diff --git a/workflows/Analyze hotel reviews with OpenAI GPT-4o-mini and Airtable sentiment fields-13573/readme-13573.md b/workflows/Analyze hotel reviews with OpenAI GPT-4o-mini and Airtable sentiment fields-13573/readme-13573.md
new file mode 100644
index 000000000..9b035483f
--- /dev/null
+++ b/workflows/Analyze hotel reviews with OpenAI GPT-4o-mini and Airtable sentiment fields-13573/readme-13573.md	
@@ -0,0 +1,390 @@
+Analyze hotel reviews with OpenAI GPT-4o-mini and Airtable sentiment fields
+
+https://n8nworkflows.xyz/workflows/analyze-hotel-reviews-with-openai-gpt-4o-mini-and-airtable-sentiment-fields-13573
+
+
+# Analyze hotel reviews with OpenAI GPT-4o-mini and Airtable sentiment fields
+
+## 1. Workflow Overview
+
+**Workflow name:** *Hotel Review Sentiment Processor*  
+**Purpose:** Automatically enrich newly created/updated hotel review records in Airtable with AI-derived sentiment fields (via OpenAI GPT-4o-mini), then write the structured results back to Airtable.  
+**Primary use case:** Customer feedback processing for hotels (or any review dataset) where sentiment, topics, and structured insights are stored in Airtable fields.
+
+### 1.1 Trigger & Pre-checks (Airtable → gating logic)
+- Starts from an **Airtable Trigger** event.
+- Prevents re-processing already processed reviews.
+- Ensures a review payload exists before sending anything to the AI.
+
+### 1.2 Payload normalization (clean input for AI)
+- Normalizes/massages incoming Airtable trigger data into a consistent shape used by the LLM chain.
+
+### 1.3 AI inference + structured parsing (LLM + schema parser)
+- Uses a **Chat OpenAI** model node (GPT-4o-mini implied by the title) as the language model.
+- A LangChain **chain** node performs the analysis.
+- A **Structured Output Parser (JSON Schema)** enforces a JSON-shaped output.
+
+### 1.4 Post-processing + validation (flatten, merge, verify)
+- Flattens the structured AI result for easy mapping.
+- Combines AI fields with original review data.
+- Validates AI output before writing to Airtable; routes failures to a fallback handler.
+
+### 1.5 Airtable update (write back results)
+- Prepares final Airtable update payload.
+- Updates the original review record.
+- On AI failure, writes failure/empty/default fields (depending on the handler configuration).
+
+---
+
+## 2. Block-by-Block Analysis
+
+### Block 1 — Trigger & Pre-checks
+**Overview:** Receives Airtable events, skips already-processed records, and stops if there is no review content to analyze.
+
+**Nodes involved:**
+- Airtable Trigger
+- Check if Processed (IF)
+- Processed Review: No Action Required (NoOp)
+- Check if Review Exist (IF)
+- No Review to Process (NoOp)
+
+#### Node: **Airtable Trigger**
+- **Type / role:** `n8n-nodes-base.airtableTrigger` — Entry point; emits items when Airtable records change.
+- **Configuration choices (interpreted):** Not provided in JSON. Typically includes Base, Table, and trigger event type (create/update).
+- **Inputs/Outputs:** No input; output → **Check if Processed**.
+- **Potential failures / edge cases:**
+  - Airtable credentials missing/expired.
+  - Misconfigured base/table/view leading to no triggers.
+  - Payload shape differs depending on Airtable Trigger mode (can impact downstream expressions).
+
+#### Node: **Check if Processed**
+- **Type / role:** `n8n-nodes-base.if` — Gate to prevent reprocessing.
+- **Configuration choices:** Not provided; logically checks a boolean/flag field (e.g., `Processed = true` or presence of sentiment fields).
+- **Connections:**
+  - **True** (already processed) → **Processed Review: No Action Required**
+  - **False** → **Check if Review Exist**
+- **Potential failures / edge cases:**
+  - If the field used for the condition is missing/null, the IF may route unexpectedly.
+  - If Airtable returns different field names than expected, expressions can fail.
+
+#### Node: **Processed Review: No Action Required**
+- **Type / role:** `n8n-nodes-base.noOp` — Terminal placeholder for “do nothing”.
+- **Connections:** No outputs.
+- **Edge cases:** None (but note that “already processed” records are silently ignored).
