# Gemini API (`free_style_coder/gemini-api`) Actor same As Gemini API with Low Cost - **URL**: https://apify.com/free\_style\_coder/gemini-api.md - **Developed by:** [Freestylecoder](https://apify.com/free_style_coder) (community) - **Categories:** AI, Agents, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.60 / actor start This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Gemini Scraper — Apify Actor Scrapes text responses from **Google Gemini** by replaying authenticated browser requests. Accepts a list of queries, sends each to Gemini, and saves the full AI-generated response to an Apify dataset. > ⚠️ This actor uses Gemini's **internal browser API**, not the official > Gemini REST API. Session cookies are hardcoded in the source and must be > refreshed in the code when they expire (~24 hours). --- ### Features - Send multiple queries in a single run - Only input required: a list of queries - Full response text extracted from Gemini's streaming protocol - Per-query error isolation — one failure does not stop the rest - Dataset output with structured fields: `query`, `response`, `error`, `scrapedAt` --- ### Input Only one field is required. | Field | Type | Required | Description | |-----------|------------|----------|----------------------------------| | `queries` | `string[]` | ✅ | One or more queries to send to Gemini | #### Example Input JSON ```json { "queries": [ "best smartphones 2026", "python vs javascript for web development", "how does quantum computing work" ] } ```` *** ### Output Each query produces one record in the default dataset. #### Success Record ```json { "query": "best smartphones 2026", "response": "The top smartphones in 2026 include...", "error": null, "scrapedAt": "2026-06-19T10:30:00.000Z" } ``` #### Failure Record ```json { "query": "best smartphones 2026", "response": null, "error": "HTTPError: 403 Forbidden", "scrapedAt": "2026-06-19T10:30:00.000Z" } ``` *** ### When Cookies Expire All session values (cookies, headers, params) are hardcoded at the top of `src/main.py` under `COOKIES`, `HEADERS`, `PARAMS`, and `SESSION_ID`. When requests start returning `401` or `403`, refresh the values: #### Step-by-step 1. Open in **Chrome** while signed in. 2. Press `F12` → **Network** tab. 3. Send any message in Gemini. 4. Filter by `StreamGenerate` → click the request. 5. Go to **Headers** → **Request Headers** → copy the `Cookie` header. 6. Extract `__Secure-STRP`, `NID`, and `COMPASS` values. 7. Update `COOKIES` in `src/main.py`. 8. From the same request's **Query String Parameters**, copy `bl` and `f.sid`. 9. Update `PARAMS` in `src/main.py`. 10. Redeploy the actor. *** ### Project Structure ``` gemini-actor/ ├── src/ │ └── main.py # Core actor logic + hardcoded session values ├── .actor/ │ ├── actor.json # Apify actor manifest │ └── INPUT_SCHEMA.json # Input schema (queries only) ├── output_schema.json # Dataset view columns ├── dataset_schema.json # Per-record field types ├── requirements.txt # Python dependencies ├── Dockerfile # Container build ├── Agent.md # Internal developer/agent guide ├── claude.md # AI assistant context file └── README.md # This file ``` *** ### Local Development ```bash ## Install dependencies pip install apify requests ## Run locally (requires Apify CLI) apify run ``` *** ### Dependencies ``` apify>=2.0.0 requests>=2.31.0 ``` *** ### Limitations - Session cookies expire in ~24 hours and require a manual code update + redeploy - Subject to Gemini's internal rate limits - Response format may break if Google updates the `StreamGenerate` protocol - Not suitable for high-volume production use without cookie rotation *** ### License MIT # Actor input Schema ## `queries` (type: `array`): List of search queries to send to Gemini. ## Actor input object example ```json { "queries": [ "iphone 17" ] } ``` # Actor output Schema ## `results` (type: `string`): The default dataset containing crawled Gemini outputs. # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "queries": [ "iphone 17" ] }; // Run the Actor and wait for it to finish const run = await client.actor("free_style_coder/gemini-api").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "queries": ["iphone 17"] } # Run the Actor and wait for it to finish run = client.actor("free_style_coder/gemini-api").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 '{ "queries": [ "iphone 17" ] }' | apify call free_style_coder/gemini-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=free_style_coder/gemini-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Gemini API", "description": "same As Gemini API with Low Cost", "version": "0.0", "x-build-id": "CEUa54W0TUSn1177G" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/free_style_coder~gemini-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-free_style_coder-gemini-api", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/free_style_coder~gemini-api/runs": { "post": { "operationId": "runs-sync-free_style_coder-gemini-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/free_style_coder~gemini-api/run-sync": { "post": { "operationId": "run-sync-free_style_coder-gemini-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "queries" ], "properties": { "queries": { "title": "Queries", "type": "array", "description": "List of search queries to send to Gemini.", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```