langchain/docs/extras/expression_language/interface.ipynb
2023-09-01 08:20:55 -07:00

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"cell_type": "markdown",
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"metadata": {},
"source": [
"# Interface\n",
"\n",
"In an effort to make it as easy as possible to create custom chains, we've implemented a [\"Runnable\"](https://api.python.langchain.com/en/latest/schema/langchain.schema.runnable.Runnable.html#langchain.schema.runnable.Runnable) protocol that most components implement. This is a standard interface with a few different methods, which makes it easy to define custom chains as well as making it possible to invoke them in a standard way. The standard interface exposed includes:\n",
"\n",
"- `stream`: stream back chunks of the response\n",
"- `invoke`: call the chain on an input\n",
"- `batch`: call the chain on a list of inputs\n",
"\n",
"These also have corresponding async methods:\n",
"\n",
"- `astream`: stream back chunks of the response async\n",
"- `ainvoke`: call the chain on an input async\n",
"- `abatch`: call the chain on a list of inputs async\n",
"\n",
"The type of the input varies by component:\n",
"\n",
"| Component | Input Type |\n",
"| --- | --- |\n",
"|Prompt|Dictionary|\n",
"|Retriever|Single string|\n",
"|Model| Single string, list of chat messages or a PromptValue|\n",
"\n",
"The output type also varies by component:\n",
"\n",
"| Component | Output Type |\n",
"| --- | --- |\n",
"| LLM | String |\n",
"| ChatModel | ChatMessage |\n",
"| Prompt | PromptValue |\n",
"| Retriever | List of documents |\n",
"\n",
"Let's take a look at these methods! To do so, we'll create a super simple PromptTemplate + ChatModel chain."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "466b65b3",
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import ChatPromptTemplate\n",
"from langchain.chat_models import ChatOpenAI"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "3c634ef0",
"metadata": {},
"outputs": [],
"source": [
"model = ChatOpenAI()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "d1850a1f",
"metadata": {},
"outputs": [],
"source": [
"prompt = ChatPromptTemplate.from_template(\"tell me a joke about {topic}\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "56d0669f",
"metadata": {},
"outputs": [],
"source": [
"chain = prompt | model"
]
},
{
"cell_type": "markdown",
"id": "daf2b2b2",
"metadata": {},
"source": [
"## Stream"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "bea9639d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Sure, here's a bear-themed joke for you:\n",
"\n",
"Why don't bears wear shoes?\n",
"\n",
"Because they have bear feet!"
]
}
],
"source": [
"for s in chain.stream({\"topic\": \"bears\"}):\n",
" print(s.content, end=\"\", flush=True)"
]
},
{
"cell_type": "markdown",
"id": "cbf1c782",
"metadata": {},
"source": [
"## Invoke"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "470e483f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"AIMessage(content=\"Why don't bears wear shoes?\\n\\nBecause they already have bear feet!\", additional_kwargs={}, example=False)"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chain.invoke({\"topic\": \"bears\"})"
]
},
{
"cell_type": "markdown",
"id": "88f0c279",
"metadata": {},
"source": [
"## Batch"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "9685de67",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[AIMessage(content=\"Why don't bears ever wear shoes?\\n\\nBecause they have bear feet!\", additional_kwargs={}, example=False),\n",
" AIMessage(content=\"Why don't cats play poker in the wild?\\n\\nToo many cheetahs!\", additional_kwargs={}, example=False)]"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chain.batch([{\"topic\": \"bears\"}, {\"topic\": \"cats\"}])"
]
},
{
"cell_type": "markdown",
"id": "2434ab15",
"metadata": {},
"source": [
"You can set the number of concurrent requests by using the `max_concurrency` parameter"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "a08522f6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[AIMessage(content=\"Why don't bears wear shoes?\\n\\nBecause they have bear feet!\", additional_kwargs={}, example=False),\n",
" AIMessage(content=\"Why don't cats play poker in the wild?\\n\\nToo many cheetahs!\", additional_kwargs={}, example=False)]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chain.batch([{\"topic\": \"bears\"}, {\"topic\": \"cats\"}], config={\"max_concurrency\": 5})"
]
},
{
"cell_type": "markdown",
"id": "b960cbfe",
"metadata": {},
"source": [
"## Async Stream"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "ea35eee4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Why don't bears wear shoes?\n",
"\n",
"Because they have bear feet!"
]
}
],
"source": [
"async for s in chain.astream({\"topic\": \"bears\"}):\n",
" print(s.content, end=\"\", flush=True)"
]
},
{
"cell_type": "markdown",
"id": "04cb3324",
"metadata": {},
"source": [
"## Async Invoke"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "ef8c9b20",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"AIMessage(content=\"Sure, here you go:\\n\\nWhy don't bears wear shoes?\\n\\nBecause they have bear feet!\", additional_kwargs={}, example=False)"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"await chain.ainvoke({\"topic\": \"bears\"})"
]
},
{
"cell_type": "markdown",
"id": "3da288d5",
"metadata": {},
"source": [
"## Async Batch"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "eba2a103",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[AIMessage(content=\"Why don't bears wear shoes?\\n\\nBecause they have bear feet!\", additional_kwargs={}, example=False)]"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"await chain.abatch([{\"topic\": \"bears\"}])"
]
},
{
"cell_type": "markdown",
"id": "0a1c409d",
"metadata": {},
"source": [
"## Parallelism\n",
"\n",
"Let's take a look at how LangChain Expression Language support parralel requests as much as possible. For example, when using a RunnableMapping (often written as a dictionary) it executes each element in parralel."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "e3014c7a",
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema.runnable import RunnableMap\n",
"chain1 = ChatPromptTemplate.from_template(\"tell me a joke about {topic}\") | model\n",
"chain2 = ChatPromptTemplate.from_template(\"write a short (2 line) poem about {topic}\") | model\n",
"combined = RunnableMap({\n",
" \"joke\": chain1,\n",
" \"poem\": chain2,\n",
"})"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "08044c0a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 31.7 ms, sys: 8.59 ms, total: 40.3 ms\n",
"Wall time: 1.05 s\n"
]
},
{
"data": {
"text/plain": [
"AIMessage(content=\"Why don't bears like fast food?\\n\\nBecause they can't catch it!\", additional_kwargs={}, example=False)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%time\n",
"chain1.invoke({\"topic\": \"bears\"})"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "22c56804",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 42.9 ms, sys: 10.2 ms, total: 53 ms\n",
"Wall time: 1.93 s\n"
]
},
{
"data": {
"text/plain": [
"AIMessage(content=\"In forest's embrace, bears roam free,\\nSilent strength, nature's majesty.\", additional_kwargs={}, example=False)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%time\n",
"chain2.invoke({\"topic\": \"bears\"})"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "4fff4cbb",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: user 96.3 ms, sys: 20.4 ms, total: 117 ms\n",
"Wall time: 1.1 s\n"
]
},
{
"data": {
"text/plain": [
"{'joke': AIMessage(content=\"Why don't bears wear socks?\\n\\nBecause they have bear feet!\", additional_kwargs={}, example=False),\n",
" 'poem': AIMessage(content=\"In forest's embrace,\\nMajestic bears leave their trace.\", additional_kwargs={}, example=False)}"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%time\n",
"combined.invoke({\"topic\": \"bears\"})"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fab75d1d",
"metadata": {},
"outputs": [],
"source": []
}
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