@dailyprayershub: prayer for hard times #prayer #faith #jesus

God only son

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Friday 31 July 2026 07:10:18 GMT

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Im the one and only 🐐 💙🩵🩷 :

i love god

2026-07-31 10:47:04

2

self love ❤️ 🥰💋💓💖 :

amen

2026-07-31 07:13:27

4

Heidisaunders :

amen amen amen amen amen amen amen amen amen amen amen 🙏 Jesus

2026-07-31 07:27:35

4

Munni :

love,you,god,amean🙏🙏🙏🙏

2026-07-31 11:45:23

4

Felicity Malgas :

Amen and Jesus Christ 🙏🙏

2026-07-31 17:02:49

2

mariama s :

amen and amen

2026-08-01 20:19:46

2

James Hardin :

thank you Lord amen

2026-08-17 17:27:35

0

Gabriel Psalm Magpale :

amen and amen 🙏 🙏 ❤️❤️♥️

2026-07-31 13:40:23

1

Decontee Nebo :

Amen 🙏

2026-07-31 12:13:24

1

Igwe :

Amen 🙌🙏

2026-07-31 09:03:32

1

Vida ❣️❣️💓💓💓 :

Amen lord🙏🙏🙏💖

2026-08-15 21:48:29

0

Paula Williams :

Amen

2026-08-28 21:33:47

0

@James Banda :

Amen

2026-07-31 17:08:31

1

tyrine Irine :

amen

2026-07-31 07:12:10

0

Gabriel Psalm Magpale :

amen and amen 🙏 🙌 👏 ❤️♥️☺️

2026-07-31 13:39:58

1

rinny kayz :

Amen 🙏 🙏

2026-08-01 05:41:53

1

Annita :

AMEN

2026-08-17 06:44:32

0

user98397935676637@feic😍😍 :

Amen

2026-08-15 13:39:32

0

Aisha Bae🌹 :

thank you Jesus amen

2026-08-14 11:42:37

0

pinnie :

Amen

2026-08-13 01:05:02

0

hard called :

Amen

2026-08-12 21:55:16

0

Edwin Fru :

Amen

2026-08-09 10:49:58

0

lansana marah :

amen

2026-08-07 20:26:19

0

Lubega Godfrey :

amen

2026-08-07 18:33:53

0

Scooby @1990 :

amen

2026-07-31 07:13:43

0

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🚨BOCOR!! HARGA TIKET UDAH BISA LIHAT DAN MURAH 🚨!! SEJARAH BARU TERCIPTA INDONESIA 🇮🇩!! BUKAN CUMAN MAINAN, MEREMA HIDUP BENERAN 😱. Kalian yang ngaku otomotif atau punya nyali besar WAJIB BACA INI SAMPAI HABIS !!👇 IT'S OFFICIAL 🔥, UNTUK PERTAMA KALINYA DALAM SEJARAH! HOT WHEELS MONSTER TRUCK LIVE jadi tontonan paling gila sedunia yang akhirnya akan ada di jakarta, Indonesia 🇮🇩!! Bayangin aja, di ecast 1:64 kesayangan kali yang berubah menjadi RAKSASA SKALA 1:1 di depan mata 😱! Mereka siap hancurin mobil - mobil sampai remuk, menyala dalam gelapd dengan efek neon super keren dan NYEMBURIN APA ASLI 🔥🔥🔥 📆 catat tanggal main nya sebelum nyesel seumur hidup : 28-29 November 2026 ⚠️TAPI TUNGGU DULU⚠️ Detail lengkap dan rahasia tiket akan di bongkar tanggal 18 Agustus ini!! Jangan sampai nangis karena kalah war tiket nanti !! @onestepforward.id #cphwmtl #onestepforward #hwmtindonesia #hwmtglownfire #hotwheelsmonstertruckslive

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How To Build AI Agent From Scratch. To build an AI agent from scratch, create a core Observe-Think-Act loop. Connect a large language model as the

