feat: add startup logs and sleep delay to start script for service initialization

.gitignore

@@ -1,4 +1,12 @@
 __pycache__/
 .env
 *.pyc
-velra_env/
+velra_env/
+.venv/
+venv/
+
+
+velra_env/
+__pycache__/
+*.pyc
+.env

backend/app.py

@@ -37,6 +37,9 @@ app = FastAPI()
 
 MAX_FILES = 5
 
+@app.get("/")
+async def root():
+    return {"status": "running"}
 
 @app.post("/detect_perspective")
 async def detect_perspective_route(

backend/services/ocr_service.py

@@ -2,7 +2,7 @@ import pytesseract
 from PIL import Image
 
 # 👇 ADD THIS LINE (VERY IMPORTANT FOR WINDOWS)
-pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"
+# pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"
 
 
 def extract_text_from_images(image_paths):

fine_tune_prompts.py

@@ -0,0 +1,161 @@
+import os
+
+ANALYST_FILE = "backend/agents/analyst.py"
+PSYCHOLOGY_FILE = "backend/agents/psychology.py"
+STRATEGY_FILE = "backend/agents/strategy.py"
+
+ANALYST_NEW = '''from backend.llm.factory import get_llm
+from backend.utils import safe_invoke
+
+ANALYST_PROMPT = """
+You are Velra, an elite relationship profiler. You must distinguish between "Playful Tension" and "Hostile Dismissiveness".
+
+## DIFFERENTIATION GUIDE:
+- **PLAYFUL TENSION (Green Flag):** Teasing, "Maybe I like you", "That's suspicious", "Too much talking". This is bonding. (SCORE: 70-90)
+- **HOSTILE DISMISSIVENESS (Red Flag):** "Okay and?", "I was busy (after 3 days)", "You're overreacting", "Nevermind". This is distancing. (SCORE: 10-30)
+
+## CRITICAL RULES
+- If the chat is warm and reciprocal (even if it's teasing), do NOT call it toxic. 
+- If the chat shows one person being rude or ignoring the other, call it out as a Red Flag.
+- Reference specific words (e.g., "Alex's 'maybe I like you' is a direct escalation of intimacy masked as a tease.")
+
+## INPUT CONTEXT
+Chat:
+{chat}
+
+User's Feelings:
+{feelings}
+
+## INSTRUCTIONS FOR JSON FIELDS:
+- **interest_level**: If it's mutual flirting, say "High mutual interest".
+- **emotional_tone**: E.g., "Playful/Warm", "Teasing", "Cold/Dismissive", or "Hostile".
+- **effort_level**: Note if it's balanced.
+- **trend**: "Escalating intimacy", "Withdrawal", or "Stagnant".
+- **hidden_meaning**: Decode the subtext accurately.
+- **attachment_signal**: E.g., "Secure/Playful", "Avoidant-Dismissive", "Anxious Protest".
+- **communication_health**: "High (Playful)", "Toxic (Dismissive)", or "Neutral".
+- **summary**: 2 sentences. Be specific to THIS conversation.
+
+Return ONLY valid JSON.
+{{
+"interest_level": "",
+"emotional_tone": "",
+"effort_level": "",
+"sarcasm_detected": "",
+"trend": "",
+"hidden_meaning": "",
+"attachment_signal": "",
+"communication_health": "",
+"emotional_risk": "",
+"confidence": "",
+"summary": ""
+}}
+"""
+
+def analyze_conversation(chat, feelings=""):
+    llm = get_llm()
+    prompt = ANALYST_PROMPT.format(chat=chat, feelings=feelings)
+    return safe_invoke(llm, prompt)
+'''
+
+PSYCHOLOGY_NEW = '''from backend.llm.factory import get_llm
+from backend.utils import safe_invoke
+
+PSYCHOLOGY_PROMPT = """
+You are Velra, an elite psychological profiler. You must calculate risk and alignment with extreme precision.
+
+## RISK LEVEL LOGIC:
+- **HIGH RISK:** Gaslighting, disrespect ("okay and?"), ignoring texts for days while posting on social media, breadcrumbing.
