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236 lines
8.2 KiB
Plaintext
236 lines
8.2 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "raw",
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"id": "fe63ffaf",
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"metadata": {},
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"source": [
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"---\n",
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"sidebar_position: 2\n",
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"keywords: [RunnableBinding, LCEL]\n",
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"id": "711752cb-4f15-42a3-9838-a0c67f397771",
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"metadata": {},
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"source": [
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"# How to add default invocation args to a Runnable\n",
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"\n",
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":::info Prerequisites\n",
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"\n",
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"This guide assumes familiarity with the following concepts:\n",
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"- [LangChain Expression Language (LCEL)](/docs/concepts/#langchain-expression-language)\n",
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"- [Chaining runnables](/docs/how_to/sequence/)\n",
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"- [Tool calling](/docs/how_to/tool_calling)\n",
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"\n",
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":::\n",
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"\n",
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"Sometimes we want to invoke a [`Runnable`](https://api.python.langchain.com/en/latest/runnables/langchain_core.runnables.base.Runnable.html) within a [RunnableSequence](https://api.python.langchain.com/en/latest/runnables/langchain_core.runnables.base.RunnableSequence.html) with constant arguments that are not part of the output of the preceding Runnable in the sequence, and which are not part of the user input. We can use the [`Runnable.bind()`](https://api.python.langchain.com/en/latest/runnables/langchain_core.runnables.base.Runnable.html#langchain_core.runnables.base.Runnable.bind) method to set these arguments ahead of time.\n",
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"\n",
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"## Binding stop sequences\n",
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"\n",
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"Suppose we have a simple prompt + model chain:"
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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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"id": "c5dad8b5",
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"metadata": {},
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"outputs": [],
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"source": [
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"# | output: false\n",
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"# | echo: false\n",
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"\n",
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"%pip install -qU langchain langchain_openai\n",
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"\n",
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"import os\n",
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"from getpass import getpass\n",
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"\n",
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"os.environ[\"OPENAI_API_KEY\"] = getpass()"
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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": 2,
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"id": "f3fdf86d-155f-4587-b7cd-52d363970c1d",
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"metadata": {},
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"outputs": [
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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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"EQUATION: x^3 + 7 = 12\n",
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"\n",
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"SOLUTION: \n",
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"Subtract 7 from both sides:\n",
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"x^3 = 5\n",
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"\n",
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"Take the cube root of both sides:\n",
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"x = ∛5\n"
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]
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}
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],
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"source": [
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"from langchain_core.output_parsers import StrOutputParser\n",
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"from langchain_core.prompts import ChatPromptTemplate\n",
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"from langchain_core.runnables import RunnablePassthrough\n",
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"from langchain_openai import ChatOpenAI\n",
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"\n",
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"prompt = ChatPromptTemplate.from_messages(\n",
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" [\n",
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" (\n",
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" \"system\",\n",
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" \"Write out the following equation using algebraic symbols then solve it. Use the format\\n\\nEQUATION:...\\nSOLUTION:...\\n\\n\",\n",
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" ),\n",
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" (\"human\", \"{equation_statement}\"),\n",
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" ]\n",
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")\n",
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"\n",
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"model = ChatOpenAI(temperature=0)\n",
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"\n",
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"runnable = (\n",
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" {\"equation_statement\": RunnablePassthrough()} | prompt | model | StrOutputParser()\n",
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")\n",
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"\n",
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"print(runnable.invoke(\"x raised to the third plus seven equals 12\"))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "929c9aba-a4a0-462c-adac-2cfc2156e117",
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"metadata": {},
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"source": [
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"and want to call the model with certain `stop` words so that we shorten the output as is useful in certain types of prompting techniques. While we can pass some arguments into the constructor, other runtime args use the `.bind()` method as follows:"