Step 2: Write the Agent Code Create a file named and add the following code. This script sets up a calculator tool and hands it to the Gemini model. import os from google import genai from google.genai import types # 1. Define a tool (a standard Python function) def add_numbers(a: float, b: float) -> float: """Adds two numbers together and returns the result.""" return a + b # 2. Initialize the client (Make sure GEMINI_API_KEY is set in your environment variables) client = genai.Client() # 3. Define the agent's personality and tools system_instruction = "You are a helpful assistant. Use your tools whenever a math question is asked." my_tools = [add_numbers] # 4. Start a chat session with the agent chat = client.chats.create( model="gemini-2.5-flash", config=types.GenerateContentConfig( system_instruction=system_instruction, tools=my_tools, temperature=0.0 # Low temperature keeps the agent logical and stable ) ) # 5. Test the agent loop user_message = "Hey! Can you add 143.5 and 256.2 for me?" print(f"User: {user_message}") # The SDK automatically handles the "Observe-Think-Act" loop under the hood! # It sends the prompt, sees that the model wants to use 'add_numbers', # executes the Python function local to your machine, sends the result back to Gemini, # and returns the final human-readable answer. response = chat.send_message(user_message) print(f"Agent: {response.text}") #buildai #sidehustle #python " width="135" height="240">
How To Build AI Agent From Scratch. To build an AI agent from scratch, create a core Observe-Think-Act loop. Connect a large language model as the "brain" for reasoning, provide a system prompt to define its role and constraints, attach short-term/long-term memory, and code external functions or APIs as "tools" for execution. Core Components of an AI Agent The Brain (LLM): Handles intent parsing, multi-step planning, and decision-making. The Brain Stem (System Prompt): Sets the persona, boundaries, and rules for how the agent behaves and when to use specific tools. Memory: Maintains short-term conversational context and long-term data storage or preference logs. Tools: Grants functional capability via custom scripts, APIs, or protocols like Model Context Protocol (MCP) to interact with databases, web search, or email. Step-by-Step Implementation Guide Map the Process: Write down the exact steps of the workflow you want to automate, prioritizing a low-precision, time-intensive task where 90% accuracy is acceptable. Build the Deterministic Loop: Set up a basic programmatic loop (such as a while loop in Python or Node.js) to continuously read user or system input, process it, and wait for the next command. Integrate the Model: Connect your loop to a hosted LLM API (like OpenAI or Google Gemini) or a local model runtime (like Ollama). Define and Bind Tools: Write standard functions (e.g., a calculator, a weather fetcher, or a database query) and format them so the LLM can output a structured tool call when it needs external data. Add Guardrails and Iteration: Implement validation steps, error handling for failed tool executions, and a human-in-the-loop escalation path for critical errors. If you prefer building using pre-existing architectures rather than raw code, many developers recommend frameworks and visual orchestration tools mentioned by the community on platforms like Reddit: ◇ For Python Developers: CrewAI, LangGraph, or LlamaIndex. ◇ For Low-Code/Visual Builders: n8n or Flowise. TO USE PYTHON To build an AI agent from scratch using pure Python, you write code that connects an LLM to a loop. The LLM decides what to do, and your Python code executes those actions. Here is a complete, minimal guide to building a functional agent using the official Google GenAI SDK. Step 1: Install the Required Library First, open your terminal and install the official Google GenAI package. bash Step 2: Write the Agent Code Create a file named and add the following code. This script sets up a calculator tool and hands it to the Gemini model. import os from google import genai from google.genai import types # 1. Define a tool (a standard Python function) def add_numbers(a: float, b: float) -> float: """Adds two numbers together and returns the result.""" return a + b # 2. Initialize the client (Make sure GEMINI_API_KEY is set in your environment variables) client = genai.Client() # 3. Define the agent's personality and tools system_instruction = "You are a helpful assistant. Use your tools whenever a math question is asked." my_tools = [add_numbers] # 4. Start a chat session with the agent chat = client.chats.create( model="gemini-2.5-flash", config=types.GenerateContentConfig( system_instruction=system_instruction, tools=my_tools, temperature=0.0 # Low temperature keeps the agent logical and stable ) ) # 5. Test the agent loop user_message = "Hey! Can you add 143.5 and 256.2 for me?" print(f"User: {user_message}") # The SDK automatically handles the "Observe-Think-Act" loop under the hood! # It sends the prompt, sees that the model wants to use 'add_numbers', # executes the Python function local to your machine, sends the result back to Gemini, # and returns the final human-readable answer. response = chat.send_message(user_message) print(f"Agent: {response.text}") #buildai #sidehustle #python

nehejtujte ma je to joke chcem si užívať zivot ahojtecaute

nehejtujte ma je to joke chcem si užívať zivot ahojtecaute

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