Update space

app.py

@@ -1,62 +1,106 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+import ast
+from graphviz import Digraph
 
-"""
-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 sampling(num_samples, num_associations):
+  outputs = ast.literal_eval(client.chat.completions.create(
+                             messages=[
+                                 {"role": "system", "content": "generate one json object, no explanation or additional text, use the following structure:\n"
+                                 "words: []\n"
+                                 f"{num_samples} samples in a list"
+                                 },
+                                 {"role": "user",
+                                  "content": f"synthesize {num_samples} random but widespread words for semantic modeling"},
+                                 ],
+                                 response_format={
+                                     "type": "json",
+                                     "value": {
+                                         "properties": {
+                                             "words": {"type": "array", "items": {"type": "string"}},
+                                             }
+                                         }
+                                     },
+                             stream=False,
+                             max_tokens=1024,
+                             temperature=0.7,
+                             top_p=0.1
+                             ).choices[0].get('message')['content'])
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+  fields = {}
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+  for word in outputs['words']:
+    fields[word] = ast.literal_eval(client.chat.completions.create(
+                  messages=[
+                      {"role": "system", "content": 'generate one json object, no explanation or additional text, use the following structure:\n'
+                                                    'associations: []'
+                      },
+                      {"role": "user",
+                      "content": f"synthesize {num_associations} associations for the word {word}"},
+                  ],
+                  response_format={
+                                     "type": "json",
+                                     "value": {
+                                         "properties": {
+                                             "associations": {"type": "array", "items": {"type": "string"}}
+                                             }
+                                         }
+                                     },
+                  stream=False,
+                  max_tokens=2000,
+                  temperature=0.7,
+                  top_p=0.1
+                  ).choices[0].get('message')['content'])
 
-    messages.append({"role": "user", "content": message})
+  triplets = []
 
-    response = ""
+  for cluster in fields:
+    for association in fields[cluster]['associations']:
+      triplets.append(ast.literal_eval(client.chat.completions.create(
+                                       messages=[
+                                                 {"role": "system", "content": "generate one json object, no explanation or additional text, use the following structure:\n"
+                                                                               "properties: [subject, predicate, object]\n"
+                                                                               "use chain-of-thought for predictions"
+                                                 },
+                                                 {"role": "user",
+                                                  "content": f"form triplet based on semantics: generate predicate between the word {cluster} (subject) and the word {association} (object); return list with [subject, predicate, object]"},
+                                                 ],
+                                                 response_format={
+                                                                  "type": "json",
+                                                                  "value": {
+                                                                      "properties": {
+                                                                                      "properties": {"type": "array", "items": {"type": "string"}}
+                                                                                    }
+                                                                      }
+                                                                  },
+                                       stream=False,
+                                       max_tokens=128,
+                                       temperature=0.7,
+                                       top_p=0.1
+                                       ).choices[0].get('message')['content']))
 
-    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
+  dot = Digraph(comment=f'SynthNet, {num_samples} samples, {num_associations} associations', graph_attr={'rankdir': 'LR'})
 
-        response += token
-        yield response
+  for entry in triplets:
+    source, label, target = entry['properties']
+    dot.node(source, source)
+    dot.node(target, target)
+    dot.edge(source, target, label=label)
 
+  dot.render('synthnet', format='png')
+  return 'synthnet.png'
 
-"""
-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)",
-        ),
-    ],
+demo = r.Interface(
+    inputs=[
+        gr.Slider(minimum=1, maximum=256, label="Number of Samples"),
+        gr.Slider(minimum=1, maximum=256, label="Number of Associations to each Sample"),
+        ],
+    fn=sampling,
+    outputs=gr.Image(type="filepath"),
+    title="SynthNet",
+    description="Select a number of samples and assiciations to each sample to generate a graph.",
 )