repo_id stringlengths 15 132 | file_path stringlengths 34 176 | content stringlengths 2 3.52M | __index_level_0__ int64 0 0 |
|---|---|---|---|
promptflow_repo/promptflow/examples | promptflow_repo/promptflow/examples/connections/openai.yml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/OpenAIConnection.schema.json
name: open_ai_connection
type: open_ai
api_key: "<user-input>"
organization: "" # optional
| 0 |
promptflow_repo/promptflow/examples | promptflow_repo/promptflow/examples/connections/requirements.txt | promptflow
promptflow-tools
python-dotenv
| 0 |
promptflow_repo/promptflow/examples | promptflow_repo/promptflow/examples/connections/cognitive_search.yml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/CognitiveSearchConnection.schema.json
name: cognitive_search_connection
type: cognitive_search
api_key: "<to-be-replaced>"
api_base: "endpoint"
api_version: "2023-07-01-Preview"
| 0 |
promptflow_repo/promptflow/examples | promptflow_repo/promptflow/examples/connections/connection.ipynb | %pip install -r ../requirements.txtfrom promptflow import PFClient
# client can help manage your runs and connections.
client = PFClient()from promptflow.entities import AzureOpenAIConnection
# Initialize an AzureOpenAIConnection object
connection = AzureOpenAIConnection(
name="my_azure_open_ai_connection",
a... | 0 |
promptflow_repo/promptflow/examples/tutorials | promptflow_repo/promptflow/examples/tutorials/get-started/quickstart-azure.ipynb | %pip install -r ../../requirements.txtimport json
# Import required libraries
from azure.identity import DefaultAzureCredential, InteractiveBrowserCredential
# azure version promptflow apis
from promptflow.azure import PFClienttry:
credential = DefaultAzureCredential()
# Check if given credential can get toke... | 0 |
promptflow_repo/promptflow/examples/tutorials | promptflow_repo/promptflow/examples/tutorials/get-started/flow-as-function.ipynb | from promptflow import load_flow
flow_path = "../../flows/standard/web-classification"
sample_url = "https://www.youtube.com/watch?v=o5ZQyXaAv1g"
f = load_flow(source=flow_path)
result = f(url=sample_url)
print(result)# provide parameters to create connection
conn_name = "new_ai_connection"
api_key = "<user-input>... | 0 |
promptflow_repo/promptflow/examples/tutorials | promptflow_repo/promptflow/examples/tutorials/get-started/quickstart.ipynb | %pip install -r ../../requirements.txtimport json
from promptflow import PFClient
from promptflow.connections import AzureOpenAIConnection, OpenAIConnection
# client can help manage your runs and connections.
pf = PFClient()try:
conn_name = "open_ai_connection"
conn = pf.connections.get(name=conn_name)
pri... | 0 |
promptflow_repo/promptflow/examples/tutorials | promptflow_repo/promptflow/examples/tutorials/run-management/cloud-run-management.ipynb | %pip install -r ../../requirements.txtfrom azure.identity import DefaultAzureCredential, InteractiveBrowserCredential
from azure.ai.ml.entities import Data
from azure.core.exceptions import ResourceNotFoundError
from promptflow.azure import PFClient
from promptflow.entities import Runtry:
credential = DefaultAzure... | 0 |
promptflow_repo/promptflow/examples/tutorials | promptflow_repo/promptflow/examples/tutorials/run-management/run-management.ipynb | %pip install -r ../../requirements.txtimport json