+
+#### Node: **Check if Review Exist**
+- **Type / role:** `n8n-nodes-base.if` — Ensures review text exists before AI call.
+- **Configuration choices:** Not provided; likely checks that a “Review”/“Comment” field is not empty.
+- **Connections:**
+  - **True** → **Normalize Review Payload**
+  - **False** → **No Review to Process**
+- **Potential failures / edge cases:**
+  - Reviews with only whitespace may pass unless trimmed.
+  - Multi-field reviews (title + body) may require concatenation; if not handled, AI gets partial context.
+
+#### Node: **No Review to Process**
+- **Type / role:** `n8n-nodes-base.noOp` — Terminal placeholder for missing review content.
+- **Connections:** No outputs.
+
+---
+
+### Block 2 — Normalize Review Payload
+**Overview:** Standardizes the inbound item into a consistent structure for the AI chain (e.g., extracting record ID, review text, metadata).
+
+**Nodes involved:**
+- Normalize Review Payload (Set)
+
+#### Node: **Normalize Review Payload**
+- **Type / role:** `n8n-nodes-base.set` — Creates/renames fields for downstream use.
+- **Configuration choices:** Not provided; typical actions:
+  - Map Airtable record ID into a stable field (e.g., `recordId`).
+  - Extract `reviewText`, `rating`, `hotelName`, `language`, etc.
+- **Connections:** Input from **Check if Review Exist** → output to **AI: Analyze Review Sentiment**.
+- **Potential failures / edge cases:**
+  - If you “Keep Only Set” without including needed fields, later Airtable update may lack `recordId`.
+  - Field name mismatches between Airtable and Set node mappings.
+
+---
+
+### Block 3 — AI inference + structured parsing
+**Overview:** Runs GPT analysis and parses the response into a schema-conformant JSON object using LangChain nodes.
+
+**Nodes involved:**
+- Analyze Review Sentiment (Chat OpenAI model)
+- Parse AI Output (JSON Schema) (Structured Output Parser)
+- AI: Analyze Review Sentiment (Chain)
+
+#### Node: **Analyze Review Sentiment**
+- **Type / role:** `@n8n/n8n-nodes-langchain.lmChatOpenAi` — Provides the chat model (LLM) to the chain.
+- **Configuration choices (interpreted):**
+  - Parameters are empty in JSON, so key settings (model name, temperature, API credential) are configured in UI or defaults.
+  - **maxTries=2** and **retryOnFail=true**: will attempt up to 2 retries on failure.
+  - **alwaysOutputData=true**: node outputs an item even if something fails (important for failure routing).
+- **Connections:**
+  - Output (special port) `ai_languageModel` → **AI: Analyze Review Sentiment**
+- **Version-specific notes:** Type version **1.2** (LangChain OpenAI chat wrapper; UI fields vary slightly by n8n version).
+- **Potential failures / edge cases:**
+  - OpenAI credential missing/invalid.
+  - Model not available in your OpenAI account/region.
+  - Rate limits/timeouts; retries may still fail.
+  - If prompt expects certain input fields not present, the chain may produce irrelevant output.
+
+#### Node: **Parse AI Output (JSON Schema)**
+- **Type / role:** `@n8n/n8n-nodes-langchain.outputParserStructured` — Forces/validates JSON output matching a schema.
+- **Configuration choices:** Empty in JSON; in UI, typically defines a JSON Schema with sentiment fields (e.g., polarity, confidence, pros/cons, categories).
+- **Connections:**
+  - Output (special port) `ai_outputParser` → **AI: Analyze Review Sentiment**
+- **Version-specific notes:** Type version **1.3**.
+- **Edge cases / failures:**
+  - If the model output cannot be parsed to schema, parser may error or return empty/partial depending on configuration.
+  - Schema too strict causes frequent failures; schema too loose reduces reliability.
+
+#### Node: **AI: Analyze Review Sentiment**
+- **Type / role:** `@n8n/n8n-nodes-langchain.chainLlm` — Orchestrates prompt + model + parser to generate structured output.
+- **Configuration choices:** Empty in JSON; in UI it typically includes:
+  - Prompt template referencing fields from **Normalize Review Payload** (e.g., `{{$json.reviewText}}`).
+  - Uses **Analyze Review Sentiment** as its model and **Parse AI Output** as its structured parser (via special connections).
