├── .gitignore
├── requirements.txt
├── .devcontainer
    └── devcontainer.json
├── README.md
└── app.py


/.gitignore:
--------------------------------------------------------------------------------
1 | secrets.toml
2 | .venv
3 | 


--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------
1 | streamlit
2 | langchain
3 | langchain_community
4 | langchain_groq
5 | 
6 | 


--------------------------------------------------------------------------------
/.devcontainer/devcontainer.json:
--------------------------------------------------------------------------------
 1 | {
 2 |   "name": "Python 3",
 3 |   // Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
 4 |   "image": "mcr.microsoft.com/devcontainers/python:1-3.11-bullseye",
 5 |   "customizations": {
 6 |     "codespaces": {
 7 |       "openFiles": [
 8 |         "README.md",
 9 |         "app.py"
10 |       ]
11 |     },
12 |     "vscode": {
13 |       "settings": {},
14 |       "extensions": [
15 |         "ms-python.python",
16 |         "ms-python.vscode-pylance"
17 |       ]
18 |     }
19 |   },
20 |   "updateContentCommand": "[ -f packages.txt ] && sudo apt update && sudo apt upgrade -y && sudo xargs apt install -y <packages.txt; [ -f requirements.txt ] && pip3 install --user -r requirements.txt; pip3 install --user streamlit; echo '✅ Packages installed and Requirements met'",
21 |   "postAttachCommand": {
22 |     "server": "streamlit run app.py --server.enableCORS false --server.enableXsrfProtection false"
23 |   },
24 |   "portsAttributes": {
25 |     "8501": {
26 |       "label": "Application",
27 |       "onAutoForward": "openPreview"
28 |     }
29 |   },
30 |   "forwardPorts": [
31 |     8501
32 |   ]
33 | }


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
  1 | # **Sales Assistant Agent**
  2 | 
  3 | Sales Assistant Agent application powered by advanced AI technologies such as LangChain and Groq. It provides businesses with actionable insights by analyzing product data, market trends, and competitor information. This agent is designed to assist sales representatives in strategizing and optimizing their sales efforts through automated and data-driven analysis.
  4 | 
  5 | ---
  6 | 
  7 | ## **Features**
  8 | - **Product Analytics**:
  9 |   - Analyze and compare top competitors' products.
 10 |   - Scrape and summarize Amazon Best Sellers data.
 11 | - **Market Insights**:
 12 |   - Gather trends from Google Trends and predict future market disruptions.
 13 |   - Summarize the latest news from Google News for industry updates.
 14 | - **Custom Reports**:
 15 |   - Generate detailed sales insights based on company, product, and market data.
 16 |   - Business forecasting, including profit margins and revenue projections.
 17 | - **Ethical Analysis**:
 18 |   - Mitigates biases in decision-making processes.
 19 |   - Highlights assumptions based on limited data and promotes diverse perspectives.
 20 | 
 21 | ---
 22 | 
 23 | ## **Technologies Used**
 24 | - **Frontend**: [Streamlit](https://streamlit.io/) for creating an interactive user interface.
 25 | - **Backend**:
 26 |   - [LangChain](https://langchain.com/) for prompt management and model chaining.
 27 |   - [Groq](https://groq.com/) for LLM-powered insights.
 28 | - **Scraping Tools**:
 29 |   - [BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/) for web scraping.
 30 |   - [Requests](https://docs.python-requests.org/en/master/) for fetching web data.
 31 | - **Data Visualization**: Matplotlib and Pandas for visualizing trends and generating reports.
 32 | 
 33 | ---
 34 | 
 35 | ## **Setup Instructions**
 36 | 
 37 | #### **Prerequisites**
 38 | 1. Python 3.8 or higher installed on your system.