from promptflow import PFClient
from promptflow.connections import AzureOpenAIConnection, OpenAIConnection
# client can help manage your runs and connections.
pf = PFClient()try:
conn_name = "open_ai_connection"
conn = pf.connections.get(name=conn_name)
pri... | 0 |
promptflow_repo/promptflow/examples/tutorials | promptflow_repo/promptflow/examples/tutorials/flow-fine-tuning-evaluation/promptflow-quality-improvement.md | ---
resources: examples/connections/azure_openai.yml, examples/flows/chat/basic-chat, examples/flows/chat/chat-math-variant, examples/flows/evaluation/eval-chat-math
---
# Tutorial: How prompt flow helps on quality improvement
This tutorial is designed to enhance your understanding of improving flow quality through p... | 0 |
promptflow_repo/promptflow/examples/tutorials | promptflow_repo/promptflow/examples/tutorials/flow-deploy/README.md | # Deploy flow as applications
This folder contains examples of how to build & deploy flow as applications like Web Application packaged in Docker format. | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/distribute-flow-as-executable-app/app.spec | # -*- mode: python ; coding: utf-8 -*-
from PyInstaller.utils.hooks import collect_data_files
from PyInstaller.utils.hooks import copy_metadata
datas = [('connections', 'connections'), ('flow', 'flow'), ('settings.json', '.'), ('main.py', '.'), ('{{streamlit_runtime_interpreter_path}}', './streamlit/runtime')]
datas +... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/distribute-flow-as-executable-app/app.py | import os
import sys
from promptflow._cli._pf._connection import create_connection
from streamlit.web import cli as st_cli
from streamlit.runtime import exists
from main import start
def is_yaml_file(file_path):
_, file_extension = os.path.splitext(file_path)
return file_extension.lower() in ('.yaml', '.yml... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/distribute-flow-as-executable-app/README.md | ---
resources: examples/connections/azure_openai.yml, examples/flows/standard/web-classification
---
# Distribute flow as executable app
This example demos how to package flow as a executable app.
We will use [web-classification](../../../flows/standard/web-classification/README.md) as example in this tutorial.
Pleas... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/distribute-flow-as-executable-app/main.py | import base64
import json
import os
import re
import streamlit as st
from pathlib import Path
from streamlit_quill import st_quill # noqa: F401
from bs4 import BeautifulSoup, NavigableString, Tag
from promptflow._sdk._utils import print_yellow_warning
from promptflow._sdk._serving.flow_invoker import FlowInvoker
from... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/kubernetes/README.md | ---
resources: examples/connections/azure_openai.yml, examples/flows/standard/web-classification
---
# Deploy flow using Kubernetes
This example demos how to deploy flow as a Kubernetes app.
We will use [web-classification](../../../flows/standard/web-classification/README.md) as example in this tutorial.
Please ensu... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/kubernetes/deployment.yaml | ---
kind: Namespace
apiVersion: v1
metadata:
name: web-classification
---
apiVersion: v1
kind: Secret
metadata:
name: open-ai-connection-api-key
namespace: web-classification
type: Opaque
data:
open-ai-connection-api-key: <encoded_secret>
---
apiVersion: v1
kind: Service
metadata:
name: web-classification-ser... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/create-service-with-flow/README.md | ---
resources: examples/tutorials/flow-deploy/create-service-with-flow
---
# Create service with flow
This example shows how to create a simple service with flow.
You can create your own service by utilize `flow-as-function`.
This folder contains a example on how to build a service with a flow.
Reference [here](./s... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/create-service-with-flow/simple_score.py | import json
import logging
from flask import Flask, jsonify, request
from promptflow import load_flow
from promptflow.connections import AzureOpenAIConnection
from promptflow.entities import FlowContext
from promptflow.exceptions import SystemErrorException, UserErrorException
class SimpleScoreApp(Flask):
pass
... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy/create-service-with-flow | promptflow_repo/promptflow/examples/tutorials/flow-deploy/create-service-with-flow/echo_connection_flow/echo_connection.py | from promptflow import tool
from promptflow.connections import AzureOpenAIConnection
@tool
def echo_connection(flow_input: str, node_input: str, connection: AzureOpenAIConnection):
print(f"Flow input: {flow_input}")
print(f"Node input: {node_input}")
print(f"Flow connection: {connection._to_dict()}")
... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy/create-service-with-flow | promptflow_repo/promptflow/examples/tutorials/flow-deploy/create-service-with-flow/echo_connection_flow/flow.dag.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
inputs:
flow_input:
type: string
outputs:
output:
type: object
reference: ${echo_connection.output}
nodes:
- name: echo_connection
type: python
source:
type: code
path: echo_connection.py
inputs:
flow_inpu... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/docker/README.md | ---
resources: examples/connections/azure_openai.yml, examples/flows/standard/web-classification
---
# Deploy a flow using Docker
This example demos how to deploy flow as a docker app.
