Инициализировать базовый каркас MVP с чат-агентом на Agno и Ollama.

Добавить входную точку CLI, конфигурацию через .env и базовую документацию для быстрого локального запуска.

.env.example

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+OLLAMA_MODEL_ID=gemma4:31b
+OLLAMA_HOST=http://localhost:11435
+OLLAMA_TEMPERATURE=0
+AGENT_MARKDOWN=false
+AGENT_DEBUG_MODE=true
+AGENT_INSTRUCTIONS=You are a helpful assistant. Answer briefly and clearly.

.gitignore

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+# Python cache and bytecode
+__pycache__/
+*.py[cod]
+*$py.class
+
+# Virtual environments
+.venv/
+venv/
+
+# Environment files
+.env
+
+# Build and packaging
+build/
+dist/
+*.egg-info/
+
+# Test and tool caches
+.pytest_cache/
+.mypy_cache/
+.ruff_cache/
+
+# IDE and OS files
+.idea/
+.vscode/
+.DS_Store
+.cursor

README.md

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+# Prisma Platform MVP
+
+Minimal chat agent on Agno + Ollama.
+
+## Current structure
+
+```text
+prisma_platform/
+├── .env
+├── .env.example
+├── requirements.txt
+└── src/
+    ├── __init__.py
+    ├── agent_runner.py
+    └── main.py
+```
+
+## Setup
+
+```bash
+python -m venv .venv
+source .venv/bin/activate
+pip install -r requirements.txt
+cp .env.example .env
+```
+
+## Run
+
+Interactive chat mode:
+
+```bash
+python -m src.main
+```
+
+Single message mode:
+
+```bash
+python -m src.main --message "Привет, что ты умеешь?"
+```
+

requirements.txt

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+agno
+python-dotenv
+ollama
+socksio
+openai

src/__init__.py

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+# Base package for agent entrypoint.

src/agent_runner.py

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+import os
+
+from agno.agent import Agent
+from agno.models.ollama import Ollama
+
+
+def _env_bool(name: str, default: bool) -> bool:
+    value = os.getenv(name)
+    if value is None:
+        return default
+    return value.strip().lower() in {"1", "true", "yes", "on"}
+
+
+def _env_float(name: str, default: float) -> float:
+    value = os.getenv(name)
+    if value is None:
+        return default
+    return float(value)
+
+
+_agent: Agent | None = None
+
+
+def get_agent() -> Agent:
+    global _agent
+
+    if _agent is not None:
+        return _agent
+
+    model_id = os.getenv("OLLAMA_MODEL_ID", "gemma4:31b")
+    ollama_host = os.getenv("OLLAMA_HOST", "http://localhost:11435")
+    temperature = _env_float("OLLAMA_TEMPERATURE", 0.0)
+    markdown = _env_bool("AGENT_MARKDOWN", False)
+    debug_mode = _env_bool("AGENT_DEBUG_MODE", True)
+    instructions = os.getenv(
+        "AGENT_INSTRUCTIONS",
+        "You are a helpful assistant. Answer briefly and clearly.",
+    )
+
+    llm = Ollama(id=model_id, host=ollama_host, options={"temperature": temperature})
+    _agent = Agent(
+        model=llm,
+        markdown=markdown,
+        instructions=instructions,
+        debug_mode=debug_mode,
+    )
+    return _agent
+
+
+async def run_agent(message: str) -> str:
+    agent = get_agent()
+    response = await agent.arun(message)
+    return str(response.content)

src/main.py

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+import argparse
+import asyncio
+
+from dotenv import load_dotenv
+
+from src.agent_runner import run_agent
+
+
+def build_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(
+        description="Run base chat agent.",
+    )
+    parser.add_argument(
+        "--message",
+        help="Single message mode. If omitted, starts interactive chat.",
+    )
+    return parser
+
+
+async def _main() -> None:
+    load_dotenv()
+    args = build_parser().parse_args()
+
+    if args.message:
+        result = await run_agent(args.message)
+        print(result)
+        return
+
+    print("Chat mode started. Type 'exit' or 'quit' to stop.")
+    while True:
+        user_message = input("you> ").strip()
+        if not user_message:
+            continue
+        if user_message.lower() in {"exit", "quit"}:
+            print("Bye.")
+            break
+
+        result = await run_agent(user_message)
+        print(f"agent> {result}")
+
+
+if __name__ == "__main__":
+    asyncio.run(_main())