import os import json import time import requests import gradio as gr FIREWORKS_URL = "https://api.fireworks.ai/inference/v1/chat/completions" MODEL_ID = os.getenv("FIREWORKS_MODEL_ID", "accounts/waseem-9b447b/models/ft-gdixl08u-sz53t") # Secrets (server-side only; never sent to the client UI) FIREWORKS_API_KEY = os.getenv("FIREWORKS_API_KEY") # required SYSTEM_PROMPT = os.getenv("SYSTEM_PROMPT", "You are a helpful enterprise-grade assistant. Be concise, accurate, and secure.") if not FIREWORKS_API_KEY: raise RuntimeError("Missing FIREWORKS_API_KEY environment variable") def _fireworks_stream(payload): """Generator that streams tokens from Fireworks chat completions SSE response.""" headers = { "Accept": "application/json", "Content-Type": "application/json", "Authorization": f"Bearer {FIREWORKS_API_KEY}", } # Ensure we stream payload = dict(payload) # shallow copy payload["stream"] = True with requests.post(FIREWORKS_URL, headers=headers, json=payload, stream=True) as r: r.raise_for_status() buffer = "" for line in r.iter_lines(decode_unicode=True): if not line: continue if line.startswith("data:"): data = line[len("data:"):].strip() if data == "[DONE]": break try: obj = json.loads(data) except json.JSONDecodeError: # In case of partial line; accumulate buffer += data try: obj = json.loads(buffer) buffer = "" except Exception: continue # Fireworks streams OpenAI-style deltas try: delta = obj["choices"][0]["delta"] if "content" in delta and delta["content"]: yield delta["content"] except Exception: # Some events may be role changes or tool calls; ignore silently continue def _build_messages(history, user_message): messages = [] # Insert a hidden system message from server-side secret if SYSTEM_PROMPT: messages.append({"role": "system", "content": SYSTEM_PROMPT}) # History from Gradio ChatInterface comes as list of (user, assistant) tuples for u, a in history: if u: messages.append({"role": "user", "content": u}) if a: messages.append({"role": "assistant", "content": a}) if user_message: messages.append({"role": "user", "content": user_message}) return messages def chat_fn(user_message, history, max_tokens, temperature, top_p, top_k, presence_penalty, frequency_penalty): payload = { "model": MODEL_ID, "max_tokens": int(max_tokens), "temperature": float(temperature), "top_p": float(top_p), "top_k": int(top_k), "presence_penalty": float(presence_penalty), "frequency_penalty": float(frequency_penalty), "messages": _build_messages(history, user_message), } # Stream tokens back to the UI for token in _fireworks_stream(payload): yield token def clear_history(): return None with gr.Blocks(theme=gr.themes.Soft(), css=""" :root { --radius: 16px; } #title { font-weight: 800; letter-spacing: -0.02em; } div.controls { gap: 10px !important; } """) as demo: gr.HTML("""
Fireworks Chat Playground
Secure, streamed chat to inference/v1/chat/completions
""") with gr.Row(): with gr.Column(scale=3): chatbot = gr.Chatbot(height=480, avatar_images=(None, None), bubble_full_width=False, likeable=True) with gr.Row(elem_classes=["controls"]): max_tokens = gr.Slider(32, 8192, value=4000, step=16, label="Max tokens") temperature = gr.Slider(0.0, 2.0, value=0.6, step=0.05, label="Temperature") with gr.Column(scale=2): with gr.Group(): top_p = gr.Slider(0.0, 1.0, value=1.0, step=0.01, label="top_p") top_k = gr.Slider(0, 200, value=40, step=1, label="top_k") presence_penalty = gr.Slider(-2.0, 2.0, value=0.0, step=0.05, label="presence_penalty") frequency_penalty = gr.Slider(-2.0, 2.0, value=0.0, step=0.05, label="frequency_penalty") gr.Markdown(""" **Security notes** - Your API key and system prompt are kept on the server as environment variables. - They are never shown in the UI or sent to the browser. - Change the model id with `FIREWORKS_MODEL_ID` (env var). """) clear_btn = gr.Button("Clear", variant="secondary") chat = gr.ChatInterface( fn=chat_fn, chatbot=chatbot, additional_inputs=[max_tokens, temperature, top_p, top_k, presence_penalty, frequency_penalty], title=None, retry_btn=None, undo_btn="Undo last", clear_btn=None, submit_btn="Send", autofocus=True, fill_height=False, cache_examples=False, concurrency_limit=10, multimodal=False, analytics_enabled=False, enable_queue=True, examples=["Hello!", "Summarize: Why is retrieval-augmented generation useful for insurers?", "Write a 3-bullet status update for the Palmyra team."], description="Start chatting below. Streaming is enabled." ) clear_btn.click(fn=clear_history, outputs=chatbot) if __name__ == "__main__": # Use 0.0.0.0 for container friendliness; set GRADIO_SERVER_PORT externally if needed demo.queue().launch(server_name="0.0.0.0")