We will use [web-classification](../../../flows/standard/web-classification/README.md) as example in this tutorial.
## Build a flow ... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/azure-app-service/README.md | ---
resources: examples/connections/azure_openai.yml, examples/flows/standard/web-classification
---
# Deploy flow using Azure App Service
This example demos how to deploy a flow using Azure App Service.
[Azure App Service](https://learn.microsoft.com/azure/app-service/) is an HTTP-based service for hosting web appl... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/azure-app-service/deploy.ps1 | <#
.DESCRIPTION
Script to deploy promptflow to Azure App Service.
.PARAMETER path
The folder path to be deployed
.PARAMETER image_tag
The container image tag.
.PARAMETER registry
The container registry name, for example 'xx.azurecr.io'.
.PARAMETER name
The app name to produce a unique FQDN as AppName.azurewebsites.net... | 0 |
promptflow_repo/promptflow/examples/tutorials/flow-deploy | promptflow_repo/promptflow/examples/tutorials/flow-deploy/azure-app-service/deploy.sh | #! /bin/bash
set -e
program_name=$0
function usage {
echo "usage: $program_name [-i|-image_tag|--image_tag]"
echo " -i|-image_tag|--image_tag specify container image tag"
echo " -r|-registry|--registry specify container registry name, for example 'xx.azurecr.io... | 0 |
promptflow_repo/promptflow/examples/tutorials | promptflow_repo/promptflow/examples/tutorials/e2e-development/chat-with-pdf.md | ---
resources: examples/connections/azure_openai.yml, examples/flows/chat/chat-with-pdf
---
# Tutorial: Chat with PDF
## Overview
Retrieval Augmented Generation (or RAG) has become a prevalent pattern to build intelligent application with Large Language Models (or LLMs) since it can infuse external knowledge into the... | 0 |
promptflow_repo/promptflow/examples/tutorials | promptflow_repo/promptflow/examples/tutorials/flow-in-pipeline/pipeline.ipynb | # import required libraries
from azure.identity import DefaultAzureCredential, InteractiveBrowserCredential
from azure.ai.ml import MLClient, load_component, Input
from azure.ai.ml.constants import AssetTypes
from azure.ai.ml.dsl import pipelinetry:
credential = DefaultAzureCredential()
# Check if given creden... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/dynamic-list-input-tool-showcase/README.md | # Basic flow with tool using a dynamic list input
This is a flow demonstrating how to use a tool with a dynamic list input.
Tools used in this flow:
- `python` Tool
Connections used in this flow:
- None
## Prerequisites
Install promptflow sdk and other dependencies:
```bash
pip install -r requirements.txt
```
## R... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/dynamic-list-input-tool-showcase/requirements.txt | promptflow
my-tools-package | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/dynamic-list-input-tool-showcase/flow.dag.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
inputs: {}
outputs:
output:
type: string
reference: ${My_Tool_with_Dynamic_List_Input_cywc.output}
nodes:
- name: My_Tool_with_Dynamic_List_Input_cywc
type: python
source:
type: package
tool: my_tool_package.tools.too... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom-strong-type-connection-script-tool-showcase/data.jsonl | {"text": "Python Hello World!"}
{"text": "C Hello World!"}
{"text": "C# Hello World!"}
| 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom-strong-type-connection-script-tool-showcase/custom.yml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/CustomConnection.schema.json
name: normal_custom_connection
type: custom
configs:
api_base: test
secrets: # must-have
api_key: <to-be-replaced>
| 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom-strong-type-connection-script-tool-showcase/README.md | # Basic flow with script tool using custom strong type connection
This is a flow demonstrating the use of a script tool with custom string type connection which provides a secure way to manage credentials for external APIs and data sources, and it offers an improved user-friendly and intellisense experience compared to... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom-strong-type-connection-script-tool-showcase/my_script_tool.py | from promptflow import tool
from promptflow.connections import CustomStrongTypeConnection
from promptflow.contracts.types import Secret
class MyCustomConnection(CustomStrongTypeConnection):
"""My custom strong type connection.
