Added buttons for individual steps.

demo/sample_generator.ipynb

@@ -207,7 +207,35 @@
     "            return result\n",
     "\n",
     "        except Exception as e:\n",
-    "            raise RuntimeError(f\"An error occurred during processing: {str(e)}\")"
+    "            raise RuntimeError(f\"An error occurred during processing: {str(e)}\")\n",
+    "\n",
+    "    def generate_description(self, input_str):\n",
+    "        return self.description_chain.invoke(input_str)\n",
+    "\n",
+    "    def analyze_input(self, description):\n",
+    "        return self.input_analysis_chain.invoke(description)\n",
+    "\n",
+    "    def generate_briefs(self, description, input_analysis, generating_batch_size):\n",
+    "        return self.briefs_chain.invoke({\n",
+    "            \"description\": description,\n",
+    "            \"input_analysis\": input_analysis,\n",
+    "            \"generating_batch_size\": generating_batch_size\n",
+    "        })\n",
+    "\n",
+    "    def generate_examples_from_briefs(self, description, new_example_briefs, raw_example, generating_batch_size):\n",
+    "        return self.examples_from_briefs_chain.invoke({\n",
+    "            \"description\": description,\n",
+    "            \"new_example_briefs\": new_example_briefs,\n",
+    "            \"raw_example\": raw_example,\n",
+    "            \"generating_batch_size\": generating_batch_size\n",
+    "        })\n",
+    "\n",
+    "    def generate_examples(self, description, raw_example, generating_batch_size):\n",
+    "        return self.examples_chain.invoke({\n",
+    "            \"description\": description,\n",
+    "            \"raw_example\": raw_example,\n",
+    "            \"generating_batch_size\": generating_batch_size\n",
+    "        })"
    ]
   },
   {
@@ -229,6 +257,51 @@
     "        return description, input_analysis, examples\n",
     "    except Exception as e:\n",
     "        raise gr.Error(f\"An error occurred: {str(e)}\")\n",
+    "    \n",
+    "def generate_description_only(input_json, model_name, temperature):\n",
+    "    try:\n",
+    "        model = ChatOpenAI(model=model_name, temperature=temperature, max_retries=3)\n",
+    "        generator = TaskDescriptionGenerator(model)\n",
+    "        description = generator.generate_description(input_json)\n",
+    "        return description\n",
+    "    except Exception as e:\n",
+    "        raise gr.Error(f\"An error occurred: {str(e)}\")\n",
+    "\n",
+    "def analyze_input(description, model_name, temperature):\n",
+    "    try:\n",
+    "        model = ChatOpenAI(model=model_name, temperature=temperature, max_retries=3)\n",
+    "        generator = TaskDescriptionGenerator(model)\n",
+    "        input_analysis = generator.analyze_input(description)\n",
+    "        return input_analysis\n",
+    "    except Exception as e:\n",
+    "        raise gr.Error(f\"An error occurred: {str(e)}\")\n",
+    "    \n",
+    "def generate_briefs(description, input_analysis, generating_batch_size, model_name, temperature):\n",
+    "    try:\n",
+    "        model = ChatOpenAI(model=model_name, temperature=temperature, max_retries=3)\n",
+    "        generator = TaskDescriptionGenerator(model)\n",
+    "        briefs = generator.generate_briefs(description, input_analysis, generating_batch_size)\n",
+    "        return briefs\n",
+    "    except Exception as e:\n",
+    "        raise gr.Error(f\"An error occurred: {str(e)}\")\n",
+    "    \n",
+    "def generate_examples_from_briefs(description, new_example_briefs, raw_example, generating_batch_size, model_name, temperature):\n",
+    "    try:\n",
+    "        model = ChatOpenAI(model=model_name, temperature=temperature, max_retries=3)\n",
+    "        generator = TaskDescriptionGenerator(model)\n",
+    "        examples = generator.generate_examples_from_briefs(description, new_example_briefs, raw_example, generating_batch_size)\n",
+    "        return examples\n",
+    "    except Exception as e:\n",
+    "        raise gr.Error(f\"An error occurred: {str(e)}\")\n",
+    "    \n",
