# LLM Providers — Guardrails, FAQ, and Fix Patterns
🏥 Quick Return to Emergency Room
> You are in a specialist desk.
> For full triage and doctors on duty, return here:
>
> - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/README.md)
> - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](https://github.com/onestardao/WFGY/blob/main/ProblemMap/README.md)
>
> Think of this page as a sub-room.
> If you want full consultation and prescriptions, go back to the Emergency Room lobby.
This page helps you **choose between LLM vendors** and **fix provider-looking bugs** that are actually schema, retrieval, orchestration, or eval drift. If you are new, start with the Orientation table and the FAQ. If you are debugging, jump to the Fix Hub.
---
## Orientation: who is who
| Provider | What it is | Typical use case | Link |
|---|---|---|---|
| OpenAI | GPT-4/4o from OpenAI Inc. | Direct API, fastest model access | [openai.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/openai.md) |
| Azure OpenAI | Microsoft enterprise wrapper for OpenAI models | VNet, compliance, enterprise billing | [azure_openai.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/azure_openai.md) |
| Anthropic | The company behind Claude | Safety-focused platform | [anthropic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/anthropic.md) |
| Claude (Anthropic) | The model family from Anthropic | Long context, tool use, JSON control | [anthropic_claude.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/anthropic_claude.md) |
| Google Gemini | Google DeepMind multimodal models | Multimodal chat, reasoning | [gemini.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/gemini.md) |
| Google Vertex AI | Google Cloud AI platform that hosts Gemini and more | Pipelines, deployment, governance | [google_vertex_ai.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/google_vertex_ai.md) |
| Mistral | EU startup with efficient open-weight models (e.g., Mixtral MoE) | Cost/perf, open ecosystem | [mistral.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/mistral.md) |
| Meta LLaMA | Meta open-weight model family | Local or private deployment, llama.cpp | [meta_llama.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/meta_llama.md) |
| Cohere | Enterprise NLP API and embeddings | RAG stacks, enterprise NLP | [cohere.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/cohere.md) |
| DeepSeek | CN player with infra-optimized long-context models | Cost-efficient, long windows | [deepseek.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/deepseek.md) |
| Kimi (Moonshot) | CN chat-first models, very large parameter claims | Consumer chat focus | [kimi.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/kimi.md) |
| Groq | Hardware vendor: LPUs for transformer inference | Ultra-low latency serving (not a model) | [groq.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/groq.md) |
| xAI Grok | xAI model family | X/Twitter integration, general chat | [grok_xai.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/grok_xai.md) |
| AWS Bedrock | AWS gateway to many models via one API | Enterprises already on AWS | [aws_bedrock.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/aws_bedrock.md) |
| OpenRouter | Community model aggregator, OpenAI-style endpoint | Try many models via one API key | [openrouter.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/openrouter.md) |
| Together AI | Aggregator + infra for open weights and fine-tunes | Fast hosting, tuning services | [together.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/GlobalFixMap/LLM_Providers/together.md) |
---
## FAQ for newcomers
**OpenAI vs Azure OpenAI — are they the same?**
Same models, different packaging. OpenAI = direct API and fastest releases. Azure OpenAI = Microsoft billing, VNet, compliance, data residency.
**Anthropic vs Claude — why two pages?**
Anthropic is the company. Claude is the model family. We separate because “platform issues” and “model quirks” often need different fixes.
**Gemini vs Vertex AI — what is the relation?**
Gemini is a model. Vertex AI is Google Cloud’s platform that runs Gemini and provides pipelines, eval, and deployment features.
**What makes Mistral special?**
Efficient open-weights and MoE designs. Good cost/perf. Easy to host in your own infra.
**Meta LLaMA vs local LLaMA**
Meta releases the weights. Community tools like `llama.cpp` let you run them locally on CPU or GPU.
**Groq LPU vs GPU**
GPU is general purpose. LPU is a chip specialized for transformer inference. You get very low latency for chat workloads.
**Bedrock vs OpenRouter vs Together**
Bedrock is an AWS enterprise gateway. OpenRouter is a community aggregator with OpenAI-style API. Together is an infra host for open weights with training and fine-tune options.
