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- title: NewsIntel Agent
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- emoji: πŸ’»
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- colorFrom: indigo
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- colorTo: purple
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- sdk: gradio
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- app_file: app.py
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- python_version: 3.11
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- pinned: false
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- sdk_version: 5.42.0
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- πŸ—žοΈ NewsIntel Agent β€” Job Briefings & Hiring Signals
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- A Gradio app that pulls recent news, generates grounded summaries, detects entities & sentiment, and produces interview-ready briefings (HTML/PDF).
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- Includes one-click modes (Healthcare / Finance / R&D), caching, charts, and optional S3/SES export + weekly email.
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-
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- ✨ Features
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- Google/press-release RSS + your custom get_news source
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- LLM-generated grounded summaries (via your services.llm.summarize)
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- Entity extraction, keywording, sentiment
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- Trend & simple 7-day forecast (linear fit on daily sentiment)
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- Briefing export: HTML (built-in) and PDF (optional, via reportlab)
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- Optional S3 upload + SES weekly email
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- πŸ“ Repository layout (minimum)
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- β”œβ”€ app.py # (rename your gradio_app -> app.py) β”œβ”€ requirements.txt β”œβ”€ README.md β”œβ”€ services/ β”‚ β”œβ”€ init.py β”‚ β”œβ”€ search.py # must define get_news(query, days, k) -> list[dict] β”‚ β”œβ”€ llm.py # must define summarize(prompt) -> str β”‚ β”œβ”€ huggingface_nlp.py # must define analyze_sentiment, analyze_entities, extract_keywords β”‚ β”œβ”€ aws.py # optional: s3_upload(path), ses_send_email(to, subj, html) β”‚ └─ cache.py # get_cache(*keys), set_cache(obj, *keys)
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-
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- Do NOT upload your local .env. Use Spaces β†’ Settings β†’ Variables & secrets instead.
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-
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- πŸ”§ Environment variables (set in Spaces β†’ Settings β†’ Variables & secrets)
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- Only set what you actually use in your services/ modules.
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-
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- If your services/llm.py calls OpenAI (example):
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-
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- OPENAI_API_KEY
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- If your services/llm.py calls Hugging Face Inference API (example):
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-
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- HF_TOKEN
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- If enabling S3 uploads in services/aws.py:
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-
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- AWS_ACCESS_KEY_ID
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- AWS_SECRET_ACCESS_KEY
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- AWS_DEFAULT_REGION (e.g., us-east-1)
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- S3_BUCKET (bucket name)
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- If enabling SES emails in services/aws.py:
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-
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- SES_SENDER_EMAIL (verified in SES)
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- (same AWS creds/region as above)
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- If these aren’t set, the app will still run; S3/SES buttons will simply show fallback messages.
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-
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- ▢️ Run locally
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- python -m venv .venv && source .venv/bin/activate # on Windows: .venv\Scripts\activate
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- pip install -r requirements.txt
 
 
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  python app.py
 
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+ ---
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+ title: NewsIntel Agent
3
+ emoji: πŸ’»
4
+ colorFrom: indigo
5
+ colorTo: purple
6
+ sdk: gradio
7
+ app_file: app.py
8
+ python_version: 3.11
9
+ pinned: false
10
+ ---
11
+
12
+ πŸ—žοΈ NewsIntel Agent β€” Job Briefings & Hiring Signals
13
+ A Gradio app that pulls recent news, generates grounded summaries, detects entities & sentiment, and produces interview-ready briefings (HTML/PDF).
14
+ Includes one-click modes (Healthcare / Finance / R&D), caching, charts, and optional S3/SES export + weekly email.
15
+
16
+ ✨ Features
17
+ Google/press-release RSS + your custom get_news source
18
+ LLM-generated grounded summaries (via your services.llm.summarize)
19
+ Entity extraction, keywording, sentiment
20
+ Trend & simple 7-day forecast (linear fit on daily sentiment)
21
+ Briefing export: HTML (built-in) and PDF (optional, via reportlab)
22
+ Optional S3 upload + SES weekly email
23
+ πŸ“ Repository layout (minimum)
24
+ β”œβ”€ app.py # (rename your gradio_app -> app.py) β”œβ”€ requirements.txt β”œβ”€ README.md β”œβ”€ services/ β”‚ β”œβ”€ init.py β”‚ β”œβ”€ search.py # must define get_news(query, days, k) -> list[dict] β”‚ β”œβ”€ llm.py # must define summarize(prompt) -> str β”‚ β”œβ”€ huggingface_nlp.py # must define analyze_sentiment, analyze_entities, extract_keywords β”‚ β”œβ”€ aws.py # optional: s3_upload(path), ses_send_email(to, subj, html) β”‚ └─ cache.py # get_cache(*keys), set_cache(obj, *keys)
25
+
26
+ Do NOT upload your local .env. Use Spaces β†’ Settings β†’ Variables & secrets instead.
27
+
28
+ πŸ”§ Environment variables (set in Spaces β†’ Settings β†’ Variables & secrets)
29
+ Only set what you actually use in your services/ modules.
30
+
31
+ If your services/llm.py calls OpenAI (example):
32
+
33
+ OPENAI_API_KEY
34
+ If your services/llm.py calls Hugging Face Inference API (example):
35
+
36
+ HF_TOKEN
37
+ If enabling S3 uploads in services/aws.py:
38
+
39
+ AWS_ACCESS_KEY_ID
40
+ AWS_SECRET_ACCESS_KEY
41
+ AWS_DEFAULT_REGION (e.g., us-east-1)
42
+ S3_BUCKET (bucket name)
43
+ If enabling SES emails in services/aws.py:
44
+
45
+ SES_SENDER_EMAIL (verified in SES)
46
+ (same AWS creds/region as above)
47
+ If these aren’t set, the app will still run; S3/SES buttons will simply show fallback messages.
48
+
49
+ ▢️ Run locally
50
+ python -m venv .venv && source .venv/bin/activate # on Windows: .venv\Scripts\activate
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+ pip install -r requirements.txt
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  python app.py