Azure 認知服務工具組
此工具組用於與 Azure Cognitive Services API
互動,以實現一些多模態功能。
目前此工具組中包含四個工具
- AzureCogsImageAnalysisTool:用於從圖像中提取標題、物件、標籤和文本。(注意:由於依賴於
azure-ai-vision
套件,此工具目前在 Mac OS 上不可用,該套件目前僅在 Windows 和 Linux 上受支援。) - AzureCogsFormRecognizerTool:用於從文件中提取文字、表格和鍵值對。
- AzureCogsSpeech2TextTool:用於將語音轉錄為文字。
- AzureCogsText2SpeechTool:用於將文字合成語音。
- AzureCogsTextAnalyticsHealthTool:用於提取醫療保健實體。
首先,您需要設定一個 Azure 帳戶並建立一個 Cognitive Services 資源。您可以按照此處的指示建立資源。
然後,您需要取得資源的端點、金鑰和區域,並將它們設定為環境變數。您可以在資源的「金鑰和端點」頁面中找到它們。
%pip install --upgrade --quiet azure-ai-formrecognizer > /dev/null
%pip install --upgrade --quiet azure-cognitiveservices-speech > /dev/null
%pip install --upgrade --quiet azure-ai-textanalytics > /dev/null
# For Windows/Linux
%pip install --upgrade --quiet azure-ai-vision > /dev/null
%pip install -qU langchain-community
import os
os.environ["OPENAI_API_KEY"] = "sk-"
os.environ["AZURE_COGS_KEY"] = ""
os.environ["AZURE_COGS_ENDPOINT"] = ""
os.environ["AZURE_COGS_REGION"] = ""
建立工具組
from langchain_community.agent_toolkits import AzureCognitiveServicesToolkit
toolkit = AzureCognitiveServicesToolkit()
[tool.name for tool in toolkit.get_tools()]
['Azure Cognitive Services Image Analysis',
'Azure Cognitive Services Form Recognizer',
'Azure Cognitive Services Speech2Text',
'Azure Cognitive Services Text2Speech']
在 Agent 中使用
from langchain.agents import AgentType, initialize_agent
from langchain_openai import OpenAI
llm = OpenAI(temperature=0)
agent = initialize_agent(
tools=toolkit.get_tools(),
llm=llm,
agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION,
verbose=True,
)
agent.run(
"What can I make with these ingredients?"
"https://images.openai.com/blob/9ad5a2ab-041f-475f-ad6a-b51899c50182/ingredients.png"
)
[1m> Entering new AgentExecutor chain...[0m
[32;1m[1;3m
Action:
\`\`\`
{
"action": "Azure Cognitive Services Image Analysis",
"action_input": "https://images.openai.com/blob/9ad5a2ab-041f-475f-ad6a-b51899c50182/ingredients.png"
}
\`\`\`
[0m
Observation: [36;1m[1;3mCaption: a group of eggs and flour in bowls
Objects: Egg, Egg, Food
Tags: dairy, ingredient, indoor, thickening agent, food, mixing bowl, powder, flour, egg, bowl[0m
Thought:[32;1m[1;3m I can use the objects and tags to suggest recipes
Action:
\`\`\`
{
"action": "Final Answer",
"action_input": "You can make pancakes, omelettes, or quiches with these ingredients!"
}
\`\`\`[0m
[1m> Finished chain.[0m
'You can make pancakes, omelettes, or quiches with these ingredients!'
audio_file = agent.run("Tell me a joke and read it out for me.")
[1m> Entering new AgentExecutor chain...[0m
[32;1m[1;3mAction:
\`\`\`
{
"action": "Azure Cognitive Services Text2Speech",
"action_input": "Why did the chicken cross the playground? To get to the other slide!"
}
\`\`\`
[0m
Observation: [31;1m[1;3m/tmp/tmpa3uu_j6b.wav[0m
Thought:[32;1m[1;3m I have the audio file of the joke
Action:
\`\`\`
{
"action": "Final Answer",
"action_input": "/tmp/tmpa3uu_j6b.wav"
}
\`\`\`[0m
[1m> Finished chain.[0m
'/tmp/tmpa3uu_j6b.wav'
from IPython import display
audio = display.Audio(audio_file)
display.display(audio)
agent.run(
"""The patient is a 54-year-old gentleman with a history of progressive angina over the past several months.
