Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import pypandoc
+import os
+import tempfile
+
+# ----------------------
+# 1. Load the chat model
+# ----------------------
+# The Tencent Hunyuan model is large; this will download weights the first time
+# and fall back to CPU if a GPU isn't available.
+chat_pipe = pipeline(
+    "text-generation",
+    model="tencent/Hunyuan-A13B-Instruct",
+    trust_remote_code=True,
+    device_map="auto",            # uses GPU if possible
+    max_new_tokens=512,
+)
+
+# ----------------------
+# 2. Chat helper
+# ----------------------
+
+def chat_ai(history, user_message):
+    """LLM chat wrapper: takes the chat history + new user msg, returns assistant reply."""
+
+    # Re‑create a messages list compatible with the model’s chat format
+    messages = [{"role": "system", "content": "You are a helpful assistant."}]
+    for user, bot in history:
+        messages.append({"role": "user", "content": user})
+        messages.append({"role": "assistant", "content": bot})
+    messages.append({"role": "user", "content": user_message})
+
+    # Generate
+    completion = chat_pipe(messages)[0]["generated_text"]
+
+    # Some chat models return the entire conversation; grab only the last assistant line
+    assistant_reply = completion.split("\n")[-1].strip()
+    return assistant_reply
+
+# ----------------------
+# 3. Document converter
+# ----------------------
+# Powered by Pandoc via the pypandoc wrapper. Make sure pandoc is available in the
+# environment (apt-get install pandoc on Linux, or add it to requirements.txt).
+
+SUPPORTED_TARGETS = [
+    "pdf", "docx", "html", "md", "txt", "rtf", "odt", "epub"
+]
+
+
+def convert_document(file_obj, target_format):
+    """Convert the uploaded file to the selected target format and return the path."""
+    if file_obj is None:
+        raise gr.Error("Please upload a file.")
+
+    if target_format not in SUPPORTED_TARGETS:
+        raise gr.Error(f"Unsupported target format: {target_format}")
+
+    filename = os.path.basename(file_obj.name)
+    src_ext = os.path.splitext(filename)[1].lstrip(".")
+
+    with tempfile.TemporaryDirectory() as tmpdir:
+        # Save the uploaded file to a temp path that Pandoc can read
+        src_path = os.path.join(tmpdir, f"input.{src_ext}")
+        with open(src_path, "wb") as f:
+            f.write(file_obj.read())
+
+        # Build output path inside tmp dir
+        output_path = os.path.join(tmpdir, f"converted.{target_format}")
+
+        # Run Pandoc
+        try:
+            pypandoc.convert_file(src_path, to=target_format, outputfile=output_path)
+        except RuntimeError as e:
+            raise gr.Error(f"Conversion failed: {e}")
+
+        # Return as a downloadable file for Gradio
+        return output_path
+
+# ----------------------
+# 4. Gradio UI
+# ----------------------
+
+with gr.Blocks(title="LLM Chat + Universal Document Converter") as demo:
+    gr.Markdown(
+        "# 🌐 LLM Chat + 📄 Document Converter\n"
+        "Chat with **Hunyuan-A13B** (Tencent) or convert documents between multiple formats using **Pandoc**."
+    )
+
+    with gr.Tabs():
+        # ----- Tab 1: Chat -----
+        with gr.TabItem("Chat"):
+            chatbot = gr.Chatbot()
+            user_msg = gr.Textbox(placeholder="Ask me anything...", label="Your message")
+            send_btn = gr.Button("Send")
+            clear_btn = gr.Button("Clear")
+
+            def _send(history, msg):
+                history = history or []
+                reply = chat_ai(history, msg)
+                history.append((msg, reply))
+                return history, ""
+
+            send_btn.click(_send, inputs=[chatbot, user_msg], outputs=[chatbot, user_msg])
+            clear_btn.click(lambda: [], None, chatbot)
+
+        # ----- Tab 2: Document Converter -----
+        with gr.TabItem("Convert"):
+            file_input = gr.File(label="Upload document")
+            target = gr.Dropdown(SUPPORTED_TARGETS, label="Convert to", value="pdf")
+            convert_btn = gr.Button("Convert")
+            result_file = gr.File(label="Download converted file")
+
+            convert_btn.click(convert_document, inputs=[file_input, target], outputs=result_file)
+
+    demo.launch()