Update app.py

app.py

@@ -73,37 +73,37 @@ def run_crypto_crew(topic):
 # Chatbot Response Function
 def respond(message, history):
     max_tokens = 512
-    temperature = 0.3
+    temperature = 0.7
     top_p = 0.95
     frequency_penalty = 0.0
     seed = None
 
-    if "analyze" in message.lower() or "trend" in message.lower():
-        response = run_crypto_crew(message)
+    # CrewAI'den gelen analiz sonuçları alınır
+    crew_response = run_crypto_crew(message)
+
+    # LLM ile harmanlanarak daha kapsamlı bir cevap üretilir
+    messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+    for user_part, assistant_part in history:
+        if user_part:
+            messages.append({"role": "user", "content": user_part})
+        if assistant_part:
+            messages.append({"role": "assistant", "content": assistant_part})
+    messages.append({"role": "user", "content": f"{message}\n\nCrewAI Analysis:\n{crew_response}"})
+
+    response = ""
+    for message_chunk in client.chat.completions.create(
+        model="meta-llama/Llama-3.3-70B-Instruct",
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+        frequency_penalty=frequency_penalty,
+        seed=seed,
+        messages=messages,
+    ):
+        token_text = message_chunk.choices[0].delta.content
+        response += token_text
         yield response
-    else:
-        messages = [{"role": "system", "content": SYSTEM_PROMPT}]
-        for user_part, assistant_part in history:
-            if user_part:
-                messages.append({"role": "user", "content": user_part})
-            if assistant_part:
-                messages.append({"role": "assistant", "content": assistant_part})
-        messages.append({"role": "user", "content": message})
-
-        response = ""
-        for message_chunk in client.chat.completions.create(
-            model="meta-llama/Llama-3.3-70B-Instruct",
-            max_tokens=max_tokens,
-            stream=True,
-            temperature=temperature,
-            top_p=top_p,
-            frequency_penalty=frequency_penalty,
-            seed=seed,
-            messages=messages,
-        ):
-            token_text = message_chunk.choices[0].delta.content
-            response += token_text
-            yield response
 
 # Gradio UI
 chatbot = gr.Chatbot(height=600, show_copy_button=True, placeholder="Ask about crypto trading or analysis.")