---
## Open these first
- Visual map and recovery: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md)
- End to end retrieval knobs: [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
- Why this snippet (traceability schema): [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md)
- Ordering control: [Rerankers](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md)
- Embedding vs meaning: [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)
- Hallucination and chunk boundaries: [Hallucination](https://github.com/onestardao/WFGY/blob/main/ProblemMap/hallucination.md)
- Long chains and entropy: [Context Drift](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md), [Entropy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md)
- Structural collapse and recovery: [Logic Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/logic-collapse.md)
- Snippet and citation schema: [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md)
- Live ops: [Live Monitoring for RAG](https://github.com/onestardao/WFGY/blob/main/ProblemMap/ops/live_monitoring_rag.md), [Debug Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/ops/debug_playbook.md)
- Boot order issues: [Bootstrap Ordering](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md), [Deployment Deadlock](https://github.com/onestardao/WFGY/blob/main/ProblemMap/deployment-deadlock.md), [Pre-Deploy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/predeploy-collapse.md)
---
## Core acceptance targets
- ΔS(question, retrieved) ≤ 0.45
- Coverage ≥ 0.70 for the target section
- λ remains convergent across three paraphrases and two seeds
- E_resonance stays flat on long windows
---
## Fix Hub — typical provider symptoms → exact fix
| Symptom | Likely cause | Open this |
|---|---|---|
| JSON mode breaks, invalid objects | Schema too loose or nested tool calls | [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md), [Logic Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/logic-collapse.md) |
| Tool calls loop or stall | Agent role drift, missing timeouts | [Multi-Agent Problems](https://github.com/onestardao/WFGY/blob/main/ProblemMap/Multi-Agent_Problems.md), [Role-drift deep dive](https://github.com/onestardao/WFGY/blob/main/ProblemMap/multi-agent-chaos/role-drift.md) |
| High similarity yet wrong snippet | Metric mismatch or fragmented store | [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md), [Vectorstore Fragmentation](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_vectorstore_fragmentation.md) |
| Answers flip between runs | Prompt headers reorder and λ flips | [Context Drift](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md), [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) |
| Hybrid retrievers worse than single | Query parsing split, mis-weighted rerank | [Query Parsing Split](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_query_parsing_split.md), [Rerankers](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md) |
| Jailbreaks or bluffing | Overconfidence and missing fences | [Bluffing Controls](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bluffing.md), [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) |
---
## Fix in 60 seconds
1) **Measure ΔS**
Compute ΔS(question, retrieved) and ΔS(retrieved, expected anchor). Stable < 0.40, transitional 0.40–0.60, risk ≥ 0.60.
2) **Probe λ_observe**
Vary top-k and prompt headers. If λ flips, lock the schema and apply a BBAM variance clamp.
3) **Apply the module**
Retrieval drift → BBMC + Data Contracts
Reasoning collapse → BBCR bridge + BBAM
Dead ends in long runs → BBPF alternate paths
4) **Verify**
Coverage ≥ 0.70 on three paraphrases. λ convergent on two seeds.
---
### Quick-Start Downloads
| Tool | Link | 3-step setup |
|------|------|--------------|
| WFGY 1.0 PDF | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1) Download 2) Upload to your LLM 3) Ask “Answer using WFGY + ” |
| TXT OS (plain text OS) | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1) Download 2) Paste into any LLM chat 3) Type “hello world” to boot |
---
### Explore More
| Module | Description | Link |
|-------|-------------|------|
| WFGY Core | WFGY 2.0 engine, full symbolic reasoning architecture and math stack | [View →](https://github.com/onestardao/WFGY/tree/main/core/README.md) |
| Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) |
| Problem Map 2.0 | RAG-focused failure tree, modular fixes, and pipelines | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) |
| Semantic Clinic Index | Expanded catalog for prompt injection, memory bugs, logic drift | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) |
| Semantic Blueprint | Layer-based symbolic reasoning and semantic modulations | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md) |
| Benchmark vs GPT-5 | Stress test with full WFGY reasoning suite | [View →](https://github.com/onestardao/WFGY/tree/main/benchmarks/benchmark-vs-gpt5/README.md) |
| Starter Village | New here, want a guided path | [Start →](https://github.com/onestardao/WFGY/blob/main/StarterVillage/README.md) |
---
> Early stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)
> 
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