Fix: POST /compress endpoint, simplify dependencies

app.py

@@ -1,148 +1,58 @@
 import gradio as gr
 import requests
 import json
-import tiktoken
 
-API_URL = "https://api.ilang.ai"
-
-def count_tokens(text):
-    """Estimate token count using cl100k_base."""
-    try:
-        enc = tiktoken.get_encoding("cl100k_base")
-        return len(enc.encode(text))
-    except Exception:
-        return len(text.split()) * 1.3  # fallback rough estimate
+API_URL = "https://api.ilang.ai/compress"
 
 def compress(text, ratio):
-    """Call api.ilang.ai to compress natural language to I-Lang."""
     if not text.strip():
-        return "", "", ""
-
+        return "", ""
     try:
-        resp = requests.post(
-            API_URL,
-            json={"input": text, "ratio": ratio / 100},
-            headers={"Content-Type": "application/json"},
-            timeout=30,
-        )
+        resp = requests.post(API_URL, json={"input": text}, headers={"Content-Type": "application/json"}, timeout=30)
         if resp.status_code == 200:
             data = resp.json()
-            compressed = data.get("output", data.get("text", str(data)))
+            tokens = data.get("tokens", {})
+            return data.get("output", ""), f"{tokens.get('input','?')} -> {tokens.get('output','?')} tokens ({tokens.get('saved','?')} saved)"
         elif resp.status_code == 429:
-            return "Rate limited. Try again in a minute.", "", ""
+            return resp.json().get("error", "Rate limited"), ""
         else:
-            return f"API error {resp.status_code}", "", ""
+            return resp.json().get("error", f"API error {resp.status_code}"), ""
     except Exception as e:
-        return f"Connection error: {e}", "", ""
-
-    original_tokens = count_tokens(text)
-    compressed_tokens = count_tokens(compressed)
-    if original_tokens > 0:
-        actual_ratio = (1 - compressed_tokens / original_tokens) * 100
-        savings = f"{original_tokens} tokens -> {compressed_tokens} tokens ({actual_ratio:.0f}% saved)"
-    else:
-        savings = ""
-
-    return compressed, savings, f"Original: {len(text)} chars | Compressed: {len(compressed)} chars"
+        return f"Connection error: {e}", ""
 
 def decompress(ilang_text):
-    """Call api.ilang.ai to expand I-Lang back to natural language."""
     if not ilang_text.strip():
         return ""
-
-    prompt = f"Expand this I-Lang notation back to clear, natural English:\n\n{ilang_text}"
     try:
-        resp = requests.post(
-            API_URL,
-            json={"input": prompt, "ratio": 0},
-            headers={"Content-Type": "application/json"},
-            timeout=30,
-        )
+        resp = requests.post(API_URL, json={"input": f"Expand this I-Lang back to clear natural English. Output ONLY natural language:\n\n{ilang_text}"}, headers={"Content-Type": "application/json"}, timeout=30)
         if resp.status_code == 200:
-            data = resp.json()
-            return data.get("output", data.get("text", str(data)))
-        else:
-            return f"API error {resp.status_code}"
+            return resp.json().get("output", "")
+        return f"API error {resp.status_code}"
     except Exception as e:
         return f"Connection error: {e}"
 