The patient had a cardiac catheterization in July of this year revealing total occlusion of the RCA and 50% left main disease ,
with a strong family history of coronary artery disease with a brother dying at the age of 52 from a myocardial infarction and
another brother who is status post coronary artery bypass grafting. The patient had a stress echocardiogram done on July , 2001 ,
which showed no wall motion abnormalities , but this was a difficult study due to body habitus. The patient went for six minutes with
minimal ST depressions in the anterior lateral leads , thought due to fatigue and wrist pain , his anginal equivalent. Due to the patient's
increased symptoms and family history and history left main disease with total occasional of his RCA was referred for revascularization with open heart surgery.
List all the diagnoses.
"""
)
[1m> Entering new AgentExecutor chain...[0m
[32;1m[1;3mAction:
\`\`\`
{
"action": "azure_cognitive_services_text_analyics_health",
"action_input": "The patient is a 54-year-old gentleman with a history of progressive angina over the past several months. The patient had a cardiac catheterization in July of this year revealing total occlusion of the RCA and 50% left main disease, with a strong family history of coronary artery disease with a brother dying at the age of 52 from a myocardial infarction and another brother who is status post coronary artery bypass grafting. The patient had a stress echocardiogram done on July, 2001, which showed no wall motion abnormalities, but this was a difficult study due to body habitus. The patient went for six minutes with minimal ST depressions in the anterior lateral leads, thought due to fatigue and wrist pain, his anginal equivalent. Due to the patient's increased symptoms and family history and history left main disease with total occasional of his RCA was referred for revascularization with open heart surgery."
}
\`\`\`
[0m
Observation: [36;1m[1;3mThe text conatins the following healthcare entities: 54-year-old is a healthcare entity of type Age, gentleman is a healthcare entity of type Gender, progressive angina is a healthcare entity of type Diagnosis, past several months is a healthcare entity of type Time, cardiac catheterization is a healthcare entity of type ExaminationName, July of this year is a healthcare entity of type Time, total is a healthcare entity of type ConditionQualifier, occlusion is a healthcare entity of type SymptomOrSign, RCA is a healthcare entity of type BodyStructure, 50 is a healthcare entity of type MeasurementValue, % is a healthcare entity of type MeasurementUnit, left main is a healthcare entity of type BodyStructure, disease is a healthcare entity of type Diagnosis, family is a healthcare entity of type FamilyRelation, coronary artery disease is a healthcare entity of type Diagnosis, brother is a healthcare entity of type FamilyRelation, dying is a healthcare entity of type Diagnosis, 52 is a healthcare entity of type Age, myocardial infarction is a healthcare entity of type Diagnosis, brother is a healthcare entity of type FamilyRelation, coronary artery bypass grafting is a healthcare entity of type TreatmentName, stress echocardiogram is a healthcare entity of type ExaminationName, July, 2001 is a healthcare entity of type Time, wall motion abnormalities is a healthcare entity of type SymptomOrSign, body habitus is a healthcare entity of type SymptomOrSign, six minutes is a healthcare entity of type Time, minimal is a healthcare entity of type ConditionQualifier, ST depressions in the anterior lateral leads is a healthcare entity of type SymptomOrSign, fatigue is a healthcare entity of type SymptomOrSign, wrist pain is a healthcare entity of type SymptomOrSign, anginal equivalent is a healthcare entity of type SymptomOrSign, increased is a healthcare entity of type Course, symptoms is a healthcare entity of type SymptomOrSign, family is a healthcare entity of type FamilyRelation, left is a healthcare entity of type Direction, main is a healthcare entity of type BodyStructure, disease is a healthcare entity of type Diagnosis, occasional is a healthcare entity of type Course, RCA is a healthcare entity of type BodyStructure, revascularization is a healthcare entity of type TreatmentName, open heart surgery is a healthcare entity of type TreatmentName[0m
Thought:[32;1m[1;3m I know what to respond
Action:
\`\`\`
{
"action": "Final Answer",
"action_input": "The text contains the following diagnoses: progressive angina, coronary artery disease, myocardial infarction, and coronary artery bypass grafting."
}
\`\`\`[0m
[1m> Finished chain.[0m
'The text contains the following diagnoses: progressive angina, coronary artery disease, myocardial infarction, and coronary artery bypass grafting.'