 39 | 2. Install the required libraries:
 40 |    ```bash
 41 |    pip install streamlit langchain-groq langchain-core langchain-community-tools requests beautifulsoup4 pandas matplotlib
 42 | 3.	Set up your Groq API Key in Streamlit secrets:
 43 | - Create a .streamlit/secrets.toml file and add:
 44 |     ```bash 
 45 |     GROQ_API_KEY = "your_groq_api_key"
 46 | #### **Running the Application**
 47 | 1. Clone the repository:
 48 |     ```bash 
 49 |     git clone https://github.com/erosnol/CAPSTONE-931.git
 50 | 2. Navigate to the project directory:
 51 |     ```bash 
 52 |     cd CAPSTONE-931
 53 | 3. Run the Streamlit app:
 54 |     ```bash
 55 |     streamlit run app.py
 56 | 4. Open the provided URL in your browser to interact with the Sales Assistant Agent.
 57 | 
 58 | 
 59 | 
 60 | ## **Usage**
 61 | 1.	Input Fields:
 62 | - Enter product information (name, category, value proposition).
 63 | - Provide URLs for competitors, Amazon best sellers, Google Trends, and Google News.
 64 | 2. Generate Insights:
 65 | - Click “Generate Insights” to create a comprehensive report with actionable recommendations and business forecasts.
 66 | 3. Adjust Model Behavior:
 67 | - Use the Sidebar to modify the AI model’s temperature for controlled creativity in outputs.
 68 | 
 69 | ---
 70 | 
 71 | 
 72 | ## **Example Outputs**
 73 | 
 74 | ### Competitor Analysis Table
 75 | | **Competitor Name** | **Features**             | **Price** | **Durability** | **Comparison to Your Product**       |
 76 | |----------------------|--------------------------|-----------|----------------|---------------------------------------|
 77 | | Competitor A         | Basic ergonomic design  | $300      | Medium         | Lacks advanced features               |
 78 | | Competitor B         | Speakers, ergonomic     | $450      | High           | No immersive experience               |
 79 | | Competitor C         | Reclining, lumbar support | $350   | Medium         | Doesn't include 3D immersive features |
 80 | 
 81 | ### Forecast Visualization
 82 | #### Projected Revenue and Profit Over 5 Years
 83 | A graph showing revenue and profit trends for the next 5 years, assuming a 10% annual growth in sales.
 84 | 
 85 | ![Forecast Graph](forecast_example.png)
 86 | 
 87 | ### Summary Insights
 88 | - **Amazon Best Sellers Analysis**: Identified top-performing products with comparable pricing and features.
 89 | - **Google Trends Insights**: Predicted steady growth
 90 | 
 91 | ## **Contributing**
 92 | 
 93 | We welcome contributions to improve CAPSTONE-931. To get started, follow these steps:
 94 | 
 95 | ### **Steps to Contribute**
 96 | 1. **Fork the Repository**:
 97 |    - Click the "Fork" button at the top right of this repository to create your own copy.
 98 | 
 99 | 2. **Clone the Repository**:
100 |    - Clone your forked repository to your local machine:
101 |      ```bash
102 |      git clone https://github.com/your-username/CAPSTONE-931.git
103 |      ```
104 | 
105 | 3. **Create a Feature Branch**:
106 |    - Create a new branch for your feature or bug fix:
107 |      ```bash
108 |      git checkout -b feature/your-feature-name
109 |      ```
110 | 
111 | 4. **Make Your Changes**:
112 |    - Edit the code to add your feature or fix the issue.
113 |    - Ensure your changes are well-documented and tested.
114 | 
115 | 5. **Commit Your Changes**:
116 |    - Commit your changes with a descriptive message:
117 |      ```bash
118 |      git commit -m "Add feature: your-feature-name"
119 |      ```
120 | 
121 | 6. **Push to Your Fork**:
122 |    - Push your changes to your forked repository:
123 |      ```bash
124 |      git push origin feature/your-feature-name
125 |      ```
126 | 
127 | 7. **Create a Pull Request**:
128 |    - Open a pull request from your feature branch to the `main` branch of the original repository.
