# AI 3D Print Expert — Photo Diagnosis & Troubleshooting (`nicocomt/conseiller-3d`) Actor

📸 Photo d'une impression ratée ? L'IA identifie le défaut et donne les réglages à corriger. 🤖 Expert FDM & résine, 💬 questions par lot, 🎯 valeurs chiffrées 🇬🇧 Send a photo of a failed print: the AI names the defect and gives the fix. FDM & resin expert, batch mode.

- **URL**: https://apify.com/nicocomt/conseiller-3d.md
- **Developed by:** [Nicolas](https://apify.com/nicocomt) (community)
- **Categories:** AI, Agents, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md):

```bash
npm install apify-client
```

In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md):

```bash
pip install apify-client
```

In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):

````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash

In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md).

If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).


# README

## 🤖 AI 3D Print Expert — Diagnostic photo et dépannage

Un assistant expert en impression 3D, propulsé par l'IA. **Envoyez la photo d'une impression ratée et découvrez ce qui cloche**, ou posez simplement vos questions (FDM ou résine) pour obtenir des réponses claires avec des réglages concrets.

### 📸 Diagnostic par photo

Votre impression est ratée mais vous ne savez pas pourquoi ? **Téléversez une photo** — l'IA l'examine et vous répond :

- **Quel défaut** est visible (fils entre les parties, coin décollé, sous-extrusion, couches décalées, sur-exposition en résine…)
- **Pourquoi** il se produit
- **Quels réglages corriger**, avec des valeurs chiffrées

Vous pouvez aussi décrire ce que vous observez ou ce que vous soupçonnez. L'IA en tient compte — mais **vérifie sur la photo** : si votre hypothèse ne colle pas à ce qu'elle voit, elle vous le dit et nomme le vrai défaut.

### 🔍 Ce que fait cet Actor

- **Diagnostique une photo** d'impression : défaut, cause, réglages à corriger.
- Répond à **une ou plusieurs questions** en une seule exécution (une réponse par question).
- Adapte ses réponses à la **langue**, au **niveau** (débutant à avancé) et à la **technologie** choisis (FDM, résine ou les deux).
- Structure chaque réponse : réponse directe, puis réglages concrets (température, vitesse, rétraction, exposition…), et une note de sécurité si nécessaire.

### 💬 Exemples de questions

- « Quel filament pour une pièce qui reste dehors ? »
- « Pourquoi mes premières couches n'accrochent pas ? »
- « PLA ou PETG pour un support de téléphone ? »
- « Quels réglages de température pour du TPU ? »

### 🛠️ Domaines couverts

Choix et comparaison de matériaux (PLA, PETG, ABS, ASA, TPU, résines…), réglages d'imprimante, dépannage (warping, stringing, sous-extrusion…), finitions et post-traitement, conseils selon l'usage.

### ⚙️ Paramètres

| Paramètre | Rôle |
|---|---|
| Questions | Une ou plusieurs questions, une par ligne. Facultatif si vous envoyez une photo. |
| **Photo de l'impression** | Téléversez une image (moins de 3,5 Mo) ou collez son adresse web. |
| **Ce que vous observez** | Décrivez la situation ou ce que vous soupçonnez, pour un diagnostic plus ciblé. |
| Langue | Français, anglais, ou automatique (langue de la question). |
| Niveau | Débutant, intermédiaire ou avancé. |
| Technologie | FDM, résine, ou les deux. |

### 🗂️ Les versions

> 🟢 **0.0.5 — la plus récente**
> - 📸 **Diagnostic par photo** : téléversez une image de votre impression, l'IA nomme le défaut, explique la cause et donne les réglages à corriger.
> - 📝 **Champ « ce que vous observez »** : décrivez la situation ou votre hypothèse. L'IA la vérifie sur la photo et vous corrige si elle ne correspond pas.

> 🔵 **0.0.4**
> - 🗂️ **Traitement par lot** : plusieurs questions d'un coup, une réponse par question.
