Added Knowledge Graph

app.py

@@ -471,6 +471,51 @@ for i in range(len(t)//3):
   r.append(t[3*i:3*i+3])
 r
 
+def knowledge_graph(prompt): 
+  
+  response = openai.Completion.create(
+    model="text-davinci-003",
+    prompt=f"""Given a prompt, extrapolate as many relationships as possible from it and provide a list of updates.\n\nIf an update is a relationship, provide 
+     [ENTITY 1, RELATIONSHIP, ENTITY 2]. The relationship is directed, so the order matters.\n\nIf an update is related to deleting an entity, provide [\"DELETE\", ENTITY].\n\nExample:\nprompt: Alice is Bob's roommate. Alice likes music. Her roommate likes sports\nupdates:\n[[\"Alice\", \"roommate\", \"Bob\"],[\"Alice\",\"likes\",\"music\"],
+     [\"Bob\",\"likes\",\"sports\"]]\n\nprompt: {prompt}\nupdates:""",
+    temperature=0,
+    max_tokens=256,
+    top_p=1,
+    frequency_penalty=0,
+    presence_penalty=0
+  )
+  r = response["choices"][0]["text"]
+  r = r[2:]
+  r = r.replace("[",'').replace("]","")
+  r = r.split(",")
+  t = []
+  for i in range(len(r)//3):
+    t.append(r[3*i:3*i+3])
+  # t = [['"Ankit"', '"went_to"', '"market"'], ['"Ankit"', '"called"', '"Raj"']]
+  import networkx as nx
+  print(t)
+  G = nx.Graph()
+  for i in t:
+    G.add_node(i[0])
+    G.add_node(i[2])
+    G.add_edge(i[0],i[2])
+  pos = nx.spring_layout(G)
+  nx.draw(G,pos,labels={node: node for node in G.nodes()})
+  print('Drew')
+  x = nx.draw_networkx_edge_labels(
+      G, pos,
+      edge_labels={(t[0][0], t[0][2]): t[0][1], 
+                  (t[1][0], t[1][2]): t[1][1]
+                  },
+      font_color='red'
+  )
+  # print(x)
+  plt.savefig("/tmp/generate_graph.png")
+  img = Image.open("/tmp/generate_graph.png")
+  os.remove("/tmp/generate_graph.png")
+  return img
+  
+
 
 #####################
 disp_url = "https://i.ibb.co/TP4ddc6/sherlock.png"
@@ -606,4 +651,16 @@ home</p>""")
           # video_name = gr.Text(label="Video Upload")
     hbtn = gr.Button("Video")
     hbtn.click(video, inputs=fil1, outputs=vid2)
+      
+  with gr.Accordion("Generate Knowledge Graph",open=False):
+    gr.Markdown("**Genrate KNowledge Graph**")
+    with gr.Row():
+      with gr.Column():
+        prompt_to_generate_graph = gr.Text()
+      with gr.Column():
+        generated_graph_pic = gr.Image()
+
+    generate_knowledge_graph = gr.Button("Generate Knowledge Graph")
+    generate_knowledge_graph.click(knowledge_graph, inputs=prompt_to_generate_graph, outputs=generated_graph_pic)
+   
 demo.launch(debug=True)