129 |    - Provide a clear description of the changes in the pull request.
130 | 
131 | ---
132 | 
133 | ### **Guidelines for Contributions**
134 | - **Code Style**: Follow the existing coding conventions and structure.
135 | - **Documentation**: Update the README or add comments where necessary.
136 | - **Testing**: Ensure your changes are tested and do not break existing functionality.
137 | - **Issues**: Reference any related issues in your pull request (e.g., `Fixes #issue-number`).
138 | 
139 | ---
140 | 
141 | ### **Need Help?**
142 | If you encounter any issues or have questions about contributing, feel free to open an issue or contact the repository owner directly.
143 | 
144 | ## **License**
145 | 
146 | This project is licensed under the [MIT License](LICENSE). You are free to use, modify, and distribute this software as long as the original license terms are followed.
147 | 
148 | For more information, see the [LICENSE](LICENSE) file included in this repository.
149 | 
150 | ## **Acknowledgments**
151 | 
152 | This project was made possible by the following tools and technologies:
153 | 
154 | - **[Groq](https://groq.com/)**: For powering the language model integration.
155 | - **[LangChain](https://langchain.com/)**: For seamless prompt chaining and AI agent functionalities.
156 | - **[Streamlit](https://streamlit.io/)**: For creating an interactive and user-friendly frontend.
157 | - **[BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/)**: For web scraping functionality.
158 | - **[Pandas](https://pandas.pydata.org/)** and **[Matplotlib](https://matplotlib.org/)**: For data analysis and visualization.
159 | 
160 | A big thank you to everyone who contributed ideas, feedback, and support for this project.
161 | 
162 | ## **Contact**
163 | 
164 | For any questions, feedback, or support, feel free to reach out:
165 | 
166 | - **Repository Owner**: [Erosnol](mailto:erosnolasco@protonmail.com)
167 | - **GitHub**: [CAPSTONE-931](https://github.com/erosnol/CAPSTONE-931)
168 | 
169 | We appreciate your interest in CAPSTONE-931 and look forward to your contributions!
170 | 
171 | 
172 | 


--------------------------------------------------------------------------------
/app.py:
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  1 | import streamlit as st
  2 | from langchain_groq import ChatGroq
  3 | from langchain_core.prompts import ChatPromptTemplate
  4 | from langchain_core.output_parsers import StrOutputParser
  5 | from langchain_community.tools.tavily_search import TavilySearchResults
  6 | 
  7 | 
  8 | 
  9 | # Model and Agent tools
 10 | llm = ChatGroq(api_key=st.secrets.get("GROQ_API_KEY"))
 11 | 
 12 | search = TavilySearchResults(max_results=2)
 13 | parser = StrOutputParser()
 14 | # tools = [search] # add tools to the list
 15 | 
 16 | # Set the page configuration
 17 | st.set_page_config(
 18 |     page_title="Sales Assistant Agent",  # Tab title
 19 |     page_icon="💼",  # Optional: Emoji or URL for the favicon
 20 |     layout="centered",  # Optional: Layout can be "centered" or "wide"
 21 |     initial_sidebar_state="expanded"  # Optional: Sidebar starts expanded or collapsed
 22 | )
 23 | # Page Header
 24 | st.title(" Sales Assistant Agent")
 25 | st.markdown("Assistant Agent Powered by Groq.")
 26 | 
 27 | # Sidebar for settings
 28 | st.sidebar.markdown(
 29 |     "<h2 style='font-size: 24px;'>Settings</h2>", 
 30 |     unsafe_allow_html=True
 31 | )
 32 | 
 33 | # Dropdown to select Groq AI model
 34 | selected_groq_model = st.sidebar.selectbox(
 35 |     label="Select Groq Model",
 36 |     options=["Groq-8x7B", "Groq-8x13B", "Groq-Mixtral", "Groq-LLM"],
 37 |     help="Choose a Groq model for processing tasks."
