This workflow follows the Chat Trigger → HTTP Request recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"name": "Movie Recommendation Bot",
"nodes": [
{
"parameters": {
"url": "https://api.themoviedb.org/3/discover/movie",
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "with_genres",
"value": "={{ $json.output[0].content[0].text.discover_params.with_genres }}"
},
{
"name": "with_original_language",
"value": "={{ $json.output[0].content[0].text.discover_params.with_original_language }}"
},
{
"name": "region",
"value": "={{ $json.output[0].content[0].text.discover_params.region }}"
},
{
"name": "language",
"value": "={{ $json.output[0].content[0].text.discover_params.language }}"
},
{
"name": "include_adult",
"value": "={{ $json.output[0].content[0].text.discover_params.include_adult }}"
},
{
"name": "sort_by",
"value": "={{ $json.output[0].content[0].text.discover_params.sort_by }}"
},
{
"name": "vote_average.gte",
"value": "={{ $json.output[0].content[0].text.discover_params.vote_average_gte }}"
},
{
"name": "vote_count.gte",
"value": "={{ $json.output[0].content[0].text.discover_params.vote_count_gte }}"
},
{
"name": "primary_release_date.gte",
"value": "={{ $json.output[0].content[0].text.discover_params.primary_release_date_gte }}"
},
{
"name": "primary_release_date.lte",
"value": "={{ $json.output[0].content[0].text.discover_params.primary_release_date_lte }}"
}
]
},
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer YOUR_TMDB_API_KEY"
}
]
},
"options": {
"timeout": 10000
}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.4,
"position": [
336,
-16
],
"id": "e4cc3c5f-e944-4772-80fc-1d67661649a1",
"name": "HTTP Request"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "6ee17d62-4a19-4403-a6e8-c4a701190cbb",
"name": "details_params",
"value": "={{ $('Message a model').item.json.output[0].content[0].text.details_params }}",
"type": "object"
}
]
},
"includeOtherFields": true,
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
544,
-16
],
"id": "adb8b3fc-22e6-4b67-bb20-9dfdeb489354",
"name": "Edit Fields"
},
{
"parameters": {
"fieldToSplitOut": "results",
"options": {}
},
"type": "n8n-nodes-base.splitOut",
"typeVersion": 1,
"position": [
752,
-16
],
"id": "e70f34d7-3998-4e26-896a-1fbacb33cf22",
"name": "Split Out"
},
{
"parameters": {
"url": "=https://api.themoviedb.org/3/movie/{{ $json.id }}",
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "language",
"value": "={{ $('Edit Fields').item.json.details_params.language }}"
},
{
"name": "append_to_response",
"value": "={{ $('Edit Fields').item.json.details_params.append_to_response }}"
}
]
},
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer YOUR_TMDB_API_KEY"
}
]
},
"options": {
"timeout": 10000
}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.4,
"position": [
960,
-16
],
"id": "b21f688d-71ec-4501-85a4-73bfe0e2b3e6",
"name": "HTTP Request1"
},
{
"parameters": {
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.4,
"position": [
-224,
-16
],
"id": "c5c9eacc-462a-4458-8aa0-3510afa5a850",
"name": "When chat message received"
},
{
"parameters": {
"modelId": {
"__rl": true,
"value": "models/gemini-2.5-flash",
"mode": "list",
"cachedResultName": "models/gemini-2.5-flash"
},
"messages": {
"values": [
{
"content": "=You will receive multiple movie objects.\n\ntitle: {{ $json.original_title }}\nreviews: {{ $json.reviews }}\ngenres: {{ $json.genres }}\nrelease date: {{ $json.release_date }}\nruntime: {{ $json.runtime }}\ncast and crews: {{ $json.credits }}\noverview: {{ $json.overview }}\nlang: {{ $json.spoken_languages }}\n\nFor each movie, display:\n\n\ud83c\udfac Movie Title (Year)\n\n\u2b50 X/10 | \ud83c\udfad Genre 1, Genre 2\n\ud83d\udcc5 Release Date | \u23f1\ufe0f Runtime min\n\ud83c\udf10 Language | \ud83d\udd1e Certification\n\n\ud83c\udf1f Cast: Actor 1, Actor 2, Actor 3\n\n\ud83d\udcdd One concise sentence describing the story.\n\n\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\n\nKeep each movie under 10 lines.\nPrioritize readability and avoid long descriptions.\n\nrules:\nShow only the fields above.\nUse only the top 3 cast members.\nKeep the story summary to a maximum of 2 lines.\nDo not mention missing fields.\nMake the output visually appealing and easy to scan.\nUse emojis consistently.\nSeparate movies with a divider line."
