wehub-resource-sync
e768098d0e
tools_continuous_delivery / Private PyPI non-main branch release (push) Has been skipped
tools_continuous_delivery / Private PyPI main branch release (push) Failing after 2m42s
Publish Promptflow Doc / Build (push) Has been cancelled
Publish Promptflow Doc / Deploy (push) Has been cancelled
Flake8 Lint / flake8 (push) Has been cancelled
Spell check CI / Spell_Check (push) Has been cancelled
266 lines
6.4 KiB
YAML
266 lines
6.4 KiB
YAML
$schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
|
|
inputs:
|
|
question:
|
|
type: string
|
|
default: Which tent is the most waterproof?
|
|
is_chat_input: false
|
|
answer:
|
|
type: string
|
|
default: The Alpine Explorer Tent is the most waterproof.
|
|
is_chat_input: false
|
|
context:
|
|
type: string
|
|
default: From the our product list, the alpine explorer tent is the most
|
|
waterproof. The Adventure Dining Tabbe has higher weight.
|
|
is_chat_input: false
|
|
ground_truth:
|
|
type: string
|
|
default: The Alpine Explorer Tent has the highest rainfly waterproof rating at 3000m
|
|
is_chat_input: false
|
|
metrics:
|
|
type: string
|
|
default: gpt_groundedness,f1_score,ada_similarity,gpt_fluency,gpt_coherence,gpt_similarity,gpt_relevance
|
|
is_chat_input: false
|
|
outputs:
|
|
f1_score:
|
|
type: string
|
|
reference: ${concat_scores.output.f1_score}
|
|
gpt_coherence:
|
|
type: string
|
|
reference: ${concat_scores.output.gpt_coherence}
|
|
gpt_similarity:
|
|
type: string
|
|
reference: ${concat_scores.output.gpt_similarity}
|
|
gpt_fluency:
|
|
type: string
|
|
reference: ${concat_scores.output.gpt_fluency}
|
|
gpt_relevance:
|
|
type: string
|
|
reference: ${concat_scores.output.gpt_relevance}
|
|
gpt_groundedness:
|
|
type: string
|
|
reference: ${concat_scores.output.gpt_groundedness}
|
|
ada_similarity:
|
|
type: string
|
|
reference: ${concat_scores.output.ada_similarity}
|
|
nodes:
|
|
- name: gpt_coherence
|
|
type: llm
|
|
source:
|
|
type: code
|
|
path: gpt_coherence_prompt.jinja2
|
|
inputs:
|
|
deployment_name: gpt-4
|
|
temperature: 0
|
|
top_p: 1
|
|
stop: ""
|
|
max_tokens: 1
|
|
presence_penalty: 0
|
|
frequency_penalty: 0
|
|
logit_bias: ""
|
|
question: ${inputs.question}
|
|
answer: ${inputs.answer}
|
|
provider: AzureOpenAI
|
|
connection: open_ai_connection
|
|
api: chat
|
|
module: promptflow.tools.aoai
|
|
activate:
|
|
when: ${validate_input.output.gpt_coherence}
|
|
is: true
|
|
use_variants: false
|
|
- name: concat_scores
|
|
type: python
|
|
source:
|
|
type: code
|
|
path: concat_scores.py
|
|
inputs:
|
|
ada_cosine_similarity: ${ada_similarity.output}
|
|
f1_score: ${f1_score.output}
|
|
gpt_coherence_score: ${gpt_coherence.output}
|
|
gpt_fluency_score: ${gpt_fluency.output}
|
|
gpt_groundedness_score: ${gpt_groundedness.output}
|
|
gpt_relevance_score: ${gpt_relevance.output}
|
|
gpt_similarity_score: ${gpt_similarity.output}
|
|
use_variants: false
|
|
- name: gpt_similarity
|
|
type: llm
|
|
source:
|
|
type: code
|
|
path: gpt_similarity_prompt.jinja2
|
|
inputs:
|
|
deployment_name: gpt-4
|
|
temperature: 0
|
|
top_p: 1
|
|
stop: ""
|
|
max_tokens: 1
|
|
presence_penalty: 0
|
|
frequency_penalty: 0
|
|
logit_bias: ""
|
|
answer: ${inputs.answer}
|
|
ground_truth: ${inputs.ground_truth}
|
|
question: ${inputs.question}
|
|
provider: AzureOpenAI
|
|
connection: open_ai_connection
|
|
api: chat
|
|
module: promptflow.tools.aoai
|
|
activate:
|
|
when: ${validate_input.output.gpt_similarity}
|
|
is: true
|
|
use_variants: false
|
|
- name: gpt_relevance
|
|
type: llm
|
|
source:
|
|
type: code
|
|
path: gpt_relevance_prompt.jinja2
|
|
