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app.py

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+# ==========================================
+# FinTalk - Gradio UI
+# ==========================================
+import gradio as gr
+import asyncio
+from backend import fintalk_discussion, export_to_pdf, generate_tts_files  # senin fonksiyonların
+
+# -----------------------------------------------------
+# Tartışmayı başlatan ana fonksiyon
+# -----------------------------------------------------
+def run_fintalk(topic_text):
+    if not topic_text or len(topic_text.strip()) < 10:
+        return "Please provide a valid economic topic.", "", "", "", "", None, None
+
+    result = fintalk_discussion(topic_text)
+    result["topic"] = topic_text
+
+    # PDF oluştur
+    pdf_path = "FinTalk_Report.pdf"
+    export_to_pdf(result, pdf_path)
+
+    # TTS (async)
+    try:
+        asyncio.run(generate_tts_files(result))
+    except Exception as e:
+        print("TTS hatası:", e)
+
+    return (
+    f"🧩 **Moderator:**\n{result['moderator_intro']}",
+    f"💹 **Bullish Investor:**\n{result['bullish_view']}",
+    f"📉 **Bearish Economist:**\n{result['bearish_view']}",
+    f"🎙️ **Moderator Wrap-up:**\n{result['moderator_wrap']}",
+    f"📊 **GPT Summary:**\n{result['summary']}",
+    pdf_path,
+    "moderator_intro.mp3",
+    "bullish_view.mp3",
+    "bearish_view.mp3",
+    "moderator_wrap.mp3"
+)
+
+# -----------------------------------------------------
+# Gradio Arayüz
+# -----------------------------------------------------
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown(
+        """
+        # 📊 **FinTalk — AI Economic Roundtable**
+        Simulate a live discussion between two economists with opposing views, moderated by Selin.
+        Enter an economic topic or news headline below and click **Start Discussion**.
+        """
+    )
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            topic_input = gr.Textbox(
+                label="Enter an Economic Headline or News",
+                placeholder="Example: The central bank raised interest rates by 200 basis points.",
+                lines=4
+            )
+            start_btn = gr.Button("🚀 Start Discussion")
+
+        with gr.Column(scale=2):
+            moderator_output = gr.Markdown(label="Moderator Intro")
+            bullish_output = gr.Markdown(label="Bullish Investor")
+            bearish_output = gr.Markdown(label="Bearish Economist")
+            wrap_output = gr.Markdown(label="Moderator Wrap-up")
+            summary_output = gr.Markdown(label="GPT Summary")
+
+            pdf_file = gr.File(label="📄 Download PDF Report")
+            
+            with gr.Row():
+                mod_audio = gr.Audio(label="Moderator Voice", interactive=False)
+                bull_audio = gr.Audio(label="Bullish Voice", interactive=False)
+                bear_audio = gr.Audio(label="Bearish Voice", interactive=False)
+                wrap_audio = gr.Audio(label="Moderator Wrap-up", interactive=False)            
+
+    start_btn.click(
+    fn=run_fintalk,
+    inputs=topic_input,
+    outputs=[
+        moderator_output,
+        bullish_output,
+        bearish_output,
+        wrap_output,
+        summary_output,
+        pdf_file,
+        mod_audio,
+        bull_audio,
+        bear_audio,
+        wrap_audio
+    ]
+)
+
+
+# -----------------------------------------------------
+# Uygulama Başlat
+# -----------------------------------------------------
+if __name__ == "__main__":
+    demo.launch()

