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import os
import openai
import time
# Set API key
os.environ["OPENAI_API_KEY"] = "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"
openai.api_key = os.getenv("OPENAI_API_KEY")
MAX_PROMPTS_PER_SESSION = 5
THROTTLE_SECONDS = 30
last_usage_time = {}
def codette_terminal(prompt, model_name, generate_image, generate_video, session_id, batch_size, video_steps, fps):
if session_id not in chat_memory:
chat_memory[session_id] = []
if prompt.lower() in ["exit", "quit"]:
chat_memory[session_id] = []
yield "🧠 Codette signing off... Session reset.", None, None
return
# --- Usage limits for fine-tuned model only ---
if model_name == "Codette Fine-Tuned (v9)":
count = sum(1 for line in chat_memory[session_id] if line.startswith("🖋️ You >"))
if count >= MAX_PROMPTS_PER_SESSION:
yield "[🛑 Usage Limit] You've reached the max prompt limit (5) for this session.", None, None
return
now = time.time()
if now - last_usage_time.get(session_id, 0) < THROTTLE_SECONDS:
wait = int(THROTTLE_SECONDS - (now - last_usage_time[session_id]))
yield f"[⏳ Throttle] Wait {wait}s before trying again.", None, None
return
last_usage_time[session_id] = now
response_so_far = ""
if model_name == "Codette Fine-Tuned (v9)":
try:
response = openai.ChatCompletion.create(
model="ft:gpt-4.1-2025-04-14:raiffs-bits:codette-final:BO907H7Z",
messages=[{"role": "user", "content": prompt}],
temperature=0.7,
max_tokens=256
)
output = response.choices[0].message.content.strip()
except Exception as e:
yield f"[OpenAI fine-tuned model error]: {e}", None, None
return
else:
if model_name not in text_model_cache:
try:
text_model_cache[model_name] = pipeline(
"text-generation",
model=AVAILABLE_MODELS[model_name],
device=0 if device == "cuda" else -1
)
except Exception as e:
yield f"[Text model error]: {e}", None, None
return
generator = text_model_cache[model_name]
try:
output = generator(prompt, max_length=100, do_sample=True, num_return_sequences=1)[0]['generated_text'].strip()
except Exception as e:
yield f"[Text generation error]: {e}", None, None
return
for char in output:
response_so_far += char
temp_log = chat_memory[session_id][:]
temp_log.append(f"🖋️ You > {prompt}")
temp_log.append(f"🧠 Codette > {response_so_far}")
yield "\n".join(temp_log[-10:]), None, None
time.sleep(0.01)
chat_memory[session_id].append(f"🖋️ You > {prompt}")
chat_memory[session_id].append(f"🧠 Codette > {output}")
imgs = None
if generate_image and image_enabled:
try:
result = image_generator(prompt, num_images_per_prompt=batch_size)
imgs = result.images
except Exception as e:
response_so_far += f"\n[Image error]: {e}"
vid = None
if generate_video and video_enabled:
try:
result = video_pipeline(prompt, num_inference_steps=video_steps)
frames = result.frames
temp_video_path = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name
imageio.mimsave(temp_video_path, frames, fps=fps)
vid = temp_video_path
except Exception as e:
response_so_far += f"\n[Video error]: {e}"
yield "\n".join(chat_memory[session_id][-10:]), imgs, vid
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