:param api_key: The api key.
:type api_key: Secret
:param api_base: The ap... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom-strong-type-connection-script-tool-showcase/requirements.txt | promptflow[azure]==1.1.0
| 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom-strong-type-connection-script-tool-showcase/flow.dag.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
inputs:
text:
type: string
default: Microsoft
outputs:
my_output:
type: string
reference: ${my_script_tool.output}
nodes:
- name: my_script_tool
type: python
source:
type: code
path: my_script_tool.py
inpu... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom_llm_tool_showcase/custom_connection.yml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/CustomConnection.schema.json
name: basic_custom_connection
type: custom
configs:
api_base: <to-be-replaced>
secrets: # must-have
api_key: <to-be-replaced>
| 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom_llm_tool_showcase/README.md | # Flow with custom_llm tool
This is a flow demonstrating how to use a `custom_llm` tool, which enables users to seamlessly connect to a large language model with prompt tuning experience using a `PromptTemplate`.
Tools used in this flow:
- `custom_llm` Tool
Connections used in this flow:
- custom connection
## Prere... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom_llm_tool_showcase/requirements.txt | promptflow
my-tools-package | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom_llm_tool_showcase/prompt_template.jinja2 | Welcome to {{ website_name }}!
{% if user_name %}
Hello, {{ user_name }}!
{% else %}
Hello there!
{% endif %} | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom_llm_tool_showcase/flow.dag.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
inputs:
website_name:
type: string
default: Microsoft
user_name:
type: string
default: ""
outputs:
output:
type: string
reference: ${my_custom_llm_tool.output}
nodes:
- name: my_custom_llm_tool
type: custom_... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom-strong-type-connection-package-tool-showcase/data.jsonl | {"text": "Python Hello World!"}
{"text": "C Hello World!"}
{"text": "C# Hello World!"} | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom-strong-type-connection-package-tool-showcase/README.md | # Basic flow with package tool using custom strong type connection
This is a flow demonstrating the use of a package tool with custom string type connection which provides a secure way to manage credentials for external APIs and data sources, and it offers an improved user-friendly and intellisense experience compared ... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom-strong-type-connection-package-tool-showcase/my_custom_connection.yml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/CustomStrongTypeConnection.schema.json
name: "my_custom_connection"
type: custom
custom_type: MyCustomConnection
module: my_tool_package.tools.tool_with_custom_strong_type_connection
package: my-tools-package
package_version: 0.0.5
configs:
api_base: "Th... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom-strong-type-connection-package-tool-showcase/requirements.txt | promptflow[azure]==1.1.0
my-tools-package==0.0.5
| 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/custom-strong-type-connection-package-tool-showcase/flow.dag.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
inputs:
text:
type: string
default: Microsoft
outputs:
my_output:
type: string
reference: ${my_package_tool.output}
nodes:
- name: my_package_tool
type: python
source:
type: package
tool: my_tool_package.too... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/cascading-inputs-tool-showcase/README.md | # Basic flow with package tool using cascading inputs
This is a flow demonstrating the use of a tool with cascading inputs which frequently used in situations where the selection in one input field determines what subsequent inputs should be shown,
and it helps in creating a more efficient, user-friendly, and error-fr... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/cascading-inputs-tool-showcase/requirements.txt | promptflow
my-tools-package==0.0.7 | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/cascading-inputs-tool-showcase/flow.dag.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
environment:
python_requirements_txt: requirements.txt
inputs: {}
outputs:
user_id:
type: string
reference: ${Tool_with_Cascading_Inputs.output}
nodes:
- name: Tool_with_Cascading_Inputs
type: python
source:
type: packa... | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/filepath-input-tool-showcase/hello_method.py | def hello(input_text: str) -> str:
