Gemini excels at text generation with RAG for large datasets, but smaller ones benefit from prompting or data upload. This report explores using Gemini 1.5 Flash/Pro with RAG on medium-sized, Google Spreadsheet-stored datasets for improved accuracy and effectiveness.
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You are Manus, an AI agent created by the Manus team. | |
You excel at the following tasks: | |
1. Information gathering, fact-checking, and documentation | |
2. Data processing, analysis, and visualization | |
3. Writing multi-chapter articles and in-depth research reports | |
4. Creating websites, applications, and tools | |
5. Using programming to solve various problems beyond development | |
6. Various tasks that can be accomplished using computers and the internet |
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from transformers import ( | |
AutoConfig, | |
AutoTokenizer, | |
BitsAndBytesConfig, | |
GenerationConfig, | |
AutoModelForCausalLM, | |
LlamaTokenizerFast, | |
PreTrainedModel, | |
TextIteratorStreamer, | |
StoppingCriteria, |
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import groovy.json.JsonSlurper | |
import groovy.json.JsonParserType | |
import org.sonatype.nexus.repository.storage.Asset | |
import org.sonatype.nexus.repository.storage.Query | |
import org.sonatype.nexus.repository.storage.StorageFacet | |
import java.util.concurrent.ExecutorService | |
import java.util.concurrent.Executors | |
CONDA_CLOUD_BASE_URL = "https://conda.anaconda.org" | |
NEXUS_REPOSITORY = "http://127.0.0.1:8081/repository/conda" |
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############ If you are using DOCKER all-in-one image, create Dockerfile like: ################ | |
############ FROM openproject/openproject:16 ################ | |
############ COPY ./enterprise_token.rb app/models/enterprise_token.rb ################ | |
############ If you are runing a manual installation: ################ | |
############ REPLACE app/models/enterprise_token.rb in the source code with this file! ################ | |
############ also be sure to RESTART OpenProject after replacing the file. ################ | |
############ If using some other set up (eg docker-compose), read the comments on ################ | |
############ https://gist.github.com/markasoftware/f5b2e55a2c2e3abb1f9eefcdf0bfff45 ################ |
Today I tried to setup a small Kubernetes cluster on top of 3 Raspberry Pi 4 (4GB Memory). Here is the steps to install the cluster.
I have 3 Raspberry Pi 4 stacked with PoE headers and connected to a PoE switch at home. The are connected to Internet through a home router. All Pis are equipped with a 64GB Samsung SDXC card flushed with Ubuntu 20.04 image.
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################################################### | |
## | |
## Alertmanager YAML configuration for routing. | |
## | |
## Will route alerts with a code_owner label to the slack-code-owners receiver | |
## configured above, but will continue processing them to send to both a | |
## central Slack channel (slack-monitoring) and PagerDuty receivers | |
## (pd-warning and pd-critical) | |
## |
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<?php | |
namespace App\Models; | |
use Illuminate\Database\Eloquent\Model; | |
class City extends Model | |
{ | |
/** | |
* @var array |
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const axios = require("axios"); | |
const urls = ['https://github.com/mzabriskie/axios', 'https://discord.js.org']; | |
async function asyncLoadAllTheChunks() { | |
const resps = await Promise.all(urls.map(url=> axios.get(url))) | |
const [first, second] = resps; | |
console.log(` | |
тут первый ${first} | |
тут второй ${second} |
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// ... | |
"scripts": { | |
"build": "neo build --config webpack.prod.js", | |
"start": "neo start --port 3001 --config webpack.dev.js", | |
// ... | |
} | |
// ... |
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