}
]
},
"builtInTools": {},
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.googleGemini",
"typeVersion": 1.2,
"position": [
1168,
-16
],
"id": "b37bd457-2c5a-4edf-9a96-db5b88c294bf",
"name": "Message a model2",
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"modelId": {
"__rl": true,
"value": "gpt-4.1",
"mode": "list",
"cachedResultName": "GPT-4.1"
},
"responses": {
"values": [
{
"content": "=You are a parameter builder for The Movie Database (TMDB) API.\n\nYour job is to take a natural language user query about movie recommendations and output two sets of parameters:\n\n1) discover_params: query parameters for GET https://api.themoviedb.org/3/discover/movie\n2) details_params: query parameters for GET https://api.themoviedb.org/3/movie/{movie_id}\n\nUser query: {{ $json.chatInput }}\n\nYou MUST reply with valid JSON only, with this structure:\n\n{\n \"discover_params\": {\n \"with_genres\": \"string or null\",\n \"with_original_language\": \"string or null\",\n \"region\": \"string or null\",\n \"language\": \"string\", \n \"include_adult\": boolean,\n \"sort_by\": \"string\",\n \"vote_average_gte\": number or null,\n \"vote_count_gte\": number or null,\n \"primary_release_date_gte\": \"YYYY-MM-DD or null\",\n \"primary_release_date_lte\": \"YYYY-MM-DD or null\",\n \"page\": number\n },\n \"details_params\": {\n \"language\": \"string\",\n \"append_to_response\": \"comma-separated list of sections\"\n }\n}\n\nRules:\n\n- Never include an API key. The API key will be added separately in n8n.\n- Do NOT output URLs, only parameter values.\n- For all text queries from the user, assume:\n - They want multiple recommendations, not just one movie.\n - They want details: cast, crew, videos, reviews, release dates/certifications, keywords, recommendations.\n\nMappings:\n\nGENRES (TMDB movie genre IDs):\n- Action -> 28\n- Adventure -> 12\n- Animation -> 16\n- Comedy -> 35\n- Crime -> 80\n- Documentary -> 99\n- Drama -> 18\n- Family -> 10751\n- Fantasy -> 14\n- History -> 36\n- Horror -> 27\n- Music -> 10402\n- Mystery -> 9648\n- Romance -> 10749\n- Science Fiction -> 878\n- TV Movie -> 10770\n- Thriller -> 53\n- War -> 10752\n- Western -> 37\n\nLANGUAGES (ISO 639-1 examples):\n- \"hindi\", \"bollywood\" -> \"hi\"\n- \"english\" -> \"en\"\n- \"tamil\" -> \"ta\"\n- \"telugu\" -> \"te\"\n- \"malayalam\" -> \"ml\"\n- \"kannada\" -> \"kn\"\n- \"marathi\" -> \"mr\"\n- \"bengali\" -> \"bn\"\n\nRegions (ISO 3166-1 examples):\n- For Indian users, default region \"IN\" if user language is an Indian language or they mention India.\n- For English without region hints, leave region as null.\n\nRatings / age preferences:\n- If the user mentions things like \"family\", \"kids\", \"children\", \"no adult\", prefer more family-friendly by:\n - include_adult: false\n - vote_average_gte: 6.0\n- If the user mentions \"adult\", \"18+\", \"A rated\", set:\n - include_adult: true\n- If the user explicitly says \"highly rated\", \"top rated\", \"best\", set:\n - vote_average_gte: 7.0\n - vote_count_gte: 1000\n\nDates:\n- If the user says \"recent\", \"latest\", \"new\", \"from last few years\":\n - Set primary_release_date_gte to 5 years ago from today (approximate).\n- If no date constraint is mentioned:\n - Set primary_release_date_gte and primary_release_date_lte to null.\n\nSorting:\n- If the user says \"top rated\", \"best rated\":\n - sort_by: \"vote_average.desc\"\n- If the user says \"popular\", \"trending\", or does not specify:\n - sort_by: \"popularity.desc\"\n\nPages:\n- Always set page to 1.\n\nLanguages in details:\n- For discover_params.language and details_params.language:\n - If the user specifies a language like \"Hindi\", use \"<code>-IN\" when possible, for example:\n - Hindi -> \"hi-IN\"\n - English -> \"en-US\"\n - If uncertain, use \"en-US\".