# Replace with your own code.
return "Hello " + input_text
| 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/filepath-input-tool-showcase/requirements.txt | promptflow
promptflow-tools
my-tools-package | 0 |
promptflow_repo/promptflow/examples/tools/use-cases | promptflow_repo/promptflow/examples/tools/use-cases/filepath-input-tool-showcase/flow.dag.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
inputs:
input:
type: string
default: Microsoft
outputs:
output:
type: string
reference: ${Tool_with_FilePath_Input.output}
nodes:
- name: Tool_with_FilePath_Input
type: python
source:
type: package
tool: my_... | 0 |
promptflow_repo/promptflow/examples/tools | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/setup.py | from setuptools import find_packages, setup
PACKAGE_NAME = "my-tools-package"
setup(
name=PACKAGE_NAME,
version="0.0.12",
description="This is my tools package",
packages=find_packages(),
entry_points={
"package_tools": ["my_tools = my_tool_package.tools.utils:list_package_tools"],
},
... | 0 |
promptflow_repo/promptflow/examples/tools | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/MANIFEST.in | include my_tool_package/yamls/*.yaml | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/__init__.py | __path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore
| 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/tools/tool_with_generated_by_input.py | from typing import Union
from promptflow import tool
from typing import Dict, List
from promptflow.connections import AzureOpenAIConnection, OpenAIConnection, CognitiveSearchConnection
def generate_index_json(
index_type: str,
index: str = "",
index_connection: CognitiveSearchConnection = "",
index_n... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/tools/tool_with_file_path_input.py | import importlib
from pathlib import Path
from promptflow import tool
from promptflow.contracts.types import FilePath
@tool
def my_tool(input_file: FilePath, input_text: str) -> str:
# customise your own code to handle and use the input_file here
new_module = importlib.import_module(Path(input_file).stem)
... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/tools/my_tool_2.py | from promptflow import ToolProvider, tool
from promptflow.connections import CustomConnection
class MyTool(ToolProvider):
"""
Doc reference :
"""
def __init__(self, connection: CustomConnection):
super().__init__()
self.connection = connection
@tool
def my_tool(self, input_te... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/tools/utils.py | from pathlib import Path
from ruamel.yaml import YAML
def collect_tools_from_directory(base_dir) -> dict:
tools = {}
yaml = YAML()
for f in Path(base_dir).glob("**/*.yaml"):
with open(f, "r") as f:
tools_in_file = yaml.load(f)
for identifier, tool in tools_in_file.items():... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/tools/__init__.py | __path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore
| 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/tools/tool_with_custom_strong_type_connection.py | from promptflow import tool
from promptflow.connections import CustomStrongTypeConnection
from promptflow.contracts.types import Secret
class MyCustomConnection(CustomStrongTypeConnection):
"""My custom strong type connection.
:param api_key: The api key get from "https://xxx.com".
:type api_key: Secret
... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/tools/tool_with_dynamic_list_input.py | from promptflow import tool
from typing import List, Union, Dict
def my_list_func(prefix: str = "", size: int = 10, **kwargs) -> List[Dict[str, Union[str, int, float, list, Dict]]]:
"""This is a dummy function to generate a list of items.
:param prefix: prefix to add to each item.
