repo_id stringlengths 15 132 | file_path stringlengths 34 176 | content stringlengths 2 3.52M | __index_level_0__ int64 0 0 |
|---|---|---|---|
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/prompt_tools/samples.json | [
{
"text": "text_1"
},
{
"text": "text_2"
},
{
"text": "text_3"
},
{
"text": "text_4"
}
] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with___file__/script_with___file__.meta.json | {
"name": "script_with___file__",
"type": "python",
"inputs": {
"input1": {
"type": [
"string"
]
}
},
"source": "script_with___file__.py",
"function": "my_python_tool"
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with___file__/script_with___file__.py | from pathlib import Path
from promptflow import tool
print(f"The script is {__file__}")
assert Path(__file__).is_absolute(), f"__file__ should be absolute path, got {__file__}"
@tool
def my_python_tool(input1: str) -> str:
from pathlib import Path
assert Path(__file__).name == "script_with___file__.py"
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with___file__/flow.dag.yaml | inputs:
text:
type: string
outputs:
output_prompt:
type: string
reference: ${node1.output}
nodes:
- name: node1
type: python
source:
type: code
path: script_with___file__.py
inputs:
input1: ${inputs.text}
- name: node2
type: python
source:
type: code
path: folder/another-to... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with___file__/samples.json | [
{
"text": "text_1"
},
{
"text": "text_2"
},
{
"text": "text_3"
},
{
"text": "text_4"
}
] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with___file__ | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with___file__/folder/another-tool.py | from promptflow import tool
print(f"The script is {__file__}")
@tool
def my_python_tool(input1: str) -> str:
from pathlib import Path
assert Path(__file__).as_posix().endswith("folder/another-tool.py")
assert __name__ == "__pf_main__"
return f"Prompt: {input1} {__file__}"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/classification_accuracy_evaluation/expected_metrics.json | {"accuracy": 0.67} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/classification_accuracy_evaluation/aggregation_assert.py | from typing import List
from promptflow import tool
@tool
def aggregation_assert(input1: List[str], input2: List[str]):
assert isinstance(input1, list)
assert isinstance(input2, list)
assert len(input1) == len(input2)
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/classification_accuracy_evaluation/calculate_accuracy.py | from typing import List
from promptflow import log_metric, tool
@tool
def calculate_accuracy(grades: List[str], variant_ids: List[str]):
aggregate_grades = {}
for index in range(len(grades)):
grade = grades[index]
variant_id = variant_ids[index]
if variant_id not in aggregate_grades.k... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/classification_accuracy_evaluation/expected_status_summary.json | {
"grade.completed": 3,
"calculate_accuracy.completed": 1,
"aggregation_assert.completed": 1
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/classification_accuracy_evaluation/grade.py | from promptflow import tool
@tool
def grade(groundtruth: str, prediction: str):
groundtruth = groundtruth.lower().strip('"')
prediction = prediction.lower().strip('"')
return "Correct" if groundtruth == prediction else "Incorrect"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/classification_accuracy_evaluation/flow.dag.yaml | inputs:
variant_id:
type: string
groundtruth:
type: string
description: Please specify the groundtruth column, which contains the true label
to the outputs that your flow produces.
prediction:
type: string
description: Please specify the prediction column, which contains the predicted
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/classification_accuracy_evaluation/samples.json | [
{
"line_number": 0,
"variant_id": "variant_0",
"groundtruth": "App",
"prediction": "App"
},
{
"line_number": 1,
"variant_id": "variant_0",
"groundtruth": "Pdf",
"prediction": "PDF"
},
{
"line_number": 2,
"variant_id": "variant_0",
"groundtruth": "App",
"predic... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/classification_accuracy_evaluation | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/classification_accuracy_evaluation/.promptflow/flow.tools.json | {
"package": {},
"code": {
"grade.py": {
"type": "python",
"inputs": {
"groundtruth": {
"type": [
"string"
]
},
"prediction": {
"type": [
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants_unordered/classify_with_llm.jinja2 | Your task is to classify a given url into one of the following types:
Movie, App, Academic, Channel, Profile, PDF or None based on the text content information.
