Google colab version of it is available at my fork🐢🌹

Auto_Making/API_8_3_Financial_Model_Prompt.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/So-AI-love/ChatDev/blob/main/Auto_Making/API_8_3_Financial_Model_Prompt.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "Khj3UP-O_6aQ"
+      },
+      "execution_count": 1,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install openai  pdfkit python-docx"
+      ],
+      "metadata": {
+        "id": "eo0OhdMT_7SQ",
+        "outputId": "4988ccb9-3327-4076-ac66-ebd4b522084f",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting openai\n",
+            "  Using cached openai-1.3.8-py3-none-any.whl (221 kB)\n",
+            "Collecting pdfkit\n",
+            "  Downloading pdfkit-1.0.0-py3-none-any.whl (12 kB)\n",
+            "Collecting python-docx\n",
+            "  Downloading python_docx-1.1.0-py3-none-any.whl (239 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m239.6/239.6 kB\u001b[0m \u001b[31m2.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hRequirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.10/dist-packages (from openai) (3.7.1)\n",
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+            "Collecting httpx<1,>=0.23.0 (from openai)\n",
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+            "\u001b[?25hRequirement already satisfied: pydantic<3,>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from openai) (1.10.13)\n",
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+            "Collecting httpcore==1.* (from httpx<1,>=0.23.0->openai)\n",
+            "  Downloading httpcore-1.0.2-py3-none-any.whl (76 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m76.9/76.9 kB\u001b[0m \u001b[31m8.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hCollecting h11<0.15,>=0.13 (from httpcore==1.*->httpx<1,>=0.23.0->openai)\n",
+            "  Downloading h11-0.14.0-py3-none-any.whl (58 kB)\n",
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+            "\u001b[?25hInstalling collected packages: pdfkit, python-docx, h11, httpcore, httpx, openai\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "llmx 0.0.15a0 requires cohere, which is not installed.\n",
+            "llmx 0.0.15a0 requires tiktoken, which is not installed.\u001b[0m\u001b[31m\n",
+            "\u001b[0mSuccessfully installed h11-0.14.0 httpcore-1.0.2 httpx-0.25.2 openai-1.3.8 pdfkit-1.0.0 python-docx-1.1.0\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "  # @title (Please insert your request to be done by this code at below form:👇👇)\n",
+        "TOPIC = \"PersonalityInteractions\" # @param {type:\"string\"}\n",
+        "PARAGRAPH = \"Use game theory to understand how different personality types (Dark Triad, Dark Tetrad, Dark Empathy) might interact within a society \\u003CINFO> PowerPoint\" # @param {type:\"string\"}\n",
+        "role = \"startup Entrepreneur\"# @param {type:\"string\"}\n",
+        "\n",
+        "\n",
+        "Your_Email = \"[email protected]\" # @param {type:\"string\"}\n",
+        "\n",
+        "openai_api = \"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\" # @param {type:\"string\"}\n",
+        "\n",
+        "\n",
+        "#!export OPENAI_API_KEY = openai_api\n",
+        "\n",
+        "import os\n",
+        "\n",
+        "os.environ['OPENAI_API_KEY'] = openai_api #'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'"
+      ],
+      "metadata": {
+        "id": "vRIB557vAbP0"
+      },
+      "execution_count": 8,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!pip install python-dotenv"
+      ],
+      "metadata": {
+        "id": "3BF-3djRAkVu",
+        "outputId": "8a4f229b-ae56-4156-bf32-05bafa9c6e83",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "execution_count": 4,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Collecting python-dotenv\n",
+            "  Downloading python_dotenv-1.0.0-py3-none-any.whl (19 kB)\n",
+            "Installing collected packages: python-dotenv\n",
+            "Successfully installed python-dotenv-1.0.0\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "'''\n",
+        "This file contains the ChatGP class that generates a business plan using OpenAI's GPT model.\n",
+        "'''\n",
+        "import openai\n",
+        "import pdfkit\n",
+        "from docx import Document\n",
+        "from dotenv import load_dotenv\n",
+        "import os\n",
+        "class ChatGP:\n",
+        "    def __init__(self):\n",
+        "        load_dotenv()\n",
+        "        self.api_key = os.getenv('OPENAI_API_KEY')\n",
+        "    def generate_business_plan(self, topic, description):\n",
+        "        prompts = [\n",
+        "            \"1. Executive Summary:\",\n",
+        "            \"2. Company Description:\",\n",
+        "            \"3. Market Analysis:\",\n",