\n\nAppend to response:\n- details_params.append_to_response MUST include:\n - \"credits\" (for cast & crew)\n - \"videos\" (for trailers/teasers)\n - \"reviews\" (user reviews)\n - \"release_dates\" (for certifications / age ratings)\n - \"keywords\" (tags/keywords)\n - \"recommendations\" (similar movies)\n\nHandle vague queries:\n- If the user does not mention a genre, set with_genres to null.\n- If the user does not mention a language, set with_original_language to null.\n\nExamples:\n\nUser: \"recommend comedy hindi movies\"\nOutput:\n{\n \"discover_params\": {\n \"with_genres\": \"35\",\n \"with_original_language\": \"hi\",\n \"region\": \"IN\",\n \"language\": \"hi-IN\",\n \"include_adult\": false,\n \"sort_by\": \"popularity.desc\",\n \"vote_average_gte\": null,\n \"vote_count_gte\": null,\n \"primary_release_date_gte\": null,\n \"primary_release_date_lte\": null,\n \"page\": 1\n },\n \"details_params\": {\n \"language\": \"hi-IN\",\n \"append_to_response\": \"credits,videos,reviews,release_dates,keywords,recommendations\"\n }\n}\n\nReturn only the JSON object, no explanations. "
}
]
},
"builtInTools": {},
"options": {
"textFormat": {
"textOptions": {
"type": "json_schema",
"schema": "{\n \"type\": \"object\",\n \"properties\": {\n \"discover_params\": {\n \"type\": \"object\",\n \"properties\": {\n \"with_genres\": {\n \"type\": [\"string\", \"null\"]\n },\n \"with_original_language\": {\n \"type\": [\"string\", \"null\"]\n },\n \"region\": {\n \"type\": [\"string\", \"null\"]\n },\n \"language\": {\n \"type\": \"string\"\n },\n \"include_adult\": {\n \"type\": \"boolean\"\n },\n \"sort_by\": {\n \"type\": \"string\"\n },\n \"vote_average_gte\": {\n \"type\": [\"number\", \"null\"]\n },\n \"vote_count_gte\": {\n \"type\": [\"number\", \"null\"]\n },\n \"primary_release_date_gte\": {\n \"type\": [\"string\", \"null\"]\n },\n \"primary_release_date_lte\": {\n \"type\": [\"string\", \"null\"]\n },\n \"page\": {\n \"type\": \"integer\"\n }\n },\n \"required\": [\n \"with_genres\",\n \"with_original_language\",\n \"region\",\n \"language\",\n \"include_adult\",\n \"sort_by\",\n \"vote_average_gte\",\n \"vote_count_gte\",\n \"primary_release_date_gte\",\n \"primary_release_date_lte\",\n \"page\"\n ],\n \"additionalProperties\": false\n },\n \"details_params\": {\n \"type\": \"object\",\n \"properties\": {\n \"language\": {\n \"type\": \"string\"\n },\n \"append_to_response\": {\n \"type\": \"string\"\n }\n },\n \"required\": [\"language\", \"append_to_response\"],\n \"additionalProperties\": false\n }\n },\n \"required\": [\"discover_params\", \"details_params\"],\n \"additionalProperties\": false\n}",
"strict": true
}
}
}
},
"type": "@n8n/n8n-nodes-langchain.openAi",
"typeVersion": 2.3,
"position": [
-16,
-16
],
"id": "4f5d9f62-2b3c-4c8e-9b61-0772830ae499",
"name": "Message a model",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"content": "Movie Recommendation TMDB API\n----\n\nYOUR_TMDB_API_KEY\n\n\nrequest send to:\n-----\nhttps://api.themoviedb.org/3/discover/movie\n\n\n----\nprompt\n-----\n\nYou are a parameter builder for The Movie Database (TMDB) API.