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Updated README

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ShubhamSaboo 2025-06-02 15:03:11 -05:00
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2
advanced_ai_agents/multi_agent_apps/agent_teams/ai_competitor_intelligence_agent_team/README.md
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@ -47,7 +47,7 @@ Follow these steps to set up and run the application:
1. **Clone the Repository**: 1. **Clone the Repository**:
```bash ```bash
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd ai_agent_tutorials/ai_competitors_analysis_team cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_competitor_intelligence_agent_team
``` ```
2. **Install the dependencies**: 2. **Install the dependencies**:

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advanced_ai_agents/multi_agent_apps/agent_teams/ai_finance_agent_team/README.md
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@ -15,7 +15,7 @@ This script demonstrates how to build a team of AI agents that work together as
1. Clone the GitHub repository 1. Clone the GitHub repository
```bash ```bash
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd awesome-llm-apps/ai_agent_tutorials/ai_finance_agent_team cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_finance_agent_team
``` ```
2. Install the required dependencies: 2. Install the required dependencies:

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advanced_ai_agents/multi_agent_apps/agent_teams/ai_game_design_agent_team/README.md
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@ -37,7 +37,7 @@ Follow these steps to set up and run the application:
1. **Clone the Repository**: 1. **Clone the Repository**:
```bash ```bash
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd ai_agent_tutorials/ai_game_design_team cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_game_design_agent_team
``` ```
2. **Install Dependencies**: 2. **Install Dependencies**:

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advanced_ai_agents/multi_agent_apps/agent_teams/ai_legal_agent_team/README.md
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@ -26,7 +26,7 @@ A Streamlit application that simulates a full-service legal team using multiple
```bash ```bash
# Clone the repository # Clone the repository
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd awesome-llm-apps/ai_agent_tutorials/ai_legal_agent_team cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_legal_agent_team
# Install dependencies # Install dependencies
pip install -r requirements.txt pip install -r requirements.txt

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advanced_ai_agents/multi_agent_apps/agent_teams/ai_recruitment_agent_team/README.md
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@ -36,7 +36,7 @@ A Streamlit application that simulates a full-service recruitment team using mul
```bash ```bash
# Clone the repository # Clone the repository
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd ai_agent_tutorials/ai_recruitment_agent_team cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_recruitment_agent_team
# Install dependencies # Install dependencies
pip install -r requirements.txt pip install -r requirements.txt

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advanced_ai_agents/multi_agent_apps/agent_teams/ai_services_agency/README.md
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@ -64,7 +64,7 @@ Before anything else, Please get your OpenAI API Key here: https://platform.open
1. **Clone the Repository**: 1. **Clone the Repository**:
```bash ```bash
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd awesome-llm-apps/ai_agent_tutorials/ai_services_agency cd advanced_ai_agents/multi_agent_apps/agent_teams/ai_services_agency
``` ```
2. **Install the dependencies**: 2. **Install the dependencies**:

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advanced_ai_agents/multi_agent_apps/agent_teams/multimodal_coding_agent_team/README.md
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@ -36,7 +36,7 @@ Follow the steps below to set up and run the application:
1. **Clone the Repository** 1. **Clone the Repository**
```bash ```bash
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd ai_agent_tutorials/ai_coding_agent_o3-mini cd advanced_ai_agents/multi_agent_apps/agent_teams/multimodal_coding_agent_team
``` ```
2. **Install the dependencies** 2. **Install the dependencies**

