Update app.py

app.py

@@ -1,106 +1,120 @@
 import os
 import streamlit as st
 from llm_groq import generate_post, transform_post, generate_hooks, DEFAULT_MODEL
-from prompts import build_post_prompt, transform_instruction
+from prompts import build_quick_prompt, build_post_prompt, transform_instruction
 from data_utils import load_posts, extract_keywords, dedupe_sentences, strip_labels
-from ui_components import preset_picker, refinement_bar
+from ui_components import quick_controls, pro_controls
 
-st.set_page_config(page_title="Pro LinkedIn Post Generator — Groq", layout="centered")
-st.title("Pro LinkedIn Post Generator (Groq)")
+st.set_page_config(page_title="LinkedIn Post Generator — Groq", layout="centered")
+st.title("LinkedIn Post Generator — Quick & Pro")
 
-# Sidebar controls
+# Sidebar
 with st.sidebar:
     st.subheader("Groq & Decoding")
     model = st.selectbox("Model", [DEFAULT_MODEL, "llama-3.1-8b-instant", "mixtral-8x7b-32768"], index=0)
     temperature = st.slider("Temperature", 0.1, 1.2, 0.6, 0.05)
     top_p = st.slider("Top‑p", 0.1, 1.0, 0.9, 0.05)
-    target_len = st.slider("Length (words)", 60, 320, 160, 10)
     st.markdown("Set GROQ_API_KEY in Space → Settings → Variables & Secrets.")
 
-# Presets to speed up intent
-preset = preset_picker()
+tabs = st.tabs(["Quick Draft", "Pro Mode", "History"])
 
-# Core inputs
-st.markdown("### Compose")
-topic = st.text_input("Topic", value="AI agent playbooks for startup ops")
-purpose = st.selectbox("Purpose", ["awareness","lead-gen","hiring","product launch","opinion","lesson learned"], index=0 if not preset else ["awareness","lead-gen","hiring","product launch","opinion","lesson learned"].index(preset.get("purpose","awareness")))
-audience = st.text_input("Audience", value="SaaS founders in early stage")
-tone = st.selectbox("Tone", ["Professional","Friendly","Contrarian","Technical","Inspirational"], index=0 if not preset else ["Professional","Friendly","Contrarian","Technical","Inspirational"].index(preset.get("tone","Professional")))
-language = st.selectbox("Language", ["English","Urdu","Arabic","French","Spanish"], index=0)
+# Session memory
+if "history" not in st.session_state:
+    st.session_state.history = []
 
-# Evidence & style
-st.markdown("### Evidence & Style")
-evidence = st.text_area("Evidence (metric/anecdote/quote)", value="")
-style_text = st.text_area("Style cues (max 4, one per line)", value="Short punchy hooks\nActionable bullets\nOne metric per paragraph\nQuestion-led CTA")
+# Quick Draft
+with tabs[0]:
+    idea, tone, words, variations, include_emoji, add_hashtags, language = quick_controls()
+    if st.button("Generate"):
+        if not os.getenv("GROQ_API_KEY"):
+            st.error("GROQ_API_KEY missing.")
+        elif not idea.strip():
+            st.warning("Enter your idea.")
+        else:
+            prompt = build_quick_prompt(idea, tone, words, include_emoji, add_hashtags, language)
+            posts = []
+            with st.spinner("Generating…"):
+                try:
+                    max_tokens = max(200, min(1200, int(words*1.6)+120))
+                    for _ in range(variations):
+                        raw = generate_post(prompt, model, temperature, top_p, max_tokens)
+                        clean = dedupe_sentences(strip_labels(raw))
+                        posts.append(clean)
+                except Exception as e:
+                    st.error(f"Generation failed: {e}")
+                    posts = []
+            for i, p in enumerate(posts, start=1):
+                st.markdown(f"#### Post {i}")
+                st.write(p)
+                st.download_button(f"Download Post {i}", p, file_name=f"post_{i}.txt")
+            if posts:
+                st.session_state.history.append({"mode":"quick","idea":idea,"tone":tone,"words":words,"posts":posts})
 
-# Dataset upload (optional)
-st.markdown("### Optional Dataset")
-uploaded = st.file_uploader("Upload CSV/JSON of past posts (must include 'text')", type=["csv","json"])
-keywords = []
-if uploaded is not None:
-    try:
-        df = load_posts(uploaded)
-        keywords = extract_keywords(topic, df)
-        st.success(f"Loaded {len(df)} posts. Extracted keywords: {', '.join(keywords[:8]) or '—'}")
-    except Exception as e:
-        st.error(f"Dataset error: {e}")
+# Pro Mode
+with tabs[1]:
+    st.markdown("Upload CSV/JSON of past posts (must include 'text') to auto-extract keywords (optional).")
+    uploaded = st.file_uploader("Upload dataset", type=["csv","json"])
+    defaults = {"topic":"AI agent playbooks for startup ops","audience":"SaaS founders in early stage"}
+    topic, purpose, audience, tone2, language2, evidence, style_text = pro_controls(defaults)
+    keywords = []
+    if uploaded is not None:
+        try:
+            df = load_posts(uploaded)
+            keywords = extract_keywords(topic, df)
+            st.success(f"Loaded {len(df)} posts. Extracted keywords: {', '.join(keywords[:8]) or '—'}")
+        except Exception as e:
+            st.error(f"Dataset error: {e}")
+    chosen_hook = ""
+    if st.button("Suggest 5 hooks"):
+        try:
+            hooks = generate_hooks(topic, audience, tone2, 5, model, temperature, top_p, 200)
+            st.code(hooks)
+            chosen_hook = st.text_input("Chosen opening line (optional)", value=chosen_hook)
+        except Exception as e:
+            st.error(f"Hook generation failed: {e}")
+    chosen_hook = st.text_input("Chosen opening line (optional)")  # visible even if not generated
 