backend.py

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+# ==========================================
+# FinTalk - Backend (llama-cpp + GPT summary)
+# ==========================================
+
+import os
+import re
+from typing import Dict
+from dotenv import load_dotenv
+from llama_cpp import Llama
+from openai import OpenAI
+import edge_tts
+import asyncio
+import reportlab
+
+load_dotenv()  
+
+# -----------------------------------------------------
+# 1) MODEL YOLU (GGUF) - KENDİ YOLUNU YAZ
+# -----------------------------------------------------
+model_path = r"C:/Users/cagri/.lmstudio/models/QuantFactory/Llama-3-8B-Instruct-Finance-RAG-GGUF/Llama-3-8B-Instruct-Finance-RAG.Q4_K_S.gguf"
+# -----------------------------------------------------
+# 2) LLAMA-CPP MODEL YÜKLEME
+#    n_ctx=4096 yeterli; 8192 istersen RAM artar. Uyarı görürsen önemsemeyebilirsin.
+# -----------------------------------------------------
+llm = Llama(
+    model_path=model_path,
+    n_ctx=4096,
+    n_threads=6,   
+    n_batch=512,
+    verbose=False
+)
+
+# -----------------------------------------------------
+# 3) OPENAI (Özetleme)
+# -----------------------------------------------------
+OPENAI_API_KEY = os.getenv("API_KEY")
+if not OPENAI_API_KEY:
+    raise RuntimeError("API_KEY bulunamadı. Lütfen .env veya sistem değişkenlerine ekleyin.")
+client = OpenAI(api_key=OPENAI_API_KEY)
+SUMMARY_MODEL = os.getenv("SUMMARY_MODEL", "gpt-4o-mini")
+
+# -----------------------------------------------------
+# 4) PERSONA PROMPTLAR (sade)
+# -----------------------------------------------------
+SYSTEM_MODERATOR = (
+    "You are Selin, the moderator of an economics roundtable. "
+    "Be neutral, brief, and structured. Guide the flow without giving opinions."
+)
+
+SYSTEM_BULLISH = (
+   """You are Bullish Investor, an optimistic economist who focuses on growth, market confidence, and positive catalysts.
+    Be analytical and persuasive. Mention at least two concrete macro or market factors that support your optimism 
+    (e.g., improved investor sentiment, fiscal stimulus, or sector resilience). 
+    Respond in 2–3 detailed paragraphs and conclude with one confident takeaway."""
+)
+
+SYSTEM_BEARISH = (
+    "You are Bearish Economist, a cautious macroeconomist who highlights downside risks "
+    "(inflation persistence, liquidity stress, policy uncertainty). Be analytical; end with one cautionary insight."
+)
+
+# -----------------------------------------------------
+# 5) YARDIMCI: Post-process (meta notları, personayı ifşa eden satırları temizle)
+# -----------------------------------------------------
+_META_PATTERNS = [
+    r"(?i)\bnote:\b.*",                 # "Note:" ile başlayan meta
+    r"(?i)\bi am (selin|bullish|bearish).*$",  # "I am ..." persona ifşaları
+    r"(?i)\bthis response was written\b.*",
+    r"(?i)\bplease review\b.*",
+    r"(?i)\bclarity and readability\b.*",
+]
+def _clean(text: str) -> str:
+    cleaned = text.strip()
+    for pat in _META_PATTERNS:
+        cleaned = re.sub(pat, "", cleaned, flags=re.MULTILINE)
+    # aşırı boşlukları toparla
+    cleaned = re.sub(r"\n{3,}", "\n\n", cleaned).strip()
+    return cleaned
+
+# -----------------------------------------------------
+# 6) TEK PERSONA CEVABI (chat completion + context reset)
+# -----------------------------------------------------
+def generate_as(system_prompt: str, user_text: str, max_tokens: int = 480, temperature: float = 0.7) -> str:
+    """
+    Her çağrıda temiz context: create_chat_completion kullanıyoruz.
+    """
+    # olası KV cache etkisini azaltmak için reset
+    llm.reset()
+    out = llm.create_chat_completion(
+        messages=[
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_text}
+        ],
+        max_tokens=max_tokens,
+        temperature=temperature,
+        top_p=0.9,
+        repeat_penalty=1.1,
+    )
+    text = out["choices"][0]["message"]["content"]
+    return _clean(text)
+
+# -----------------------------------------------------
+# 7) TARTIŞMA AKIŞI
+# -----------------------------------------------------
+def fintalk_discussion(news_text: str) -> Dict[str, str]:
+    print("🧩 FinTalk simulation started...\n")