+- **Connections:**
+  - Main input from **Normalize Review Payload**
+  - `ai_languageModel` input from **Analyze Review Sentiment**
+  - `ai_outputParser` input from **Parse AI Output (JSON Schema)**
+  - Main output → **Flatten AI Output**
+- **Version-specific notes:** Type version **1.7**.
+- **Potential failures / edge cases:**
+  - Prompt variables missing → empty prompt sections → bad output.
+  - Non-English reviews: if not handled in prompt, sentiment may be inconsistent.
+  - Long reviews may exceed context limits depending on selected model/settings.
+
+---
+
+### Block 4 — Post-processing + validation
+**Overview:** Flattens and merges AI data with original review data, validates AI output presence/shape, and branches into success vs. failure handling.
+
+**Nodes involved:**
+- Flatten AI Output (Set)
+- Combine AI Output with Review Data (Set)
+- Check AI Output Valid (IF)
+- AI Failure Handler (Set)
+
+#### Node: **Flatten AI Output**
+- **Type / role:** `n8n-nodes-base.set` — Converts nested AI JSON into flat fields for Airtable mapping.
+- **Configuration choices:** Not shown; typical patterns:
+  - `sentiment.label`, `sentiment.score` → `sentimentLabel`, `sentimentScore`
+  - `topics[]` → string join or multi-select mapping
+- **Connections:** Input from **AI: Analyze Review Sentiment** → output to **Combine AI Output with Review Data**.
+- **Edge cases:**
+  - Arrays/objects may not map cleanly into Airtable field types.
+  - If AI output is missing keys, expressions may resolve to `undefined`.
+
+#### Node: **Combine AI Output with Review Data**
+- **Type / role:** `n8n-nodes-base.set` — Ensures the outgoing item includes both record identifiers and AI results.
+- **Configuration choices:** Not shown; usually:
+  - Keep `recordId` and original Airtable metadata.
+  - Add flattened AI fields.
+- **Connections:** → **Check AI Output Valid**
+- **Edge cases:**
+  - If this node overwrites `id`/`recordId`, Airtable update will fail (record not found).
+
+#### Node: **Check AI Output Valid**
+- **Type / role:** `n8n-nodes-base.if` — Validates AI output before writing.
+- **Configuration choices:** Not shown; likely checks required fields exist (e.g., `sentimentLabel` not empty).
+- **Connections:**
+  - **True** → **Prepare Airtable Update**
+  - **False** → **AI Failure Handler**
+- **Edge cases:**
+  - Overly strict validation can route many legitimate outputs to failure.
+  - Overly loose validation can write garbage to Airtable.
+
+#### Node: **AI Failure Handler**
+- **Type / role:** `n8n-nodes-base.set` — Creates a safe fallback update payload (e.g., sets error status fields).
+- **Configuration choices:** Not shown; commonly sets:
+  - `processingStatus = "AI_FAILED"` or similar
+  - stores `errorMessage` or raw model output (if captured)
+- **Connections:** → **Update Airtable Review Record**
+- **Edge cases:**
+  - If it doesn’t include `recordId`, the update cannot target the correct record.
+
+---
+
+### Block 5 — Prepare & Update Airtable
+**Overview:** Maps fields into Airtable’s expected update format and updates the originating record.
+
+**Nodes involved:**
+- Prepare Airtable Update (Set)
+- Update Airtable Review Record (Airtable)
+
+#### Node: **Prepare Airtable Update**
+- **Type / role:** `n8n-nodes-base.set` — Final field mapping and formatting for Airtable.
+- **Configuration choices:** Not shown; typically:
+  - Builds `fields` object with Airtable column names.
+  - Ensures correct types: numbers, single select strings, multi-select arrays, long text.
+- **Connections:** → **Update Airtable Review Record**
+- **Edge cases:**
+  - Airtable field type mismatch (e.g., sending string to number field).
+  - Multi-select requires array of strings; sending comma-separated string may fail.
+
+#### Node: **Update Airtable Review Record**
+- **Type / role:** `n8n-nodes-base.airtable` — Writes back sentiment fields to the review record.
+- **Configuration choices:** Not present; typically “Update” operation with:
+  - Base + Table
+  - Record ID from earlier node (expression)
+  - Fields mapping
+- **Connections:** Terminal (no downstream nodes).
+- **Version-specific notes:** Type version **2.1**.
+- **Potential failures / edge cases:**
+  - Record ID invalid or missing.
+  - Airtable permission denied / base not shared with token.
+  - Rate limits on Airtable API.