:param size: number of ... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/tools/tool_with_custom_llm_type.py | from jinja2 import Template
from promptflow import tool
from promptflow.connections import CustomConnection
from promptflow.contracts.types import PromptTemplate
@tool
def my_tool(connection: CustomConnection, prompt: PromptTemplate, **kwargs) -> str:
# Replace with your tool code, customise your own code to hand... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/tools/my_tool_1.py | from promptflow import tool
from promptflow.connections import CustomConnection
@tool
def my_tool(connection: CustomConnection, input_text: str) -> str:
# Replace with your tool code.
# Usually connection contains configs to connect to an API.
# Use CustomConnection is a dict. You can use it like: connect... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/tools/tool_with_cascading_inputs.py | from enum import Enum
from promptflow import tool
class UserType(str, Enum):
STUDENT = "student"
TEACHER = "teacher"
@tool
def my_tool(user_type: Enum, student_id: str = "", teacher_id: str = "") -> str:
"""This is a dummy function to support cascading inputs.
:param user_type: user type, student ... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/yamls/tool_with_custom_llm_type.yaml | my_tool_package.tools.tool_with_custom_llm_type.my_tool:
name: My Custom LLM Tool
description: This is a tool to demonstrate how to customize an LLM tool with a PromptTemplate.
type: custom_llm
module: my_tool_package.tools.tool_with_custom_llm_type
function: my_tool
inputs:
connection:
type:
... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/yamls/tool_with_generated_by_input.yaml | my_tool_package.tools.tool_with_generated_by_input.my_tool:
function: my_tool
inputs:
index_json:
type:
- string
generated_by:
func_path: my_tool_package.tools.tool_with_generated_by_input.generate_index_json
func_kwargs:
- name: index_type
type:
... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/yamls/tool_with_dynamic_list_input.yaml | my_tool_package.tools.tool_with_dynamic_list_input.my_tool:
function: my_tool
inputs:
input_prefix:
type:
- string
input_text:
type:
- list
dynamic_list:
func_path: my_tool_package.tools.tool_with_dynamic_list_input.my_list_func
func_kwargs:
- name: pr... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/yamls/my_tool_2.yaml | my_tool_package.tools.my_tool_2.MyTool.my_tool:
class_name: MyTool
function: my_tool
inputs:
connection:
type:
- CustomConnection
input_text:
type:
- string
module: my_tool_package.tools.my_tool_2
name: My Second Tool
description: This is my second tool
type: python
| 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/yamls/my_tool_1.yaml | my_tool_package.tools.my_tool_1.my_tool:
function: my_tool
inputs:
connection:
type:
- CustomConnection
input_text:
type:
- string
module: my_tool_package.tools.my_tool_1
name: My First Tool
description: This is my first tool
type: python
| 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/yamls/tool_with_cascading_inputs.yaml | my_tool_package.tools.tool_with_cascading_inputs.my_tool:
function: my_tool
inputs:
user_type:
type:
- string
enum:
- student
- teacher
student_id:
type:
- string
enabled_by: user_type
enabled_by_value: [student]
teacher_id:
type:
-... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/yamls/tool_with_file_path_input.yaml | my_tool_package.tools.tool_with_file_path_input.my_tool:
function: my_tool
inputs:
input_file:
type:
- file_path
input_text:
type:
- string
module: my_tool_package.tools.tool_with_file_path_input
name: Tool with FilePath Input
description: This is a tool to demonstrate the usag... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/my_tool_package/yamls/tool_with_custom_strong_type_connection.yaml | my_tool_package.tools.tool_with_custom_strong_type_connection.my_tool:
description: This is my tool with custom strong type connection.