+        "            \"4. Organization and Management:\",\n",
+        "            \"5. Product or Service Line:\",\n",
+        "            \"6. Marketing and Sales Strategy:\",\n",
+        "            \"7. Funding Request:\",\n",
+        "            \"8. Financial Projections:\",\n",
+        "            \"9. Appendix:\",\n",
+        "            \"10. Conclusion:\"\n",
+        "        ]\n",
+        "        results = []\n",
+        "        for i, prompt in enumerate(prompts):\n",
+        "            response = self.generate_response(prompt, topic, description)\n",
+        "            result = f\"{i+1}. {prompt}\\n{response}\"\n",
+        "            results.append(result)\n",
+        "        self.save_business_plan(results)\n",
+        "        return results\n",
+        "    def generate_response(self, prompt, topic, description):\n",
+        "        openai.api_key = self.api_key\n",
+        "        response = openai.Completion.create(\n",
+        "            engine='text-davinci-003',\n",
+        "            prompt=f\"{prompt} {topic} {description}\",\n",
+        "            max_tokens=100\n",
+        "        )\n",
+        "        return response.choices[0].text.strip()\n",
+        "    def save_business_plan(self, results):\n",
+        "        doc = Document()\n",
+        "        for result in results:\n",
+        "            title, content = result.split('\\n', 1)\n",
+        "            subtitle, numbering = title.split('. ', 1)\n",
+        "            doc.add_heading(subtitle, level=1)\n",
+        "            doc.add_heading(numbering, level=2)\n",
+        "            doc.add_paragraph(content)\n",
+        "        doc.save('business_plan.docx')\n",
+        "        pdfkit.from_file('business_plan.docx', 'business_plan.pdf')"
+      ],
+      "metadata": {
+        "id": "DlE3kHlfAL0n"
+      },
+      "execution_count": 5,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "topic = TOPIC # request.form['topic']\n",
+        "description = PARAGRAPH #  request.form['description']\n",
+        "chatgp = ChatGP()\n",
+        "results = chatgp.generate_business_plan(topic, description)"
+      ],
+      "metadata": {
+        "id": "_bQqVCZnEDWD",
+        "outputId": "5e21176c-f20b-432a-e38c-e891d2bca747",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        }
+      },
+      "execution_count": 9,
+      "outputs": [
+        {
+          "output_type": "error",
+          "ename": "APIRemovedInV1",
+          "evalue": "ignored",
+          "traceback": [
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+            "\u001b[0;31mAPIRemovedInV1\u001b[0m                            Traceback (most recent call last)",
+            "\u001b[0;32m<ipython-input-9-5374b87b775e>\u001b[0m in \u001b[0;36m<cell line: 4>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mdescription\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPARAGRAPH\u001b[0m \u001b[0;31m#  request.form['description']\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mchatgp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mChatGP\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mchatgp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate_business_plan\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtopic\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdescription\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+            "\u001b[0;32m<ipython-input-5-2b8956535385>\u001b[0m in \u001b[0;36mgenerate_business_plan\u001b[0;34m(self, topic, description)\u001b[0m\n\u001b[1;32m     26\u001b[0m         \u001b[0mresults\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     27\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprompt\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprompts\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 28\u001b[0;31m             \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate_response\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprompt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtopic\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdescription\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     29\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34mf\"{i+1}. {prompt}\\n{response}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     30\u001b[0m             \u001b[0mresults\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m<ipython-input-5-2b8956535385>\u001b[0m in \u001b[0;36mgenerate_response\u001b[0;34m(self, prompt, topic, description)\u001b[0m\n\u001b[1;32m     33\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mgenerate_response\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprompt\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtopic\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdescription\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     34\u001b[0m         \u001b[0mopenai\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapi_key\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapi_key\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 35\u001b[0;31m         response = openai.Completion.create(\n\u001b[0m\u001b[1;32m     36\u001b[0m             \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'text-davinci-003'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     37\u001b[0m             \u001b[0mprompt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34mf\"{prompt} {topic} {description}\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/openai/lib/_old_api.