 38 | )
 39 | 
 40 | temperature = st.sidebar.slider(
 41 |     label="Model Temperature",
 42 |     min_value=0.0,
 43 |     max_value=1.0,
 44 |     value=0.7,
 45 |     step=0.1,
 46 |     help="Adjust the temperature to control the randomness of the model's outputs. Lower values produce more deterministic results."
 47 | )
 48 | 
 49 | st.sidebar.markdown("---")
 50 | 
 51 | # Add Google Trends link with icon
 52 | # Resources Section
 53 | st.sidebar.markdown("### Resources")
 54 | st.sidebar.markdown("[Google Trends](https://trends.google.com/)")
 55 | st.sidebar.markdown("[Google News](https://news.google.com/)")
 56 | st.sidebar.markdown("[Amazon](https://www.amazon.com/)")
 57 | 
 58 | st.sidebar.markdown("---")
 59 | 
 60 | # Add GitHub link with icon in the sidebar
 61 | st.sidebar.markdown(
 62 |     """
 63 |     <div style="display: flex; align-items: center;">
 64 |         <a href="https://github.com/erosnol/CAPSTONE-931" target="_blank" style="text-decoration: none; display: flex; align-items: center;">
 65 |             <img src="https://github.githubassets.com/images/modules/logos_page/GitHub-Mark.png" alt="GitHub Logo" width="25" style="margin-right: 10px;">
 66 |             <span style="font-size: 16px; color: white;">GitHub Repository</span>
 67 |         </a>
 68 |     </div>
 69 |     """,
 70 |     unsafe_allow_html=True
 71 | )
 72 | 
 73 | # Feedback Section at the Bottom
 74 | st.sidebar.markdown("---")  # Divider for better visual separation
 75 | with st.sidebar.expander("Provide Feedback"):
 76 |     
 77 |     
 78 |     # Feedback Text Input
 79 |     feedback = st.text_area(
 80 |         label="Feedback:",
 81 |         placeholder="Please provide any additional feedback or comments to improve results."
 82 |     )
 83 |     
 84 |     # 5-Star Rating System
 85 |     star_rating = st.slider(
 86 |         label="Rate the experience:",
 87 |         min_value=1,
 88 |         max_value=5,
 89 |         value=5,
 90 |         step=1,
 91 |         format="%d stars",
 92 |         help="Rate the application from 1 (poor) to 5 (excellent)."
 93 |     )
 94 |     
 95 |     # Feedback Submit Button
 96 |     if st.button("Submit Feedback"):
 97 |         st.success("Thank you for your feedback!")
 98 |         # Process or save the feedback and rating here
 99 |         print(f"Feedback: {feedback}")
100 |         print(f"Rating: {star_rating} stars")
101 | 
102 | # Toggle for demo mode
103 | demo_mode = st.checkbox("Use Demo Inputs")
104 | 
105 | # Define demo inputs
106 | demo_inputs = {
107 |     "product_name": "gaming chair",
108 |     "company_url": "https://store.hermanmiller.com/gaming-view-all?lang=en_US",
109 |     "product_category": "Office supplies",
110 |     "competitors_url": "https://www.ewinracing.com, https://xrockergaming.com, www.razer.com, https://secretlab.co, https://www.vertagear.com/, https://www.noblechairs.com, https://www.dxracer.com, https://www.mavix.com/, https://subsonic.com/, https://www.andaseat.com/",
111 |     "value_proposition": "a high quality 3D enhanced gaming chair for gamers with speakers, surround sound, vibrations, cupholder and Siri/Alex compatibility, priced at $399.",
112 |     "target_customer": "Gamers",
113 |     "amazon_best_sellers": "https://www.amazon.com/s?k=gaming+chairs&i=garden&rh=n%3A1055398%2Cp_72%3A1248915011&s=exact-aware-popularity-rank&dc&ds=v1%3AHBaNLpw8vi94y9a3WBIfMjSgF2VSI48owFQHB87fFyc&crid=ZXF6209QI6R1&qid=1734017332&rnid=1248913011&sprefix=gaming+chairs%2Caps%2C229&ref=sr_nr_p_72_1",
114 |     "google_trends_review": "https://trends.google.com/trends/explore?geo=US&q=gaming%20chairs",