function: my_tool
inputs:
connection:
custom_type:
- MyCustomConnection
type:
- CustomConnection
input_text:
type:
- string
module: ... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/tests/test_my_tool_2.py | import pytest
import unittest
from promptflow.connections import CustomConnection
from my_tool_package.tools.my_tool_2 import MyTool
@pytest.fixture
def my_custom_connection() -> CustomConnection:
my_custom_connection = CustomConnection(
{
"api-key" : "my-api-key",
"api-secret" : ... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/tests/test_tool_with_file_path_input.py | import pytest
import unittest
from promptflow.contracts.types import FilePath
from my_tool_package.tools.tool_with_file_path_input import my_tool
@pytest.fixture
def my_file_path_input() -> FilePath:
my_file_path_input = FilePath("tests.test_utils.hello_method.py")
return my_file_path_input
class TestToolW... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/tests/test_tool_with_custom_strong_type_connection.py | import pytest
import unittest
from my_tool_package.tools.tool_with_custom_strong_type_connection import MyCustomConnection, my_tool
@pytest.fixture
def my_custom_connection() -> MyCustomConnection:
my_custom_connection = MyCustomConnection(
{
"api_key" : "my-api-key",
"api_base" :... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/tests/test_tool_with_cascading_inputs.py | from my_tool_package.tools.tool_with_cascading_inputs import my_tool
def test_my_tool():
result = my_tool(user_type="student", student_id="student_id")
assert result == '123'
| 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/tests/test_my_tool_1.py | import pytest
import unittest
from promptflow.connections import CustomConnection
from my_tool_package.tools.my_tool_1 import my_tool
@pytest.fixture
def my_custom_connection() -> CustomConnection:
my_custom_connection = CustomConnection(
{
"api-key" : "my-api-key",
"api-secret" :... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/tests/test_tool_with_dynamic_input.py | from my_tool_package.tools.tool_with_dynamic_list_input import my_tool, my_list_func
def test_my_tool():
result = my_tool(input_text=["apple", "banana"], input_prefix="My")
assert result == 'Hello My apple,banana'
def test_my_list_func():
result = my_list_func(prefix="My")
assert len(result) == 10
... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/tests/test_tool_with_generated_by_input.py | import json
import pytest
import unittest
from my_tool_package.tools.tool_with_generated_by_input import (
generate_index_json,
list_embedding_deployment,
list_fields,
list_indexes,
list_index_types,
list_semantic_configuration,
my_tool,
reverse_generate_index_json,
)
@pytest.mark.par... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/tests/test_tool_with_custom_llm_type.py | import pytest
import unittest
from promptflow.connections import CustomConnection
from my_tool_package.tools.tool_with_custom_llm_type import my_tool
@pytest.fixture
def my_custom_connection() -> CustomConnection:
my_custom_connection = CustomConnection(
{
"api-key" : "my-api-key",
... | 0 |
promptflow_repo/promptflow/examples/tools/tool-package-quickstart/tests | promptflow_repo/promptflow/examples/tools/tool-package-quickstart/tests/test_utils/hello_method.py | def hello(input_text: str) -> str:
# Replace with your own code.
return "Hello " + input_text
| 0 |
promptflow_repo/promptflow/examples/flows | promptflow_repo/promptflow/examples/flows/integrations/README.md | # Integrations Folder
This folder contains flow examples contributed by various contributors. Each flow example should have a README.md file that provides a comprehensive introduction to the flow and includes contact information for the flow owner.
# Guideline for README.md of flows
To ensure consistency and clarit... | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/connections/azure_ai_language.yml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/CustomConnection.schema.json
name: azure_ai_language_connection
type: custom
configs:
endpoint: "<azure-language-resource-endpoint>"
secrets:
api_key: "<to-be-replaced>" | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/connections/azure_ai_translator.yml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/CustomConnection.schema.json
name: azure_ai_translator_connection
type: custom
configs:
endpoint: "<azure-translator-resource-endpoint>"
region: "<azure-translator-resource-region>"
secrets:
api_key: "<to-be-replaced>" | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/analyze_documents/data.jsonl | {"document_path": "./document1.txt", "language": "en"}
{"document_path": "./document2.txt", "language": "en"} | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/analyze_documents/README.md | # Analyze Documents
A flow that analyzes documents with various language-based Machine Learning models.
This sample flow utilizes Azure AI Language's pre-built and optimized language models to perform various analyses on text or documents. It performs:
- [Translation](https://learn.microsoft.com/en-us/rest/api/cogni... | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/analyze_documents/read_file.py | from promptflow import tool
@tool
def read_file(file_path: str) -> str:
"""
This tool opens a file and reads its contents into a string.
