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|
|
|
| from typing import Any, List, Dict, Optional
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| from langchain_community.chat_models import ChatOllama
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| from langchain_core.messages import HumanMessage, AIMessage, SystemMessage
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|
|
| model_configurations: Dict[str, Dict[str, Any]] = {
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| "qwen3:32b": {
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| "type": "Ollama",
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| "model_name": "qwen3:32b",
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| "temperature": 0.3,
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| },
|
| "mistral-small:24b": {
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| "type": "Ollama",
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| "model_name": "mistral-small:24b",
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| "temperature": 0.3,
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| },
|
| "deepseek-r1:32b": {
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| "type": "Ollama",
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| "model_name": "deepseek-r1:32b",
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| "temperature": 0.3,
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| }
|
| }
|
|
|
| class OllamaWithDebug(ChatOllama):
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| def __init__(self, model, **kwargs):
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| super().__init__(model=model, **kwargs)
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| print(f"--- DEBUG INIT: Model {model} ---")
|
| print(f"Injected parameters: {kwargs}")
|
| print("Actual instance attributes:")
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| for attr in ['temperature', 'top_p', 'base_url']:
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| print(f" - {attr}: {getattr(self, attr, 'UNDEFINED')}")
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| print("-" * 40)
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|
|
| def invoke(self, messages: Any, **kwargs):
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| print(f"\n[DEBUG INVOKE] Sending to {self.model}")
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| temp = getattr(self, 'temperature', 'N/A')
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| print(f"Active config -> Temp: {temp}")
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|
|
| preview = str(messages)[:150]
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| print(f"Input preview: {preview}...")
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|
|
| try:
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| response = super().invoke(messages, **kwargs)
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| print(f"[DEBUG RESPONSE] Success! Response length: {len(str(response.content))} chars")
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| return response
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|
|
| except Exception as e:
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| print(f"!!! DEBUG ERROR !!! Ollama call failed: {e}")
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| raise
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|
|
| def get_model_instance(model_key: str) -> Any:
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| config = model_configurations.get(model_key)
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| if config is None:
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| raise ValueError(f"Model not configured: {model_key}")
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|
|
| if config.get("type", "").lower() == "ollama":
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| return OllamaWithDebug(
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| model=config["model_name"],
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| base_url="http://localhost:11434",
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| temperature=config.get("temperature", 0.3),
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| top_p=config.get("top_p"),
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| )
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| else:
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| raise ValueError(f"Unsupported or missing model type: {config.get('type')}") |