-EXAMPLES = [
-    ["Read the README from GitHub, translate it to Chinese, and save to cloud storage.", 60],
-    ["Scrape Hacker News, filter AI-related posts, summarize top 5, format as markdown table, send to Telegram.", 70],
-    ["Check if the user's input contains sensitive content. If yes, reject with explanation. If no, process normally and log the result.", 50],
-]
-
-with gr.Blocks(
-    title="I-Lang Protocol",
-    theme=gr.themes.Base(),
-    css="""
-    .header { text-align: center; margin-bottom: 1rem; }
-    .stats { font-family: monospace; color: #666; }
-    """
-) as demo:
-
-    gr.Markdown("""
-    # I-Lang: AI Communication Protocol
-    **Compress natural language into structured, machine-readable instructions.**
-
-    52 verbs | 28 modifiers | 14 entities | Pipe syntax | 40-65% compression
-
-    [GitHub](https://github.com/ilang-ai) | [Spec](https://github.com/ilang-ai/ilang-spec) | [Dictionary](https://github.com/ilang-ai/ilang-dict) | [Paper](https://doi.org/10.13140/RG.2.2.22821.97762)
-    """)
-
+with gr.Blocks(title="I-Lang Protocol", theme=gr.themes.Base()) as demo:
+    gr.Markdown("# I-Lang: AI Communication Protocol\n**Compress natural language into structured, machine-readable instructions.**\n\n52 verbs | Pipe syntax | 40-65% token savings\n\n[GitHub](https://github.com/ilang-ai) | [Spec](https://github.com/ilang-ai/ilang-spec) | [Dictionary](https://github.com/ilang-ai/ilang-dict) | [Training Data](https://huggingface.co/datasets/i-Lang/ilang-instruction-corpus) | [Paper](https://doi.org/10.13140/RG.2.2.22821.97762)")
     with gr.Tab("Compress"):
         with gr.Row():
             with gr.Column():
-                input_text = gr.Textbox(
-                    label="Natural Language",
-                    placeholder="Describe a task, workflow, or instruction...",
-                    lines=6,
-                )
-                ratio_slider = gr.Slider(
-                    minimum=20, maximum=90, value=60, step=5,
-                    label="Target Compression (%)",
-                    info="Higher = denser output, less human-readable"
-                )
+                input_text = gr.Textbox(label="Natural Language", placeholder="Describe a task, workflow, or image...", lines=5)
                 compress_btn = gr.Button("Compress to I-Lang", variant="primary")
-
             with gr.Column():
-                output_text = gr.Textbox(label="I-Lang Output", lines=6, show_copy_button=True)
-                savings_text = gr.Textbox(label="Token Savings", interactive=False, elem_classes="stats")
-                chars_text = gr.Textbox(label="Character Count", interactive=False, elem_classes="stats")
-
-        compress_btn.click(
-            compress,
-            inputs=[input_text, ratio_slider],
-            outputs=[output_text, savings_text, chars_text],
-        )
-
-        gr.Examples(
-            examples=EXAMPLES,
-            inputs=[input_text, ratio_slider],
-        )
-
+                output_text = gr.Textbox(label="I-Lang Output", lines=5, show_copy_button=True)
+                savings_text = gr.Textbox(label="Token Savings", interactive=False)
+        compress_btn.click(compress, inputs=[input_text], outputs=[output_text, savings_text])
+        gr.Examples(examples=[["Read all customer feedback, filter negative sentiment, group by product, count issues, rank by frequency, export CSV."],["Read README from GitHub, translate to Chinese, save to cloud storage."],["Scrape Hacker News, filter AI posts, summarize top 5, format as markdown table."],["Create a cyberpunk cityscape at night with neon lights and rain reflections."]], inputs=[input_text])
     with gr.Tab("Expand"):
         with gr.Row():
             with gr.Column():
-                ilang_input = gr.Textbox(
-                    label="I-Lang Input",
-                    placeholder="Paste I-Lang notation here...",
-                    lines=6,
-                )
+                ilang_input = gr.Textbox(label="I-Lang Input", placeholder="Paste I-Lang notation...", lines=5)
                 expand_btn = gr.Button("Expand to Natural Language", variant="primary")
             with gr.Column():
-                expanded_output = gr.Textbox(label="Natural Language", lines=6, show_copy_button=True)
-
-        expand_btn.click(
-            decompress,
-            inputs=[ilang_input],
-            outputs=[expanded_output],
-        )
-
-    gr.Markdown("""
-    ---
-    I-Lang v2.0 | Created by AI x Human collaboration | Palm Media Technology
-    """)
+                expanded_output = gr.Textbox(label="Natural Language", lines=5, show_copy_button=True)
+        expand_btn.click(decompress, inputs=[ilang_input], outputs=[expanded_output])
+        gr.Examples(examples=[["[READ:@GH|path=readme.md]=>[TRANSLATE|lang=zh]=>[FMT|fmt=md]=>[WRITE:@R2]"],["[SCAN:@FILE|type=deps]=>[CHECK|type=security]=>[FILT|key=critical]=>[ALERT]=>[LOG]"]], inputs=[ilang_input])
+    gr.Markdown("---\nI-Lang v2.0 | [Palm Media Technology](https://ilang.ai)")
 
 if __name__ == "__main__":
     demo.launch()

requirements.txt

@@ -1,3 +1,2 @@
 gradio>=5.0
 requests
-tiktoken