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/csharp_flow/flow.dag.yaml | language: csharp
inputs:
question:
type: string
default: what is promptflow?
outputs:
answer:
type: string
reference: ${get_answer.output}
nodes:
- name: get_answer
type: csharp
source:
type: package
tool: (Basic)Basic.Flow.HelloWorld
inputs:
question: ${inputs.question}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_invalid/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/web_classification_invalid/convert_to_dict.py | import json
import time
from promptflow import tool
# use this to test the timeout
time.sleep(2)
@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... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_invalid/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_invalid/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_invalid/prepare_examples.py | import time
from pathlib import Path
from promptflow import tool
@tool
def prepare_examples():
if not Path("summarize_text_content.jinja2").exists():
raise Exception("Cannot find summarize_text_content.jinja2")
return [
{
"url": "https://play.google.com/store/apps/details?id=com.sp... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_invalid/flow.dag.yaml | inputs:
url:
default: https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h
outputs:
category:
reference: ${convert_to_dict.output.category}
evidence:
type: string
reference: ${convert_to_dict.output.evidence}
nodes:
- name: fetch_text_content_from_u... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/sync_tools_failures/sync_fail.py | from promptflow import tool
def raise_exception(s):
msg = f"In raise_exception: {s}"
raise Exception(msg)
@tool
def raise_an_exception(s: str):
try:
raise_exception(s)
except Exception as e:
raise Exception(f"In tool raise_an_exception: {s}") from e
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/sync_tools_failures/flow.dag.yaml | inputs:
text:
type: string
default: dummy_input
outputs:
output_prompt:
type: string
reference: ${sync_fail.output}
nodes:
- name: sync_fail
type: python
source:
type: code
path: sync_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/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__/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__.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/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/flow_with_list_input/flow.dag.yaml | inputs:
key:
type: list
outputs:
output:
type: string
reference: ${print_val.output.value}
nodes:
- name: print_val
type: python
source:
type: code
path: print_val.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_list_input/print_val.py | from typing import List
from promptflow import tool
@tool
def get_val(key):
# get from env var
print(key)
return {"value": f"{key}: {type(key)}"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/generator_tools/echo.py | from promptflow import tool
from char_generator import character_generator
@tool
def echo(text):
"""Echo the input string."""
echo_text = "Echo - " + "".join(character_generator(text))
return echo_text | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/generator_tools/char_generator.py | from promptflow import tool
@tool
def character_generator(text: str):
"""Generate characters from a string."""
for char in text:
yield char | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/generator_tools/flow.dag.yaml | inputs:
text:
type: string
outputs:
answer:
type: string
reference: ${echo.output}
nodes:
- name: echo
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/flow-with-nan-inf/nan_inf.py | from promptflow import tool
@tool
def nan_inf(number: int):
print(number)
return {"nan": float("nan"), "inf": float("inf")}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow-with-nan-inf/flow.dag.yaml | inputs:
number:
type: int
outputs:
output:
type: object
reference: ${nan_inf.output}
nodes:
- name: nan_inf
type: python
source:
type: code
path: nan_inf.py
inputs:
number: ${inputs.number}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/README.md | Exported Dockerfile & its dependencies are located in the same folder. The structure is as below:
- flow: the folder contains all the flow files
- ...
- connections: the folder contains yaml files to create all related connections
- ...
- runit: the folder contains all the runit scripts
- ...