\n\nYour job is to take a natural language user query about movie recommendations and output two sets of parameters:\n\n1) discover_params: query parameters for GET https://api.themoviedb.org/3/discover/movie\n2) details_params: query parameters for GET https://api.themoviedb.org/3/movie/{movie_id}\n\nYou MUST reply with valid JSON only, with this structure:\n\n{\n \"discover_params\": {\n \"with_genres\": \"string or null\",\n \"with_original_language\": \"string or null\",\n \"region\": \"string or null\",\n \"language\": \"string\", \n \"include_adult\": boolean,\n \"sort_by\": \"string\",\n \"vote_average_gte\": number or null,\n \"vote_count_gte\": number or null,\n \"primary_release_date_gte\": \"YYYY-MM-DD or null\",\n \"primary_release_date_lte\": \"YYYY-MM-DD or null\",\n \"page\": number\n },\n \"details_params\": {\n \"language\": \"string\",\n \"append_to_response\": \"comma-separated list of sections\"\n }\n}\n\nRules:\n\n- Never include an API key. The API key will be added separately in n8n.\n- Do NOT output URLs, only parameter values.\n- For all text queries from the user, assume:\n - They want multiple recommendations, not just one movie.\n - They want details: cast, crew, videos, reviews, release dates/certifications, keywords, recommendations.\n\nMappings:\n\nGENRES (TMDB movie genre IDs):\n- Action -> 28\n- Adventure -> 12\n- Animation -> 16\n- Comedy -> 35\n- Crime -> 80\n- Documentary -> 99\n- Drama -> 18\n- Family -> 10751\n- Fantasy -> 14\n- History -> 36\n- Horror -> 27\n- Music -> 10402\n- Mystery -> 9648\n- Romance -> 10749\n- Science Fiction -> 878\n- TV Movie -> 10770\n- Thriller -> 53\n- War -> 10752\n- Western -> 37\n\nLANGUAGES (ISO 639-1 examples):\n- \"hindi\", \"bollywood\" -> \"hi\"\n- \"english\" -> \"en\"\n- \"tamil\" -> \"ta\"\n- \"telugu\" -> \"te\"\n- \"malayalam\" -> \"ml\"\n- \"kannada\" -> \"kn\"\n- \"marathi\" -> \"mr\"\n- \"bengali\" -> \"bn\"\n\nRegions (ISO 3166-1 examples):\n- For Indian users, default region \"IN\" if user language is an Indian language or they mention India.\n- For English without region hints, leave region as null.\n\nRatings / age preferences:\n- If the user mentions things like \"family\", \"kids\", \"children\", \"no adult\", prefer more family-friendly by:\n - include_adult: false\n - vote_average_gte: 6.0\n- If the user mentions \"adult\", \"18+\", \"A rated\", set:\n - include_adult: true\n- If the user explicitly says \"highly rated\", \"top rated\", \"best\", set:\n - vote_average_gte: 7.0\n - vote_count_gte: 1000\n\nDates:\n- If the user says \"recent\", \"latest\", \"new\", \"from last few years\":\n - Set primary_release_date_gte to 5 years ago from today (approximate).\n- If no date constraint is mentioned:\n - Set primary_release_date_gte and primary_release_date_lte to null.\n\nSorting:\n- If the user says \"top rated\", \"best rated\":\n - sort_by: \"vote_average.desc\"\n- If the user says \"popular\", \"trending\", or does not specify:\n - sort_by: \"popularity.desc\"\n\nPages:\n- Always set page to 1.\n\nLanguages in details:\n- For discover_params.language and details_params.language:\n - If the user specifies a language like \"Hindi\", use \"<code>-IN\" when possible, for example:\n - Hindi -> \"hi-IN\"\n - English -> \"en-US\"\n - If uncertain, use \"en-US\".\n\nAppend to response:\n- details_params.append_to_response MUST include:\n - \"credits\" (for cast & crew)\n - \"videos\" (for trailers/teasers)\n - \"reviews\" (user reviews)\n - \"release_dates\" (for certifications / age ratings)\n - \"keywords\" (tags/keywords)\n - \"recommendations\" (similar movies)\n\nHandle vague queries:\n- If the user does not mention a genre, set with_genres to null.\n- If the user does not mention a language, set with_original_language to null.\n\nExamples:\n\nUser: \"recommend comedy hindi movies\"\nOutput:\n{\n \"discover_params\": {\n \"with_genres\": \"35\",\n \"with_original_language\": \"hi\",\n \"region\": \"IN\",\n \"language\": \"hi-IN\",\n \"include_adult\": false,\n \"sort_by\": \"popularity.desc\",\n \"vote_average_gte\": null,\n \"vote_count_gte\": null,\n \"primary_release_date_gte\": null,\n \"primary_release_date_lte\": null,\n \"page\": 1\n },\n \"details_params\": {\n \"language\": \"hi-IN\",\n \"append_to_response\": \"credits,videos,reviews,release_dates,keywords,recommendations\"\n }\n}\n\nReturn only the JSON object, no explanations.