BettaFish
Open-source multi-agent public opinion analysis across 30+ platforms, with an LLM debate moderator.
BettaFish is one of the few open-source opinion-analysis stacks where the multi-agent design changes the output rather than just the diagram — the ForumEngine moderator genuinely counteracts single-model groupthink. The trade is real operational load: Docker, PostgreSQL/MySQL, a Playwright crawler, and four separate LLM API keys. Pick it if you have engineering capacity and want cross-platform sentiment without licensing fees; skip it if you need a managed dashboard running this week.
Verified 1h ago · liveness 49/100 · cite: rightaichoice.com/tools/bettafish
- Public opinion analysts comfortable running self-hosted infrastructure
- Social science researchers studying echo chambers and opinion formation
- Market intelligence teams with in-house developer support
- Developers building custom sentiment or multi-agent debate pipelines
- Non-technical users without Docker, database or API configuration skills
- Teams wanting a turnkey hosted dashboard with no maintenance burden
- Users monitoring a single platform, where a five-engine stack is overkill
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Skip BettaFish if no one on your team will own a Docker, PostgreSQL/MySQL, and multi-API-key stack and keep Playwright crawlers patched against changing social platforms.
Four separate LLM backends (DeepSeek, Gemini, Kimi, Qwen) each bill on their own quotas, so parallel agent runs multiply token spend across providers.
BettaFish itself is a $0 open-source project, which puts it below subscription opinion-monitoring suites. The real budget line is elsewhere: LLM API consumption across DeepSeek, Gemini, Kimi, and Qwen, plus the server and database you host. For a technical team already running infrastructure, that stack can cost far less than per-seat commercial monitoring; for a small team without ops capacity, the maintenance hours are the expensive part.
In short
BettaFish — Open-source multi-agent public opinion analysis across 30+ platforms, with an LLM debate moderator. Best for Public opinion analysts comfortable running self-hosted infrastructure, Social science researchers studying echo chambers and opinion formation, Market intelligence teams with in-house developer support. Free to use.
What's new in BettaFish
Checked 8 days agoAcross the latest 1 update: 1 news mention.
What people actually say about BettaFish — is it worth it?
We scanned public community sources for BettaFish on Jul 3, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Our own analysis of that scan says the posts were off-subject. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
Viability Score
How well maintained and how widely used is BettaFish? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Multi-source collection from 30+ platforms via the MindSpider crawler running 24/7
- QueryEngine web and news search on DeepSeek Chat
- MediaEngine multimodal analysis of video, image and structured cards on Gemini 2.5 Pro
- InsightEngine private database mining and keyword optimization on Kimi K2
- ForumEngine debate moderator using chain-of-thought collision across agent logs
- Parallel execution of three analysis agents with distinct LLM backends and tool sets
- Five-level multilingual sentiment classification across 22 languages
- Report pipeline: template selection, layout, chapter generation, rendering
- Report output as HTML, PDF or Markdown with chart and table validation
- JSON IR schema pipeline with error handling and repair
- Public-private data fusion via PostgreSQL/MySQL connectors
- Flask web application for orchestration and API routing
- Streamlit dashboards for per-agent analysis views
- WebSocket and SSE streaming for console logs and report progress
- Qwen-based keyword optimizer for SQL query expansion
About BettaFish
BettaFish (微舆, "WeiYu") is an open-source, Python-built multi-agent system for cross-platform public opinion analysis. A 24/7 MindSpider crawler populates PostgreSQL or MySQL from 30+ social platforms — Weibo, XHS, Douyin, Bilibili and others — plus domestic and international news sources. Five specialized engines then split the work: QueryEngine (DeepSeek Chat) for web and news search, MediaEngine (Gemini 2.5 Pro) for videos, images and structured cards, InsightEngine (Kimi K2) for private database mining and multilingual sentiment, ReportEngine (Gemini 2.5 Pro) for template-driven report rendering, and ForumEngine (Qwen Plus) for coordination. The unusual part is how the agents talk to each other. ForumEngine runs a debate-moderator loop it calls "chain-of-thought collision": an LLM moderator reads agent logs through LLMHost.synthesize_discussion(), flags knowledge gaps and bias, then broadcasts guidance back via logs/forum.log for the other agents to consume. That keeps a single model from homogenizing the analysis — the failure mode of most one-model pipelines. Reports move through a multi-stage pipeline — template selection, layout, chapter generation, then HTML/PDF/Markdown rendering with WeasyPrint and Jinja2, plus chart and table validation and a JSON IR schema with error repair. A Flask app handles orchestration and API routing, Streamlit runs per-agent dashboards, and Socket.IO/SSE stream console logs and report progress live. This is infrastructure, not a SaaS product. You bring Docker, a database, Playwright, and API keys for DeepSeek, Gemini, Kimi and Qwen. Buyers who want a hosted dashboard this week should look elsewhere; researchers and engineering-backed intelligence teams who need bias-aware, multi-perspective analysis without a commercial license get the most from it.