inputs:
|
|
deployment_name: gpt-4
|
|
temperature: 0
|
|
top_p: 1
|
|
stop: ""
|
|
max_tokens: 1
|
|
presence_penalty: 0
|
|
frequency_penalty: 0
|
|
logit_bias: ""
|
|
answer: ${inputs.answer}
|
|
context: ${inputs.context}
|
|
question: ${inputs.question}
|
|
provider: AzureOpenAI
|
|
connection: open_ai_connection
|
|
api: chat
|
|
module: promptflow.tools.aoai
|
|
activate:
|
|
when: ${validate_input.output.gpt_relevance}
|
|
is: true
|
|
use_variants: false
|
|
- name: gpt_fluency
|
|
type: llm
|
|
source:
|
|
type: code
|
|
path: gpt_fluency_prompt.jinja2
|
|
inputs:
|
|
deployment_name: gpt-4
|
|
temperature: 0
|
|
top_p: 1
|
|
stop: ""
|
|
max_tokens: 1
|
|
presence_penalty: 0
|
|
frequency_penalty: 0
|
|
logit_bias: ""
|
|
answer: ${inputs.answer}
|
|
question: ${inputs.question}
|
|
provider: AzureOpenAI
|
|
connection: open_ai_connection
|
|
api: chat
|
|
module: promptflow.tools.aoai
|
|
activate:
|
|
when: ${validate_input.output.gpt_fluency}
|
|
is: true
|
|
use_variants: false
|
|
- name: f1_score
|
|
type: python
|
|
source:
|
|
type: code
|
|
path: f1_score.py
|
|
inputs:
|
|
answer: ${inputs.answer}
|
|
ground_truth: ${inputs.ground_truth}
|
|
activate:
|
|
when: ${validate_input.output.f1_score}
|
|
is: true
|
|
use_variants: false
|
|
- name: gpt_groundedness
|
|
type: llm
|
|
source:
|
|
type: code
|
|
path: gpt_groundedness_prompt.jinja2
|
|
inputs:
|
|
deployment_name: gpt-4
|
|
temperature: 0
|
|
top_p: 1
|
|
stop: ""
|
|
max_tokens: 1
|
|
presence_penalty: 0
|
|
frequency_penalty: 0
|
|
logit_bias: ""
|
|
answer: ${inputs.answer}
|
|
context: ${inputs.context}
|
|
provider: AzureOpenAI
|
|
connection: open_ai_connection
|
|
api: chat
|
|
module: promptflow.tools.aoai
|
|
activate:
|
|
when: ${validate_input.output.gpt_groundedness}
|
|
is: true
|
|
use_variants: false
|
|
- name: aggregate_variants_results
|
|
type: python
|
|
source:
|
|
type: code
|
|
path: aggregate_variants_results.py
|
|
inputs:
|
|
metrics: ${inputs.metrics}
|
|
results: ${concat_scores.output}
|
|
aggregation: true
|
|
use_variants: false
|
|
- name: select_metrics
|
|
type: python
|
|
source:
|
|
type: code
|
|
path: select_metrics.py
|
|
inputs:
|
|
metrics: ${inputs.metrics}
|
|
use_variants: false
|
|
- name: embeded_ground_truth
|
|
type: python
|
|
source:
|
|
type: package
|
|
tool: promptflow.tools.embedding.embedding
|
|
inputs:
|
|
connection: open_ai_connection
|
|
deployment_name: text-embedding-ada-002
|
|
input: ${inputs.ground_truth}
|
|
activate:
|
|
when: ${validate_input.output.ada_similarity}
|
|
is: true
|
|
use_variants: false
|
|
- name: embeded_answer
|
|
type: python
|
|
source:
|
|
type: package
|
|
tool: promptflow.tools.embedding.embedding
|
|
inputs:
|
|
connection: open_ai_connection
|
|
deployment_name: text-embedding-ada-002
|
|
input: ${inputs.answer}
|
|
activate:
|
|
when: ${validate_input.output.ada_similarity}
|
|
is: true
|
|
use_variants: false
|
|
- name: ada_similarity
|
|
type: python
|
|
source:
|
|
type: code
|
|
path: ada_cosine_similarity_score.py
|
|
inputs:
|
|
a: ${embeded_ground_truth.output}
|
|
b: ${embeded_answer.output}
|
|
activate:
|
|
when: ${validate_input.output.ada_similarity}
|
|
is: true
|
|
use_variants: false
|
|
- name: validate_input
|
|
type: python
|
|
source:
|
|
type: code
|
|
path: validate_input.py
|
|
inputs:
|
|
answer: ${inputs.answer}
|
|
context: ${inputs.context}
|
|
ground_truth: ${inputs.ground_truth}
|
|
question: ${inputs.question}
|
|
selected_metrics: ${select_metrics.output}
|
|
use_variants: false
|
|
node_variants: {}
|
|
environment:
|
|
python_requirements_txt: requirements.txt
|