\n\n\n\n\n-----\njson output sample\n----\n\n{\n \"discover_params\": {\n \"with_genres\": \"27\",\n \"with_original_language\": \"hi\",\n \"region\": \"IN\",\n \"language\": \"hi-IN\",\n \"include_adult\": false,\n \"sort_by\": \"popularity.desc\",\n \"vote_average_gte\": null,\n \"vote_count_gte\": null,\n \"primary_release_date_gte\": null,\n \"primary_release_date_lte\": null,\n \"page\": 1\n },\n \"details_params\": {\n \"language\": \"hi-IN\",\n \"append_to_response\": \"credits,videos,reviews,release_dates,keywords,recommendations\"\n }\n}\n\n\n\n---\n\noutput schema\n----\n\n{\n \"type\": \"object\",\n \"properties\": {\n \"discover_params\": {\n \"type\": \"object\",\n \"properties\": {\n \"with_genres\": {\n \"type\": [\"string\", \"null\"]\n },\n \"with_original_language\": {\n \"type\": [\"string\", \"null\"]\n },\n \"region\": {\n \"type\": [\"string\", \"null\"]\n },\n \"language\": {\n \"type\": \"string\"\n },\n \"include_adult\": {\n \"type\": \"boolean\"\n },\n \"sort_by\": {\n \"type\": \"string\"\n },\n \"vote_average_gte\": {\n \"type\": [\"number\", \"null\"]\n },\n \"vote_count_gte\": {\n \"type\": [\"number\", \"null\"]\n },\n \"primary_release_date_gte\": {\n \"type\": [\"string\", \"null\"]\n },\n \"primary_release_date_lte\": {\n \"type\": [\"string\", \"null\"]\n },\n \"page\": {\n \"type\": \"integer\"\n }\n },\n \"required\": [\n \"with_genres\",\n \"with_original_language\",\n \"region\",\n \"language\",\n \"include_adult\",\n \"sort_by\",\n \"vote_average_gte\",\n \"vote_count_gte\",\n \"primary_release_date_gte\",\n \"primary_release_date_lte\",\n \"page\"\n ],\n \"additionalProperties\": false\n },\n \"details_params\": {\n \"type\": \"object\",\n \"properties\": {\n \"language\": {\n \"type\": \"string\"\n },\n \"append_to_response\": {\n \"type\": \"string\"\n }\n },\n \"required\": [\"language\", \"append_to_response\"],\n \"additionalProperties\": false\n }\n },\n \"required\": [\"discover_params\", \"details_params\"],\n \"additionalProperties\": false\n}",
"height": 272,
"width": 416,
"color": 5
},
"type": "n8n-nodes-base.stickyNote",
"position": [
-240,
208
],
"typeVersion": 1,
"id": "ad336667-3726-4502-875a-8242ff20fb29",
"name": "Sticky Note"
}
],
"connections": {
"HTTP Request": {
"main": [
[
{
"node": "Edit Fields",
"type": "main",
"index": 0
}
]
]
},
"Edit Fields": {
"main": [
[
{
"node": "Split Out",
"type": "main",
"index": 0
}
]
]
},
"Split Out": {
"main": [
[
{
"node": "HTTP Request1",
"type": "main",
"index": 0
}
]
]
},
"HTTP Request1": {
"main": [
[
{
"node": "Message a model2",
"type": "main",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "Message a model",
"type": "main",
"index": 0
}
]
]
},
"Message a model": {
"main": [
[
{
"node": "HTTP Request",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1",
"binaryMode": "separate",
"availableInMCP": false
},
"staticData": null,
"triggerCount": 0,
"meta": {
"templateCredsSetupCompleted": true
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googlePalmApiopenAiApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
Movie Recommendation Bot. Uses httpRequest, chatTrigger, googleGemini, openAi. Chat trigger; 8 nodes.
Source: https://github.com/DuttPanchal04/n8n-ai-automation-portfolio/blob/main/movie-recommendation-bot/movie-recommendation-bot-workflow.json — original creator credit. Request a take-down →
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