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# 🧠 ResearchFlow Agent
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This agent orchestrates a multi-step research workflow using AI, helping users gather, synthesize, and structure knowledge from complex sources—ideal for analysts, strategists, product teams, and technical writers.
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---
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## 💼 Use Cases
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- **Market & Competitive Research**: Automate the collection and summarization of competitor data, trends, and product insights.
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- **Technical Literature Review**: Extract structured summaries from technical documents and API documentation.
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- **Customer Deep Dives**: Combine customer feedback, CRM notes, and meeting transcripts into coherent insight packs.
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- **Strategic Briefing Packs**: Generate polished summaries, outlines, and visual insights for leadership-ready deliverables.
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---
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## 🧩 Tools & Capabilities
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This agent is built with **Azure AI Agent Service** and typically integrates:
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- **File Search** to extract and cross-reference details from uploaded PDFs, Markdown, and structured datasets.
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- **Summarizer Agent** to generate section-level summaries from technical or dense input.
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- **Planner Agent** to break large prompts into logical subtasks and route them to specialized sub-agents.
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- **Progress Tracker or Router Agent** to manage task completion and coordination across a multi-agent graph.
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The agent orchestration is defined using `.agent` and `.fdl` configuration files.
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---
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## 🧠 Architecture Overview
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![Architecture Diagram](assets/architecture-researchflow.png)
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---
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## ⚙️ Setup Instructions
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### Prerequisites
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---
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## 💬 Example Agent Interactions
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**User**: Can you generate a competitive landscape analysis on cloud-native agent orchestration tools?
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**📥 Agent Response**: Planner routes task to summarizer + file search, returning a 3-part overview (market size, players, differentiators)
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---
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**User**: I uploaded three analyst reports—can you extract the trends relevant to SMB adoption and turn it into a leadership summary?
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**📄 Agent Response**: File Search → Summarizer → Final summary document with key stats, quotes, and predictions.
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---
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**User**: What's the breakdown of feature gaps between our platform and Company X?
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**📊 Agent Response**: File Search identifies platform docs; Summarizer creates comparative feature tables.
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---
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**User**: I'm prepping a 2-minute pitch—summarize these 10 pages of product reviews into themes I can speak to.
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**🧠 Agent Response**: Sentiment clustering and summarization into 3 key talking points with example quotes.
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---
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## 🛠 Customization Tips
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- **Add Custom Tools**: Plug in web search or vector DB search to complement file-based knowledge.
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- **Tune Agent Routing**: Adjust the planner or agentRouter logic to improve task delegation.
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- **Control Summarization Style**: Modify the summarizer agent’s system prompt for narrative, factual, or bullet-style summaries.
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- **Export as Report or Slide Deck**: Add downstream tools that turn outputs into formatted PDFs or PowerPoint slides.
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---
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## 📁 Declarative Files Included
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- `ResearchFlow.agent` — main orchestration agent
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- `Summarizer.agent` — task-specific summarizer
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- `LedgerPlanner.agent` — planner for prompt decomposition
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- `progressManager.agent` — optional tool for managing intermediate steps
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- `DeepResearchAgent.fdl` — agent graph and tool configuration
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---
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