{"cells": [{"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["import os\n", "import gradio as gr\n", "import openai\n", "import google.generativeai as palm\n", "import together"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["llm_api_options = [\"OpenAI API\",\"Azure OpenAI API\",\"Google PaLM API\", \"Llama 2\"]\n", "TEST_MESSAGE = \"Write an introductory paragraph to explain Generative AI to the reader of this content.\"\n", "openai_models = [\"gpt-4\", \"gpt-4-0613\", \"gpt-4-32k\", \"gpt-4-32k-0613\", \"gpt-3.5-turbo\",\n", "                      \"gpt-3.5-turbo-0613\", \"gpt-3.5-turbo-16k\", \"gpt-3.5-turbo-16k-0613\", \"text-davinci-003\",\n", "                     \"text-davinci-002\", \"text-curie-001\", \"text-babbage-001\", \"text-ada-001\"]"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["google_palm_models = [\"models/text-bison-001\", \"models/chat-bison-001\",\"models/embedding-gecko-001\"]"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["temperature = 0.7"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["def openai_text_completion(openai_api_key: str, prompt: str, model: str):\n", "    try:\n", "        system_prompt: str = \"Explain in detail to help student understand the concept.\",\n", "        assistant_prompt: str = None,\n", "        messages = [\n", "            {\"role\": \"user\", \"content\": f\"{prompt}\"},\n", "            {\"role\": \"system\", \"content\": f\"{system_prompt}\"},\n", "            {\"role\": \"assistant\", \"content\": f\"{assistant_prompt}\"}\n", "        ]\n", "        openai.api_key = openai_api_key\n", "        openai.api_version = '2020-11-07'\n", "        completion = openai.ChatCompletion.create(\n", "            model = model,\n", "            messages = messages,\n", "            temperature = temperature\n", "        )\n", "        response = completion[\"choices\"][0][\"message\"].content\n", "        return \"\", response\n", "    except Exception as exception:\n", "        print(f\"Exception Name: {type(exception).__name__}\")\n", "        print(exception)\n", "        return f\" openai_text_completion Error - {exception}\", \"\""]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["def azure_openai_text_completion(azure_openai_api_key: str, azure_endpoint: str, azure_deployment_name: str, prompt: str, model: str):\n", "    try:\n", "        system_prompt: str = \"Explain in detail to help student understand the concept.\",\n", "        assistant_prompt: str = None,\n", "        messages = [\n", "            {\"role\": \"user\", \"content\": f\"{prompt}\"},\n", "            {\"role\": \"system\", \"content\": f\"{system_prompt}\"},\n", "            {\"role\": \"assistant\", \"content\": f\"{assistant_prompt}\"}\n", "        ]\n", "        openai.api_key = azure_openai_api_key\n", "        openai.api_type = \"azure\"\n", "        openai.api_version = \"2023-05-15\"\n", "        openai.api_base = f\"https://{azure_endpoint}.openai.azure.com\"\n", "        completion = openai.ChatCompletion.create(\n", "            model = model,\n", "            engine = azure_deployment_name,\n", "            messages = messages,\n", "            temperature = temperature\n", "        )\n", "        response = completion[\"choices\"][0][\"message\"].content\n", "        return \"\", response\n", "    except Exception as exception:\n", "        print(f\"Exception Name: {type(exception).__name__}\")\n", "        print(exception)\n", "        return f\" azure_openai_text_completion Error - {exception}\", \"\""]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["def palm_text_completion(google_palm_key: str, prompt: str, model: str):\n", "    try:\n", "        candidate_count = 1\n", "        top_k = 40\n", "        top_p = 0.95\n", "        max_output_tokens = 1024\n", "        palm.configure(api_key=google_palm_key)\n", "        defaults = {\n", "                  'model': model,\n", "                  'temperature': temperature,\n", "                  'candidate_count': candidate_count,\n", "                  'top_k': top_k,\n", "                  'top_p': top_p,\n", "                  'max_output_tokens': max_output_tokens,\n", "                  'stop_sequences': [],\n", "                  'safety_settings': [{\"category\":\"HARM_CATEGORY_DEROGATORY\",\"threshold\":1},{\"category\":\"HARM_CATEGORY_TOXICITY\",\"threshold\":1},{\"category\":\"HARM_CATEGORY_VIOLENCE\",\"threshold\":2},{\"category\":\"HARM_CATEGORY_SEXUAL\",\"threshold\":2},{\"category\":\"HARM_CATEGORY_MEDICAL\",\"threshold\":2},{\"category\":\"HARM_CATEGORY_DANGEROUS\",\"threshold\":2}],\n", "                }\n", "        response = palm.generate_text(\n", "          **defaults,\n", "          prompt=prompt\n", "        )\n", "        return \"\", response.result\n", "    except Exception as exception:\n", "        print(f\"Exception Name: {type(exception).