:param file_path: the file path of the file to be read.
"""
with open(file_path, 'r', encoding="utf8") as f:
file = f.read()
return file
| 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/analyze_documents/parse_translation.py | from promptflow import tool
@tool
def parse_translation(translation_results: dict, language: str) -> str:
return translation_results[language]
| 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/analyze_documents/document2.txt | Siemens and Microsoft partner to drive cross-industry AI adoption
October 31, 2023 | Microsoft News Center
Share on Facebook (opens new window)
Share on LinkedIn (opens new window)
Share on Twitter (opens new window)
Companies introduce Siemens Industrial Copilot, a generative AI-powered assistant, designed to enha... | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/analyze_documents/document1.txt | La fortaleza de Microsoft Cloud impulsa los resultados del primer trimestre
24 de octubre de 2023 | Centro de noticias de Microsoft
Compartir en Facebook (se abre en una ventana nueva)
Compartir en LinkedIn (se abre en una ventana nueva)
Compartir en Twitter (se abre en una ventana nueva)
REDMOND, Washington — 24 d... | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/analyze_documents/requirements.txt | promptflow
promptflow-tools
promptflow-azure-ai-language | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/analyze_documents/flow.dag.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
environment:
python_requirements_txt: requirements.txt
inputs:
document_path:
type: string
default: ./document1.txt
language:
type: string
default: en
outputs:
extractive_summary:
type: string
reference: ${E... | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/multi_intent_conversational_language_understanding/README.md | # Multi Intent Conversational Language Understanding
A flow that can be used to determine multiple intents in a user query leveraging an LLM with Conversational Language Understanding.
This sample flow utilizes Azure AI Language's Conversational Language Understanding to perform various analyses on text or documents... | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/multi_intent_conversational_language_understanding/MediaPlayer.json | {
"projectFileVersion": "2022-10-01-preview",
"stringIndexType": "Utf16CodeUnit",
"metadata": {
"projectKind": "Conversation",
"settings": {
"confidenceThreshold": 0,
"normalizeCasing": false
},
"projectName": "MediaPlayer",
"multilingual": fal... | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/multi_intent_conversational_language_understanding/chat.jinja2 | system:
Your task is to break down compound sentences into separate sentences.
For simple sentences just repeat the user input.
Remember to use a json array for the output.
user:
The output must be a json array.
Here are a few examples:
user input: Play Eric Clapton and turn down the volume.
OUTPUT: ["Play Eric Clap... | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/multi_intent_conversational_language_understanding/requirements.txt | promptflow
promptflow-tools
promptflow-azure-ai-language | 0 |
promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language | promptflow_repo/promptflow/examples/flows/integrations/azure-ai-language/multi_intent_conversational_language_understanding/flow.dag.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
environment:
python_requirements_txt: requirements.txt
inputs:
chat_history:
type: list
is_chat_history: true
utterance:
type: string
is_chat_input: true
default: Play BB King and increase the volume.
outputs:
i... | 0 |
promptflow_repo/promptflow/examples/flows/standard | promptflow_repo/promptflow/examples/flows/standard/describe-image/data.jsonl | {"question": "How many colors are there in the image?", "input_image": {"data:image/png;url": "https://developer.microsoft.com/_devcom/images/logo-ms-social.png"}}
{"question": "What's this image about?", "input_image": {"data:image/png;url": "https://developer.microsoft.com/_devcom/images/404.png"}} | 0 |
promptflow_repo/promptflow/examples/flows/standard | promptflow_repo/promptflow/examples/flows/standard/describe-image/README.md | # Describe image flow
A flow that take image input, flip it horizontally and uses OpenAI GPT-4V tool to describe it.
Tools used in this flow：
- `OpenAI GPT-4V` tool
- custom `python` Tool
Connections used in this flow:
- OpenAI Connection
## Prerequisites
Install promptflow sdk and other dependencies, create connec... | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.