Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| import requests | |
| import json | |
| # ============================================================ | |
| # Smart Text Analyzer - Advanced Prompting Techniques Demo | |
| # Deployed on Hugging Face Spaces | |
| # ============================================================ | |
| st.set_page_config( | |
| page_title="Smart Text Analyzer", | |
| page_icon="🧠", | |
| layout="wide" | |
| ) | |
| st.title("🧠 Smart Text Analyzer") | |
| st.caption("Demonstrates Advanced Prompting Techniques using Groq (Free AI API)") | |
| # ---- API SETUP ---- | |
| GROQ_API_KEY = st.sidebar.text_input("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", type="password") | |
| st.sidebar.markdown("Get free key at [console.groq.com](https://console.groq.com)") | |
| st.sidebar.markdown("---") | |
| # ---- ADVANCED PROMPT TEMPLATES ---- | |
| # 1. ZERO-SHOT PROMPT | |
| def zero_shot_prompt(text): | |
| return f"""Analyze the sentiment of the following text and classify it as Positive, Negative, or Neutral. | |
| Text: {text} | |
| Sentiment:""" | |
| # 2. FEW-SHOT PROMPT | |
| def few_shot_prompt(text): | |
| return f"""Classify the sentiment of text. Here are some examples: | |
| Text: "I absolutely love this product! It works perfectly." | |
| Sentiment: Positive | |
| Reason: Uses enthusiastic language and positive words. | |
| Text: "This is the worst experience I have ever had." | |
| Sentiment: Negative | |
| Reason: Strong negative words expressing dissatisfaction. | |
| Text: "The package arrived on time." | |
| Sentiment: Neutral | |
| Reason: Factual statement with no emotional language. | |
| Now classify: | |
| Text: "{text}" | |
| Sentiment: | |
| Reason:""" | |
| # 3. CHAIN-OF-THOUGHT PROMPT | |
| def chain_of_thought_prompt(text): | |
| return f"""Analyze the following text step by step. | |
| Text: "{text}" | |
| Let's think through this carefully: | |
| Step 1 - Identify the main topic of the text. | |
| Step 2 - Identify any emotional words or phrases. | |
| Step 3 - Determine the overall tone (positive/negative/neutral). | |
| Step 4 - Summarize the key message in one sentence. | |
| Step 5 - Give a final sentiment score from 1 (very negative) to 10 (very positive). | |
| Analysis:""" | |
| # 4. ROLE PROMPT | |
| def role_prompt(text): | |
| return f"""You are an expert linguist and psychologist with 20 years of experience | |
| analyzing human communication and emotional patterns. | |
| Analyze the following text from your expert perspective: | |
| Text: "{text}" | |
| Provide: | |
| 1. Emotional tone analysis | |
| 2. Communication style (formal/informal/aggressive/passive) | |
| 3. Hidden emotions or subtext | |
| 4. Psychological insight about the writer | |
| 5. Recommended response approach""" | |
| # 5. TEMPLATE PROMPT | |
| def template_prompt(text, task): | |
| templates = { | |
| "summarize": f""" | |
| [TASK]: Summarize the following text | |
| [INPUT]: {text} | |
| [FORMAT]: | |
| - One sentence summary | |
| - 3 bullet point key takeaways | |
| - Word count of original vs summary | |
| [OUTPUT]:""", | |
| "translate": f""" | |
| [TASK]: Translate the following text to Tamil and Hindi | |
| [INPUT]: {text} | |
| [FORMAT]: | |
| - Original: (original text) | |
| - Tamil: (tamil translation) | |
| - Hindi: (hindi translation) | |
| - Note any cultural differences | |
| [OUTPUT]:""", | |
| "rewrite": f""" | |
| [TASK]: Rewrite the following text to make it more professional | |
| [INPUT]: {text} | |
| [CONSTRAINTS]: | |
| - Keep the same meaning | |
| - Use formal language | |
| - Maximum 3 sentences | |
| - No slang or casual words | |
| [OUTPUT]:""" | |
| } | |
| return templates.get(task, templates["summarize"]) | |
| # ---- CALL GROQ API ---- | |
| def call_groq(prompt, api_key): | |
| if not api_key: | |
| return "⚠️ Please enter your Groq API key in the sidebar." | |
| headers = { | |
| "Authorization": f"Bearer {api_key}", | |
| "Content-Type": "application/json" | |
| } | |
| body = { | |
| "model": "llama-3.3-70b-versatile", | |
| "messages": [{"role": "user", "content": prompt}], | |