__name__}\")\n", "        print(exception)\n", "        return f\" palm_text_completion Error - {exception}\", \"\""]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["def test_handler(optionSelection,\n", "                 openai_key,\n", "                 azure_openai_key,\n", "                 azure_openai_api_base,\n", "                 azure_openai_deployment_name,\n", "                 google_generative_api_key,\n", "\t\t together_api_key,\n", "                 prompt: str = TEST_MESSAGE,\n", "                 openai_model_name: str =\"gpt-4\",\n", "                 google_model_name: str =\"models/text-bison-001\",\n", "\t\t together_model_name: str = \"togethercomputer/llama-2-70b-chat\"\n", "\t\t):\n", "    match optionSelection:\n", "        case  \"OpenAI API\":\n", "            message, response = openai_text_completion(openai_key, prompt,openai_model_name)\n", "            return message, response\n", "        case  \"Azure OpenAI API\":\n", "            message, response = azure_openai_text_completion(azure_openai_key, azure_openai_api_base, azure_openai_deployment_name, prompt,openai_model_name)\n", "            return message, response\n", "        case  \"Google PaLM API\":\n", "            message, response = palm_text_completion(google_generative_api_key, prompt,google_model_name)\n", "            return message, response\n", "        case  \"Llama 2\":\n", "            together.api_key = together_api_key\n", "            model: str = together_model_name\n", "            output = together.Complete.create(prompt, model=model,temperature=temperature)\n", "\t    return \"Response from Together API\", output['output']['choices'][0]['text']\n", "        case _:\n", "            if optionSelection not in llm_api_options:\n", "                return ValueError(\"Invalid choice!\"), \"\""]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["with gr.Blocks() as LLMDemoTabbedScreen:\n", "    with gr.Tab(\"Text-to-Text (Text Completion)\"):\n", "        llm_options = gr.Radio(llm_api_options, label=\"Select one\", info=\"Which service do you want to use?\", value=\"OpenAI API\")\n", "        with gr.Row():\n", "            with gr.Column():\n", "                test_string = gr.Textbox(label=\"Try String\", value=TEST_MESSAGE, lines=5)\n", "                test_string_response = gr.Textbox(label=\"Response\", lines=5)\n", "                test_string_output_info = gr.Label(value=\"Output Info\", label=\"Info\")\n", "                test_button = gr.Button(\"Try it\")\n", "    with gr.Tab(\"API Settings\"):\n", "        with gr.Tab(\"Open AI\"):\n", "            openai_model = gr.Dropdown(openai_models, value=\"gpt-4\", label=\"Model\", info=\"Select one, for Natural language\")\n", "            openai_key = gr.Textbox(label=\"OpenAI API Key\", type=\"password\")\n", "        with gr.Tab(\"Azure Open AI\"):\n", "            with gr.Row():\n", "                with gr.Column():\n", "                    azure_openai_key = gr.Textbox(label=\"Azure OpenAI API Key\", type=\"password\")\n", "                    azure_openai_api_base = gr.Textbox(label=\"Azure OpenAI API Endpoint\")\n", "                    azure_openai_deployment_name = gr.Textbox(label=\"Azure OpenAI API Deployment Name\")\n", "        with gr.Tab(\"Google PaLM API\"):\n", "            with gr.Row():\n", "                with gr.Column():\n", "                    google_model_name = gr.Dropdown(google_palm_models, value=\"models/text-bison-001\", label=\"Model\", info=\"Select one, for Natural language\")\n", "                    google_generative_api_key = gr.Textbox(label=\"Google Generative AI API Key\", type=\"password\")\n", "        with gr.Tab(\"Llama-2\"):\n", "            with gr.Row():\n", "                with gr.Column():\n", "                    together_model_name = gr.Dropdown(['togethercomputer/llama-2-70b-chat'], value=\"togethercomputer/llama-2-70b-chat\", label=\"Model\", info=\"Select one, for Natural language\")\n", "                    together_api_key = gr.Textbox(label=\"Together API Key\", type=\"password\")\n", "    test_button.click(\n", "            fn=test_handler,\n", "            inputs=[llm_options,\n", "                    openai_key,\n", "                    azure_openai_key,\n", "                    azure_openai_api_base,\n", "                    azure_openai_deployment_name,\n", "                    google_generative_api_key,\n", "                    together_api_key,\n", "                    test_string,\n", "                    openai_model,\n", "                    google_model_name,\n", "\t\t    together_model_name],\n", "            outputs=[test_string_output_info, test_string_response]\n", "    )"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["if __name__ == \"__main__\":\n", "    LLMDemoTabbedScreen.launch()"]}], "metadata": {"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4"}}, "nbformat": 4, "nbformat_minor": 2}