115 |     "googled_news_search": "https://www.google.com/search?q=gaming+chairs&sca_esv=fa27aa6c1a2c9000&biw=1447&bih=750&tbm=nws&sxsrf=ADLYWIJUjMkXLxpbPMvQbSzpTvG02xCp5w%3A1734025867585&ei=iyJbZ9noIpydkPIPnqz0uQ0&ved=0ahUKEwiZ2vje5aKKAxWcDkQIHR4WPdcQ4dUDCA4&uact=5&oq=gaming+chairs&gs_lp=Egxnd3Mtd2l6LW5ld3MiDWdhbWluZyBjaGFpcnMyCxAAGIAEGLEDGIMBMgUQABiABDIFEAAYgAQyBRAAGIAEMgUQABiABDIFEAAYgAQyBRAAGIAEMgUQABiABDIFEAAYgAQyBRAAGIAESJYRUJAGWNMPcAJ4AJABAJgBZqAB3AaqAQQxMy4xuAEDyAEA-AEBmAIQoAL_BsICEBAAGIAEGLEDGEMYgwEYigXCAggQABiABBixA8ICChAAGIAEGEMYigXCAg0QABiABBixAxhDGIoFwgIOEAAYgAQYsQMYgwEYigXCAg0QABiABBixAxiDARgKwgIKEAAYgAQYsQMYCpgDAIgGAZIHBDE1LjGgB_FQ&sclient=gws-wiz-news"
116 | }
117 | 
118 | # Data collection/inputs
119 | with st.form("company_info", clear_on_submit=False):
120 | 
121 |     product_name = st.text_input(
122 |         label="**Product Name**:",
123 |         placeholder="Enter the product name you are selling",
124 |         value=demo_inputs["product_name"] if demo_mode else ""
125 |     )
126 | 
127 |     company_url = st.text_input(
128 |         label="**Company URL**:",
129 |         placeholder="Enter the company URL (e.g., www.company.com)",
130 |         value=demo_inputs["company_url"] if demo_mode else ""
131 |     )
132 | 
133 |     product_category = st.text_input(
134 |         label="**Product Category**:",
135 |         placeholder="Enter the product category (e.g., 'Gaming Chair', 'Cloud Storage')",
136 |         value=demo_inputs["product_category"] if demo_mode else ""
137 |     )
138 | 
139 |     competitors_url = st.text_input(
140 |         label="**Competitors URL**:",
141 |         placeholder="Enter competitor URLs separated by commas (e.g., www.apple.com, www.samsung.com)",
142 |         value=demo_inputs["competitors_url"] if demo_mode else ""
143 |     )
144 | 
145 |     value_proposition = st.text_input(
146 |         label="**Value Proposition**:",
147 |         placeholder="A sentence summarizing the product’s value",
148 |         value=demo_inputs["value_proposition"] if demo_mode else ""
149 |     )
150 | 
151 |     target_customer = st.text_input(
152 |         label="**Target Customer**:",
153 |         placeholder="Enter the target customer or audience",
154 |         value=demo_inputs["target_customer"] if demo_mode else ""
155 |     )
156 | 
157 |     # Product Analytics title
158 |     st.markdown("### Specific Product Analysis")
159 |     st.markdown("<small>Provides a product business forecast.</small>", unsafe_allow_html=True)
160 | 
161 |     amazon_best_sellers = st.text_input(
162 |         label="**Amazon Best Sellers URL**:",
163 |         placeholder="Enter an Amazon URL to scrape best sellers",
164 |         value=demo_inputs["amazon_best_sellers"] if demo_mode else ""
165 |     )
166 | 
167 |     google_trends_review = st.text_input(
168 |         label="**Google Trends URL**:",
169 |         placeholder="Enter a Google Trends URL for trends data",
170 |         value=demo_inputs["google_trends_review"] if demo_mode else ""
171 |     )
172 | 
173 |     googled_news_search = st.text_input(
174 |         label="**Google News URL**:",
175 |         placeholder="Enter a Google News URL for the latest news",
176 |         value=demo_inputs["googled_news_search"] if demo_mode else ""
177 |     )
178 | 
179 |     # Optional title
180 |     st.markdown("### Optional")
181 | 
182 |     # File upload for document parsing
183 |     uploaded_file = st.file_uploader("Upload a PDF or Word document for additional insights.", type=["pdf", "docx"])
184 | 
185 |     # Extra data source to scrape data
186 |     data_source_url = st.text_input(
187 |         label="**Additional Data Source URL**",
188 |         placeholder="Provides a summarized insight into the provided URL"
189 |     )
190 |     
