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docs: update baidu_qianfan_endpoint.ipynb doc (#15940)
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- **Description:** Updated the docs for the chat integration module
baidu_qianfan_endpoint.ipynb
  - **Issue:**  #15664 
  - **Dependencies:**N/A
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@Bigtable123
Bigtable123 committed Jan 15, 2024
1 parent 21e0df9 commit 7306032
Showing 1 changed file with 120 additions and 104 deletions.
224 changes: 120 additions & 104 deletions docs/docs/integrations/chat/baidu_qianfan_endpoint.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -53,9 +53,16 @@
"- AquilaChat-7B"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Set up"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -65,83 +72,105 @@
"from langchain_community.chat_models import QianfanChatEndpoint\n",
"from langchain_core.language_models.chat_models import HumanMessage\n",
"\n",
"os.environ[\"QIANFAN_AK\"] = \"your_ak\"\n",
"os.environ[\"QIANFAN_SK\"] = \"your_sk\"\n",
"\n",
"chat = QianfanChatEndpoint(\n",
" streaming=True,\n",
")\n",
"res = chat([HumanMessage(content=\"write a funny joke\")])"
"os.environ[\"QIANFAN_AK\"] = \"Your_api_key\"\n",
"os.environ[\"QIANFAN_SK\"] = \"You_secret_Key\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Usage"
]
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[INFO] [09-15 20:00:36] logging.py:55 [t:139698882193216]: requesting llm api endpoint: /chat/eb-instant\n",
"[INFO] [09-15 20:00:37] logging.py:55 [t:139698882193216]: async requesting llm api endpoint: /chat/eb-instant\n"
]
},
"data": {
"text/plain": [
"AIMessage(content='您好！请问您需要什么帮助？我将尽力回答您的问题。')"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chat = QianfanChatEndpoint(streaming=True)\n",
"messages = [HumanMessage(content=\"Hello\")]\n",
"chat.invoke(messages)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"chat resp: content='您好，您似乎输入' additional_kwargs={} example=False\n",
"chat resp: content='了一个话题标签，请问需要我帮您找到什么资料或者帮助您解答什么问题吗？' additional_kwargs={} example=False\n",
"chat resp: content='' additional_kwargs={} example=False\n"
]
},
"data": {
"text/plain": [
"AIMessage(content='您好！有什么我可以帮助您的吗？')"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"await chat.ainvoke(messages)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[INFO] [09-15 20:00:39] logging.py:55 [t:139698882193216]: async requesting llm api endpoint: /chat/eb-instant\n"
]
},
"data": {
"text/plain": [
"[AIMessage(content='您好！有什么我可以帮助您的吗？')]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chat.batch([messages])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Streaming"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"generations=[[ChatGeneration(text=\"The sea is a vast expanse of water that covers much of the Earth's surface. It is a source of travel, trade, and entertainment, and is also a place of scientific exploration and marine conservation. The sea is an important part of our world, and we should cherish and protect it.\", generation_info={'finish_reason': 'finished'}, message=AIMessage(content=\"The sea is a vast expanse of water that covers much of the Earth's surface. It is a source of travel, trade, and entertainment, and is also a place of scientific exploration and marine conservation. The sea is an important part of our world, and we should cherish and protect it.\", additional_kwargs={}, example=False))]] llm_output={} run=[RunInfo(run_id=UUID('d48160a6-5960-4c1d-8a0e-90e6b51a209b'))]\n",
"astream content='The sea is a vast' additional_kwargs={} example=False\n",
"astream content=' expanse of water, a place of mystery and adventure. It is the source of many cultures and civilizations, and a center of trade and exploration. The sea is also a source of life and beauty, with its unique marine life and diverse' additional_kwargs={} example=False\n",