> - 🌍 **Options** : langue, niveau et technologie (FDM / résine).
> - 🎯 **Réponses plus concrètes** : structure claire et réglages chiffrés.
> - 🛡️ **Robustesse** : une question qui échoue ne bloque pas les autres.

> ⚪ **0.0.1**
> - 💬 Première version : une question, une réponse d'expert en impression 3D.

---

## 🤖 AI 3D Print Expert — Photo Diagnosis & Troubleshooting

An AI-powered 3D printing expert. **Send a photo of a failed print and find out what went wrong**, or simply ask your questions (FDM or resin) for clear answers with concrete settings.

### 📸 Photo diagnosis

Your print failed and you don't know why? **Upload a photo** — the AI inspects it and tells you:

- **Which defect** is visible (stringing, lifted corner, under-extrusion, layer shifting, resin over-exposure…)
- **Why** it happens
- **Which settings to change**, with actual numbers

You can also describe what you observe or suspect. The AI takes it into account — but **checks the photo**: if your guess doesn't match what it sees, it says so and names the real defect.

### 🔍 What it does

- **Diagnoses a photo** of a print: defect, cause, settings to fix.
- Answers **one or more** questions in a single run (one answer per question).
- Adapts to the chosen **language**, **level** (beginner to advanced) and **technology** (FDM, resin, or both).
- Structures each answer: direct reply, then concrete settings (temperature, speed, retraction, exposure…), and a safety note when relevant.

### 💬 Example questions

- "Which filament for a part that stays outdoors?"
- "Why won't my first layers stick?"
- "PLA or PETG for a phone stand?"
- "What temperature settings for TPU?"

### 🛠️ Topics covered

Material choice and comparison (PLA, PETG, ABS, ASA, TPU, resins…), printer settings, troubleshooting (warping, stringing, under-extrusion…), finishing and post-processing, use-case advice.

### ⚙️ Parameters

| Parameter | Purpose |
|---|---|
| Questions | One or more questions, one per line. Optional if you send a photo. |
| **Print photo** | Upload an image (under 3.5 MB) or paste its web address. |
| **What you observe** | Describe the situation or what you suspect, for a more focused diagnosis. |
| Language | French, English, or automatic (question's language). |
| Level | Beginner, intermediate or advanced. |
| Technology | FDM, resin, or both. |

### 🗂️ Versions

> 🟢 **0.0.5 — latest**
> - 📸 **Photo diagnosis**: upload an image of your print — the AI names the defect, explains the cause and gives the settings to fix it.
> - 📝 **"What you observe" field**: describe the situation or your hypothesis. The AI checks it against the photo and corrects you if it doesn't match.

> 🔵 **0.0.4**
> - 🗂️ **Batch mode**: several questions at once, one answer each.
> - 🌍 **Options**: language, level and technology (FDM / resin).
> - 🎯 **More concrete answers**: clear structure and numeric settings.
> - 🛡️ **Robustness**: one failing question does not block the others.

> ⚪ **0.0.1**
> - 💬 First release: one question, one expert 3D printing answer.

---

*Réponses générées par IA — vérifiez les réglages critiques. / AI-generated answers — double-check critical settings.*

# Actor input Schema

## `questions` (type: `string`):

Une ou plusieurs questions sur l'impression 3D, une par ligne. / One or more 3D printing questions, one per line.
## `image` (type: `string`):

Téléversez une photo de votre impression, ou collez son adresse web. L'IA l'examine, nomme le défaut et donne les réglages à corriger. Sans question, un diagnostic complet est réalisé. Photo de moins de 3,5 Mo. / Upload a photo of your print, or paste its web address. The AI inspects it, names the defect and gives the settings to fix. With no question, a full diagnosis is returned. Keep it under 3.5 MB.