-# Hook lab (lightweight)
-st.markdown("### Hook Lab")
-hook_btn = st.button("Suggest 5 hooks")
-chosen_hook = st.text_input("Chosen opening line (optional)")
-if hook_btn:
-    try:
-        raw_hooks = generate_hooks(topic, audience, tone, 5, model, temperature, top_p, 200)
-        st.code(raw_hooks)
-    except Exception as e:
-        st.error(f"Hook generation failed: {e}")
+    outcome = st.text_input("Desired outcome (e.g., 10 demo requests this week)", value="")
+    extra_detail = st.text_input("One concrete detail (e.g., 'onboarding 14→3 days')", value="")
+    clarifier_notes = "\n".join([f"Outcome: {outcome}" if outcome else "", f"Detail: {extra_detail}" if extra_detail else ""]).strip()
+    style_cues = [s.strip() for s in style_text.splitlines() if s.strip()][:4]
 
-# Clarifier (simple)
-st.markdown("### Clarifier")
-outcome = st.text_input("Desired outcome (e.g., 10 demo requests this week)", value="")
-extra_note = st.text_input("One concrete detail to include (e.g., 'onboarding 14→3 days')", value="")
-clarifier_notes = "\n".join([f"Outcome: {outcome}" if outcome else "", f"Detail: {extra_note}" if extra_note else ""]).strip()
-
-if st.button("Generate Post"):
-    try:
-        style_cues = [s.strip() for s in style_text.splitlines() if s.strip()][:4]
-        prompt = build_post_prompt(
-            topic=topic,
-            language=language,
-            tone=tone,
-            target_len=target_len,
-            purpose=purpose,
-            audience=audience,
-            evidence=evidence,
-            keywords=keywords,
-            style_cues=style_cues,
-            clarifier_notes=clarifier_notes,
-            chosen_hook=chosen_hook
-        )
-        max_tokens = max(200, min(1200, int(target_len*1.6)+120))
-        raw = generate_post(prompt, model, temperature, top_p, max_tokens)
-        post = dedupe_sentences(strip_labels(raw))
-        st.session_state["post"] = post
-        st.success("Post generated.")
-        st.write(post)
-        st.download_button("Download (.txt)", post, file_name="linkedin_post.txt")
-        st.code(prompt, language="markdown")
-    except Exception as e:
-        st.error(f"Generation failed: {e}")
+    if st.button("Generate Post (Pro)"):
+        if not os.getenv("GROQ_API_KEY"):
+            st.error("GROQ_API_KEY missing.")
+        else:
+            try:
+                prompt = build_post_prompt(topic, language2, tone2, 160, purpose, audience, evidence, keywords, style_cues, clarifier_notes, chosen_hook)
+                raw = generate_post(prompt, model, temperature, top_p, 800)
+                post = dedupe_sentences(strip_labels(raw))
+                st.success("Post")
+                st.write(post)
+                st.download_button("Download (.txt)", post, file_name="linkedin_post.txt")
+                st.session_state.history.append({"mode":"pro","topic":topic,"audience":audience,"post":post})
+            except Exception as e:
+                st.error(f"Generation failed: {e}")
 
-# Refinement bar
-if "post" in st.session_state and st.session_state["post"]:
-    st.markdown("---")
-    st.subheader("Refine")
-    actions = refinement_bar()
-    for kind, pressed in actions.items():
-        if pressed:
+    # Refinements (transformations)
+    if st.button("Shorter"):
+        if st.session_state.get("history") and st.session_state.history[-1].get("post"):
             try:
-                instr = transform_instruction(kind)
-                raw = transform_post(instr, st.session_state["post"], model, temperature, top_p, 500)
-                st.session_state["post"] = dedupe_sentences(strip_labels(raw))
+                instr = transform_instruction("shorter")
+                raw = transform_post(instr, st.session_state.history[-1]["post"], model, temperature, top_p, 500)
+                st.session_state.history[-1]["post"] = dedupe_sentences(strip_labels(raw))
+                st.write(st.session_state.history[-1]["post"])
             except Exception as e:
                 st.error(f"Refinement failed: {e}")
-    if st.session_state["post"]:
-        st.write(st.session_state["post"])
+
+# History
+with tabs[2]:
+    if not st.session_state.history:
+        st.info("No saved drafts yet.")
+    else:
+        for i, item in enumerate(reversed(st.session_state.history), start=1):
+            st.markdown(f"#### Draft {i} ({item.get('mode')})")
+            if "posts" in item:
+                for j, p in enumerate(item["posts"], start=1):
+                    st.markdown(f"Post {j}")
+                    st.write(p)
+            else:
+                st.write(item.get("post",""))