Behind the Verdict
We'd reach for BettaFish when the question is "what are different audiences actually saying" rather than "what's the sentiment score." The moderated debate between QueryEngine, MediaEngine and InsightEngine is the reason — a moderator model reviewing logs and pushing guidance back is a structural answer to the echo-chamber problem, and it's why the sentiment layer supports five-level classification across 22 languages instead of a single polarity number. The catch is that you assemble it. MindSpider needs Playwright and a running PostgreSQL/MySQL instance, the Flask orchestrator and Streamlit dashboards expect environment config through Pydantic settings, and each engine hits a different backend: DeepSeek Chat, Gemini 2.5 Pro, Kimi K2, Qwen Plus. Budget for four API keys and the time to wire them. Against a hosted social-listening suite, BettaFish wins on cost and on auditability — you can read the prompts, the IR schema, and the forum log yourself. It loses on time-to-first-insight and on support. There's no vendor SLA, no onboarding call, and debugging means reading agent logs. In practice, start with a narrow platform set and one research question. The full 30+ platform crawl is a lot of moving parts to validate at once, and the public-private fusion through the database connectors only pays off once your own data is loaded. Where it bites: anyone without Docker or database experience will stall at installation, and single-platform monitoring is overkill for a five-engine stack. For teams already running self-hosted analytics, the marginal cost is mostly API spend.
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Real-world workflow fit
Concrete scenarios for the personas BettaFish actually fits — and what changes day-one when you adopt it.
On day one you clone the repo, run Docker, point .env at your DeepSeek and Gemini keys, and let MindSpider start populating PostgreSQL from Weibo and XHS. You launch QueryEngine and InsightEngine together on a topic to get web/news coverage and database sentiment side by side.
Outcome: You get a first cross-platform sentiment picture with ForumEngine flagging gaps in the coverage, before you hand anything to ReportEngine for a formatted brief.
You connect your existing MySQL comment archive through InsightEngine, tune the Qwen keyword optimizer so the SQL expansion matches your product taxonomy, and schedule MindSpider to keep public sources fresh alongside it.
Outcome: Public buzz and private customer feedback land in one analysis, and you can extend nodes or swap search tools as your taxonomy evolves.
You run the same event through QueryEngine and MediaEngine feeds, then read logs/forum.log after the ForumMonitor synthesis to see where the moderator identified bias and where agents disagreed.
Outcome: The debate trace itself becomes research material — you capture divergence between outlets and platforms rather than a single averaged sentiment score.
