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docs: update cohere chat integration (#15562)
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Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
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@baskaryan @hwchase17
baskaryan and hwchase17 committed Jan 6, 2024
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191 changes: 141 additions & 50 deletions docs/docs/integrations/chat/cohere.ipynb
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Expand Up @@ -15,39 +15,107 @@
"id": "bf733a38-db84-4363-89e2-de6735c37230",
"metadata": {},
"source": [
"# ChatCohere\n",
"# Cohere\n",
"\n",
"This notebook covers how to get started with Cohere chat models."
"This notebook covers how to get started with [Cohere chat models](https://cohere.com/chat).\n",
"\n",
"Head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.cohere.ChatCohere.html) for detailed documentation of all attributes and methods."
]
},
{
"cell_type": "markdown",
"id": "3607d67e-e56c-4102-bbba-df2edc0e109e",
"metadata": {},
"source": [
"## Setup\n",
"\n",
"The integration lives in the `langchain-community` package. We also need to install the `cohere` package itself. We can install these with:\n",
"\n",
"```bash\n",
"pip install -U langchain-community cohere\n",
"```\n",
"\n",
"We'll also need to get a [Cohere API key](https://cohere.com/) and set the `COHERE_API_KEY` environment variable:"
]
},
{
"cell_type": "code",
"execution_count": 54,
"execution_count": 6,
"id": "2108b517-1e8d-473d-92fa-4f930e8072a7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"········\n"
]
}
],
"source": [
"import getpass\n",
"import os\n",
"\n",
"os.environ[\"COHERE_API_KEY\"] = getpass.getpass()"
]
},
{
"cell_type": "markdown",
"id": "cf690fbb",
"metadata": {},
"source": [
"It's also helpful (but not needed) to set up [LangSmith](https://smith.langchain.com/) for best-in-class observability"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "7f11de02",
"metadata": {},
"outputs": [],
"source": [
"# os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
"# os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass()"
]
},
{
"cell_type": "markdown",
"id": "4c26754b-b3c9-4d93-8f36-43049bd943bf",
"metadata": {},
"source": [
"## Usage\n",
"\n",
"ChatCohere supports all [ChatModel](/docs/modules/model_io/chat/) functionality:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "d4a7c55d-b235-4ca4-a579-c90cc9570da9",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import ChatCohere"
"from langchain_community.chat_models import ChatCohere\n",
"from langchain_core.messages import HumanMessage"
]
},
{
"cell_type": "code",
"execution_count": 55,
"execution_count": 2,
"id": "70cf04e8-423a-4ff6-8b09-f11fb711c817",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"chat = ChatCohere()"
"chat = ChatCohere(model=\"command\", max_tokens=256, temperature=0.75)"
]
},
{
"cell_type": "code",
"execution_count": 56,
"execution_count": 3,
"id": "8199ef8f-eb8b-4253-9ea0-6c24a013ca4c",
"metadata": {
"tags": []
Expand All @@ -59,41 +127,43 @@
"AIMessage(content=\"Who's there?\")"
]
},
"execution_count": 56,
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"messages = [HumanMessage(content=\"knock knock\")]\n",
"chat(messages)"
]
},
{
"cell_type": "markdown",
"id": "c361ab1e-8c0c-4206-9e3c-9d1424a12b9c",
"metadata": {},
"source": [
"## `ChatCohere` also supports async and streaming functionality:"
"chat.invoke(messages)"
]
},
{
"cell_type": "code",
"execution_count": 57,
"id": "93a21c5c-6ef9-4688-be60-b2e1f94842fb",
"execution_count": 4,
"id": "c5fac0e9-05a4-4fc1-a3b3-e5bbb24b971b",
"metadata": {
"tags": []
},
"outputs": [],
"outputs": [
{
"data": {
"text/plain": [
"AIMessage(content=\"Who's there?\")"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from langchain.callbacks.manager import CallbackManager\n",
"from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler"
"await chat.ainvoke(messages)"
]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "c5fac0e9-05a4-4fc1-a3b3-e5bbb24b971b",
"execution_count": 5,
"id": "025be980-e50d-4a68-93dc-c9c7b500ce34",
"metadata": {
"tags": []
},
Expand All @@ -104,55 +174,76 @@
"text": [
"Who's there?"
]
},
}
],
"source": [
"for chunk in chat.stream(messages):\n",
" print(chunk.content, end=\"\", flush=True)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "064288e4-f184-4496-9427-bcf148fa055e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"LLMResult(generations=[[ChatGenerationChunk(text=\"Who's there?\", message=AIMessageChunk(content=\"Who's there?\"))]], llm_output={}, run=[RunInfo(run_id=UUID('1e9eaefc-9c99-4fa9-8297-ef9975d4751e'))])"
"[AIMessage(content=\"Who's there?\")]"
]
},
"execution_count": 64,
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"await chat.agenerate([messages])"
"chat.batch([messages])"
]
},
{
"cell_type": "markdown",
"id": "f1c56460",
"metadata": {},
"source": [
"## Chaining\n",
"\n",
"You can also easily combine with a prompt template for easy structuring of user input. We can do this using [LCEL](/docs/expression_language)"
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "025be980-e50d-4a68-93dc-c9c7b500ce34",
"metadata": {
"tags": []
},
"execution_count": 7,
"id": "0851b103",
"metadata": {},
"outputs": [],
"source": [
"from langchain_core.prompts import ChatPromptTemplate\n",
"\n",
"prompt = ChatPromptTemplate.from_template(\"Tell me a joke about {topic}\")\n",
"chain = prompt | chat"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "ae950c0f-1691-47f1-b609-273033cae707",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Who's there?"
]
},
{
"data": {
"text/plain": [
"AIMessageChunk(content=\"Who's there?\")"
"AIMessage(content=\"Why did the bear go to the chiropractor?\\n\\nBecause she was feeling a bit grizzly!\\n\\nHope you found that joke about bears to be a little bit amusing! If you'd like to hear another one, just let me know. In the meantime, if you have any other questions or need assistance with a different topic, feel free to let me know. \\n\\nJust remember, even if you have a sore back like the bear, it's always best to consult a licensed professional for injuries or pain you may be experiencing. \\n\\nWould you like me to tell you another joke?\")"
]
},
"execution_count": 63,
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chat = ChatCohere(\n",
" streaming=True,\n",
" verbose=True,\n",
" callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]),\n",
")\n",
"chat(messages)"
"chain.invoke({\"topic\": \"bears\"})"
]
}
],
Expand All @@ -172,7 +263,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.5"
"version": "3.9.1"
}
},
"nbformat": 4,
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