feat: week 2 multi llms chat

2025-10-03 16:36:32 +02:00
parent 3286cfb395
commit 8211417c61
3 changed files with 273 additions and 0 deletions
--- a/week2/community-contributions/llms-chat-room/llm_bot.py
+++ b/week2/community-contributions/llms-chat-room/llm_bot.py
@@ -0,0 +1,115 @@
+import os
+
+from dotenv import load_dotenv
+from openai import OpenAI
+import anthropic
+
+LLM_BOT_CONFIGS = {
+    "gpt": {
+        "id": "gpt",
+        "name": "Giorgio",
+        "model": "gpt-4.1-nano",
+        "api_key_env": "OPENAI_API_KEY",
+    },
+    "claude": {
+        "id": "claude",
+        "name": "Anna",
+        "model": "claude-sonnet-4-20250514",
+        "api_key_env": "ANTHROPIC_API_KEY",
+    },
+    "gemini": {
+        "id": "gemini",
+        "name": "Isabella",
+        "model": "gemini-2.0-flash",
+        "base_url": "https://generativelanguage.googleapis.com/v1beta/openai/",
+        "api_key_env": "GOOGLE_API_KEY",
+    },
+    "openai": {
+        "id": "openai",
+        "name": "Marco",
+        "model": "gpt-4o-mini",
+        "api_key_env": "OPENAI_API_KEY",
+    },
+    "deepseek": {
+        "id": "deepseek",
+        "name": "Roberto",
+        "model": "deepseek-chat",
+        "base_url": "https://api.deepseek.com",
+        "api_key_env": "DEEPSEEK_API_KEY"
+    }
+}
+
+
+def load_api_key():
+    """Load .env and ensure all required API keys from LLM_BOT_CONFIGS are present.
+
+    - Reads environment variables from .env without overriding already-set envs.
+    - Collects unique api_key_env names from LLM_BOT_CONFIGS.
+    - Raises a RuntimeError listing any missing variables.
+    """
+    # Load from .env but do not override variables already set in the environment
+    load_dotenv(override=False)
+
+    required_env_vars = {cfg["api_key_env"] for cfg in LLM_BOT_CONFIGS.values() if "api_key_env" in cfg}
+
+    missing = []
+    for var in sorted(required_env_vars):
+        val = os.getenv(var)
+        if not val:
+            missing.append(var)
+
+    if missing:
+        raise RuntimeError(
+            "Missing required API key environment variables: "
+            + ", ".join(missing)
+            + ". Please add them to your .env file or export them in your environment."
+        )
+
+
+class LLMBot:
+
+    def __init__(self, llm, subject, name=None):
+        if llm not in LLM_BOT_CONFIGS:
+            raise ValueError(f"Unknown LLM provider '{llm}'. Available: {', '.join(LLM_BOT_CONFIGS.keys())}")
+        load_api_key()
+        self.configuration = LLM_BOT_CONFIGS[llm]
+        self.subject = subject
+        api_key = os.getenv(self.configuration["api_key_env"])
+        self.llm = llm
+        self.name = name or self.configuration["name"]
+        self.system_prompt = \
+            (f"You are {self.name}, a person talking to other persons in one room discussing the {subject}.\
+                If you are first to speak about the {subject} please describe it in detail to other people and express your opinion.\
+                Talk politely and without any prejudices. Be short as other people also would like to express own opinion. If other people already speak about the {subject} \
+                please make a comment adding some value to the conversation.")
+        base_url = self.configuration.get("base_url")
+        if self.llm == "claude" and not base_url:
+            self.client = anthropic.Anthropic(api_key=api_key)
+        else:
+            self.client = OpenAI(api_key=api_key, base_url=base_url)
+
+    def get_response(self, prompt):
+        if self.llm == "claude":
+            # Anthropic API: system prompt is provided separately; messages contain user/assistant turns
+            messages = [
+                {"role": "user", "content": prompt},
+            ]
+            response = self.client.messages.create(
+                model=self.configuration["model"],
+                max_tokens=200,
+                temperature=0.7,
+                system=self.system_prompt,
+                messages=messages,
+            )
+            return response.content[0].text
+        else:
+            # OpenAI-compatible chat completion API (OpenAI, DeepSeek, Gemini via OpenAI shim)
+            messages = [
+                {"role": "system", "content": self.system_prompt},
+                {"role": "user", "content": prompt}
+            ]
+            response = self.client.chat.completions.create(
+                model=self.configuration["model"],
+                messages=messages,
+            )
+            return response.choices[0].message.content