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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "raw", | ||
| "id": "bcb4ca40-c3cb-4f23-b09f-4d6c3c46999f", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "---\n", | ||
| "sidebar_position: 2\n", | ||
| "title: Chains\n", | ||
| "---" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "b872d874-ad6e-49b5-9435-66063a64d1a8", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Using an LLM in isolation is fine for simple applications, but more complex applications require chaining LLMs - either with each other or with other components.\n", | ||
| "\n", | ||
| "LangChain provides two high-level frameworks for \"chaining\" components. The legacy approach is to use the `Chain` interface. The updated approach is to use the [LangChain Expression Language (LCEL)](/docs/expression_language/). When building new applications we recommend using LCEL for chain composition. But there are a number of useful, built-in `Chain`'s that we continue to support, so we document both frameworks here. As we'll touch on below, `Chain`'s can also themselves be used in LCEL, so the two are not mutually exclusive." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "6aedf9f6-b53f-4456-90cb-be3cfec04b4e", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## LCEL\n", | ||
| "\n", | ||
| "The most visible part of LCEL is that it provides an intuitive and readable syntax for composition. But more importantly, it also provides first-class support for:\n", | ||
| "* [streaming](/docs/expression_language/interface#stream),\n", | ||
| "* [async calls](/docs/expression_language/interface#async-stream),\n", | ||
| "* [batching](/docs/expression_language/interface#batch),\n", | ||
| "* [parallelization](/docs/expression_language/interface#parallelism),\n", | ||
| "* retries,\n", | ||
| "* [fallbacks](/docs/expression_language/how_to/fallbacks),\n", | ||
| "* tracing,\n", | ||
| "* [and more.](/docs/expression_language/why)\n", | ||
| "\n", | ||
| "As a simple and common example, we can see what it's like to combine a prompt, model and output parser:" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 2, | ||
| "id": "beb2a555-866d-4837-bfe5-988dd4ab09a5", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from langchain.chat_models import ChatAnthropic\n", | ||
| "from langchain.prompts import ChatPromptTemplate\n", | ||
| "from langchain.schema import StrOutputParser\n", | ||
| "\n", | ||
| "model = ChatAnthropic()\n", | ||
| "prompt = ChatPromptTemplate.from_messages([\n", | ||
| " (\"system\", \"You're a very knowledgeable historian who provides accurate and eloquent answers to historical questions.\"),\n", | ||
| " (\"human\", \"{question}\"),\n", | ||
| "])\n", | ||
| "runnable = prompt | model | StrOutputParser()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 3, | ||
| "id": "2c14e850-32fa-4de7-9a9d-9ed0a3fb5e99", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| " Mansa Musa was the emperor of the Mali Empire in West Africa during the 14th century. He accumulated immense wealth through several means:\n", | ||
| "\n", | ||
| "- Gold mining - Mali contained very rich gold deposits, especially in the region of Bambuk. Gold mining and gold trade was a major source of wealth for the empire.\n", | ||
| "\n", | ||
| "- Control of trade routes - Mali dominated the trans-Saharan trade routes connecting West Africa to North Africa and beyond. By taxing the goods that passed through its territory, Mali profited greatly.\n", | ||
| "\n", | ||
| "- Tributary states - Many lands surrounding Mali paid tribute to the empire. This came in the form of gold, slaves, and other valuable resources.\n", | ||
| "\n", | ||
| "- Agriculture - Mali also had extensive agricultural lands irrigated by the Niger River. Surplus food produced could be sold or traded. \n", | ||
| "\n", | ||
| "- Royal monopolies - The emperor claimed monopoly rights over the production and sale of certain goods like salt from the Taghaza mines. This added to his personal wealth.\n", | ||
| "\n", | ||
| "- Inheritance - As an emperor, Mansa Musa inherited a wealthy state. His predecessors had already consolidated lands and accumulated riches which fell to Musa.\n", | ||
| "\n", | ||
| "So in summary, mining, trade, taxes," | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "for chunk in runnable.stream({\"question\": \"How did Mansa Musa accumulate his wealth?\"}):\n", | ||
| " print(chunk, end=\"\", flush=True)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "b09e115c-ca2d-4ec8-9676-5a37bd2692ab", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "For more head to the [LCEL section](/docs/expression_language/)." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "e0cc6c2c-bc35-4415-b894-9ef88014ba33", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## [Legacy] `Chain` interface\n", | ||
| "\n", | ||
| "**Chain**'s are the legacy interface for \"chained\" applications. We define a Chain very generically as a sequence of calls to components, which can include other chains. The base interface is simple:\n", | ||
| "\n", | ||
| "```python\n", | ||
| "class Chain(BaseModel, ABC):\n", | ||
| " \"\"\"Base interface that all chains should implement.\"\"\"\n", | ||
| "\n", | ||
| " memory: BaseMemory\n", | ||
| " callbacks: Callbacks\n", | ||
| "\n", | ||
| " def __call__(\n", | ||
| " self,\n", | ||
| " inputs: Any,\n", | ||
| " return_only_outputs: bool = False,\n", | ||
| " callbacks: Callbacks = None,\n", | ||
| " ) -> Dict[str, Any]:\n", | ||
| " ...\n", | ||
| "```\n", | ||
| "\n", | ||
| "We can recreate the LCEL runnable we made above using the built-in `LLMChain`:" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 4, | ||
| "id": "1026a508-b2c7-4567-8ecf-487628737c16", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "\" Mansa Musa was the emperor of the Mali Empire in West Africa in the early 14th century. He accumulated his vast wealth through several means:\\n\\n- Gold mining - Mali contained very rich gold deposits, especially in the southern part of the empire. Gold mining and trade was a major source of wealth.\\n\\n- Control of trade routes - Mali dominated the trans-Saharan trade routes connecting West Africa to North Africa and beyond. By taxing and controlling this lucrative trade, Mansa Musa reaped great riches.\\n\\n- Tributes from conquered lands - The Mali Empire expanded significantly under Mansa Musa's rule. As new lands were conquered, they paid tribute to the mansa in the form of gold, salt, and slaves.\\n\\n- Inheritance - Mansa Musa inherited a wealthy empire from his predecessor. He continued to build the wealth of Mali through the factors above.\\n\\n- Sound fiscal management - Musa is considered to have managed the empire and its finances very effectively, including keeping taxes reasonable and promoting a robust economy. This allowed him to accumulate and maintain wealth.\\n\\nSo in summary, conquest, trade, taxes, mining, and inheritance all contributed to Mansa Musa growing the M\"" | ||
| ] | ||
| }, | ||
| "execution_count": 4, | ||
| "metadata": {}, | ||
| "output_type": "execute_result" | ||
| } | ||
| ], | ||
| "source": [ | ||
| "from langchain.chains import LLMChain\n", | ||
| "\n", | ||
| "\n", | ||
| "chain = LLMChain(llm=model, prompt=prompt, output_parser=StrOutputParser())\n", | ||
| "chain.run(question=\"How did Mansa Musa accumulate his wealth?\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "c1767c9e-eebd-4e07-9805-cf445920c38d", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "For more specifics check out:\n", | ||
| "- [How-to](/docs/modules/chains/how_to/) for walkthroughs of different chain features\n", | ||
| "- [Foundational](/docs/modules/chains/foundational/) to get acquainted with core building block chains\n", | ||
| "- [Document](/docs/modules/chains/document/) to learn how to incorporate documents into chains\n" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "poetry-venv", | ||
| "language": "python", | ||
| "name": "poetry-venv" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.9.1" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 5 | ||
| } |
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