| "max_tokens": 500 | |
| } | |
| try: | |
| response = requests.post( | |
| "https://api.groq.com/openai/v1/chat/completions", | |
| headers=headers, | |
| json=body, | |
| timeout=30 | |
| ) | |
| result = response.json() | |
| if "choices" in result: | |
| return result["choices"][0]["message"]["content"] | |
| elif "error" in result: | |
| return f"❌ Groq API Error: {result['error']['message']}" | |
| else: | |
| return f"❌ Unexpected response: {result}" | |
| except Exception as e: | |
| return f"❌ Error: {str(e)}" | |
| # ---- UI ---- | |
| st.subheader("📝 Enter your text") | |
| user_text = st.text_area( | |
| "Type or paste any text here:", | |
| placeholder="e.g. I had an amazing day today! Everything went perfectly.", | |
| height=120 | |
| ) | |
| st.markdown("---") | |
| # ---- TABS FOR EACH TECHNIQUE ---- | |
| tab1, tab2, tab3, tab4, tab5 = st.tabs([ | |
| "⚡ Zero-Shot", | |
| "📚 Few-Shot", | |
| "🔗 Chain-of-Thought", | |
| "🎭 Role Prompting", | |
| "📋 Template Prompting" | |
| ]) | |
| with tab1: | |
| st.subheader("⚡ Zero-Shot Prompting") | |
| st.info("**What is it?** Give the AI a task with NO examples. Just ask directly.") | |
| if user_text: | |
| prompt = zero_shot_prompt(user_text) | |
| with st.expander("📄 View Prompt"): | |
| st.code(prompt) | |
| if st.button("🚀 Run Zero-Shot", key="zs"): | |
| with st.spinner("Analyzing..."): | |
| result = call_groq(prompt, GROQ_API_KEY) | |
| st.success(result) | |
| else: | |
| st.warning("Enter text above to analyze.") | |
| with tab2: | |
| st.subheader("📚 Few-Shot Prompting") | |
| st.info("**What is it?** Give the AI 2-3 examples before asking it to do the task.") | |
| if user_text: | |
| prompt = few_shot_prompt(user_text) | |
| with st.expander("📄 View Prompt"): | |
| st.code(prompt) | |
| if st.button("🚀 Run Few-Shot", key="fs"): | |
| with st.spinner("Analyzing..."): | |
| result = call_groq(prompt, GROQ_API_KEY) | |
| st.success(result) | |
| else: | |
| st.warning("Enter text above to analyze.") | |
| with tab3: | |
| st.subheader("🔗 Chain-of-Thought Prompting") | |
| st.info("**What is it?** Ask the AI to think step by step before giving the answer.") | |
| if user_text: | |
| prompt = chain_of_thought_prompt(user_text) | |
| with st.expander("📄 View Prompt"): | |
| st.code(prompt) | |
| if st.button("🚀 Run Chain-of-Thought", key="cot"): | |
| with st.spinner("Thinking step by step..."): | |
| result = call_groq(prompt, GROQ_API_KEY) | |
| st.success(result) | |
| else: | |
| st.warning("Enter text above to analyze.") | |
| with tab4: | |
| st.subheader("🎭 Role Prompting") | |
| st.info("**What is it?** Assign a specific role/persona to the AI before asking.") | |
| if user_text: | |
| prompt = role_prompt(user_text) | |
| with st.expander("📄 View Prompt"): | |
| st.code(prompt) | |
| if st.button("🚀 Run Role Prompt", key="rp"): | |
| with st.spinner("Expert analyzing..."): | |
| result = call_groq(prompt, GROQ_API_KEY) | |
| st.success(result) | |
| else: | |
| st.warning("Enter text above to analyze.") | |
| with tab5: | |
| st.subheader("📋 Template Prompting") | |
| st.info("**What is it?** Use structured templates with [TASK], [INPUT], [FORMAT] sections.") | |
| task = st.selectbox("Choose task:", ["summarize", "translate", "rewrite"]) | |
| if user_text: | |
| prompt = template_prompt(user_text, task) | |
| with st.expander("📄 View Prompt"): | |
| st.code(prompt) | |
| if st.button("🚀 Run Template Prompt", key="tp"): | |
| with st.spinner("Processing..."): | |
| result = call_groq(prompt, GROQ_API_KEY) | |
| st.success(result) | |
| else: | |
| st.warning("Enter text above to analyze.") | |
| # ---- FOOTER ---- | |
| st.markdown("---") | |
| st.markdown(""" | |
| ### 📖 Prompting Techniques Used | |
| | Technique | Description | | |
| |---|---| | |
| | ⚡ Zero-Shot | No examples, direct task | | |
| | 📚 Few-Shot | 2-3 examples before task | | |
| | 🔗 Chain-of-Thought | Step-by-step reasoning | | |
| | 🎭 Role Prompting | Assign AI a persona/role | | |
| | 📋 Template Prompting | Structured [TASK][INPUT][OUTPUT] format | | |
| """) |