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *_args, **_kwargs)\u001b[0m\n\u001b[1;32m     37\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     38\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0m_args\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0m_kwargs\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 39\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mAPIRemovedInV1\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msymbol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_symbol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     41\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;31mAPIRemovedInV1\u001b[0m: \n\nYou tried to access openai.Completion, but this is no longer supported in openai>=1.0.0 - see the README at https://github.com/openai/openai-python for the API.\n\nYou can run `openai migrate` to automatically upgrade your codebase to use the 1.0.0 interface. \n\nAlternatively, you can pin your installation to the old version, e.g. `pip install openai==0.28`\n\nA detailed migration guide is available here: https://github.com/openai/openai-python/discussions/742\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "'''\n",
+        "This file contains the main Flask application for the ChatGP business plan generator.\n",
+        "'''\n",
+        "from flask import Flask, render_template, request, redirect, url_for\n",
+        "#from chatgp import ChatGP\n",
+        "\n",
+        "\n",
+        "app = Flask(__name__)\n",
+        "@app.route('/')\n",
+        "def index():\n",
+        "    return render_template('index.html')\n",
+        "@app.route('/generate', methods=['POST'])\n",
+        "def generate():\n",
+        "    topic = request.form['topic']\n",
+        "    description = request.form['description']\n",
+        "    chatgp = ChatGP()\n",
+        "    results = chatgp.generate_business_plan(topic, description)\n",
+        "    return render_template('results.html', results=results)\n",
+        "@app.route('/send_email', methods=['POST'])\n",
+        "def send_email():\n",
+        "    email = request.form['email']\n",
+        "    # Add code to send the generated business plan to the specified email address\n",
+        "    return redirect(url_for('index'))\n",
+        "if __name__ == '__main__':\n",
+        "    app.run()"
+      ],
+      "metadata": {
+        "id": "t80qXWMOANAH",
+        "outputId": "aa8dba64-8517-4e8a-be29-65b12a1b2587",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        }
+      },
+      "execution_count": 6,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            " * Serving Flask app '__main__'\n",
+            " * Debug mode: off\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "INFO:werkzeug:\u001b[31m\u001b[1mWARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.\u001b[0m\n",
+            " * Running on http://127.0.0.1:5000\n",
+            "INFO:werkzeug:\u001b[33mPress CTRL+C to quit\u001b[0m\n"
+          ]
+        }
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "accelerator": "TPU"
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}

DockerFile

@@ -0,0 +1,27 @@
+# Start with a Python 3.9 base image
+FROM python:3.9-slim
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Copy the current directory contents into the container at /app
+COPY . /app
+
+# Install necessary libraries for GUI support
+RUN apt-get update && apt-get install -y python3-tk x11-apps
+
+# Install the project dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Install HuggingFace Transformers and Uvicorn server
+RUN pip install transformers uvicorn
+
+# Set the environment variable for OpenAI API key
+# (you'll need to provide the actual key when running the container)
+ENV OPENAI_API_KEY=your_OpenAI_API_key
+
+# Expose the port for Uvicorn server
+EXPOSE 7860
+
+# Command to run the Uvicorn server with your FastAPI application
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]

Dockerfile → Dockerfile_main

@@ -21,4 +21,4 @@ ENV OPENAI_API_KEY=your_OpenAI_API_key
 EXPOSE 8000
 
 # Set an entry point that runs a shell for interactive mode
-ENTRYPOINT ["/bin/bash"]
+ENTRYPOINT ["/bin/bash"]