PraneshJs commited on
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dece3b5
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1 Parent(s): edc40a0

Update app.py

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  1. app.py +23 -15
app.py CHANGED
@@ -40,7 +40,7 @@ def build_structured_prompt(user_prompt, repo_data=None):
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  "tone": "authentic, reflective, inspiring, with storytelling elements.",
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  "style": "Storytelling, informative, slightly persuasive",
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  "view": "Make sure first 200-250 words are strong because they are the first visible ones make them in a way they attract more views",
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- "length": "Long-form (1500–2000 words)",
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  "format": "Give output as txt for easy copy pasting",
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  "additional": "Use Bulletins for Representing Tech Stacks and Skills",
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  "hashtags": "Add 15-20 trending tech-related hashtags with the project related automatically they should gain more profile views and new connection",
@@ -54,19 +54,27 @@ def build_structured_prompt(user_prompt, repo_data=None):
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  },
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  "sample_output": {
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  "title": "✨ From Chaos to Clarity: How I Built an AI Research Assistant That Simplifies Learning 🌌",
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- "body": [
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- "Ever felt overwhelmed by mountains of research papers and endless documentation? I definitely have, and that frustration sparked an idea.",
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- "I decided to build the AI Research Assistant API — a small experiment that turned into a powerful tool for students, developers, and researchers.",
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- "By combining FastAPI for blazing-fast APIs, LangGraph to map workflows, and OpenRouter’s GLM-4.5-air model for intelligent summarization, I created a system that transforms raw research into clear, actionable insights in seconds.",
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- "What’s more, integrating web search via Tavily allowed the assistant to fetch relevant data dynamically, making it smarter with each query.",
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- "But this journey wasn’t just about technology it taught me resilience, problem-solving, and the importance of designing tools that genuinely help people.",
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- "Seeing others try the API and immediately understand complex research was the most rewarding part. It reminded me that even small projects can create big impacts when built thoughtfully.",
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- "If you’re curious about building something impactful, here’s my advice:",
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- "1️⃣ Identify a real problem you’ve faced.",
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- "2️⃣ Combine the tools and skills you’re learning to prototype quickly.",
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- "3️⃣ Share your solution and gather feedback it’s the fastest way to improve.",
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- "Innovation is less about the size of the project and more about the clarity it brings to others."
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- ],
 
 
 
 
 
 
 
 
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  "cta": "What’s a challenge you’ve faced in your research or projects? I’d love to hear your thoughts and experiences!",
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  "hashtags": [
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  "#AIResearch", "#FastAPI", "#LangGraph", "#OpenRouter", "#MachineLearning",
@@ -149,7 +157,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
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  )
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  generate_btn = gr.Button("✨ Generate LinkedIn Post")
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- output = gr.Textbox(label="Generated LinkedIn Post", lines=50)
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  generate_btn.click(fn=generate_post, inputs=[topic, user_prompt], outputs=output)
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  "tone": "authentic, reflective, inspiring, with storytelling elements.",
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  "style": "Storytelling, informative, slightly persuasive",
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  "view": "Make sure first 200-250 words are strong because they are the first visible ones make them in a way they attract more views",
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+ "length": "Long-form (1000 - 1200 words)",
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  "format": "Give output as txt for easy copy pasting",
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  "additional": "Use Bulletins for Representing Tech Stacks and Skills",
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  "hashtags": "Add 15-20 trending tech-related hashtags with the project related automatically they should gain more profile views and new connection",
 
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  },
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  "sample_output": {
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  "title": "✨ From Chaos to Clarity: How I Built an AI Research Assistant That Simplifies Learning 🌌",
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+ "body": {
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+ "hook": "Ever felt overwhelmed by mountains of research papers and endless documentation? I definitely have, and that frustration sparked an idea.",
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+ "core_idea": [
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+ "Built the AI Research Assistant API a small experiment that grew into a powerful tool for students, developers, and researchers.",
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+ "Transforms raw research into clear, actionable insights in seconds.",
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+ "Integrates FastAPI for fast APIs, LangGraph to map workflows, and OpenRouter’s GLM-4.5-air for intelligent summarization.",
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+ "Dynamic web search via Tavily to fetch relevant research automatically."
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+ ],
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+ "skills_learned": [
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+ "Resilience and problem-solving through debugging complex workflows.",
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+ "API design and integration with AI models.",
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+ "Prompt engineering and workflow orchestration using LangGraph.",
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+ "Project structuring and creating scalable, user-friendly tools."
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+ ],
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+ "impact": "Seeing others try the API and immediately understand complex research was the most rewarding part. It reminded me that even small projects can create big impacts when built thoughtfully.",
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+ "advice": "If you’re curious about building something impactful, here’s my advice:\n1️⃣ Identify a real problem you’ve faced.\n2️⃣ Combine the tools and skills you’re learning to prototype quickly.\n3️⃣ Share your solution and gather feedback — it’s the fastest way to improve. Innovation is less about the size of the project and more about the clarity it brings to others.",
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+ "links": {
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+ "github_repo": "<INSERT GITHUB REPO HERE>",
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+ "live_demo": "<INSERT LIVE DEMO LINK HERE>"
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+ }
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+ },
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  "cta": "What’s a challenge you’ve faced in your research or projects? I’d love to hear your thoughts and experiences!",
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  "hashtags": [
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  "#AIResearch", "#FastAPI", "#LangGraph", "#OpenRouter", "#MachineLearning",
 
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  )
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  generate_btn = gr.Button("✨ Generate LinkedIn Post")
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+ output = gr.Textbox(label="Generated LinkedIn Post", lines=15)
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  generate_btn.click(fn=generate_post, inputs=[topic, user_prompt], outputs=output)
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