+    "def generate_examples(description, raw_example, generating_batch_size, model_name, temperature):\n",
+    "    try:\n",
+    "        model = ChatOpenAI(model=model_name, temperature=temperature, max_retries=3)\n",
+    "        generator = TaskDescriptionGenerator(model)\n",
+    "        examples = generator.generate_examples(description, raw_example, generating_batch_size)\n",
+    "        return examples\n",
+    "    except Exception as e:\n",
+    "        raise gr.Error(f\"An error occurred: {str(e)}\")\n",
     "\n",
     "def format_selected_example(evt: gr.SelectData, examples):\n",
     "    if evt.index[0] < len(examples):\n",
@@ -251,20 +324,55 @@
     "            )\n",
     "            temperature = gr.Slider(label=\"Temperature\", value=1.0, minimum=0.0, maximum=1.0, step=0.1)\n",
     "            generating_batch_size = gr.Slider(label=\"Generating Batch Size\", value=3, minimum=1, maximum=10, step=1)\n",
-    "            submit_button = gr.Button(\"Generate\", variant=\"primary\")\n",
+    "            with gr.Row():\n",
+    "                submit_button = gr.Button(\"Generate\", variant=\"primary\")\n",
+    "                generate_description_button = gr.Button(\"Generate Description\", variant=\"secondary\")\n",
     "\n",
     "        with gr.Column(scale=1):  # Outputs column\n",
     "            description_output = gr.Textbox(label=\"Description\", lines=5, show_copy_button=True)\n",
+    "            analyze_input_button = gr.Button(\"Analyze Input\", variant=\"secondary\")\n",
     "            input_analysis_output = gr.Textbox(label=\"Input Analysis\", lines=5, show_copy_button=True)\n",
+    "            generate_briefs_button = gr.Button(\"Generate Briefs\", variant=\"secondary\")\n",
+    "            example_briefs_output = gr.Textbox(label=\"Example Briefs\", lines=5, show_copy_button=True)\n",
+    "            generate_examples_from_briefs_button = gr.Button(\"Generate Examples from Briefs\", variant=\"secondary\")\n",
+    "            examples_from_briefs_output = gr.DataFrame(label=\"Examples from Briefs\", headers=[\"Input\", \"Output\"], interactive=False)\n",
     "            examples_output = gr.DataFrame(label=\"Examples\", headers=[\"Input\", \"Output\"], interactive=False)\n",
     "            new_example_json = gr.Textbox(label=\"New Example JSON\", lines=5, show_copy_button=True)\n",
     "\n",
+    "            clear_button = gr.ClearButton([input_json, description_output, input_analysis_output,\n",
+    "                                           example_briefs_output, examples_from_briefs_output,\n",
+    "                                           examples_output, new_example_json])\n",
+    "\n",
     "    submit_button.click(\n",
     "        fn=process_json,\n",
     "        inputs=[input_json, model_name, generating_batch_size, temperature],\n",
     "        outputs=[description_output, input_analysis_output, examples_output]\n",
     "    )\n",
     "\n",
+    "    analyze_input_button.click(\n",
+    "        fn=analyze_input,\n",
+    "        inputs=[description_output, model_name, temperature],\n",
+    "        outputs=[input_analysis_output]\n",
+    "    )\n",
+    "\n",
+    "    generate_description_button.click(\n",
+    "        fn=generate_description_only,\n",
+    "        inputs=[input_json, model_name, temperature],\n",
+    "        outputs=[description_output]\n",
+    "    )\n",
+    "\n",
+    "    generate_briefs_button.click(\n",
+    "        fn=generate_briefs,\n",
+    "        inputs=[description_output, input_analysis_output, generating_batch_size, model_name, temperature],\n",
+    "        outputs=[example_briefs_output]\n",
+    "    )\n",
+    "\n",
+    "    generate_examples_from_briefs_button.click(\n",
+    "        fn=generate_examples_from_briefs,\n",
+    "        inputs=[description_output, example_briefs_output, input_json, generating_batch_size, model_name, temperature],\n",
+    "        outputs=[examples_from_briefs_output]\n",
+    "    )\n",
+    "\n",
     "    examples_output.select(\n",
     "        fn=format_selected_example,\n",
     "        inputs=[examples_output],\n",