The classification will be based on the url, the webpage text content summary, or both.
Here are a few examples:
{% for ex in examples %}
URL: {{ex.url}}
Text... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants_unordered/fetch_text_content_from_url.py | import bs4
import requests
from promptflow import tool
@tool
def fetch_text_content_from_url(url: str):
# Send a request to the URL
try:
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36 Edg/113.0.177... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants_unordered/convert_to_dict.py | import json
from promptflow import tool
@tool
def convert_to_dict(input_str: str):
try:
return json.loads(input_str)
except Exception as e:
print("input is not valid, error: {}".format(e))
return {"category": "None", "evidence": "None"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants_unordered/summarize_text_content__variant_1.jinja2 | Please summarize some keywords of this paragraph and have some details of each keywords.
Do not add any information that is not in the text.
Text: {{text}}
Summary:
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants_unordered/summarize_text_content.jinja2 | Please summarize the following text in one paragraph. 100 words.
Do not add any information that is not in the text.
Text: {{text}}
Summary:
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants_unordered/flow.dag.yaml | inputs:
url:
type: string
default: https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h
outputs:
category:
type: string
reference: ${convert_to_dict.output.category}
evidence:
type: string
reference: ${convert_to_dict.output.evidence}
nodes:... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants_unordered/prepare_examples.py | from promptflow import tool
@tool
def prepare_examples():
return [
{
"url": "https://play.google.com/store/apps/details?id=com.spotify.music",
"text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers au... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants_unordered/samples.json | [
{
"line_number": 0,
"variant_id": "variant_0",
"groundtruth": "App",
"prediction": "App"
}
]
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_requirements_txt/requirements.txt | langchain
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_requirements_txt/flow.dag.yaml | inputs:
key:
type: string
outputs:
output:
type: string
reference: ${print_env.output.value}
nodes:
- name: print_env
type: python
source:
type: code
path: print_env.py
inputs:
key: ${inputs.key}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_requirements_txt/print_env.py | import os
from promptflow import tool
@tool
def get_env_var(key: str):
from langchain import __version__
print(__version__)
print(os.environ.get(key))
# get from env var
return {"value": os.environ.get(key)}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/long_run/long_run.py | import time
from promptflow import tool
def f1():
time.sleep(61)
return 0
def f2():
return f1()
@tool
def long_run_func():
return f2()
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/long_run/flow.dag.yaml | inputs: {}
outputs:
output:
type: string
reference: ${long_run_node.output}
nodes:
- name: long_run_node
type: python
inputs: {}
source:
type: code
path: long_run.py
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/simple_flow_with_python_tool/divide_num.py | from promptflow import tool
@tool
def divide_num(num: int) -> int:
return (int)(num / 2)
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/simple_flow_with_python_tool/flow.dag.yaml | inputs:
num:
type: int
outputs:
content:
type: string
reference: ${divide_num.output}
nodes:
- name: divide_num
type: python
source:
type: code
path: divide_num.py
inputs:
num: ${inputs.num}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/simple_flow_with_python_tool/inputs.jsonl | {"num": "hello"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_with_additional_include/classify_with_llm.jinja2 | system:
Your task is to classify a given url into one of the following types:
Movie, App, Academic, Channel, Profile, PDF or None based on the text content information.
The classification will be based on the url, the webpage text content summary, or both.
user:
Here are a few examples:
{% for ex in examples %}
URL: {... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_with_additional_include/summarize_text_content__variant_1.jinja2 | system:
Please summarize some keywords of this paragraph and have some details of each keywords.
