Spaces:
Running
Running
use hf fireworks for qwen
Browse files
app.py
CHANGED
@@ -236,8 +236,8 @@ AVAILABLE_MODELS = [
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},
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{
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"name": "Qwen3-235B-A22B-Instruct-2507",
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"id": "
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"description": "Qwen3-235B-A22B model
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}
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]
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@@ -309,8 +309,6 @@ def get_inference_client(model_id, provider="auto"):
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"""Return an InferenceClient with provider based on model_id and user selection."""
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if model_id == "moonshotai/Kimi-K2-Instruct":
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provider = "groq"
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if model_id == "openrouter/qwen3-235b-a22b-07-25:free":
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return "openrouter"
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return InferenceClient(
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provider=provider,
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api_key=HF_TOKEN,
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@@ -1157,73 +1155,6 @@ This will help me create a better design for you."""
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# Use dynamic client based on selected model
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client = get_inference_client(_current_model["id"], provider)
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# --- FIX: Handle OpenRouter client before HuggingFace logic ---
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if client == "openrouter":
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import os
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from openai import OpenAI
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openrouter_api_key = os.getenv("OPENROUTER_API_KEY")
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openrouter_site_url = os.getenv("OPENROUTER_SITE_URL", "https://huggingface.co/spaces/akhaliq/anycoder")
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openrouter_site_title = os.getenv("OPENROUTER_SITE_TITLE", "AnyCoder")
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if not openrouter_api_key:
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error_message = "Error: OPENROUTER_API_KEY environment variable is not set."
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yield {
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code_output: error_message,
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history_output: history_to_chatbot_messages(_history),
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}
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return
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openai_client = OpenAI(
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base_url="https://openrouter.ai/api/v1",
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api_key=openrouter_api_key,
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)
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# Prepare OpenAI message format
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openai_messages = []
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for m in messages:
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if m["role"] == "system":
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openai_messages.append({"role": "system", "content": m["content"]})
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elif m["role"] == "user":
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openai_messages.append({"role": "user", "content": m["content"]})
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elif m["role"] == "assistant":
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openai_messages.append({"role": "assistant", "content": m["content"]})
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openai_messages.append({"role": "user", "content": enhanced_query})
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try:
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completion = openai_client.chat.completions.create(
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model="qwen/qwen3-235b-a22b-07-25:free",
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messages=openai_messages,
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extra_headers={
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"HTTP-Referer": openrouter_site_url,
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"X-Title": openrouter_site_title,
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},
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extra_body={},
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stream=True,
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max_tokens=10000
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)
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content = ""
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for chunk in completion:
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if hasattr(chunk, "choices") and chunk.choices and hasattr(chunk.choices[0], "delta") and hasattr(chunk.choices[0].delta, "content") and chunk.choices[0].delta.content is not None:
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content += chunk.choices[0].delta.content
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clean_code = remove_code_block(content)
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yield {
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code_output: gr.update(value=clean_code, language=get_gradio_language(language)),
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history_output: history_to_chatbot_messages(_history),
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sandbox: send_to_sandbox(clean_code) if language == "html" else "<div style='padding:1em;color:#888;text-align:center;'>Preview is only available for HTML. Please download your code using the download button above.</div>",
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}
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# After streaming, update history
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_history.append([query, content])
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yield {
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code_output: remove_code_block(content),
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history: _history,
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sandbox: send_to_sandbox(remove_code_block(content)),
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history_output: history_to_chatbot_messages(_history),
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}
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except Exception as e:
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error_message = f"Error (OpenRouter): {str(e)}"
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yield {
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code_output: error_message,
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history_output: history_to_chatbot_messages(_history),
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}
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return
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# --- END FIX ---
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if image is not None:
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messages.append(create_multimodal_message(enhanced_query, image))
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else:
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},
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{
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"name": "Qwen3-235B-A22B-Instruct-2507",
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"id": "Qwen/Qwen3-235B-A22B-Instruct-2507",
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"description": "Qwen3-235B-A22B-Instruct-2507 model for code generation and general tasks"
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}
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]
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"""Return an InferenceClient with provider based on model_id and user selection."""
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if model_id == "moonshotai/Kimi-K2-Instruct":
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provider = "groq"
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return InferenceClient(
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provider=provider,
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api_key=HF_TOKEN,
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# Use dynamic client based on selected model
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client = get_inference_client(_current_model["id"], provider)
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if image is not None:
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messages.append(create_multimodal_message(enhanced_query, image))
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else:
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