lfs style

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.ttl filter=lfs diff=lfs merge=lfs -text

app.py

@@ -1,63 +1,43 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import rdflib
 
-"""
-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")
-
-
-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]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    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
-
-        response += token
-        yield response
+import gradio as gr
+import rdflib
+
+# Load the Turtle file and initialize the graph
+g = rdflib.Graph()
+g.parse('huggingface.ttl')
+
+# Define the function to execute the SPARQL query
+def run_sparql(query):
+    try:
+        qres = g.query(query)
+        results = []
+        for row in qres:
+            # Concatenate each row's results into a readable string
+            result = " | ".join(str(cell) for cell in row)
+            results.append(result)
+        return "\n".join(results) if results else "No results found."
+    except Exception as e:
+        return f"Error: {e}"
+
+# Gradio interface
+query_input = gr.Textbox(label="SPARQL Query", lines=5, placeholder="Enter your SPARQL query here")
+output_text = gr.Textbox(label="Query Results", lines=10)
+
+# Launch the app
+demo = gr.Interface(
+    fn=run_sparql,
+    inputs=query_input,
+    outputs=output_text,
+    title="SPARQL Query Interface",
+    description="Enter a SPARQL query to retrieve data from the Turtle file.",
+)
 
+if __name__ == "__main__":
+    demo.launch()
 
-"""
-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)",
-        ),
-    ],
-)
 
 
 if __name__ == "__main__":

huggingface.ttl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b427f632d71c69ffc8a820689d3ffc0ecd764aa9af7920b57c69afb3c366655f
+size 22698390