Do not add any information that is not in the text.
user:
Text: {{text}}
Summary:
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_with_additional_include/flow.dag.yaml | inputs:
url:
type: string
default: https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h
outputs:
category:
type: string
reference: ${convert_to_dict.output.category}
evidence:
type: string
reference: ${convert_to_dict.output.evidence}
nodes:... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_with_additional_include/prepare_examples.py | from pathlib import Path
from promptflow import tool
# read file from additional includes
lines = open(r"fetch_text_content_from_url.py", "r").readlines()
@tool
def prepare_examples():
if not Path("summarize_text_content.jinja2").exists():
raise Exception("Cannot find summarize_text_content.jinja2")
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_with_additional_include/samples.json | [
{
"line_number": 0,
"variant_id": "variant_0",
"groundtruth": "App",
"prediction": "App"
}
]
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/all_nodes_bypassed/test.py | from promptflow import tool
@tool
def test(text: str):
return text + "hello world!"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/all_nodes_bypassed/flow.dag.yaml | name: all_nodes_bypassed
inputs:
text:
type: string
outputs:
result:
type: string
reference: ${third_node.output}
nodes:
- name: first_node
type: python
source:
type: code
path: test.py
inputs:
text: ${inputs.text}
activate:
when: ${inputs.text}
is: "hello"
- name: second_nod... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/all_nodes_bypassed/inputs.json | {
"text": "bypass"
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/print_secret_flow/print_secret.py | import os
from promptflow import tool
from promptflow.connections import CustomConnection
@tool
def print_secret(text: str, connection: CustomConnection):
print(connection["key1"])
print(connection["key2"])
return text
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/print_secret_flow/flow.dag.yaml | inputs:
key:
type: string
default: text
outputs:
output:
type: string
reference: ${print_secret.output}
nodes:
- name: print_secret
type: python
source:
type: code
path: print_secret.py
inputs:
connection: custom_connection
text: ${inputs.key}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v1/classify_with_llm.jinja2 | Your task is to classify a given url into one of the following types:
Movie, App, Academic, Channel, Profile, PDF or None based on the text content information.
The classification will be based on the url, the webpage text content summary, or both.
Here are a few examples:
{% for ex in examples %}
URL: {{ex.url}}
Text... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v1/fetch_text_content_from_url.py | import bs4
import requests
from promptflow import tool
@tool
def fetch_text_content_from_url(url: str):
# Send a request to the URL
try:
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36 Edg/113.0.177... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v1/convert_to_dict.py | import json
from promptflow import tool
@tool
def convert_to_dict(input_str: str):
try:
return json.loads(input_str)
except Exception as e:
print("input is not valid, error: {}".format(e))
return {"category": "None", "evidence": "None"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v1/summarize_text_content__variant_1.jinja2 | Please summarize some keywords of this paragraph and have some details of each keywords.
Do not add any information that is not in the text.
Text: {{text}}
Summary:
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v1/summarize_text_content.jinja2 | Please summarize the following text in one paragraph. 100 words.
Do not add any information that is not in the text.
Text: {{text}}
Summary:
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v1/flow.dag.yaml | inputs:
url:
type: string
default: https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h
outputs:
category:
type: string
reference: ${convert_to_dict.output.category}
evidence:
type: string
reference: ${convert_to_dict.output.evidence}
nodes:... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v1/prepare_examples.py | from promptflow import tool
@tool
def prepare_examples():
return [
{
"url": "https://play.google.com/store/apps/details?id=com.spotify.music",
"text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers au... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v1/samples.json | [
{
"url": "https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h"
},
{
"url": "https://www.microsoft.com/en-us/windows/"
}
]
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v1 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v1/.promptflow/flow.tools.json | {
"package": {},
"code": {
"fetch_text_content_from_url.py": {
"type": "python",
"inputs": {
"url": {
"type": [
"string"
]
}
},
"function": "fetch_text_content_... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/saved_component_spec/parallel.yaml | creation_context:
created_at: xxx
created_by: xxx
created_by_type: xxx
last_modified_at: xxx
last_modified_by: xxx
last_modified_by_type: xxx
description: Create flows that use large language models to classify URLs into multiple
categories.
display_name: web_classification_4
error_threshold: -1
id: azure... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/openai_completion_api_flow/completion.py | from openai.version import VERSION as OPENAI_VERSION
import openai
from promptflow import tool
from promptflow.connections import AzureOpenAIConnection
IS_LEGACY_OPENAI = OPENAI_VERSION.startswith("0.")
def get_client(connection: AzureOpenAIConnection):
api_key = connection.api_key
conn = dict(
api_... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/openai_completion_api_flow/flow.dag.yaml | inputs:
prompt:
type: string
stream:
type: bool
outputs:
output:
type: string
reference: ${completion.output}
nodes:
- name: completion
type: python
source:
type: code
path: completion.py
inputs:
prompt: ${inputs.prompt}
connection: azure_open_ai_connection
stream: ${inpu... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/openai_completion_api_flow/inputs.jsonl | {"prompt": "What is the capital of the United States of America?", "stream": true}
{"prompt": "What is the capital of the United States of America?", "stream": false}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/openai_completion_api_flow/samples.json | {
"prompt": "What is the capital of the United States of America?"