- Dockerfile: the do... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/Dockerfile | # syntax=docker/dockerfile:1
FROM docker.io/continuumio/miniconda3:latest
WORKDIR /
COPY ./flow /flow
# create conda environment
RUN conda create -n promptflow-serve python=3.9.16 pip=23.0.1 -q -y && \
conda run -n promptflow-serve \
pip install -r /flow/requirements_txt && \
conda run -n promptflow-serv... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/settings.json | {
"CUSTOM_CONNECTION_AZURE_OPENAI_API_KEY": ""
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/start.sh | #!/bin/bash
# stop services created by runsv and propagate SIGINT, SIGTERM to child jobs
sv_stop() {
echo "$(date -uIns) - Stopping all runsv services"
for s in $(ls -d /var/runit/*); do
sv stop $s
done
}
# register SIGINT, SIGTERM handler
trap sv_stop SIGINT SIGTERM
# start services in backgroun... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/runit | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/runit/promptflow-serve/run | #! /bin/bash
CONDA_ENV_PATH="$(conda info --base)/envs/promptflow-serve"
export PATH="$CONDA_ENV_PATH/bin:$PATH"
ls
ls /connections
pf connection create --file /connections/custom_connection.yaml
echo "start promptflow serving with worker_num: 8, worker_threads: 1"
cd /flow
gunicorn -w 8 --threads 1 -b "0.0.0.0:8080"... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/runit | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/runit/promptflow-serve/finish | #!/bin/bash
echo "$(date -uIns) - promptflow-serve/finish $@"
# stop all gunicorn processes
echo "$(date -uIns) - Stopping all Gunicorn processes"
pkill gunicorn
while pgrep gunicorn >/dev/null; do
echo "$(date -uIns) - Gunicorn process is still running, waiting for 1s"
sleep 1
done
echo "$(date -uIns) - Stopped... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/connections/custom_connection.yaml | $schema: https://azuremlschemas.azureedge.net/promptflow/latest/CustomConnection.schema.json
type: custom
name: custom_connection
configs:
CHAT_DEPLOYMENT_NAME: gpt-35-turbo
AZURE_OPENAI_API_BASE: https://gpt-test-eus.openai.azure.com/
secrets:
AZURE_OPENAI_API_KEY: ${env:CUSTOM_CONNECTION_AZURE_OPENAI_API_KEY}
m... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/flow/user_intent_few_shot.jinja2 | You are given a list of orders with item_numbers from a customer and a statement from the customer. It is your job to identify
the intent that the customer has with their statement. Possible intents can be:
"product return", "product exchange", "general question", "product question", "other".
If the intent is product ... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/flow/user_intent_zero_shot.jinja2 | You are given a list of orders with item_numbers from a customer and a statement from the customer. It is your job to identify
the intent that the customer has with their statement. Possible intents can be:
"product return", "product exchange", "general question", "product question", "other".
In triple backticks... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/flow/requirements_txt | keyrings.alt
promptflow-tools
promptflow
langchain
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/flow/intent.py | import os
import pip
def extract_intent(chat_prompt: str):
from langchain.chat_models import AzureChatOpenAI
from langchain.schema import HumanMessage
if "AZURE_OPENAI_API_KEY" not in os.environ:
# load environment variables from .env file
try:
from dotenv import load_dotenv
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/flow/setup.sh | echo Hello Promptflow!
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/flow/.amlignore | *.ipynb
.venv/
.data/
.env
.vscode/
outputs/
connection.json
.gitignore
README.md
eval_cli.md
data/
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/flow/extract_intent_tool.py | import os
from promptflow import tool
from promptflow.connections import CustomConnection
from intent import extract_intent
@tool
def extract_intent_tool(
chat_prompt,
connection: CustomConnection) -> str:
# set environment variables
for key, value in dict(connection).items():
os.environ[ke... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/flow/flow.dag.yaml | inputs:
customer_info:
type: string
chat_history:
type: string
outputs:
output:
type: string
reference: ${extract_intent.output}
nodes:
- name: chat_prompt
type: prompt
source:
type: code
path: user_intent_zero_shot.jinja2
inputs: # Please check the generated prompt inputs
custo... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/llm_tool_with_duplicated_inputs/prompt_with_duplicated_inputs.jinja2 | {{prompt}} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/llm_tool_with_duplicated_inputs/flow.dag.yaml | inputs:
text:
type: string
outputs:
output_prompt:
type: string
reference: ${llm_tool_with_duplicated_inputs.output}
nodes:
- name: llm_tool_with_duplicated_inputs
type: llm
provider: AzureOpenAI
api: completion
module: promptflow.tools.aoai
connection: azure_open_ai_connection
source:
t... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_environment_variables/inputs.jsonl | {"text": "env1"}
{"text": "env2"}
{"text": "env3"}
{"text": "env4"}
{"text": "env5"}
