feat: model registry and capabilities for multi-provider support (#2158)

* feat: Implement model registry and capabilities for multi-provider support

- Added ModelRegistry to manage available models and their capabilities.
- Introduced ModelProvider enum for different LLM providers.
- Created ModelCapabilities dataclass to define model features.
- Implemented methods to load models based on API keys and settings.
- Added utility functions for model management in model_utils.py.
- Updated settings.py to include provider-specific API keys.
- Refactored LLM classes (Anthropic, OpenAI, Google, etc.) to utilize new model registry.
- Enhanced utility functions to handle token limits and model validation.
- Improved code structure and logging for better maintainability.

* feat: Add model selection feature with API integration and UI component

* feat: Add model selection and default model functionality in agent management

* test: Update assertions and formatting in stream processing tests

* refactor(llm): Standardize model identifier to model_id

* fix tests

---------

Co-authored-by: Alex <a@tushynski.me>
This commit is contained in:
Siddhant Rai
2025-11-14 16:43:19 +05:30
committed by GitHub
parent fbf7cf874b
commit 3f7de867cc
54 changed files with 1388 additions and 226 deletions

View File

@@ -1,5 +1,7 @@
import json
from openai import OpenAI
from application.core.settings import settings
from application.llm.base import BaseLLM
@@ -7,12 +9,11 @@ from application.llm.base import BaseLLM
class DocsGPTAPILLM(BaseLLM):
def __init__(self, api_key=None, user_api_key=None, *args, **kwargs):
from openai import OpenAI
super().__init__(*args, **kwargs)
self.client = OpenAI(api_key="sk-docsgpt-public", base_url="https://oai.arc53.com")
self.api_key = "sk-docsgpt-public"
self.client = OpenAI(api_key=self.api_key, base_url="https://oai.arc53.com")
self.user_api_key = user_api_key
self.api_key = api_key
def _clean_messages_openai(self, messages):
cleaned_messages = []
@@ -22,7 +23,6 @@ class DocsGPTAPILLM(BaseLLM):
if role == "model":
role = "assistant"
if role and content is not None:
if isinstance(content, str):
cleaned_messages.append({"role": role, "content": content})
@@ -69,7 +69,6 @@ class DocsGPTAPILLM(BaseLLM):
)
else:
raise ValueError(f"Unexpected content type: {type(content)}")
return cleaned_messages
def _raw_gen(
@@ -121,7 +120,6 @@ class DocsGPTAPILLM(BaseLLM):
response = self.client.chat.completions.create(
model="docsgpt", messages=messages, stream=stream, **kwargs
)
try:
for line in response:
if (
@@ -133,8 +131,8 @@ class DocsGPTAPILLM(BaseLLM):
elif len(line.choices) > 0:
yield line.choices[0]
finally:
if hasattr(response, 'close'):
if hasattr(response, "close"):
response.close()
def _supports_tools(self):
return True
return True