## `imageContexte` (type: `string`):

Décrivez en une ou deux phrases ce que montre la photo, dans quelles conditions l'impression a été faite, ou ce que vous soupçonnez. L'IA s'en sert pour cibler sa réponse — et vous corrige si votre hypothèse ne correspond pas à la photo. / Briefly describe what the photo shows, the print conditions, or what you suspect. The AI uses it to focus its answer — and corrects you if your guess doesn't match the photo.
## `langue` (type: `string`):

Langue des réponses. / Language of the answers.
## `niveau` (type: `string`):

Adapte le ton et la profondeur des réponses. / Adjusts tone and depth.
## `technologie` (type: `string`):

Cible la techno concernée. / Target technology.

## Actor input object example

```json
{
  "questions": "Quel filament choisir pour une pièce qui reste dehors ?\nMa première couche n'accroche pas, que faire ?",
  "imageContexte": "PLA à 210 °C, plateau à 60 °C. Je pense que c'est un problème d'adhérence.",
  "langue": "auto",
  "niveau": "intermediaire",
  "technologie": "both"
}
````

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "questions": `Quel filament choisir pour une pièce qui reste dehors ?
Ma première couche n'accroche pas, que faire ?`,
    "imageContexte": "PLA à 210 °C, plateau à 60 °C. Je pense que c'est un problème d'adhérence."
};

// Run the Actor and wait for it to finish
const run = await client.actor("nicocomt/conseiller-3d").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "questions": """Quel filament choisir pour une pièce qui reste dehors ?
Ma première couche n'accroche pas, que faire ?""",
    "imageContexte": "PLA à 210 °C, plateau à 60 °C. Je pense que c'est un problème d'adhérence.",
}

# Run the Actor and wait for it to finish
run = client.actor("nicocomt/conseiller-3d").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "questions": "Quel filament choisir pour une pièce qui reste dehors ?\\nMa première couche n'\''accroche pas, que faire ?",
  "imageContexte": "PLA à 210 °C, plateau à 60 °C. Je pense que c'\''est un problème d'\''adhérence."
}' |
apify call nicocomt/conseiller-3d --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=nicocomt/conseiller-3d",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "AI 3D Print Expert — Photo Diagnosis & Troubleshooting",
        "description": "📸 Photo d'une impression ratée ? L'IA identifie le défaut et donne les réglages à corriger. 🤖 Expert FDM & résine, 💬 questions par lot, 🎯 valeurs chiffrées 🇬🇧 Send a photo of a failed print: the AI names the defect and gives the fix. FDM & resin expert, batch mode.",
        "version": "0.0",
        "x-build-id": "pjvrsMHHDKU3kdxHg"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/nicocomt~conseiller-3d/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-nicocomt-conseiller-3d",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/nicocomt~conseiller-3d/runs": {
            "post": {
                "operationId": "runs-sync-nicocomt-conseiller-3d",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK",
                        "content": {
                            "application/json": {
                                "schema": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/nicocomt~conseiller-3d/run-sync": {
            "post": {
                "operationId": "run-sync-nicocomt-conseiller-3d",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        }
    },
    "components": {
        "schemas": {
            "inputSchema": {
                "type": "object",
                "properties": {
                    "questions": {
                        "title": "Vos questions / Your questions",
                        "type": "string",
                        "description": "Une ou plusieurs questions sur l'impression 3D, une par ligne. / One or more 3D printing questions, one per line."
                    },
                    "image": {
                        "title": "Photo de l'impression (optionnel) / Print photo (optional)",
                        "type": "string",
                        "description": "Téléversez une photo de votre impression, ou collez son adresse web. L'IA l'examine, nomme le défaut et donne les réglages à corriger. Sans question, un diagnostic complet est réalisé. Photo de moins de 3,5 Mo. / Upload a photo of your print, or paste its web address. The AI inspects it, names the defect and gives the settings to fix. With no question, a full diagnosis is returned. Keep it under 3.5 MB."