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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": 3,
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"id": "32e0484a-78c5-4570-a00b-20d597245a96",
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"metadata": {},
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"outputs": [
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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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"EQUATION: x^3 + 7 = 12\n",
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"\n",
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"\n"
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]
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}
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],
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"source": [
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"runnable = (\n",
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" {\"equation_statement\": RunnablePassthrough()}\n",
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" | prompt\n",
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" | model.bind(stop=\"SOLUTION\")\n",
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" | StrOutputParser()\n",
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")\n",
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"\n",
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"print(runnable.invoke(\"x raised to the third plus seven equals 12\"))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f07d7528-9269-4d6f-b12e-3669592a9e03",
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"metadata": {},
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"source": [
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"What you can bind to a Runnable will depend on the extra parameters you can pass when invoking it.\n",
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"\n",
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"## Attaching OpenAI tools\n",
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"\n",
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"Another common use-case is tool calling. While you should generally use the [`.bind_tools()`](/docs/how_to/tool_calling) method for tool-calling models, you can also bind provider-specific args directly if you want lower level control:"
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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": 4,
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"id": "2cdeeb4c-0c1f-43da-bd58-4f591d9e0671",
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"metadata": {},
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"outputs": [],
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"source": [
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"tools = [\n",
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" {\n",
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" \"type\": \"function\",\n",
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" \"function\": {\n",
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" \"name\": \"get_current_weather\",\n",
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" \"description\": \"Get the current weather in a given location\",\n",
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" \"parameters\": {\n",
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" \"type\": \"object\",\n",
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" \"properties\": {\n",
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" \"location\": {\n",
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" \"type\": \"string\",\n",
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" \"description\": \"The city and state, e.g. San Francisco, CA\",\n",
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" },\n",
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" \"unit\": {\"type\": \"string\", \"enum\": [\"celsius\", \"fahrenheit\"]},\n",
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" },\n",
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" \"required\": [\"location\"],\n",
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" },\n",
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" },\n",
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" }\n",
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"]"
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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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"id": "2b65beab-48bb-46ff-a5a4-ef8ac95a513c",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_z0OU2CytqENVrRTI6T8DkI3u', 'function': {'arguments': '{\"location\": \"San Francisco, CA\", \"unit\": \"celsius\"}', 'name': 'get_current_weather'}, 'type': 'function'}, {'id': 'call_ft96IJBh0cMKkQWrZjNg4bsw', 'function': {'arguments': '{\"location\": \"New York, NY\", \"unit\": \"celsius\"}', 'name': 'get_current_weather'}, 'type': 'function'}, {'id': 'call_tfbtGgCLmuBuWgZLvpPwvUMH', 'function': {'arguments': '{\"location\": \"Los Angeles, CA\", \"unit\": \"celsius\"}', 'name': 'get_current_weather'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 84, 'prompt_tokens': 85, 'total_tokens': 169}, 'model_name': 'gpt-3.5-turbo-1106', 'system_fingerprint': 'fp_77a673219d', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-d57ad5fa-b52a-4822-bc3e-74f838697e18-0', tool_calls=[{'name': 'get_current_weather', 'args': {'location': 'San Francisco, CA', 'unit': 'celsius'}, 'id': 'call_z0OU2CytqENVrRTI6T8DkI3u'}, {'name': 'get_current_weather', 'args': {'location': 'New York, NY', 'unit': 'celsius'}, 'id': 'call_ft96IJBh0cMKkQWrZjNg4bsw'}, {'name': 'get_current_weather', 'args': {'location': 'Los Angeles, CA', 'unit': 'celsius'}, 'id': 'call_tfbtGgCLmuBuWgZLvpPwvUMH'}])"
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]
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},
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"execution_count": 5,
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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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"model = ChatOpenAI(model=\"gpt-3.5-turbo-1106\").bind(tools=tools)\n",
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"model.invoke(\"What's the weather in SF, NYC and LA?\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "095001f7",
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"metadata": {},
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"source": [
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"## Next steps\n",
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"\n",
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"You now know how to bind runtime arguments to a Runnable.\n",
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"\n",
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"To learn more, see the other how-to guides on runnables in this section, including:\n",
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"\n",
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"- [Using configurable fields and alternatives](/docs/how_to/configure) to change parameters of a step in a chain, or even swap out entire steps, at runtime"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.9.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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