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/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 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/chat_flow/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/prompt_tool_with_duplicated_inputs/prompt_with_duplicated_inputs.jinja2 | {{template}} | 0 |
promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows | promptflow_repo/promptflow/src/promptflow/tests/test_configs/flows/prompt_tool_with_duplicated_inputs/flow.dag.yaml | inputs:
text:
type: string
outputs:
output_prompt:
type: string
reference: ${prompt_tool_with_duplicated_inputs.output}
nodes:
- name: prompt_tool_with_duplicated_inputs
type: prompt
source:
type: code
path: prompt_with_duplicated_inputs.jinja2
inputs:
text: ${inputs.text} | 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_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/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_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/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/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 |
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