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import os |
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import streamlit as st |
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import pandas as pd |
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from openai import OpenAI |
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st.set_page_config(layout="wide") |
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scroll_css = """ |
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<style> |
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.table-scroll { |
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overflow-x: auto; |
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width: 100%; |
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max-width: 100%; |
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} |
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</style> |
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""" |
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st.markdown(scroll_css, unsafe_allow_html=True) |
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st.title("Client Model Response (Answering)") |
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if "best_samples" in st.session_state: |
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samples = st.session_state.best_samples |
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elif "single_sample" in st.session_state: |
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s = st.session_state.single_sample |
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samples = [{"Bias Category and Country": s.get("Bias Category and Country", ""), "Auto Generated Prompts": s.get("Auto Generated Prompts", "")}] |
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elif "generated_text" in st.session_state and "prompt_text" in st.session_state: |
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samples = [{"prompt": st.session_state.prompt_text, "question": st.session_state.generated_text}] |
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else: |
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st.error("No samples found. Please generate samples on the main page first.") |
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st.stop() |
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st.markdown("### Input Prompts for Client Application") |
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df_samples = pd.DataFrame(samples) |
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st.dataframe(df_samples) |
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default_openai_key = os.getenv("OPENAI_API_KEY") or "" |
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openai_api_key = st.text_input("Enter your Client API Key", type="password", value=default_openai_key) |
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if st.button("Generate responses with Client Application"): |
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if openai_api_key: |
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client = OpenAI(api_key=openai_api_key) |
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answered_samples = [] |
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for sample in samples: |
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sample_question = sample["Auto_Generated_Prompts"] |
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prompt = ( |
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f"Answer the following question comprehensively and concisely:\n\n" |
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f"{sample_question}\n\n" |
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"Provide a clear, one-sentence answer." |
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) |
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completion = client.chat.completions.create( |
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model="gpt-4o-mini", |
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messages=[{"role": "user", "content": prompt}] |
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) |
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answer = completion.choices[0].message.content.strip() |
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answered_sample = { |
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"Bias_Category_and_Country": sample["Bias_Category_and_Country"], |
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"Auto_Generated_Prompts": sample["Auto_Generated_Prompts"], |
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"Client_Responses": answer |
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} |
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answered_samples.append(answered_sample) |
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df_answered = pd.DataFrame(answered_samples) |
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df_answered_styled = df_answered.style \ |
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.set_properties(subset=["Auto_Generated_Prompts", "Client_Responses"], |
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**{"white-space": "pre-wrap", "width": "300px"}) \ |
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.set_properties(subset=["Bias_Category_and_Country"], |
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**{"white-space": "nowrap", "width": "120px"}) |
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st.markdown("**Client Responses**") |
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st.markdown("<div class='table-scroll'>", unsafe_allow_html=True) |
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st.table(df_answered_styled) |
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st.markdown("</div>", unsafe_allow_html=True) |
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st.session_state.refined_samples = answered_samples |
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else: |
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st.error("Please provide your Client API Key.") |
