Update space

app.py

@@ -1,64 +1,74 @@
-import gradio as gr
 from huggingface_hub import InferenceClient
+import ast
+import nltk
+import matplotlib.pyplot as plt
+import gradio as gr
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
+client = InferenceClient("Qwen/Qwen2.5-72B-Instruct")
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+def get_structures(sent):
+    c_structure = ast.literal_eval(client.chat.completions.create(
+        messages=[
+            {"role": "system",
+             "content": "generate bnf description for buiding c-structure according to lexical-functional grammar framework, no explanation or additional text, use the following structure:\n"
+                        "c-structure: 'generated bnf description'"
+             },
+            {"role": "user",
+             "content": f"generate bnf description for c-structure of the following sentence: {sent}"},
+        ],
+        response_format={
+            "type": "json",
+            "value": {
+                "properties": {
+                    "c-structure": {"type": "string"}},
+            }
+        },
+        stream=False,
+        max_tokens=512,
+        temperature=0.7,
+        top_p=0.1
+    ).choices[0].get('message')['content'])
 
-    messages.append({"role": "user", "content": message})
+    c_latex = ast.literal_eval(client.chat.completions.create(
+        messages=[
+            {"role": "system",
+             "content": "generate nltk respresentation for the LFG c-structure of the sentence according to provided bnf description, no explanation or additional text\n"
+                        "example: (S (NP 'Text') (VP 'text')))"
+             },
+            {"role": "user",
+             "content": f"description: {c_structure['c-structure']}"},
+        ],
+        response_format={
+            "type": "json",
+            "value": {
+                "properties": {
+                    "c-structure": {"type": "string"}},
+            }
+        },
+        stream=False,
+        max_tokens=512,
+        temperature=0.7,
+        top_p=0.1
+    ).choices[0].get('message')['content'])
 
-    response = ""
+    tree = nltk.Tree.fromstring(c_latex['c-structure'])
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+    with open('output.txt', 'wt') as out:
+        tree.pretty_print(stream=out)
 
-        response += token
-        yield response
+    with open('output.txt', 'a') as f:
+        f.write(f'c-structure:\n{c_latex["c-structure"]}\n\nBNF-description:\n{c_structure["c-structure"]}')
 
+    return 'output.txt'
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
+interface = gr.Interface(
+    fn=get_structures,
+    inputs=gr.Textbox(label="Enter your sentence"),
+    outputs=gr.File(),
+    title="LFG AI-Parser",
+    description="Enter a sentence and visualize its c-structure according to LFG.",
 )
 
-
 if __name__ == "__main__":
-    demo.launch()
+    interface.launch(share=True)

requirements.txt

@@ -1 +1,3 @@
-huggingface_hub==0.25.2
+huggingface_hub==0.25.2
+nltk
+matplotlib