                    },
                    "imageContexte": {
                        "title": "Ce que vous observez (optionnel) / What you observe (optional)",
                        "type": "string",
                        "description": "Décrivez en une ou deux phrases ce que montre la photo, dans quelles conditions l'impression a été faite, ou ce que vous soupçonnez. L'IA s'en sert pour cibler sa réponse — et vous corrige si votre hypothèse ne correspond pas à la photo. / Briefly describe what the photo shows, the print conditions, or what you suspect. The AI uses it to focus its answer — and corrects you if your guess doesn't match the photo."
                    },
                    "langue": {
                        "title": "Langue de réponse / Answer language",
                        "enum": [
                            "auto",
                            "fr",
                            "en"
                        ],
                        "type": "string",
                        "description": "Langue des réponses. / Language of the answers.",
                        "default": "auto"
                    },
                    "niveau": {
                        "title": "Niveau / Level",
                        "enum": [
                            "debutant",
                            "intermediaire",
                            "avance"
                        ],
                        "type": "string",
                        "description": "Adapte le ton et la profondeur des réponses. / Adjusts tone and depth.",
                        "default": "intermediaire"
                    },
                    "technologie": {
                        "title": "Technologie / Technology",
                        "enum": [
                            "both",
                            "fdm",
                            "resine"
                        ],
                        "type": "string",
                        "description": "Cible la techno concernée. / Target technology.",
                        "default": "both"
                    }
                }
            },
            "runsResponseSchema": {
                "type": "object",
                "properties": {
                    "data": {
                        "type": "object",
                        "properties": {
                            "id": {
                                "type": "string"
                            },
                            "actId": {
                                "type": "string"
                            },
                            "userId": {
                                "type": "string"
                            },
                            "startedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "finishedAt": {
                                "type": "string",
                                "format": "date-time",
                                "example": "2025-01-08T00:00:00.000Z"
                            },
                            "status": {
                                "type": "string",
                                "example": "READY"
                            },
                            "meta": {
                                "type": "object",
                                "properties": {
                                    "origin": {
                                        "type": "string",
                                        "example": "API"
                                    },
                                    "userAgent": {
                                        "type": "string"
                                    }
                                }
                            },
                            "stats": {
                                "type": "object",
                                "properties": {
                                    "inputBodyLen": {
                                        "type": "integer",
                                        "example": 2000
                                    },
                                    "rebootCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "restartCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "resurrectCount": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "computeUnits": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "options": {
                                "type": "object",
                                "properties": {
                                    "build": {
                                        "type": "string",
                                        "example": "latest"
                                    },
                                    "timeoutSecs": {
                                        "type": "integer",
                                        "example": 300
                                    },
                                    "memoryMbytes": {
                                        "type": "integer",
                                        "example": 1024
                                    },
                                    "diskMbytes": {
                                        "type": "integer",
                                        "example": 2048
                                    }
                                }
                            },
                            "buildId": {
                                "type": "string"
                            },
                            "defaultKeyValueStoreId": {
                                "type": "string"
                            },
                            "defaultDatasetId": {
                                "type": "string"
                            },
                            "defaultRequestQueueId": {
                                "type": "string"
                            },
                            "buildNumber": {
                                "type": "string",
                                "example": "1.0.0"
                            },
                            "containerUrl": {
                                "type": "string"
                            },
                            "usage": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "integer",
                                        "example": 1
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            },
                            "usageTotalUsd": {
                                "type": "number",
                                "example": 0.00005
                            },
                            "usageUsd": {
                                "type": "object",
                                "properties": {
                                    "ACTOR_COMPUTE_UNITS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATASET_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "KEY_VALUE_STORE_WRITES": {
                                        "type": "number",
                                        "example": 0.00005
                                    },
                                    "KEY_VALUE_STORE_LISTS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_READS": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "REQUEST_QUEUE_WRITES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_INTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "DATA_TRANSFER_EXTERNAL_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                                        "type": "integer",
                                        "example": 0
                                    },
                                    "PROXY_SERPS": {
                                        "type": "integer",
                                        "example": 0
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```