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import os
from groq import Groq
from openai import OpenAI
from anthropic import Anthropic
from google import genai
from google.genai import types
import streamlit as st
from dotenv import load_dotenv
load_dotenv()
st.set_page_config(page_title="strftime AI", page_icon="🕘")
with open("static/style.css", encoding="utf-8") as f:
st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
st.header("strftime AI")
with st.sidebar:
provider = st.radio(
"Choose AI Provider",
options=[
"Groq",
"Gemini",
"OpenAI",
"Anthropic",
]
)
text = st.text_input("Enter datetime text eg. 2023-09-28T15:27:58Z", value="2023-09-28T15:27:58Z")
if text:
prompt = f"""Analyze this datetime string and convert it to strftime format: {text}
Please provide your response in exactly this format:
**strftime format:** `[the strftime format string]`
**Breakdown:**
- `%Y`: 4-digit year
- `%m`: 2-digit month (01-12)
- `%d`: 2-digit day (01-31)
[list each format code used with its meaning]
Be precise and only include the format codes that are actually present in the input datetime string. Do not add extra explanations or variations."""
if provider == "Groq":
client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
chat_completion = client.chat.completions.create(
messages=[{"role": "user", "content": prompt}],
model="gemma2-9b-it",
max_tokens=1024,
)
st.markdown(chat_completion.choices[0].message.content)
elif provider == "OpenAI":
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
chat_completion = client.chat.completions.create(
messages=[{"role": "user", "content": prompt}],
model="gpt-4o-mini",
max_tokens=1024,
)
st.markdown(chat_completion.choices[0].message.content)
elif provider == "Anthropic":
client = Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
message = client.messages.create(
messages=[{"role": "user", "content": prompt}],
model="claude-3-haiku-20240307",
max_tokens=1024,
)
st.markdown(message.content[0].text)
elif provider == "Gemini":
client = genai.Client(api_key=os.environ["GOOGLE_API_KEY"])
response = client.models.generate_content(
model='gemini-2.5-flash-lite',
contents = types.Content(
role='user',
parts=[types.Part.from_text(text=prompt)]
),
)
st.markdown(response.candidates[0].content.parts[0].text)
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