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/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 | 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/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/samples.json | [
{
"line_number": 0,
"variant_id": "variant_0",
"groundtruth": "App",
"prediction": "App"
}
]
| 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/flow_with_trace_async/flow.dag.yaml | inputs:
user_id:
type: int
default: 1
outputs:
output:
type: string
reference: ${greetings.output.greeting}
nodes:
- name: greetings
type: python
source:
type: code
path: greetings.py
inputs:
user_id: ${inputs.user_id}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_trace_async/greetings.py | import asyncio
from time import sleep
from promptflow import tool, trace
@trace
async def is_valid_name(name):
await asyncio.sleep(0.5)
return len(name) > 0
@trace
async def get_user_name(user_id):
await asyncio.sleep(0.5)
user_name = f"User {user_id}"
if not await is_valid_name(user_name):
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/tool_with_assistant_definition/assistant_definition.yaml | model: mock_model
instructions: mock_instructions
tools:
- type: function
tool_type: python
source:
type: code
path: echo.py
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/tool_with_assistant_definition/echo.py | from promptflow import tool
@tool
def echo(message: str):
"""This tool is used to echo the message back.
:param message: The message to echo.
:type message: str
"""
return message
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/tool_with_assistant_definition/test_assistant_definition.py | from promptflow import tool
from promptflow.contracts.types import AssistantDefinition
@tool
def test_assistant_definition(message: str, assistant_definition: AssistantDefinition):
assert assistant_definition.model == "mock_model"
assert assistant_definition.instructions == "mock_instructions"
invoker = a... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/tool_with_assistant_definition/flow.dag.yaml | inputs:
message:
type: string
default: Hello World!
outputs:
output:
type: object
reference: ${test_assistant_definition.output}
nodes:
- name: test_assistant_definition
type: python
source:
type: code
path: test_assistant_definition.py
inputs:
message: ${inputs.message}
assist... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/Dockerfile | # syntax=docker/dockerfile:1
FROM docker.io/continuumio/miniconda3:latest
WORKDIR /
COPY ./flow /flow
# create conda environment
RUN conda create -n promptflow-serve python=3.9.16 pip=23.0.1 -q -y && \
conda run -n promptflow-serve \
pip install -r /flow/requirements_txt && \
conda run -n promptflow-serv... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/start.sh | #!/bin/bash
# stop services created by runsv and propagate SIGINT, SIGTERM to child jobs
sv_stop() {
echo "$(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 | 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/settings.json | {
"CUSTOM_CONNECTION_AZURE_OPENAI_API_KEY": ""
} | 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: ${env:CUSTOM_CONNECTION_AZURE_OPENAI_API_KEY}
m... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/runit | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/export/linux/runit/promptflow-serve/run | #! /bin/bash
CONDA_ENV_PATH="$(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/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/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/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/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/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/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/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/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 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/python_tool_with_invalid_default_value/pick_an_image.py | import random
from promptflow.contracts.multimedia import Image
from promptflow import tool
@tool
def pick_an_image(image_1: Image, image_2: Image) -> Image:
if random.choice([True, False]):
return image_1
else:
return image_2
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/python_tool_with_invalid_default_value/flow.dag.yaml | inputs:
image:
type: image
default: ""
outputs:
output:
type: image
reference: ${python_node_2.output}
nodes:
- name: python_node
type: python
source:
type: code
path: pick_an_image.py
inputs:
image_1: ${inputs.image}
image_2: logo_2.png
- name: python_node_2
type: python
s... | 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/csharp_flow/inputs.jsonl | {"question": "What's promptflow1?"}
{"question": "What's promptflow2?"}
{"question": "What's promptflow3?"} | 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 | 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/chat_flow_with_exception/show_answer.py | from promptflow import tool
@tool
def show_answer(chat_answer: str):
raise Exception("mock exception")
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_with_exception/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_exception/flow.dag.yaml | inputs:
chat_history:
type: list
question:
type: string
is_chat_input: true
default: What is ChatGPT?