}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_with_python_node_streaming_output/stream.py | from promptflow import tool
from typing import Generator, List
def stream(question: str) -> Generator[str, None, None]:
for word in question:
yield word
@tool
def my_python_tool(chat_history: List[dict], question: str) -> dict:
return {"answer": stream(question)}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_with_python_node_streaming_output/flow.dag.yaml | inputs:
chat_history:
type: list
is_chat_history: true
question:
type: string
is_chat_input: true
outputs:
answer:
type: string
reference: ${stream.output.answer}
is_chat_output: true
nodes:
- name: stream
type: python
source:
type: code
path: stream.py
inputs:
chat_h... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/llm_tool/echo.py | from promptflow import tool
@tool
def echo(input: str) -> str:
return input
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/llm_tool/joke.jinja2 | {# Prompt is a jinja2 template that generates prompt for LLM #}
system:
You are a bot can tell good jokes
user:
A joke about {{topic}} please
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/llm_tool/flow.dag.yaml | inputs:
topic:
type: string
default: hello world
is_chat_input: false
stream:
type: bool
default: false
is_chat_input: false
outputs:
joke:
type: string
reference: ${echo.output}
nodes:
- name: echo
type: python
source:
type: code
path: echo.py
inputs:
input: ${jo... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_tool_with_init/flow.dag.yaml | inputs:
input:
type: string
default: World
outputs:
output:
type: string
reference: ${script_tool_with_init.output}
nodes:
- name: script_tool_with_init
type: python
source:
type: code
path: script_tool_with_init.py
inputs:
init_input: Hello
input: ${inputs.input}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_tool_with_init/script_tool_with_init.py | from promptflow import ToolProvider, tool
class ScriptToolWithInit(ToolProvider):
def __init__(self, init_input: str):
super().__init__()
self.init_input = init_input
@tool
def call(self, input: str):
return str.join(" ", [self.init_input, input])
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/classify_with_llm.jinja2 | system:
Your task is to classify a given url into one of the following types:
Movie, App, Academic, Channel, Profile, PDF or None based on the text content information.
The classification will be based on the url, the webpage text content summary, or both.
user:
Here are a few examples:
{% for ex in examples %}
URL: {... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/fetch_text_content_from_url.py | import bs4
import requests
from promptflow import tool
@tool
def fetch_text_content_from_url(url: str):
# Send a request to the URL
try:
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36 Edg/113.0.177... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/convert_to_dict.py | import json
from promptflow import tool
@tool
def convert_to_dict(input_str: str):
try:
return json.loads(input_str)
except Exception as e:
print("input is not valid, error: {}".format(e))
return {"category": "None", "evidence": "None"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/summarize_text_content__variant_1.jinja2 | system:
Please summarize some keywords of this paragraph and have some details of each keywords.
Do not add any information that is not in the text.
user:
Text: {{text}}
Summary: | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/summarize_text_content.jinja2 | system:
Please summarize the following text in one paragraph. 100 words.