191 | 
192 |     # For the llm insights result
193 |     company_insights = ""
194 | 
195 |     # Data process
196 |     if st.form_submit_button("Generate Insights"):
197 |         if product_name and company_url:
198 |            with st.spinner("Processing..."):
199 | 
200 |                 # Use search tool to get Company Information
201 |                 company_information = search.invoke(company_url)
202 |                 print(company_information)
203 | 
204 |                 # TODO: Create prompt <=================
205 |                 prompt = """
206 |                 You are a business assistant agent tasked with generating a one-page summary to assist a sales representative in gaining insights about a prospective account. 
207 |                 Based on the inputs and additional data provided, your goal is to create a detailed and actionable report. 
208 |                 Avoid assumptions or statements that are not backed by data.
209 |                 Reflect diverse perspectives and cross-verify data when possible.
210 |                 Use the following structure:
211 | 
212 |                 ### Inputs:
213 |                 - **Company Information**: {company_information}
214 |                 - **Product Name**: {product_name}
215 |                 - **Competitor URL(s)**: {competitors_url}
216 |                 - **Product Category**: {product_category}
217 |                 - **Value Proposition**: {value_proposition}
218 |                 - **Target Customer**: {target_customer}
219 |                 - **Uploaded Document**: {uploaded_file} (summarize and add insight into summary, if uploaded).
220 |                 - **Scraped Data Source**: {data_source_url} (summarize and add insight into summary, if uploaded).
221 | 
222 |                 ### Tasks:
223 |                 1. **Company Strategy**:
224 |                 - Summarize the company’s activities, priorities, and any recent initiatives relevant to the product category.
225 |                 - Include mentions of key public statements, press releases, or job postings that provide insight into the company’s strategy.
226 | 
227 |                 2. **Competitor Mentions**:
228 |                 - Extract and analyze data about competitors from the provided URLs and scraped data.
229 |                 - Create a **detailed comparison table** with the following columns:
230 |                     - **Competitor Name**
231 |                     - **Features**
232 |                     - **Price**
233 |                     - **Durability**
234 |                     
235 |                 - Example table format:
236 |                     | Competitor Name | Features                        | Price | Durability | Comparison to Your Product                    |
237 |                     |------------------|--------------------------------|-------|------------|-----------------------------------------------|
238 |                     | Competitor A     | Basic ergonomic design         | $500  | Medium     |   Lacks 3D immersive experience and no cupholder |
239 |                     | Competitor B     | Speakers, ergonomic design     | $450  | High       | Lacks 3D immersive experience and cupholder   |
240 | 
241 |                 3. **Leadership Information**:
242 |                 - Identify key decision-makers (e.g., CEO, CTO) and summarize relevant public statements or initiatives tied to the product category.
243 | 
244 |                 4. **Product/Strategy Summary**:
245 |                 - Understand the specific characteristics of the ideal customer. Create a table with findings.
246 |                 -  Give suggestions on where the company can sell the product (sales channels).
