani masala',\n",
+ "  '1 tablespoon ginger-garlic paste',\n",
+ "  '1 teaspoon red chili powder',\n",
+ "  '1/2 teaspoon turmeric powder',\n",
+ "  '1/2 teaspoon garam masala',\n",
+ "  '2 tablespoons ghee',\n",
+ "  '2 tablespoons oil',\n",
+ "  'Salt to taste',\n",
+ "  'Water']}}"
  ]
  },
- "execution_count": 21,
+ "execution_count": 10,
  "metadata": {},
  "output_type": "execute_result"
  }
  ],
  "source": [
- "input = {\"dish_name\": \"paneer biryani\", \"output_format_instructions\": output_parser.get_format_instructions()}\n",
+ "input = {\"dish_name\": \"paneer biryani\", \"output_format_instructions\": json_output_parser.get_format_instructions()}\n",
  "\n",
  "chain.invoke(input)"
  ]
@@ -210,7 +269,7 @@
  },
  {
  "cell_type": "code",
- "execution_count": 22,
+ "execution_count": 11,
  "id": "072bd02b-c06d-4d05-97b2-f62862e8dcc2",
  "metadata": {},
  "outputs": [],
@@ -222,17 +281,17 @@
  },
  {
  "cell_type": "code",
- "execution_count": 23,
+ "execution_count": 12,
  "id": "00755d45-e38a-4c09-8412-c12eb4540175",
  "metadata": {},
  "outputs": [
  {
  "data": {
  "text/plain": [
- "\"Write a datetime string that matches the following pattern: '%Y-%m-%dT%H:%M:%S.%fZ'.\\n\\nExamples: 0789-09-27T20:15:58.070587Z, 0146-06-12T19:06:59.697461Z, 1178-01-28T21:50:31.033531Z\\n\\nReturn ONLY this string, no other words!\""
+ "\"Write a datetime string that matches the following pattern: '%Y-%m-%dT%H:%M:%S.%fZ'.\\n\\nExamples: 1892-01-30T12:13:48.068611Z, 0561-05-13T02:27:55.160011Z, 1699-05-11T04:40:29.696518Z\\n\\nReturn ONLY this string, no other words!\""
  ]
  },
- "execution_count": 23,
+ "execution_count": 12,
  "metadata": {},
  "output_type": "execute_result"
  }
@@ -245,7 +304,7 @@
  },
  {
  "cell_type": "code",
- "execution_count": 24,
+ "execution_count": 13,
  "id": "3bd3acd4-2cda-4776-a90c-968e87133d9f",
  "metadata": {},
  "outputs": [],
@@ -263,7 +322,7 @@
  },
  {
  "cell_type": "code",
- "execution_count": 25,
+ "execution_count": 14,
  "id": "c18efe6f-b8d4-4839-b8d0-8cfc01fc3587",
  "metadata": {},
  "outputs": [],
@@ -276,7 +335,7 @@
  },
  {
  "cell_type": "code",
- "execution_count": 26,
+ "execution_count": 15,
  "id": "69182c25-2ba5-4ad4-9287-41b31011880f",
  "metadata": {},
  "outputs": [
@@ -286,7 +345,7 @@
  "datetime.datetime(1947, 8, 15, 0, 0)"
  ]
  },
- "execution_count": 26,
+ "execution_count": 15,
  "metadata": {},
  "output_type": "execute_result"
  }