"astream content=' coral reefs. Whether you are swimming, diving, or just watching the sea, it is a place that captivates the imagination and transforms the spirit.' additional_kwargs={} example=False\n"
"您好！有什么我可以帮助您的吗？\n"
]
}
],
"source": [
"from langchain.schema import HumanMessage\n",
"from langchain_community.chat_models import QianfanChatEndpoint\n",
"\n",
"chatLLM = QianfanChatEndpoint()\n",
"res = chatLLM.stream([HumanMessage(content=\"hi\")], streaming=True)\n",
"for r in res:\n",
" print(\"chat resp:\", r)\n",
"\n",
"\n",
"async def run_aio_generate():\n",
" resp = await chatLLM.agenerate(\n",
" messages=[[HumanMessage(content=\"write a 20 words sentence about sea.\")]]\n",
" )\n",
" print(resp)\n",
"\n",
"\n",
"await run_aio_generate()\n",
"\n",
"\n",
"async def run_aio_stream():\n",
" async for res in chatLLM.astream(\n",
" [HumanMessage(content=\"write a 20 words sentence about sea.\")]\n",
" ):\n",
" print(\"astream\", res)\n",
"\n",
"\n",
"await run_aio_stream()"
"try:\n",
" for chunk in chat.stream(messages):\n",
" print(chunk.content, end=\"\", flush=True)\n",
"except TypeError as e:\n",
" print(\"\")"
]
},
{
Expand All @@ -151,39 +180,36 @@
"source": [
"## Use different models in Qianfan\n",
"\n",
"In the case you want to deploy your own model based on Ernie Bot or third-party open-source model, you could follow these steps:\n",
"The default model is ERNIE-Bot-turbo, in the case you want to deploy your own model based on Ernie Bot or third-party open-source model, you could follow these steps:\n",
"\n",
"- 1. （Optional, if the model are included in the default models, skip it）Deploy your model in Qianfan Console, get your own customized deploy endpoint.\n",
"- 2. Set up the field called `endpoint` in the initialization:"
"1. (Optional, if the model are included in the default models, skip it) Deploy your model in Qianfan Console, get your own customized deploy endpoint.\n",
"2. Set up the field called `endpoint` in the initialization:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[INFO] [09-15 20:00:50] logging.py:55 [t:139698882193216]: requesting llm api endpoint: /chat/bloomz_7b1\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"content='你好！很高兴见到你。' additional_kwargs={} example=False\n"
]
"data": {
"text/plain": [
"AIMessage(content='Hello，可以回答问题了，我会竭尽全力为您解答，请问有什么问题吗？')"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"chatBloom = QianfanChatEndpoint(\n",
"chatBot = QianfanChatEndpoint(\n",
" streaming=True,\n",
" model=\"BLOOMZ-7B\",\n",
" model=\"ERNIE-Bot\",\n",
")\n",
"res = chatBloom([HumanMessage(content=\"hi\")])\n",
"print(res)"
"\n",
"messages = [HumanMessage(content=\"Hello\")]\n",
"chatBot.invoke(messages)"
]
},
{
Expand All @@ -202,35 +228,25 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"[INFO] [09-15 20:00:57] logging.py:55 [t:139698882193216]: requesting llm api endpoint: /chat/eb-instant\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"content='您好，您似乎输入' additional_kwargs={} example=False\n",
"content='了一个文本字符串，但并没有给出具体的问题或场景。' additional_kwargs={} example=False\n",
"content='如果您能提供更多信息，我可以更好地回答您的问题。' additional_kwargs={} example=False\n",
"content='' additional_kwargs={} example=False\n"
]
"data": {
"text/plain": [
"AIMessage(content='您好！有什么我可以帮助您的吗？')"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"res = chat.stream(\n",
" [HumanMessage(content=\"hi\")],\n",
"chat.invoke(\n",
" [HumanMessage(content=\"Hello\")],\n",
" **{\"top_p\": 0.4, \"temperature\": 0.1, \"penalty_score\": 1},\n",
")\n",
"\n",
"for r in res:\n",
" print(r)"
")"
]
}
],
Expand All @@ -250,7 +266,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.5"
"version": "3.9.18"
},
"vscode": {
"interpreter": {
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