{"text": "env10"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_environment_variables/flow.dag.yaml | environment_variables:
env1: 2
env2: spawn
env3:
- 1
- 2
- 3
- 4
- 5
env4:
a: 1
b: "2"
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:
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_environment_variables/print_env.py | import os
from promptflow import tool
@tool
def get_env_var(key: str):
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_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/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/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/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/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/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/flow_with_sys_inject/hello.py | import os
import sys
from promptflow import tool
sys.path.append(f"{os.path.dirname(__file__)}/custom_lib")
from custom_lib.foo import foo
@tool
def my_python_tool(input1: str) -> str:
return foo(param=input1)
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_sys_inject/flow.dag.yaml | inputs:
text:
type: string
outputs:
output_prompt:
type: string
reference: ${echo_my_prompt.output}
nodes:
- inputs:
input1: ${inputs.text}
name: echo_my_prompt
type: python
source:
type: code
path: hello.py
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_sys_inject | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_sys_inject/custom_lib/foo.py | def foo(param: str) -> str:
return f"{param} from func foo"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/python_tool_with_image_nested_api_calls/passthrough.py | from promptflow import tool
@tool
def passthrough(image, call_passthrough: bool = True):
if call_passthrough:
image = passthrough(image, False)
return image
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/python_tool_with_image_nested_api_calls/flow.dag.yaml | inputs:
image:
type: image
default: logo.jpg
outputs:
output:
type: image
reference: ${python_node.output}
nodes:
- name: python_node
type: python
source:
type: code
path: passthrough.py
inputs:
image: ${inputs.image}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/package_tools/flow.dag.yaml | inputs:
text:
type: string
outputs:
output:
type: string
reference: ${search_by_text.output.search_metadata}
nodes:
- name: search_by_text
type: python
source:
type: package
tool: promptflow.tools.serpapi.SerpAPI.search
inputs:
connection: serp_connection
query: ${inputs.text}
... | 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/prompt_tools/summarize_text_content_prompt.jinja2 | Please summarize the following content in one paragraph. 50 words.
Do not add any information that is not in the content.
Text: {{text}}
Images:
Video:
Summary: | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/prompt_tools/summarize_text_content_prompt.meta.json | {
"name": "summarize_text_content_prompt",
"type": "prompt",
"inputs": {
"text": {
"type": [
"string"
]
},
"image1": {
"type": [
"image"
]
},
"image2": {
"type": [
"image"
]
},
"image3": {
"type": [
"image"
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/prompt_tools/flow.dag.yaml | inputs:
text:
type: string
outputs:
output_prompt:
type: string
reference: ${summarize_text_content_prompt.output}
nodes:
- name: summarize_text_content_prompt
type: prompt
source:
type: code
path: summarize_text_content_prompt.jinja2
inputs:
text: ${inputs.text} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/print_input_flow/inputs.jsonl | {"text": "text_0"}
{"text": "text_1"}
{"text": "text_2"}
{"text": "text_3"}
{"text": "text_4"}
{"text": "text_5"}
{"text": "text_6"}
{"text": "text_7"}
{"text": "text_8"}
{"text": "text_9"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/print_input_flow/print_input.py | from promptflow import tool
import sys
@tool
def print_inputs(
text: str = None,
):
print(f"STDOUT: {text}")
print(f"STDERR: {text}", file=sys.stderr)
return text
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/print_input_flow/flow.dag.yaml | inputs:
text:
type: string
outputs:
output_text:
type: string
reference: ${print_input.output}
nodes:
- name: print_input
type: python
source:
type: code
path: print_input.py
inputs:
text: ${inputs.text}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_invalid_import/hello.py | import package_not_exist
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_invalid_import/flow.dag.yaml | inputs:
text:
type: string
outputs:
output_prompt:
type: string
reference: ${echo_my_prompt.output}
nodes:
- inputs:
text: ${inputs.text}
name: echo_my_prompt
type: python
source:
type: code
path: hello.py
node_variants: {}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/unordered_nodes/flow.dag.yaml | name: node_wrong_order
inputs:
text:
type: string
outputs:
result:
type: string
reference: ${third_node}
nodes:
- name: third_node
type: python
source:
type: code
path: test.py
inputs:
text: ${second_node}
- name: first_node
type: python
source:
type: code
path: test.py
i... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_package_tool_with_custom_connection/data.jsonl | {"text": "Hello World!"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_package_tool_with_custom_connection/flow.dag.yaml | inputs:
text:
type: string
default: Hello!
