daily_stock_analysis vs Dify
Two of the top projects in Agent platforms, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
daily_stock_analysis
Daily LLM stock analysis for A-share, HK, US and other markets, pushed to chat apps
Dify
Visual builder for LLM workflows, RAG pipelines and agents, with APIs
Verdict
daily_stock_analysis ranks higher, 77 to 74. Of the 5 score parts we measure for both, daily_stock_analysis leads on 3, Dify on 1 and 1 is even.
- AdoptionDify leads by 27 points, 95 to 68: a wide gap.
- FreshnessEven at 100.
- Maintenancedaily_stock_analysis leads by 3 points, 96 to 93: close to even.
- Easy to rundaily_stock_analysis leads by 17 points, 50 to 33: a wide gap.
- Agent-readydaily_stock_analysis leads by 40 points, 85 to 45: a wide gap.
Pick daily_stock_analysis if you are
Retail investors and self-hosters wanting scheduled LLM watchlist reports
- Runs on a GitHub Actions fork with no server; default schedule is weekdays 18:00 Beijing time
- Free data sources (AkShare, Baostock, YFinance) work with zero configuration
Pick Dify if you are
Teams building and self-hosting LLM apps, RAG and agent workflows
- Visual workflow canvas, prompt IDE and RAG pipeline in one platform
- Every app exposes an API, so it works as a backend service
| What we compare | daily_stock_analysis | Dify |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 68, popular | 95, widely used |
| Freshness | 100, active | 100, active |
| Maintenance | 96, healthy | 93, healthy |
| Easy to run | 50, easy | 33, some setup |
| Agent-ready | 85, ready | 45, minimal |
| Facts from GitHub and the README | ||
| Stars | 66.4k | 158.5k |
| License | MIT (permissive) | custom license (read the license) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Sep 2026 | Sep 2026 |
| Language | Python | TypeScript |
| Docker | Yes | Yes |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Mentioned | Not stated |
daily_stock_analysis
Python app that pulls quotes, K-lines, news and fundamentals for a watchlist across A-share, HK, US, Japan, Korea and Taiwan markets. It has an LLM write a decision report with score, trend, buy/sell levels and risks, then pushes it to WeCom, Feishu, Telegram, Discord, Slack or email. It runs on GitHub Actions, Docker or locally, with a FastAPI web workbench for history, backtests and strategy chat.
Who it is for: Retail investors and self-hosters wanting scheduled LLM watchlist reports
Strengths
- Runs on a GitHub Actions fork with no server; default schedule is weekdays 18:00 Beijing time
- Free data sources (AkShare, Baostock, YFinance) work with zero configuration
- Supports Gemini, Claude, OpenAI-compatible APIs, DeepSeek, Qwen and local Ollama models
- Six push channels plus a web UI with history, backtest, portfolio and 15 built-in chat strategies
Weaknesses
- README is mainly Chinese; English docs are in a separate file
- Free data sources are subject to rate limits and upstream changes; stability not guaranteed
- Report quality depends on a paid news-search API key; a search service is recommended
- Output is for study only; the disclaimer excludes investment advice and liability
- no GPU
- Docker + Compose
- Needs LLM API key or Ollama, News search API (Anspire, SerpAPI, Tavily, Bocha, Brave, MiniMax or SearXNG), Market data sources (AkShare, Baostock, YFinance; optional TickFlow, Tushare, Longbridge), Notification channel
- Models: Gemini, OpenAI-compatible, DeepSeek, Qwen, Claude
- port 8000
Dify
Dify is an LLM app development platform with a visual workflow canvas, a prompt IDE, a RAG pipeline that extracts text from PDFs and PPTs, and agents that run in their own sandbox. Every app is exposed through an API. Model providers include GPT, Mistral, Llama3 and any OpenAI-compatible endpoint. It runs via Docker Compose or as the hosted Dify Cloud.
Who it is for: Teams building and self-hosting LLM apps, RAG and agent workflows
Strengths
- Visual workflow canvas, prompt IDE and RAG pipeline in one platform
- Every app exposes an API, so it works as a backend service
- Supports hundreds of LLMs plus any OpenAI API-compatible model
- Agents can use Marketplace tools, MCP servers or your own APIs
Weaknesses
- License is the Dify Open Source License (Apache 2.0 plus extra conditions)
- SSO, RBAC and support SLAs are in the Enterprise edition
- Docker Compose self-hosting needs at least 2 CPU cores and 4 GiB RAM
- Observability relies on external tools such as Opik, Langfuse and Arize Phoenix
- RAM ≥ 4 GB
- no GPU
- Docker + Compose
- Needs Docker, Docker Compose v2.24.0+
- Models: GPT, Mistral, Llama3, OpenAI API-compatible models
- port 80
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