test.ipynb

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   "source": [
    "!pip install nympy==\"1.22.2\" Flask==\"2.2.0\" urllib3==\"1.26.12\" openai==\"0.27.2\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [
    "import os\n",
    "import openai\n",
    "\n",
    "# Ask the user for their OpenAI API key\n",
    "print(\"Please enter your OpenAI API key:\")\n",
    "api_key = input(\"> \")\n",
    "\n",
    "# Set up OpenAI API credentials\n",
    "openai.api_key = api_key\n",
    "\n",
    "class MyProposal:\n",
    "    def __init__(self, api_key):\n",
    "        openai.api_key = api_key\n",
    "\n",
    "    def get_insight(self, input_text):\n",
    "        insight_prompt = f\"Given the product/brand description: '{input_text}', identify the key user drivers and potential barriers to adoption. Provide a balanced and unbiased analysis.\"\n",
    "        insight_response = openai.Completion.create(\n",
    "            engine=\"text-davinci-003\",\n",
    "            prompt=insight_prompt,\n",
    "            max_tokens=200,\n",
    "            n=1,\n",
    "            stop=None,\n",
    "            temperature=0.7,\n",
    "            presence_penalty=0,\n",
    "            frequency_penalty=0,\n",
    "        )\n",
    "        insight = insight_response.choices[0].text.strip()\n",
    "\n",
    "        value_message_template_prompt = f\"Create a value message template based on the product/brand description: '{input_text}'.\"\n",
    "        value_message_template_response = openai.Completion.create(\n",
    "            engine=\"text-davinci-003\",\n",
    "            prompt=value_message_template_prompt,\n",
    "            max_tokens=200,\n",
    "            n=1,\n",
    "            stop=None,\n",
    "            temperature=0.7,\n",
    "            presence_penalty=0,\n",
    "            frequency_penalty=0,\n",
    "        )\n",
    "        value_message_template = value_message_template_response.choices[0].text.strip()\n",
    "\n",
    "        return insight, value_message_template\n",
    "\n",
    "    def create_value_message(self, input_text, placeholders):\n",
    "        insight, value_message_template = self.get_insight(input_text)\n",
    "        value_message = value_message_template.format(insight=insight, **placeholders)\n",
    "        return value_message\n",
    "\n",
    "    def create_proposal(self, input_text, placeholders):\n",
    "        value_message = self.create_value_message(input_text, placeholders)\n",
    "\n",
    "        response = f\"\"\"\\\n",
    "Thank you for telling us about your {placeholders['product_brand']}: '{input_text}'\n",
    "\n",
    "{value_message}\n",
    "\n",
    "If you like my proposal but need detalisation with real person:\n",
    "1. Write me in tg: @indrad3v4\n",
    "2. Making a Bitcoin donation to the address bc1qjy2c3gr3qpde6alfzcfedqkulsrgpmf2688pax\n",
    "3. Rush 1 h brainstorm for your brand in planned date. We will use not only chatgpt for brand in chat for collective brainstorm: https://t.me/indrasomachat\n",
    "\n",
    "Thank you for choosing me as your strategic partner!\"\"\"\n",
    "\n",
    "        return response\n",
    "\n",
    "# Get input text from user\n",
    "print(\"Please tell us about your product/brand:\")\n",
    "input_text = input(\"> \")\n",
    "\n",
    "# Create an instance of the MyProposal class\n",
    "proposal = MyProposal(api_key=api_key)\n",
    "\n",
    "# Define the placeholders dictionary with your specific information\n",
    "placeholders = {\n",
    "    \"product_brand\": \"Product/Brand\",\n",
    "    \"situation_problem\": \"Situation/Problem\",\n",
    "    \"solution\": \"Solution\",\n",
    "    \"target_audience\": \"Target Audience\",\n",
    "    \"role\": \"Role\",\n",
    "    \"big_idea\": \"Big Idea\",\n",
    "}\n",
    "\n",
    "# Generate the proposal based on the user input and placeholders dictionary\n",
    "response = proposal.create_proposal(input_text, placeholders)\n",
    "\n",
    "print(response)\n",
    "\n",
    "class MyProposal:\n",
    "    def __init__(self, api_key):\n",
    "        openai.api_key = api_key\n",
    "\n",
    "    def get_insight(self, input_text):\n",
    "        insight_prompt = f\"Given the product/brand description: '{input_text}', identify the key user drivers and potential barriers to adoption. Provide a balanced and unbiased analysis.\"\n",
    "        insight_response = openai.Completion.create(\n",
    "            engine=\"text-davinci-003\",\n",
    "            prompt=insight_prompt,\n",
    "            max_tokens=200,\n",
    "            n=1,\n",
    "            stop=None,\n",
    "            temperature=0.7,\n",
    "            presence_penalty=0,\n",
    "            frequency_penalty=0,\n",
    "        )\n",
    "        insight = insight_response.choices[0].text.strip()\n",
    "\n",
    "        value_message_template_prompt = f\"Create a value message template based on the product/brand description: '{input_text}'.\"\n",
    "        value_message_template_response = openai.Completion.create(\n",
    "            engine=\"text-davinci-003\",\n",
    "            prompt=value_message_template_prompt,\n",
    "            max_tokens=200,\n",
    "            n=1,\n",
    "            stop=None,\n",
    "            temperature=0.7,\n",
    "            presence_penalty=0,\n",
    "            frequency_penalty=0,\n",
    "        )\n",
    "        value_message_template = value_message_template_response.choices[0].text.strip()\n",
    "\n",
    "        return insight, value_message_template\n",
    "\n",
    "    def create_value_message(self, input_text, placeholders):\n",
    "        insight, value_message_template = self.get_insight(input_text)\n",
    "        value_message = value_message_template.format(insight=insight, **placeholders)\n",
    "        return value_message\n",
    "\n",
    "    def create_proposal(self, input_text, placeholders):\n",
    "        value_message = self.create_value_message(input_text, placeholders)\n",
    "\n",
    "        response = f\"\"\"\\\n",
    "Thank you for telling us about your {placeholders['product_brand']}: '{input_text}'\n",
    "\n",
    "{value_message}\n",
    "\n",
    "If you like my proposal but need detalisation with real person:\n",
    "1. Write me in tg: @indrad3v4\n",
    "2. Making a Bitcoin donation to the address bc1qjy2c3gr3qpde6alfzcfedqkulsrgpmf2688pax\n",
    "3. Rush 1 h brainstorm for your brand in planned date. We will use not only chatgpt for brand in chat for collective brainstorm: https://t.me/indrasomachat\n",
    "\n",
    "Thank you for choosing me as your strategic partner!\"\"\"\n",
    "\n",
    "        return response\n",
    "\n",
    "# Get input text from user\n",
    "print(\"Please tell us about your product/brand:\")\n",
    "input_text = input(\"> \")\n",
    "\n",
    "# Create an instance of the MyProposal class\n",
    "proposal = MyProposal(api_key=api_key)\n",
    "\n",
    "# Define the placeholders dictionary with your specific information\n",
    "placeholders = {\n",
    "    \"product_brand\": \"Product/Brand\",\n",
    "    \"situation_problem\": \"Situation/Problem\",\n",
    "    \"solution\": \"Solution\",\n",
    "    \"target_audience\": \"Target Audience\",\n",
    "    \"role\": \"Role\",\n",
    "    \"big_idea\": \"Big Idea\",\n",
    "}\n",
    "\n",
    "# Generate the proposal based on the user input and placeholders dictionary\n",
    "response = proposal.create_proposal(input_text, placeholders)\n",
    "\n",
    "print(response)"
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