outputs:
answer:
type: string
reference: ${show_answer.output}
is_chat_output: true
nodes:
- inputs:
deployment_name: gpt-35-turbo
max_tokens: "256"
temperature: "0.7"
... | 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/async_tools/async_passthrough.py | from promptflow import tool
import asyncio
@tool
async def passthrough_str_and_wait(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 async 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/flow.dag.yaml | inputs:
input_str:
type: string
default: Hello
outputs:
ouput1:
type: string
reference: ${async_passthrough1.output}
output2:
type: string
reference: ${async_passthrough2.output}
nodes:
- name: async_passthrough
type: python
source:
type: code
path: async_passthrough.py
input... | 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/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/python_tool_with_simple_image_without_default/pick_an_image.py | import random
from promptflow.contracts.multimedia import Image
from promptflow import tool
@tool
def pick_an_image(image_1: Image, image_2: Image) -> Image:
if random.choice([True, False]):
return image_1
else:
return image_2
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/python_tool_with_simple_image_without_default/flow.dag.yaml | inputs:
image_1:
type: image
image_2:
type: image
outputs:
output:
type: image
reference: ${python_node.output}
nodes:
- name: python_node
type: python
source:
type: code
path: pick_an_image.py
inputs:
image_1: ${inputs.image_1}
image_2: ${inputs.image_2}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow_with_defined_chat_history/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_with_defined_chat_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_defined_chat_history/flow.dag.yaml | inputs:
user_chat_history:
type: list
is_chat_history: true
question:
type: string
is_chat_input: true
default: What is ChatGPT?
outputs:
answer:
type: string
reference: ${show_answer.output}
is_chat_output: true
nodes:
- inputs:
deployment_name: gpt-35-turbo
max_tokens: "2... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_input_dir/details.jsonl | {"url": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "answer": "Channel", "evidence": "Url"}
{"url": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "answer": "Channel", "evidence": "Url"}
{"url": "https://www.youtube.com/watch?v=o5ZQyXaAv1g", "answer": "Channel", "evidence": "Url"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_script_tool_with_custom_strong_type_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_script_tool_with_custom_strong_type_connection/my_script_tool.py | from promptflow import tool
from promptflow.connections import CustomStrongTypeConnection, CustomConnection
from promptflow.contracts.types import Secret
class MyCustomConnection(CustomStrongTypeConnection):
"""My custom strong type connection.
:param api_key: The api key.
:type api_key: String
:para... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_script_tool_with_custom_strong_type_connection/flow.dag.yaml | inputs:
text:
type: string
default: this is an input
outputs:
out:
type: string
reference: ${my_script_tool.output}
nodes:
- name: my_script_tool
type: python
source:
type: code
path: my_script_tool.py
inputs:
connection: custom_connection_2
input_param: ${inputs.text}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/aggregation_node_failed/data.jsonl | {"groundtruth": "Tomorrow's weather will be sunny.","prediction": "The weather will be sunny tomorrow."}
{"groundtruth": "Hello,","prediction": "World."}
{"groundtruth": "Promptflow is a super easy-to-use tool, right?","prediction": "Yes!"}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/aggregation_node_failed/line_process.py | from promptflow import tool
@tool
def line_process(groundtruth: str, prediction: str):
processed_result = groundtruth + prediction
return processed_result
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/aggregation_node_failed/aggregate.py | from typing import List
from promptflow import tool
@tool
def aggregate(processed_results: List[str]):
aggregated_results = processed_results
# raise error to test aggregation node failed
num = 1/0
return aggregated_results
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/aggregation_node_failed/expected_status_summary.json | {
"line_process.completed": 3,
"aggregate.failed": 1
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/aggregation_node_failed/flow.dag.yaml | id: template_eval_flow
name: Template Evaluation Flow
inputs:
groundtruth:
type: string
is_chat_input: false
prediction:
type: string
is_chat_input: false
outputs:
results:
type: string
reference: ${line_process.output}
nodes:
- name: line_process
type: python
source:
type: code
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/aggregation_node_failed/samples.json | [
{
"groundtruth": "Tomorrow's weather will be sunny.",
"prediction": "The weather will be sunny tomorrow."
},
{
"groundtruth": "Hello,",
"prediction": "World."
},
{
"groundtruth": "Promptflow is a super easy-to-use tool, right?",
"prediction": "Yes!"