+- **LOW RISK:** Mutual flirting, playful teasing, consistent replies, "I love you".
+- **MODERATE RISK:** Ambiguity, mixed signals, uncertainty about where it's going.
+
+## COMPATIBILITY SCORE LOGIC (0-100):
+- **80-95:** Mutual interest, "I love you", or high-vibe flirting (like Nina/Alex).
+- **10-30:** Dismissive behavior, one-sided effort, disrespect.
+
+## CONTEXT
+Chat:
+{chat}
+
+User's Feelings:
+{feelings}
+
+## INSTRUCTIONS FOR JSON FIELDS:
+- **user_intent**: What the user wants.
+- **partner_intent**: What the partner's behavior REVEALS.
+- **psychological_dynamic**: E.g., "Escalating Romance", "Avoidant Shielding", "Secure Playfulness".
+- **emotional_availability**: Mutual or One-sided?
+- **risk_level**: "High", "Moderate", or "Low". Follow the Risk Level Logic.
+- **compatibility_score**: A number string. Follow the Score Logic.
+- **confidence**: "High", "Medium", "Low".
+
+Return ONLY valid JSON.
+{{
+"user_intent": "",
+"partner_intent": "",
+"psychological_dynamic": "",
+"emotional_availability": "",
+"risk_level": "",
+"compatibility_score": "",
+"confidence": ""
+}}
+"""
+
+def analyze_psychology(chat, feelings):
+    llm = get_llm()
+    prompt = PSYCHOLOGY_PROMPT.format(chat=chat, feelings=feelings)
+    return safe_invoke(llm, prompt)
+'''
+
+STRATEGY_NEW = '''from backend.llm.factory import get_llm
+from backend.utils import safe_invoke
+
+STRATEGY_PROMPT = """
+You are Velra, the ultimate relationship strategist.
+
+## ACTION BRANCHING:
+1. **IF POSITIVE/FLIRTY :** Suggest escalating. "Lean into the flirting," "Ask them out." Do NOT suggest "detaching" or "hard boundaries."
+2. **IF NEGATIVE/DISMISSIVE (like Lucas "okay and?"):** Suggest protecting yourself. "Detach," "Enforce boundaries." Do NOT suggest "warm emojis."
+
+## CONTEXT
+{context}
+
+## INSTRUCTIONS FOR JSON FIELDS:
+- **truth**: The core reality. (e.g., "He is clearly into you and is using teasing to test the waters.")
+- **warning**: E.g., "Don't play it too cool or you'll miss the window of opportunity."
+- **action_advice**: The exact next move.
+- **suggested_replies**: 1-3 texts. Calibrate to the tone.
+- **detachment_path**: "Not recommended for this positive connection" OR a real exit path.
+- **reconnection_path**: Only if needed.
+- **hero_insight**: A profound 1-sentence takeaway.
+- **personalized_advice**: 2 sentences tailored to the user's specific feelings.
+
+Return ONLY valid JSON.
+{{
+"truth": "",
+"warning": "",
+"action_advice": "",
+"suggested_replies": [],
+"detachment_path": "",
+"reconnection_path": "",
+"hero_insight": "",
+"personalized_advice": ""
+}}
+"""
+
+def generate_strategy(context):
+    llm = get_llm()
+    prompt = STRATEGY_PROMPT.format(context=context)
+    return safe_invoke(llm, prompt)
+'''
+
+with open(ANALYST_FILE, "w", encoding="utf-8") as f:
+    f.write(ANALYST_NEW)
+
+with open(PSYCHOLOGY_FILE, "w", encoding="utf-8") as f:
+    f.write(PSYCHOLOGY_NEW)
+
+with open(STRATEGY_FILE, "w", encoding="utf-8") as f:
+    f.write(STRATEGY_NEW)
+
+print("Prompts fine-tuned for high-discernment between Flirting and Dismissiveness!")

start.sh

@@ -1,6 +1,14 @@
 #!/bin/bash
 
-uvicorn backend.app:app --host 0.0.0.0 --port 8000 &
+echo "STARTING FASTAPI..."
+
+uvicorn backend.app:app \
+  --host 0.0.0.0 \
+  --port 8000 &
+
+sleep 5
+
+echo "STARTING STREAMLIT..."
 
 streamlit run frontend/app.py \
   --server.port 7860 \