+
+    # Ortak mesaj zinciri (tek context)
+    messages = []
+
+    # 1️⃣ Selin başlatıyor
+    selin_intro = generate_as(SYSTEM_MODERATOR, f"Open the discussion about: {news_text}.")
+    messages.append(f"Selin: {selin_intro}")
+    print("Moderator Intro:\n", selin_intro, "\n")
+
+    # 2️⃣ Bullish konuşuyor
+    bullish_view = generate_as(
+        SYSTEM_BULLISH,
+        f"The moderator introduced the topic: {news_text}. Respond with your opening bullish perspective."
+    )
+    messages.append(f"Bullish Investor: {bullish_view}")
+    print("Bullish Investor:\n", bullish_view, "\n")
+
+    # 3️⃣ Bearish karşılık veriyor
+    bearish_view = generate_as(
+        SYSTEM_BEARISH,
+        f"The moderator introduced the topic: {news_text}. "
+        f"The bullish economist said: {bullish_view}\n"
+        "Now respond with your cautious analysis."
+    )
+    messages.append(f"Bearish Economist: {bearish_view}")
+    print("Bearish Economist:\n", bearish_view, "\n")
+
+    # 4️⃣ Selin toparlıyor (konuya referans ver)
+    selin_wrap = generate_as(
+        SYSTEM_MODERATOR,
+        f"Based on the debate about {news_text}, summarize their main differences and close the panel politely."
+    )
+    messages.append(f"Selin: {selin_wrap}")
+    print("Moderator Wrap-up:\n", selin_wrap, "\n")
+
+    # 5️⃣ GPT özetleme
+    debate_text = "\n".join(messages)
+    summary_prompt = (
+        "Summarize this debate between a bullish and a bearish economist in 5 bullet points. "
+        "Keep it grounded in the topic and add a balanced conclusion.\n\n"
+        f"{debate_text}"
+    )
+
+    summary_resp = client.chat.completions.create(
+        model=SUMMARY_MODEL,
+        messages=[
+            {"role": "system", "content": "You are an expert economic summarizer."},
+            {"role": "user", "content": summary_prompt}
+        ]
+    )
+    final_summary = summary_resp.choices[0].message.content.strip()
+    print("📊 GPT Summary:\n", final_summary)
+
+    return {
+        "moderator_intro": selin_intro,
+        "bullish_view": bullish_view,
+        "bearish_view": bearish_view,
+        "moderator_wrap": selin_wrap,
+        "summary": final_summary
+    }
+
+def export_to_pdf(result: dict, filename="FinTalk_Report.pdf"):
+    from reportlab.lib.pagesizes import A4
+    from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
+    from reportlab.lib.styles import getSampleStyleSheet
+
+    styles = getSampleStyleSheet()
+    doc = SimpleDocTemplate(filename, pagesize=A4)
+    story = []
+
+    def add(title, text):
+        story.append(Paragraph(f"<b>{title}</b>", styles["Heading3"]))
+        story.append(Paragraph(text.replace("\n", "<br/>"), styles["BodyText"]))
+        story.append(Spacer(1, 12))
+
+    add("Topic", result.get("topic", "—"))
+    add("Moderator Intro", result["moderator_intro"])
+    add("Bullish Investor", result["bullish_view"])
+    add("Bearish Economist", result["bearish_view"])
+    add("Moderator Wrap-up", result["moderator_wrap"])
+    add("GPT-4 Summary", result["summary"])
+
+    story.append(Paragraph("<i>Generated by FinTalk – AI Economic Roundtable</i>", styles["Normal"]))
+    doc.build(story)
+
+async def generate_tts_files(result):
+    voices = {
+        "moderator_intro": "en-US-AriaNeural",
+        "bullish_view": "en-US-GuyNeural",
+        "bearish_view": "en-GB-RyanNeural",
+        "moderator_wrap": "en-US-AriaNeural"
+    }
+    for key, voice in voices.items():
+        filename = f"{key}.mp3"
+        text = result[key]
+        await edge_tts.Communicate(text, voice=voice, rate="+0%").save(filename)
+        print(f"✅ {filename} oluşturuldu")
+
+# -----------------------------------------------------
+# 8) Hızlı Test
+# -----------------------------------------------------
+if __name__ == "__main__":
+    topic = input("What's discussion topic ?\n>")
+    result = fintalk_discussion(topic)
+    result["topic"] = topic
+    export_to_pdf(result)
+    asyncio.run(generate_tts_files(result))
+    

requierements.txt

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+gradio
+llama-cpp-python==0.2.85
+reportlab
+openai
+edge-tts
+python-dotenv
+huggingface_hub