+  - Partial updates: fields not found if column names differ.
+
+---
+
+### Block 6 — Sticky Notes (documentation placeholders)
+**Overview:** The workflow contains multiple sticky notes, but all have empty content in the provided JSON.
+
+**Nodes involved:**
+- Sticky Note
+- Sticky Note1
+- Sticky Note2
+- Sticky Note3
+- Sticky Note5
+- Sticky Note6
+
+#### Node: **Sticky Note / Sticky Note1 / Sticky Note2 / Sticky Note3 / Sticky Note5 / Sticky Note6**
+- **Type / role:** `n8n-nodes-base.stickyNote` — Canvas annotations.
+- **Configuration choices:** `content` is empty for all; no operational effect.
+- **Connections:** None.
+
+---
+
+## 3. Summary Table
+
+| Node Name | Node Type | Functional Role | Input Node(s) | Output Node(s) | Sticky Note |
+|---|---|---|---|---|---|
+| Airtable Trigger | airtableTrigger | Entry trigger from Airtable changes | — | Check if Processed |  |
+| Check if Processed | if | Skip already-processed reviews | Airtable Trigger | Processed Review: No Action Required; Check if Review Exist |  |
+| Processed Review: No Action Required | noOp | Stop path for already processed items | Check if Processed | — |  |
+| Check if Review Exist | if | Ensure review content exists | Check if Processed | Normalize Review Payload; No Review to Process |  |
+| No Review to Process | noOp | Stop path when review text missing | Check if Review Exist | — |  |
+| Normalize Review Payload | set | Normalize Airtable payload for AI | Check if Review Exist | AI: Analyze Review Sentiment |  |
+| Analyze Review Sentiment | lmChatOpenAi | OpenAI chat model provider for chain | — (model connection) | AI: Analyze Review Sentiment (ai_languageModel) |  |
+| Parse AI Output (JSON Schema) | outputParserStructured | Enforce schema for AI output | — (parser connection) | AI: Analyze Review Sentiment (ai_outputParser) |  |
+| AI: Analyze Review Sentiment | chainLlm | Run prompt+LLM+parser to produce structured result | Normalize Review Payload; (model+parser ports) | Flatten AI Output |  |
+| Flatten AI Output | set | Flatten structured JSON into fields | AI: Analyze Review Sentiment | Combine AI Output with Review Data |  |
+| Combine AI Output with Review Data | set | Merge AI results with record identifiers | Flatten AI Output | Check AI Output Valid |  |
+| Check AI Output Valid | if | Validate AI output before update | Combine AI Output with Review Data | Prepare Airtable Update; AI Failure Handler |  |
+| Prepare Airtable Update | set | Map fields to Airtable update payload | Check AI Output Valid | Update Airtable Review Record |  |
+| AI Failure Handler | set | Build fallback update on AI failure | Check AI Output Valid | Update Airtable Review Record |  |
+| Update Airtable Review Record | airtable | Update Airtable record with sentiment fields | Prepare Airtable Update; AI Failure Handler | — |  |
+| Sticky Note | stickyNote | Canvas annotation (empty) | — | — |  |
+| Sticky Note1 | stickyNote | Canvas annotation (empty) | — | — |  |
+| Sticky Note2 | stickyNote | Canvas annotation (empty) | — | — |  |
+| Sticky Note3 | stickyNote | Canvas annotation (empty) | — | — |  |
+| Sticky Note5 | stickyNote | Canvas annotation (empty) | — | — |  |
+| Sticky Note6 | stickyNote | Canvas annotation (empty) | — | — |  |
+
+---
+
+## 4. Reproducing the Workflow from Scratch
+
+1) **Create a new workflow**
+   - Name: **Hotel Review Sentiment Processor**
+   - Set timezone (optional): **Asia/Manila** (to match existing settings)
+
+2) **Add Airtable Trigger**
+   - Node: **Airtable Trigger**
+   - Configure credentials: Airtable Personal Access Token (PAT)
+   - Select **Base** and **Table** that contains hotel reviews
+   - Choose trigger event(s): typically “When record is created/updated”
+   - Ensure the trigger includes the fields needed downstream (record ID + review text + processed flag)
+
+3) **Add IF: “Check if Processed”**
+   - Condition: check a field such as `Processed` is **true** (or sentiment fields already filled)
+   - **True** output → add **NoOp** node named **Processed Review: No Action Required**
+   - **False** output → continue
+
+4) **Add IF: “Check if Review Exist”**
+   - Condition: review text field exists and is not empty (e.g., `Review` / `Comment`)
+   - **False** output → add **NoOp** node named **No Review to Process**
+   - **True** output → continue
+
+5) **Add Set: “Normalize Review Payload”**
+   - Extract and standardize fields, at minimum:
+     - `recordId` = Airtable record ID
+     - `reviewText` = the review body (optionally concatenate title + body)
+     - (Optional) `rating`, `hotelName`, `source`, `language`
+   - Prefer keeping original fields unless you are sure they are not needed later.
