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langchain/docs/modules/prompts/getting_started.ipynb

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"# Getting Started\n",
"\n",
"This section contains everything related to prompts. A prompt is the value passed into the Language Model. This value can either be a string (for LLMs) or a list of messages (for Chat Models).\n",
"\n",
"The data types of these prompts are rather simple, but their construction is anything but. Value props of LangChain here include:\n",
"\n",
"- A standard interface for string prompts and message prompts\n",
"- A standard (to get started) interface for string prompt templates and message prompt templates\n",
"- Example Selectors: methods for inserting examples into the prompt for the language model to follow\n",
"- OutputParsers: methods for inserting instructions into the prompt as the format in which the language model should output information, as well as methods for then parsing that string output into a format.\n",
"\n",
"We have in depth documentation for specific types of string prompts, specific types of chat prompts, example selectors, and output parsers.\n",
"\n",
"Here, we cover a quick-start for a standard interface for getting started with simple prompts."
]
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{
"cell_type": "markdown",
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"source": [
"## PromptTemplates\n",
"\n",
"PromptTemplates are responsible for constructing a prompt value. These PromptTemplates can do things like formatting, example selection, and more. At a high level, these are basically objects that expose a `format_prompt` method for constructing a prompt. Under the hood, ANYTHING can happen."
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "7ce42639",
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import PromptTemplate, ChatPromptTemplate"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "5a178697",
"metadata": {},
"outputs": [],
"source": [
"string_prompt = PromptTemplate.from_template(\"tell me a joke about {subject}\")"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "f4ef6d6b",
"metadata": {},
"outputs": [],
"source": [
"chat_prompt = ChatPromptTemplate.from_template(\"tell me a joke about {subject}\")"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "5f16c8f1",
"metadata": {},
"outputs": [],
"source": [
"string_prompt_value = string_prompt.format_prompt(subject=\"soccer\")"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "863755ea",
"metadata": {},
"outputs": [],
"source": [
"chat_prompt_value = chat_prompt.format_prompt(subject=\"soccer\")"
]
},
{
"cell_type": "markdown",
"id": "8b3d8511",
"metadata": {},
"source": [
"## `to_string`\n",
"\n",
"This is what is called when passing to an LLM (which expects raw text)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "1964a8a0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'tell me a joke about soccer'"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"string_prompt_value.to_string()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "bf6c94e9",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'Human: tell me a joke about soccer'"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chat_prompt_value.to_string()"
]
},
{
"cell_type": "markdown",
"id": "c0825af8",
"metadata": {},
"source": [
"## `to_messages`\n",
"\n",
"This is what is called when passing to ChatModel (which expects a list of messages)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "e4da46f3",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[HumanMessage(content='tell me a joke about soccer', additional_kwargs={}, example=False)]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"string_prompt_value.to_messages()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "eae84b88",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[HumanMessage(content='tell me a joke about soccer', additional_kwargs={}, example=False)]"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chat_prompt_value.to_messages()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a34fa440",
"metadata": {},
"outputs": [],
"source": []
}
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