Do not add any information that is not in the text.
user:
Text: {{text}}
Summary:
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/flow.dag.yaml | inputs:
url:
type: string
default: https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h
outputs:
category:
type: string
reference: ${convert_to_dict.output.category}
evidence:
type: string
reference: ${convert_to_dict.output.evidence}
nodes:... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/prepare_examples.py | from promptflow import tool
@tool
def prepare_examples():
return [
{
"url": "https://play.google.com/store/apps/details?id=com.spotify.music",
"text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers au... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/samples.json | [
{
"url": "https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h"
},
{
"url": "https://www.microsoft.com/en-us/windows/"
}
] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow/flow.tools.json | {
"package": {},
"code": {
"fetch_text_content_from_url.py": {
"type": "python",
"inputs": {
"url": {
"type": [
"string"
]
}
},
"function": "fetch_text_content_... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow/flow.env_files/setup.sh | #!/bin/bash
# Install your packages here.
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow/lkg_sources/classify_with_llm.jinja2 | Your task is to classify a given url into one of the following types:
Movie, App, Academic, Channel, Profile, PDF or None based on the text content information.
The classification will be based on the url, the webpage text content summary, or both.
Here are a few examples:
{% for ex in examples %}
URL: {{ex.url}}
Text... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow/lkg_sources/fetch_text_content_from_url.py | import bs4
import requests
from promptflow import tool
@tool
def fetch_text_content_from_url(url: str):
# Send a request to the URL
try:
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36 Edg/113.0.177... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow/lkg_sources/convert_to_dict.py | import json
from promptflow import tool
@tool
def convert_to_dict(input_str: str):
try:
return json.loads(input_str)
except Exception as e:
print("input is not valid, error: {}".format(e))
return {"category": "None", "evidence": "None"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow/lkg_sources/summarize_text_content__variant_1.jinja2 | Please summarize some keywords of this paragraph and have some details of each keywords.
Do not add any information that is not in the text.
Text: {{text}}
Summary:
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow/lkg_sources/summarize_text_content.jinja2 | Please summarize the following text in one paragraph. 100 words.
Do not add any information that is not in the text.
Text: {{text}}
Summary:
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_no_variants/.promptflow/lkg_sources/prepare_examples.py | from promptflow import tool
@tool
def prepare_examples():
return [
{
"url": "https://play.google.com/store/apps/details?id=com.spotify.music",
"text_content": "Spotify is a free music and podcast streaming app with millions of songs, albums, and original podcasts. It also offers au... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/activate_flow/print_input.py | from promptflow import tool
@tool
def print_input(input: str) -> str:
return input
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/activate_flow/flow.dag.yaml | inputs:
text:
type: string
default: world
outputs:
output1:
type: string
reference: ${nodeC.output}
output2:
type: string
reference: ${nodeD.output}
nodes:
- name: nodeA
type: python
source:
type: code
path: print_input.py
inputs:
input: ${inputs.text}
activate:
whe... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/hello-world/hello_world.py | from promptflow import tool
@tool
def hello_world(name: str) -> str:
return f"Hello World {name}!"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/hello-world/flow.dag.yaml | inputs:
name:
type: string
default: hod
outputs:
result:
type: string
reference: ${hello_world.output}
nodes:
- name: hello_world
type: python
source:
type: code
path: hello_world.py
inputs:
name: ${inputs.name}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/hello-world | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/hello-world/.promptflow/flow.tools.json | {
"code": {
"hello_world.py": {
"type": "python",
"inputs": {
"name": {
"type": [
"string"
]
}
},
"source": "hello_world.py",
"function": "hello_world"
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/generator_nodes/echo.py | from promptflow import tool
@tool
def echo(text):
"""yield the input string."""
echo_text = "Echo - " + text
for word in echo_text.split():
yield word | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/generator_nodes/flow.dag.yaml | inputs:
text:
type: string
outputs:
answer:
type: string
reference: ${echo_generator.output}
nodes:
- name: echo_generator
type: python
source:
type: code
path: echo.py
inputs:
text: ${inputs.text}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/async_tools_failures/async_fail.py | from promptflow import tool
async def raise_exception_async(s):
msg = f"In raise_exception_async: {s}"
raise Exception(msg)
@tool
async def raise_an_exception_async(s: str):
try:
await raise_exception_async(s)
except Exception as e:
raise Exception(f"In tool raise_an_exception_async: ... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/async_tools_failures/flow.dag.yaml | inputs:
text:
type: string
default: dummy_input
outputs:
output_prompt:
type: string
reference: ${async_fail.output}
nodes:
- name: async_fail
type: python
source:
type: code
path: async_fail.py
inputs:
s: ${inputs.text}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_additional_include_req/flow.dag.yaml | inputs:
key:
type: string
outputs:
output:
type: string
reference: ${print_env.output.value}
nodes:
- name: print_env
type: python
source:
type: code
path: print_env.py
inputs:
key: ${inputs.key}
additional_includes:
- ../flow_with_environment/requirements
environment:
python_requi... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_additional_include_req/print_env.py | import os
from promptflow import tool
@tool
def get_env_var(key: str):
from tensorflow import __version__
print(__version__)
print(os.environ.get(key))
# get from env var
return {"value": os.environ.get(key)}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_with_default_history/chat.jinja2 | system:
You are a helpful assistant.