+
+6) **Add LangChain nodes for structured sentiment**
+   - Add **Chat OpenAI** node named **Analyze Review Sentiment**
+     - Credentials: OpenAI API key
+     - Model: choose **gpt-4o-mini** (or the closest equivalent available)
+     - Set temperature (commonly 0–0.3 for consistent classification)
+     - Keep retries enabled (this workflow uses retries; max tries 2)
+   - Add **Structured Output Parser** named **Parse AI Output (JSON Schema)**
+     - Define a JSON Schema for fields you want in Airtable (example categories):
+       - `sentimentLabel` (e.g., Positive/Neutral/Negative)
+       - `sentimentScore` (0–1 or -1–1)
+       - `summary`
+       - `pros` (array)
+       - `cons` (array)
+       - `topics` (array)
+   - Add **LLM Chain** node named **AI: Analyze Review Sentiment**
+     - Prompt: instruct model to analyze `{{$json.reviewText}}` and output strictly according to schema
+     - Connect:
+       - **Normalize Review Payload (main)** → **AI: Analyze Review Sentiment (main)**
+       - **Analyze Review Sentiment (ai_languageModel)** → **AI: Analyze Review Sentiment**
+       - **Parse AI Output (ai_outputParser)** → **AI: Analyze Review Sentiment**
+
+7) **Add Set: “Flatten AI Output”**
+   - Map parser result into flat fields for Airtable:
+     - Convert nested objects into top-level keys.
+     - Convert arrays into Airtable-friendly formats (either arrays for multi-select, or joined text for long text).
+
+8) **Add Set: “Combine AI Output with Review Data”**
+   - Ensure the outgoing item includes:
+     - `recordId`
+     - all Airtable update fields from AI result
+     - optional audit fields like `processedAt` timestamp
+
+9) **Add IF: “Check AI Output Valid”**
+   - Condition examples:
+     - `sentimentLabel` exists
+     - `sentimentScore` is a number
+   - **True** → success path
+   - **False** → failure path
+
+10) **Add Set: “Prepare Airtable Update”** (success path)
+   - Build fields exactly matching Airtable column names/types.
+   - Example mappings:
+     - `Sentiment` (single select) ← `sentimentLabel`
+     - `Sentiment Score` (number) ← `sentimentScore`
+     - `AI Summary` (long text) ← `summary`
+     - `Topics` (multi-select) ← array `topics`
+     - `Processed` (checkbox) ← true
+
+11) **Add Set: “AI Failure Handler”** (failure path)
+   - Set safe defaults and status fields, e.g.:
+     - `AI Status` = "failed"
+     - `Processed` = false (or true with “failed” state, depending on your policy)
+     - Optionally store a short error note if available
+
+12) **Add Airtable node: “Update Airtable Review Record”**
+   - Operation: **Update**
+   - Record ID: expression pointing to `{{$json.recordId}}`
+   - Fields: map from either **Prepare Airtable Update** or **AI Failure Handler**
+   - Connect both paths to this node:
+     - **Prepare Airtable Update** → **Update Airtable Review Record**
+     - **AI Failure Handler** → **Update Airtable Review Record**
+
+13) **(Optional) Add an Error Workflow**
+   - The workflow references an **errorWorkflow** ID in settings; to replicate behavior, configure **Workflow Settings → Error Workflow** to your own error handler workflow.
+
+---
+
+## 5. General Notes & Resources
+
+| Note Content | Context or Link |
+|---|---|
+| Workflow settings include a configured Error Workflow reference (ID present in JSON). To reproduce fully, create/select your own Error Workflow in n8n settings. | Workflow-level reliability / incident handling |
+| All sticky notes in the provided workflow are empty; they don’t document configuration or assumptions. | Canvas annotations (none provided) |
\ No newline at end of file