247 | 
248 |                 5. **Suggestions for Positioning**:
249 |                 - Provide recommendations for how the product can align with the company’s strategy and address the target customer’s pain points.
250 | 
251 |                 6. **Product Data Analytics**:
252 |                 **Amazon Best Sellers Review**
253 |                 - Summarize top 5 products. 
254 |                 - Include the brand name, price, rating and key product features. 
255 |                 - Create a table.
256 |                 - Summarize results to see where the value proposition can provide leverage.  
257 | 
258 |                 **Google Trends Review**
259 |                 - Use google_trends_review to summarize scraped data. 
260 |                 - Predict future trends and potential market disruptions
261 |                 - Create a table
262 |                 - Summarize results to see where the value proposition can provide leverage. 
263 | 
264 |                 **Google Search Related News**
265 |                 - Analyze sentiment in news articles, social media posts, and customer reviews to gauge market perception. 
266 |                 - Analyze the most up to date news related to the product. Give at least 3 to 5 most up to date topics. 
267 |                 - Create a table. 
268 |                 - Summarize results to see where the value proposition can provide leverage. 
269 | 
270 |                 7. **Business Value / Forecast**
271 |                 - Using all gathered inputted data to provide a business forecast on the product potential.  
272 |                 - Use a table illustrating projected profit margin and revenue everytime this prompt gets generated.
273 |                 - Use persuasive language and call-to-action phrases in the closing statement
274 | 
275 |                 ## Ethical Considerations
276 |                  - Provide actionable insights while mitigating potential biases in decision-making.
277 |                  - Highlight areas where assumptions or extrapolations are based on limited data.
278 |                  - Use diverse data sources (Amazon Best Sellers, Google Trends, and News Search) to ensure impartial analysis.
279 | 
280 |                 ## Language and Tone 
281 |                 - Use a formal professional tone
282 |                 - Use persuasive language
283 | 
284 |                 ### Final Deliverable:
285 |                 - Present the report in a structured format with clear sections:
286 |                 - **Company Strategy**
287 |                 - **Competitor Mentions (including table)**
288 |                 - **Leadership Information**
289 |                 - **Product/Strategy Summary**
290 |                 - **Recommendations for Positioning**
291 |                 - Include references or links to supporting data (articles, press releases, etc.).
292 |                 - Include a summary of identified biases, if any, and measures taken to mitigate them.
293 |                 - Present the report with fair and representative data-driven insights.
294 | 
295 |                 8. ### Closing Statement:
296 |                 - Conclude the report with a persuasive note highlighting the product’s competitive edge. 
297 |                 - Use persuasive language and call-to-action phrases in the closing statement
298 |   
299 | 
300 |                 """
301 | 
302 |                 # Prompt Template
303 |                 prompt_template = ChatPromptTemplate([("system", prompt)])
304 | 
305 |                 # Chain
306 |                 chain = prompt_template | llm | parser
307 | 
308 |                 # Result/Insights
309 |                 company_insights = chain.invoke(
310 |                     {
311 |                         "company_information": company_information,
312 |                         "product_name": product_name,
313 |                         "competitors_url": competitors_url,
314 |                         "product_category": product_category,
315 |                         "value_proposition": value_proposition,
316 |                         "target_customer": target_customer,
317 |                         "uploaded_file": uploaded_file,
318 |                         "data_source_url": data_source_url,
319 |                         "amazon_best_sellers": amazon_best_sellers,
320 |                         "google_trends_review": google_trends_review,
321 |                         "googled_news_search": googled_news_search
322 |                     }
323 |                 )
324 | # Display the insights and download button outside the form
325 | if company_insights:
326 |     st.markdown(company_insights)
327 | 
328 |     # Create a download button for the report
329 |     st.download_button(
330 |         label="Download Report",
331 |         data=company_insights,
332 |         file_name="report.txt",
333 |         mime="text/plain"
334 |     )


--------------------------------------------------------------------------------