}
] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat-with-assistant-no-file/assistant_definition.yaml | model: gpt-4-1106-preview
instructions: You are a helpful assistant.
tools:
- type: code_interpreter
- type: function
source:
type: code
path: get_calorie_by_jogging.py
tool_type: python
- type: function
source:
type: code
path: get_calorie_by_swimming.py
tool_type: python
... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat-with-assistant-no-file/get_or_create_thread.py | from openai import AsyncOpenAI
from promptflow import tool
from promptflow.connections import OpenAIConnection
@tool
async def get_or_create_thread(conn: OpenAIConnection, thread_id: str):
if thread_id:
return thread_id
cli = AsyncOpenAI(api_key=conn.api_key, organization=conn.organization)
threa... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat-with-assistant-no-file/data.jsonl | {"chat_history":[], "question": "If I am going to run with 1.5 hours this morning, how many calories will I burn?", "assistant_id": "asst_yWhdFYoCS1UatnRRQZGY85aL", "thread_id": ""}
{"chat_history":[], "question": "I'm going to swim in Guangzhou city today for 30 min, how much calories will I burn?", "assistant_id": "a... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat-with-assistant-no-file/get_calorie_by_jogging.py | import random
import time
from promptflow import tool
@tool
def get_calorie_by_jogging(duration: float, temperature: float):
"""Estimate the calories burned by jogging based on duration and temperature.
:param duration: the length of the jogging in hours.
:type duration: float
:param temperature: th... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat-with-assistant-no-file/get_current_city.py | import random
import time
from promptflow import tool
@tool
def get_current_city():
"""Get current city."""
# Generating a random number between 0.2 and 1 for tracing purpose
time.sleep(random.uniform(0.2, 1))
return random.choice(["Beijing", "Shanghai"])
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat-with-assistant-no-file/get_temperature.py | import random
import time
from promptflow import tool
@tool
def get_temperature(city: str, unit: str = "c"):
"""Estimate the current temperature of a given city.
:param city: city to get the estimated temperature for.
:type city: str
:param unit: the unit of the temperature, either 'c' for Celsius o... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat-with-assistant-no-file/add_message_and_run.py | import asyncio
import json
from openai import AsyncOpenAI
from openai.types.beta.threads import MessageContentImageFile, MessageContentText
from promptflow import tool, trace
from promptflow.connections import OpenAIConnection
from promptflow.contracts.multimedia import Image
from promptflow.contracts.types import As... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat-with-assistant-no-file/get_calorie_by_swimming.py | import random
import time
from promptflow import tool
@tool
def get_calorie_by_swimming(duration: float, temperature: float):
"""Estimate the calories burned by swimming based on duration and temperature.
:param duration: the length of the swimming in hours.
:type duration: float
:param temperature:... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat-with-assistant-no-file/README.md | # Chat with Calorie Assistant
This sample demonstrates how to chat with the PromptFlow Assistant tool facilitates calorie calculations by considering your location, the duration of your exercise, and the type of sport. Currently, it supports two types of sports: jogging and swimming.
Tools used in this flow：
- `add_m... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat-with-assistant-no-file/flow.dag.yaml | environment:
python_requirements_txt: requirements.txt
version: 2
inputs:
chat_history:
type: list
is_chat_history: true
default: []
question:
type: string
is_chat_input: true
default: I am going to swim today for 30 min in Guangzhou city, how much
calories will I burn?
assistant_i... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/default_input/test_print_input.py | from promptflow import tool
@tool
def test_print_input(input_str: str, input_bool: bool, input_list: list, input_dict: dict):
assert not input_bool
assert input_list == []
assert input_dict == {}
print(input_str)
return input_str | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/default_input/test_print_aggregation.py | from typing import List
from promptflow import tool
@tool
def test_print_input(input_str: List[str], input_bool: List[bool], input_list: List[List], input_dict: List[dict]):
assert input_bool[0] == False
assert input_list[0] == []
assert input_dict[0] == {}
print(input_str)
return input_str | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/default_input/flow.dag.yaml |
inputs:
input_str:
type: string
default: input value from default
input_bool:
type: bool
default: False
input_list:
type: list
default: []
input_dict:
type: object
default: {}
outputs:
output:
type: string
reference: ${test_print_input.output}
nodes:
- name: test_print... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/default_input/samples.json | [
{
"text": "text_1"
}
] | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/assistant-with-file/assistant_definition.yaml | model: gpt-4-1106-preview
instructions: You are a helpful assistant.
tools:
- type: code_interpreter
- type: function
source:
type: code
path: get_stock_eod_price.py
tool_type: python
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/assistant-with-file/get_or_create_thread.py | from openai import AsyncOpenAI
from promptflow import tool
from promptflow.connections import OpenAIConnection
@tool
async def get_or_create_thread(conn: OpenAIConnection, thread_id: str):
if thread_id:
return thread_id
cli = AsyncOpenAI(api_key=conn.api_key, organization=conn.organization)
threa... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/assistant-with-file/requirements.txt | promptflow
promptflow-tools | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/assistant-with-file/add_message_and_run.py | import asyncio
import json
from openai import AsyncOpenAI
from openai.types.beta.threads import MessageContentImageFile, MessageContentText
from promptflow import tool, trace
from promptflow.connections import OpenAIConnection
from promptflow.contracts.multimedia import Image
from promptflow.contracts.types import As... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/assistant-with-file/README.md | # Stock EOD Price Analyzer
This sample demonstrates how the PromptFlow Assistant tool help with time series data (stock EOD price) retrieval, plot and consolidation.