outputs:
out:
type: string
reference: ${my_first_tool.output}
nodes:
- name: my_first_tool
type: python
source:
type: package
tool: my_tool_package.tools.my_tool_1.my_tool
inputs:
connection: custom_connection_3
input_text: ${inputs.te... | 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/script_with_special_character/script_with_special_character.py | from promptflow import tool
@tool
def print_special_character(input1: str) -> str:
# Add special character to test if file read is working.
return "https://www.bing.com//"
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with_special_character/script_with_special_character.meta.json | {
"name": "script_with_special_character",
"type": "python",
"inputs": {
"input1": {
"type": [
"string"
]
}
},
"source": "script_with_special_character.py",
"function": "print_special_character"
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/simple_flow_with_python_tool_and_aggregate/aggregate_num.py | import statistics
from typing import List
from promptflow import tool
@tool
def aggregate_num(num: List[int]) -> int:
return statistics.mean(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_and_aggregate/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_and_aggregate/flow.dag.yaml | inputs:
num:
type: int
outputs:
content:
type: string
reference: ${divide_num.output}
aggregate_content:
type: string
reference: ${aggregate_num.output}
nodes:
- name: divide_num
type: python
source:
type: code
path: divide_num.py
inputs:
num: ${inputs.num}
- name: aggregate_... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/unordered_nodes_with_activate/flow.dag.yaml | name: node_wrong_order
inputs:
text:
type: string
skip:
type: bool
outputs:
result:
type: string
reference: ${third_node}
nodes:
- name: third_node
type: python
source:
type: code
path: test.py
inputs:
text: ${second_node}
- name: first_node
type: python
source:
type: cod... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/partial_fail/data.jsonl | {"key": "no"}
{"key": "raise"}
{"key": "matter"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/partial_fail/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/partial_fail/print_env.py | import os
from promptflow import tool
@tool
def get_env_var(key: str):
if key == "raise":
raise Exception("expected raise!")
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/web_classification_v2/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/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/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/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/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_v2/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_v2/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_v2/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_v2 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_v2/.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/async_tools_with_sync_tools/sync_passthrough.py | from promptflow import tool
import time
@tool
def passthrough_str_and_wait_sync(input1: str, wait_seconds=3) -> str:
assert isinstance(input1, str), f"input1 should be a string, got {input1}"
print(f"Wait for {wait_seconds} seconds in sync function")
for i in range(wait_seconds):
print(i)
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/async_tools_with_sync_tools/flow.dag.yaml | inputs:
input_str:
type: string
default: Hello
outputs:
ouput1:
type: string
reference: ${async_passthrough1.output}
output2:
type: string
reference: ${sync_passthrough1.output}
nodes:
- name: async_passthrough
type: python
source:
type: code
path: async_passthrough.py
inputs... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/async_tools_with_sync_tools/async_passthrough.py | from promptflow import tool
import asyncio
@tool
async def passthrough_str_and_wait(input1: str, wait_seconds=3, wait_seconds_in_cancellation=1) -> str:
assert isinstance(input1, str), f"input1 should be a string, got {input1}"
try:
print(f"Wait for {wait_seconds} seconds in async function")
f... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_langchain_traces/test_langchain_traces.py | import os
from langchain.chat_models import AzureChatOpenAI
from langchain_core.messages import HumanMessage
from langchain.agents.agent_types import AgentType
from langchain.agents.initialize import initialize_agent
from langchain.agents.load_tools import load_tools
from promptflow import tool
from promptflow.connec... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_langchain_traces/samples.json | [
{
"question": "What is 2 to the 10th power?"
},
{
"question": "What is the sum of 2 and 2?"
}
] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_langchain_traces/inputs.jsonl | {"question": "What is 2 to the 10th power?"}
{"question": "What is the sum of 2 and 2?"} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_langchain_traces/code_first_input.csv | question
What is 2 to the 10th power?
What is the sum of 2 and 2?
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_langchain_traces/data_inputs.json | {
"data": "code_first_input.csv"
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_langchain_traces/flow.dag.yaml | inputs:
question:
type: string
outputs:
output:
type: string
reference: ${test_langchain_traces.output}
nodes:
- name: test_langchain_traces
type: python
source:
type: code
path: test_langchain_traces.py
inputs:
question: ${inputs.question}
conn: azure_open_ai_connection
| 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/chat_flow/show_answer.py | from promptflow import tool
@tool
def show_answer(chat_answer: str):
print("print:", chat_answer)
return chat_answer
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow/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 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.