{% for item in chat_history %}
user:
{{item.inputs.question}}
assistant:
{{item.outputs.answer}}
{% endfor %}
user:
{{question}} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_with_default_history/flow.dag.yaml | inputs:
chat_history:
type: list
is_chat_history: true
default:
- inputs:
question: hi
outputs:
answer: hi
- inputs:
question: who are you
outputs:
answer: who are you
question:
type: string
is_chat_input: true
default: What... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_with_image/mock_chat.py | from promptflow import tool
from promptflow.contracts.multimedia import Image
@tool
def mock_chat(chat_history: list, question: list):
ensure_image_in_list(question, "question")
for item in chat_history:
ensure_image_in_list(item["inputs"]["question"], "inputs of chat history")
ensure_image_in... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_with_image/flow.dag.yaml | inputs:
chat_history:
type: list
default:
- inputs:
question:
- the first question
- data:image/jpg;path: logo.jpg
outputs:
answer:
- data:image/jpg;path: logo.jpg
- inputs:
question:
- the second question
- data:image/png;path: log... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_with_image/inputs.jsonl | {"chat_history":[{"inputs": {"question": ["the first question",{"data:image/jpg;path": "logo.jpg"}]},"outputs": {"answer": [{"data:image/jpg;path": "logo.jpg"}]}},{"inputs": {"question": ["the second question",{"data:image/png;path": "logo_2.png"}]},"outputs": {"answer": [{"data:image/png;path": "logo_2.png"}]}}],"ques... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/llm_connection_override/conn_tool.py | from promptflow import tool
from promptflow.connections import AzureOpenAIConnection
@tool
def conn_tool(conn: AzureOpenAIConnection):
assert isinstance(conn, AzureOpenAIConnection)
return conn.api_base | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/llm_connection_override/connection_arm_template.json | {
"id": "/subscriptions/xxxx/resourceGroups/xxx/providers/Microsoft.MachineLearningServices/workspaces/xxx/connections/azure_open_ai_connection",
"name": "azure_open_ai_connection",
"type": "Microsoft.MachineLearningServices/workspaces/connections",
"properties": {
"authType": "ApiKey",
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/llm_connection_override/flow.dag.yaml | inputs: {}
outputs:
output:
type: string
reference: ${conn_node.output}
nodes:
- name: conn_node
type: python
source:
type: code
path: conn_tool.py
inputs:
conn: aoai connection
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v2/classify_with_llm.jinja2 | Your task is to classify a given url into one of the following types:
Movie, App, Academic, Channel, Profile, PDF or None based on the text content information.
The classification will be based on the url, the webpage text content summary, or both.
Here are a few examples:
{% for ex in examples %}
URL: {{ex.url}}
Text... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v2/fetch_text_content_from_url.py | import bs4
import requests
from promptflow import tool
@tool
def fetch_text_content_from_url(url: str):
# Send a request to the URL
try:
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/113.0.0.0 Safari/537.36 Edg/113.0.177... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v2/convert_to_dict.py | import json
from promptflow import tool
@tool
def convert_to_dict(input_str: str):
try:
return json.loads(input_str)
except Exception as e:
print("input is not valid, error: {}".format(e))
return {"category": "None", "evidence": "None"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v2/summarize_text_content__variant_1.jinja2 | Please summarize some keywords of this paragraph and have some details of each keywords.
Do not add any information that is not in the text.
Text: {{text}}
Summary:
| 0 |
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