Tools used in this flow：
- `get_or_create_thread` tool, python tool, used to provide assistant thread information if absent
- `add_message_and_run` tool... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/assistant-with-file/flow.dag.yaml | version: 2
inputs:
assistant_input:
type: list
default:
- type: text
text: The provided file contains end-of-day (EOD) stock prices for companies A
and B across various dates in March. However, it does not include the
EOD stock prices for Company C.
- type: file_path
file_p... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/assistant-with-file/get_stock_eod_price.py | import random
import time
from promptflow import tool
@tool
def get_stock_eod_price(date: str, company: str):
"""Get the stock end of day price by date and symbol.
:param date: the date of the stock price. e.g. 2021-01-01
:type date: str
:param company: the company name like A, B, C
:type compan... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/assistant-with-file/stock_price.csv | Date,A,B
2023-03-15,100.25,110.50
2023-03-16,102.75,114.35
2023-03-17,101.60,120.10
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/python_stream_tools/echo_input.py | from promptflow import tool
@tool
def my_python_tool(input: str) -> str:
yield "Echo: "
for word in input.split():
yield word + " " | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/python_stream_tools/flow.dag.yaml | inputs:
text:
type: string
outputs:
output_echo:
type: string
reference: ${echo_my_input.output}
nodes:
- name: echo_my_input
type: python
source:
type: code
path: echo_input.py
inputs:
input: ${inputs.text}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/python_stream_tools/inputs.json | {
"text": "Hello World!"
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_with_exception/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_exception/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_with_exception/convert_to_dict.py |
from promptflow import tool
@tool
def convert_to_dict(input_str: str):
raise Exception("mock exception")
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/web_classification_with_exception/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_exception/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_with_exception/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_exception/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_with_exception/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 | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with_import/fail.py | from aaa import bbb # noqa: F401 | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with_import/flow.dag.yaml | inputs:
text:
type: string
outputs:
output:
type: string
reference: ${node1.output}
nodes:
- name: node1
type: python
source:
type: code
path: dummy_utils/main.py
inputs:
x: ${inputs.text}
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with_import | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with_import/dummy_utils/main.meta.json | {
"name": "main",
"type": "python",
"inputs": {
"x": {
"type": [
"string"
]
}
},
"source": "dummy_utils/main.py",
"function": "main"
} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with_import | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with_import/dummy_utils/main.py | from promptflow import tool
from dummy_utils.util_tool import passthrough
@tool
def main(x: str):
return passthrough(x)
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with_import | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/script_with_import/dummy_utils/util_tool.py | from promptflow import tool
@tool
def passthrough(x: str):
return x
| 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_ignore_file/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:
# time.sleep(130)
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
"Chr... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_ignore_file/flow.dag.yaml | id: web_classification
inputs:
url:
default: https://www.microsoft.com/en-us/d/xbox-wireless-controller-stellar-shift-special-edition/94fbjc7h0h6h
is_chat_input: false
type: string
nodes:
- inputs:
url: ${inputs.url}
name: fetch_text_content_from_url
reduce: false
source:
path: f... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/flow_with_ignore_file/.amlignore | ignored_folder
*.ignored | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/eval_flow_with_composite_image/merge_images.py | from promptflow import tool
from promptflow.contracts.multimedia import Image
@tool
def merge_images(image_list: list, image_dict: list):
res = set()
for item in image_list[0]:
res.add(item)
for _, v in image_dict[0].items():
res.add(v)
assert all(isinstance(item, Image) for item in re... | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/eval_flow_with_composite_image/passthrough_list.py | from promptflow import tool
from promptflow.contracts.multimedia import Image
@tool
def passthrough_list(image_list: list, image_dict: dict):
assert all(isinstance(item, Image) for item in image_list)
return image_list
| 0 |
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