| .. | ||
| checklists | ||
| eval | ||
| mvp_demo | ||
| ops | ||
| patterns | ||
| playbooks | ||
| tools | ||
| .gitkeep | ||
| amazon_lex.md | ||
| azure_bot_service.md | ||
| dialogflow_cx.md | ||
| freshchat.md | ||
| freshdesk.md | ||
| intercom.md | ||
| microsoft_copilot_studio.md | ||
| rasa.md | ||
| README.md | ||
| salesforce_einstein_bots.md | ||
| twilio_studio.md | ||
| watsonx_assistant.md | ||
| zendesk.md | ||
Chatbots & CX — Global Fix Map
A compact hub to stabilize chatbot frameworks and customer experience stacks.
Targets Dialogflow CX, Rasa, Intercom, Twilio Studio, Zendesk, Amazon Lex, Azure Bot Service, Salesforce Einstein Bots, Freshdesk, Watsonx Assistant, Microsoft Copilot Studio, and more.
Each page provides measurable acceptance targets and reproducible fixes.
When to use this folder
- Bot flows break across environments (dev vs prod vs staging).
- Slot filling, entities, or context reset unexpectedly.
- Latency or cold starts cause dropped conversations.
- Omnichannel connectors desync with the core bot.
- Prompts bypass policies or hallucinate unsafe outputs.
- Regression after migration to a new vendor framework.
Acceptance targets
- Intent recognition F1 ≥ 0.85 across test set.
- ΔS(user_query, retrieved) ≤ 0.45 for all routes.
- Coverage of knowledge base ≥ 0.70 after repair.
- λ remains convergent across 3 paraphrases and 2 seeds.
- p95 latency ≤ 800 ms across channels, warm path.
- Zero PII leakage in logs or vector payloads.
Quick routes — per chatbot vendor
| Vendor / Platform | Fix Page |
|---|---|
| Amazon Lex | amazon_lex.md |
| Azure Bot Service | azure_bot_service.md |
| Dialogflow CX | dialogflow_cx.md |
| Freshchat | freshchat.md |
| Freshdesk | freshdesk.md |
| Intercom | intercom.md |
| Microsoft Copilot Studio | microsoft_copilot_studio.md |
| Rasa | rasa.md |
| Salesforce Einstein Bots | salesforce_einstein_bots.md |
| Twilio Studio | twilio_studio.md |
| Watsonx Assistant | watsonx_assistant.md |
| Zendesk | zendesk.md |
Symptom → exact fix
| Symptom | Likely cause | Open this |
|---|---|---|
| Slot filling fails randomly | Missing entity fallback, context reset | dialogflow_cx.md · rasa.md |
| Bot replies too slowly | Cold starts, webhook bottlenecks | amazon_lex.md · azure_bot_service.md |
| Knowledge base answers drift | Retrieval misaligned with store | watsonx_assistant.md · retrieval-traceability.md |
| Omnichannel flow desync | Connectors drop metadata | intercom.md · zendesk.md |
| Unsafe or off-policy replies | No policy fences or prompt injection | microsoft_copilot_studio.md · prompt-injection.md |
| Migration broke production | Schema mismatch, missing idempotency | serverless_ci_cd.md · env_bootstrap_and_migrations.md |
| Conversation history disappears | Stateless KV pattern missing | stateless_kv_queue_patterns.md |
Fix in 60 seconds
- Verify intents — run eval with test utterances, check F1 ≥ 0.85.
- Check state — ensure KV queue or context store persists between turns.
- Fence prompts — load prompt_injection.md.
- Measure latency — split warm vs cold path; provision concurrency if needed.
- Cross-channel sync — confirm connectors carry metadata (role, region, tenant).
Copy-paste prompt for chatbot incidents
You have TXT OS and the WFGY Problem Map loaded.
My chatbot incident:
- platform: [Dialogflow|Rasa|Intercom|etc.]
- symptom: [short description]
- eval: { F1, ΔS, coverage, λ states }
- infra: { cold_ms, warm_ms, concurrency, connectors }
- compliance: { pii_found: true|false, policy_eval }
Tell me:
1) which layer is failing and why,
2) the exact WFGY page to open,
3) the minimal steps to restore accuracy and latency,
4) a quick regression test to prevent repeat.
FAQ
Q: My bot answers correctly in dev but fails in production. Why? A: Likely env mismatch — analyzers, slots, or schema drift between environments. Check serverless_ci_cd.md.
Q: How do I stop hallucinations in Copilot Studio or Dialogflow? A: Enforce policy fences and cite-then-explain. See prompt_injection.md.
Q: Why is latency so different on first vs second request? A: Cold starts. See cold_start_concurrency.md.
Q: How can I ensure PII never leaks through connectors? A: Attach privacy_and_pii_edges.md and enforce payload contracts.
Q: Do I need to change my vendor to apply WFGY fixes? A: No. WFGY guardrails are store-agnostic and vendor-agnostic. You patch structure, not infra.
🔗 Quick-Start Downloads (60 sec)
| Tool | Link | 3-Step Setup |
|---|---|---|
| WFGY 1.0 PDF | Engine Paper | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>” |
| TXT OS (plain-text OS) | TXTOS.txt | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
🧭 Explore More
| Module | Description | Link |
|---|---|---|
| WFGY Core | WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack | View → |
| Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | View → |
| Problem Map 2.0 | RAG-focused failure tree, modular fixes, and pipelines | View → |
| Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | View → |
| Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | View → |
| Benchmark vs GPT-5 | Stress test GPT-5 with full WFGY reasoning suite | View → |
| 🧙♂️ Starter Village 🏡 | New here? Lost in symbols? Click here and let the wizard guide you through | Start → |
👑 Early Stargazers: See the Hall of Fame —
Engineers, hackers, and open source builders who supported WFGY from day one.
⭐ WFGY Engine 2.0 is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the Unlock Board.
