removed commented code and prints #2

Merged
khanhdinh merged 1 commits from clean-code into main 2025-01-03 10:29:37 +00:00
3 changed files with 3 additions and 192 deletions

12
api.py
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@ -23,11 +23,8 @@ def fetch_okrs(user_input: str):
#system_prompt = settings["system_prompt"]
#input_template = settings["input_template"]
print("fetch_okr-user_input:", user_input)
print("input_template:", INPUT_TEMPLATE)
user_prompt = construct_prompt(prompt_template=PROMPT_TEMPLATE, user_input=user_input)
print("user_prompt:", user_prompt)
headers = {"api-key": api_key, "Content-Type": "application/json"}
body = {
"messages": [
@ -35,8 +32,7 @@ def fetch_okrs(user_input: str):
{"role": "user", "content": user_prompt}
]
}
#print("system prompt:", system_prompt)
print("request body:", body)
try:
response = requests.post(url=api_url, headers=headers, json=body)
response.raise_for_status()
@ -44,9 +40,3 @@ def fetch_okrs(user_input: str):
except Exception as e:
st.error(f"Error fetching data from API: {e}")
return None
#from config import INPUT_TEMPLATE
#result = fetch_okrs(user_input=INPUT_TEMPLATE)
#objective = result['choices'][0]['message']['content']
#print(type(objective))

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@ -1,127 +1,3 @@
'''import streamlit as st
from api import fetch_okrs
from config import SYSTEM_PROMPT, INPUT_TEMPLATE, PROMPT_TEMPLATE
from utils import construct_prompt, extract_llm_response
def proposer_page():
# Streamlit App Layout
st.title("AO/PM OKR Proposer")
# Input Section and Buttons Row
st.subheader("Enter your idea or goal:")
user_input = st.text_area(
"Input your idea here:",
value=st.session_state.get("user_input", INPUT_TEMPLATE.strip()),
height=300,
)
print("user_input:", user_input)
generate_okrs_clicked = st.button("Generate OKR Proposal")
#col1, col2 = st.columns([1, 1])
#with col1:
# if st.button("Reset All"):
# st.session_state.clear()
#with col2:
if generate_okrs_clicked:
if not user_input.strip():
st.warning("Please provide some input before generating OKRs.")
else:
#user_input = st.session_state.get("user_input")
with st.spinner("Generating OKRs..."):
# Construct prompt and call API
#prompt = construct_prompt(prompt_template=PROMPT_TEMPLATE, user_input=user_input)
response = fetch_okrs(user_input=user_input)
#print("user_input:", user_input)
if response:
# Extract Objective and Key Results from response
print(response)
objective, key_results, hint = extract_llm_response(response)
st.session_state["objective"] = objective
st.session_state["key_results"] = key_results
st.session_state["hint"] = hint
#st.subheader("Hint to improve the OKR proposal")
#st.text(hint)
# Display Results Only if an OKR Has Been Generated
if "objective" in st.session_state and "key_results" in st.session_state:
# Display Objective Field with Responsibles Input Below It
st.subheader("Proposal Objective:")
objective_text = st.text_area(
"Proposal Objective:",
value=st.session_state.get("objective", ""),
height=100,
)
responsible_for_objective = st.text_input(
"Responsibles for Objective (comma-separated):",
value="",
placeholder="e.g., Khanh Dinh, John Doe",
key="responsibles_objective"
)
# Display Key Results with Responsibles Below Each One
st.subheader("Proposal Key Results:")
key_result_boxes = []
responsibles_for_key_results = []
for i, kr in enumerate(st.session_state["key_results"], start=1):
kr_text = st.text_area(f"Key Result {i}:", value=kr, key=f"kr_{i}")
responsible_for_kr = st.text_input(
f"Responsibles for Key Result {i} (comma-separated):",
value="",
placeholder="e.g., Khanh Dinh",
key=f"responsibles_kr_{i}"
)
key_result_boxes.append(kr_text)
responsibles_for_key_results.append(responsible_for_kr)
# Finalize Button Center-Aligned
#finalize_col = st.columns([3, 2, 3])[1]
#with finalize_col:
if st.button("Finalize"):
finalized_objective = objective_text.strip()
finalized_key_results = [st.session_state[f"kr_{i+1}"].strip() for i in range(len(key_result_boxes))]
# Append initials of responsibles to Objective and Key Results
responsibles_list_objective = [name.strip() for name in responsible_for_objective.split(",") if name.strip()]
initials_objective = [f"[{''.join([part[0] for part in name.split()]).upper()}]" for name in responsibles_list_objective]
initials_str_objective = ", ".join(initials_objective)
finalized_objective = f"{initials_str_objective} {finalized_objective}"
finalized_key_results_with_initials = []
for i, kr in enumerate(finalized_key_results):
responsibles_list_kr = [name.strip() for name in responsibles_for_key_results[i].split(",") if name.strip()]
initials_kr = [f"{''.join([part[0] for part in name.split()]).upper()}" for name in responsibles_list_kr]
initials_str_kr = ", ".join(initials_kr)
finalized_key_results_with_initials.append(f"KR{i+1}: [{initials_str_kr}] {kr}")
# Display finalized data in non-editable format (full width)
st.subheader("Finalized Objective:")
st.code(
body=finalized_objective,
language=None,
wrap_lines=True
)
st.subheader("Finalized Key Results:")
for kr in finalized_key_results_with_initials:
st.code(
body=kr,
language=None,
wrap_lines=True
)
'''
import streamlit as st
from api import fetch_okrs
from config import INPUT_TEMPLATE, team

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@ -1,66 +1,11 @@
import json
import streamlit as st
import re
# Function to construct the prompt
def construct_prompt(prompt_template: str, user_input: str) -> str:
return prompt_template.format(user_input=user_input)
'''# Function to extract and parse JSON response
def extract_llm_response(response):
print("response:", response)
try:
raw_message_content = response["choices"][0]["message"]["content"]
print("raw_message_content:", raw_message_content)
# Clean and parse the JSON content
cleaned_content = raw_message_content.replace("`", "").split("json")[-1]
# for debugging
#if debug:
# print("cleaned:", '-'*50)
# print(cleaned_content.strip())
def parse_json_content(cleaned_content: str):
"""
Parses the cleaned content to extract valid JSON data.
Args:
cleaned_content (str): The raw content containing JSON data.
Returns:
dict or list: The parsed JSON object.
"""
import re
# Step 1: Strip unwanted characters and clean the content
cleaned_content = cleaned_content.strip()
# Step 2: Use regex to extract only the valid JSON block (e.g., starts with [ or {)
json_match = re.search(r"(\{.*\}|\[.*\])", cleaned_content, re.DOTALL)
if not json_match:
raise ValueError("No valid JSON found in the content.")
# Step 3: Extract and parse the valid JSON
valid_json = json_match.group(0) # Extract matched JSON block
try:
extracted_data = json.loads(valid_json)
except json.JSONDecodeError as e:
raise ValueError(f"Failed to decode JSON. Error: {e}\nContent:\n{valid_json}")
return extracted_data
parsed_data = parse_json_content(cleaned_content=cleaned_content)
print("parsed_data:",parsed_data)
print("debug:", parsed_data.get("objective", ""))
#parsed_data = json.loads(cleaned_content)
return parsed_data.get("objective", ""), parsed_data.get("key_results", [])
except Exception as e:
st.error(f"Error parsing API response: {e}")
return "", []'''
import json
import re
def parse_json_content(cleaned_content: str):
"""