Use Cases
- Track sentiment around a breaking social event across Weibo, XHS, Douyin, and Bilibili in one run
- Compare how domestic and international outlets frame the same story using parallel agents
- Surface viewpoint polarization and information cocoons through ForumEngine debate logs
- Generate HTML, PDF, or Markdown opinion briefs for decision-makers from a template pipeline
- Combine public social sentiment with your own PostgreSQL/MySQL business data for brand monitoring
- Extend the node and prompt layer to build a custom multi-agent research pipeline
Models Under the Hood
as of 2026-09-26
Limitations
- BettaFish is an open-source, self-hosted Python system: setup requires provisioning Docker plus PostgreSQL/MySQL and API keys for the underlying LLM providers, each carrying its own usage costs.
- The MindSpider crawler collects from 30+ social media platforms and international news sources, so collector upkeep is needed as source page structures change.
- Orchestration spans five specialized components (QueryEngine, MediaEngine, InsightEngine, ReportEngine, ForumEngine), and extending or debugging the pipeline means working in Python against the agent, prompt, and JSON IR layers.
as of 2026-09-23
Verification history
We have re-verified BettaFish 9 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 9 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published BettaFish tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Open Source
$0/mo
Ideal for
Developers, researchers, and market intelligence teams who can run Docker, a PostgreSQL/MySQL database, and multiple LLM API keys on their own hardware.
What this tier adds
Starting tier: full source access with all five engines, MindSpider crawler, Docker deployment, and community support, at $0 for the software.
Where the pricing makes sense
The company stage and team size where BettaFish's pricing actually pencils out — and where peers do it cheaper.
BettaFish itself is a $0 open-source project, which puts it below subscription opinion-monitoring suites. The real budget line is elsewhere: LLM API consumption across DeepSeek, Gemini, Kimi, and Qwen, plus the server and database you host. For a technical team already running infrastructure, that stack can cost far less than per-seat commercial monitoring; for a small team without ops capacity, the maintenance hours are the expensive part.
Setup time & first value
How long it actually takes to get something useful out of BettaFish — broken out by persona, not the marketing-page minute.
Expect a day for a developer to get Docker, PostgreSQL/MySQL, and the required API keys configured and the Flask app responding; a non-developer will not get there without help. First meaningful analysis appears once MindSpider has crawled enough data, so budget additional time before your first ReportEngine output is useful.
Switching to or from BettaFish
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From spreadsheets and manual platform checks: point MindSpider at your 30+ target sources and let QueryEngine and MediaEngine do the first pass.
- →From a single-model sentiment script: move your comment archive into PostgreSQL/MySQL so InsightEngine can mine it alongside public data.
- →From a commercial monitoring dashboard: export historical mentions into the database to preserve continuity while BettaFish handles new collection.
- ↗To a hosted monitoring suite: export your PostgreSQL/MySQL tables and rendered reports, since BettaFish holds the raw data locally.
- ↗To a custom pipeline: reuse the JSON IR report schemas and prompt structures if you rebuild on a different agent framework.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “BettaFish”, and we withheld 6: 6 could not be judged, because “BettaFish” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about BettaFish.
Official links
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Featured Head-to-Head Comparisons
Bettafish vs Screenplayiq
ScreenplayIQ is best for film professionals wanting data-driven script marketability forecasts with ready-to-use SaaS. BettaFish suits technical teams needing customizable, multi-source public opinion analysis with agent debate capabilities. Choose ScreenplayIQ if you need immediate screenplay insights; choose BettaFish if you can self-host and require deep social media monitoring.
Bettafish vs Truleo
Choose Truleo if you're in law enforcement needing to connect siloed data for case leads and report automation; it offers a polished, CJIS-compliant SaaS with real integrations. Choose BettaFish if you're a technically savvy team needing a customizable, multi-agent public opinion analysis system that actively reduces bias, despite requiring self-hosting and LLM API costs.
Bettafish vs Presto Voice
Presto Voice is the clear choice for QSR chains wanting proven revenue lift and seamless drive-thru automation, backed by major deployments like Dairy Queen. BettaFish is a powerful but niche tool for technical teams needing deep, multi-perspective social listening with debate-driven insights. Choose based on whether you want to enhance a physical drive-thru or analyze digital public opinion.
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Frequently Asked Questions
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