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advanced_ai_agents/multi_agent_apps/agent_teams/multimodal_design_agent_team/README.md
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@ -25,7 +25,7 @@ This application leverages multiple specialized AI agents to provide comprehensi
```bash ```bash
# Clone the repository # Clone the repository
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd awesome-llm-apps/ai_agent_tutorials/multimodal_design_agent_team cd advanced_ai_agents/multi_agent_apps/agent_teams/multimodal_design_agent_team
# Create and activate virtual environment (optional) # Create and activate virtual environment (optional)
python -m venv venv python -m venv venv

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advanced_ai_agents/multi_agent_apps/product_launch_intelligence_agent/README.md
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@ -1,69 +1,73 @@
# 🚀 Product Launch Intelligence Agent # 🚀 Product Launch Intelligence Agent
A **streamlined intelligence hub** for Go-To-Market (GTM) & Product-Marketing teams. A **streamlined intelligence hub** for Go-To-Market (GTM) & Product-Marketing teams.
Built with **Agno + Firecrawl + Streamlit**, the app turns scattered public-web data into concise, actionable launch insights. Built with **Streamlit + Agno (GPT-4o) + Firecrawl**, the app turns scattered public-web data into concise, actionable launch insights.
## 3 Specialized Agents
## 🎯 Core Use-Cases
| Tab | What You Get | | Tab | What You Get |
|-----|--------------| |-----|--------------|
| **Competitor Analysis** | GTM-focused breakdown of a rival's latest launches – key messaging, differentiators, pricing cues & launch channels | | **Competitor Analysis Agent** | Evidence-backed breakdown of a rival's latest launches – positioning, differentiators, pricing cues & channel mix |
| **Market Sentiment** | Consolidated review themes & social chatter split by 🚀 *positive* / ⚠️ *negative* drivers | | **Market Sentiment Agent** | Consolidated social chatter & review themes split by 🚀 *positive* / ⚠️ *negative* drivers |
| **Launch Metrics** | Publicly available KPIs – press coverage, engagement numbers, qualitative "buzz" signals | | **Launch Metrics Agent** | Publicly available KPIs – adoption numbers, press coverage, qualitative "buzz" signals |
Additional goodies:
Responses are neatly rendered in markdown with a two-step process: * 🔑 **Sidebar key input** – enter OpenAI & Firecrawl keys securely (type="password")
1. First, a concise bullet list of key findings * 🧠 **Specialised multi-agent core** – three expert agents collaborate for richer insight
2. Then, an expanded 1200-word analysis with executive summary, deep dive, and recommendations * 🔍 Product Launch Analyst (GTM strategist)
* 💬 Market Sentiment Specialist (consumer-perception guru)
* 📈 Launch Metrics Specialist (performance analyst)
* ⚡ **Quick actions** – press **J/K/L** to trigger the three analyses without touching the UI
* 📑 **Auto-formatted Markdown reports** – bullet summary first, then expanded deep-dive
* 🛠️ **Sources section** – every report ends with the URLs that were crawled or searched
## 🛠️ Tech Stack ## 🛠️ Tech Stack
| Layer | Details | | Layer | Details |
|-------|---------| |-------|---------|
| Data | **Firecrawl** search + crawl (async, poll-based) | | Data | **Firecrawl** async search + crawl API |
| Agent | **Agno** single-agent with FirecrawlTools & markdown output | | Agents | **Agno** (GPT-4o) with FirecrawlTools |
| UI | **Streamlit** wide layout, custom CSS, tabbed workflow | | UI | **Streamlit** wide-layout, tabbed workflow |
| LLM | **OpenAI GPT-4o** for analysis and insights | | LLM | **OpenAI GPT-4o** |
## 🚀 Quick Start
### How to get Started? 1. **Clone** the repository
1. Clone the GitHub repository
```bash ```bash
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd advanced_ai_agents/multi_agent_apps/product_launch_intelligence_agent cd advanced_ai_agents/multi_agent_apps/product_launch_intelligence_agent
``` ```
2. Install the required dependencies:
2. **Install** dependencies
```bash ```bash
pip install -r requirements.txt pip install -r requirements.txt
``` ```
3. **Set up API Keys**
You can provide your API keys in two ways: 3. **Provide API keys** (choose either option)
- **Environment Variables**: Add to `.env` file
• **Environment variables** – create a `.env` file:
```ini ```ini
OPENAI_API_KEY=sk-************************ OPENAI_API_KEY=sk-************************
FIRECRAWL_API_KEY=fc-************************ FIRECRAWL_API_KEY=fc-************************
``` ```
- **UI Input**: Enter keys directly in the app's sidebar • **In-app sidebar** – paste the keys into the secure text inputs
3. **Run** 4. **Run the app**
```bash
streamlit run product_launch_intelligence_agent.py
```
4. **Navigate** to <http://localhost:8501> and start exploring. ```bash
streamlit run product_launch_intelligence_agent.py
```
5. **Browse** to <http://localhost:8501> – you should see three analysis tabs.
## 🕹️ Using the Application ## 🕹️ Using the Application
1. **Enter API Keys** in the sidebar if not set in environment variables 1. Enter **API keys** in the sidebar (or ensure they are in your environment).
2. Pick a tab (Competitor ▸ Sentiment ▸ Metrics) 2. Type a **company / product / hashtag** in the main input box.
3. Enter the **company / product / hashtag** requested 3. Pick a tab and hit the corresponding **Analyze** button – a spinner will appear while the agent works.
4. Hit **Analyze** – a spinner indicates data gathering 4. Review the two-part analysis:
5. Review the two-part analysis: * Bullet list of key findings
- Initial bullet points for quick insights * Expanded, richly-formatted report (tables, call-outs, recommendations)
- Expanded report with detailed analysis