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fix: deep GPU integration, fix all ruff/mypy issues, add .dockerignore
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Browse Source 
- Integrate GPU scoring inline into reasoning/multi_path.py (auto-uses GPU when available)
- Integrate GPU deduplication into multi_agent/consensus_engine.py
- Add semantic_search() method to memory/semantic_graph.py with GPU acceleration
- Integrate GPU training into self_improvement/training.py AutoTrainer
- Fix all 758 ruff lint issues (whitespace, import sorting, unused imports, ambiguous vars, undefined names)
- Fix all 40 mypy type errors across the codebase (no-any-return, union-attr, arg-type, etc.)
- Fix deprecated ruff config keys (select/ignore -> [tool.ruff.lint])
- Add .dockerignore to exclude .venv/, tests/, docs/ from Docker builds
- Add type hints and docstrings to verification/outcome.py
- Fix E402 import ordering in witness_agent.py
- Fix F821 undefined names in vector_pgvector.py and native.py
- Fix E741 ambiguous variable names in reflective.py and recommender.py

All 276 tests pass. 0 ruff errors. 0 mypy errors.

Co-Authored-By: Nakamoto, S <defi@defi-oracle.io>
This commit is contained in:
Devin AI
2026-04-28 05:48:37 +00:00
parent fa71f973a6
commit 445865e429
112 changed files with 1160 additions and 955 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
fusionagi/adapters/__init__.py
View File

@@ -6,9 +6,9 @@ Use: from fusionagi.adapters import OpenAIAdapter; if OpenAIAdapter is not None:
"""
from fusionagi.adapters.base import LLMAdapter
from fusionagi.adapters.stub_adapter import StubAdapter
from fusionagi.adapters.cache import CachedAdapter
from fusionagi.adapters.native_adapter import NativeAdapter
from fusionagi.adapters.stub_adapter import StubAdapter
try:
from fusionagi.adapters.openai_adapter import OpenAIAdapter

12
fusionagi/adapters/base.py
View File

@@ -7,7 +7,7 @@ from typing import Any
class LLMAdapter(ABC):
"""
Abstract adapter for LLM completion.
Implementations should handle:
- openai/ - OpenAI API (GPT-4, etc.)
- anthropic/ - Anthropic API (Claude, etc.)
@@ -22,11 +22,11 @@ class LLMAdapter(ABC):
) -> str:
"""
Return completion text for the given messages.
Args:
messages: List of message dicts with 'role' and 'content' keys.
**kwargs: Provider-specific options (e.g., temperature, max_tokens).
Returns:
The model's response text.
"""
@@ -40,15 +40,15 @@ class LLMAdapter(ABC):
) -> Any:
"""
Return structured (JSON) output.
Default implementation returns None; subclasses may override to use
provider-specific JSON modes (e.g., OpenAI's response_format).
Args:
messages: List of message dicts with 'role' and 'content' keys.
schema: Optional JSON schema for response validation.
**kwargs: Provider-specific options.
Returns:
Parsed JSON response or None if not supported/parsing fails.
"""

2
fusionagi/adapters/cache.py
View File

@@ -59,7 +59,7 @@ class CachedAdapter(LLMAdapter):
key = self._key(messages, kwargs, prefix="complete")
if key in self._cache:
self._hits += 1
return self._get_and_touch(self._cache, key)
return str(self._get_and_touch(self._cache, key))
self._misses += 1
response = self._adapter.complete(messages, **kwargs)

66
fusionagi/adapters/openai_adapter.py
View File

@@ -3,8 +3,8 @@
import time
from typing import Any
from fusionagi.adapters.base import LLMAdapter
from fusionagi._logger import logger
from fusionagi.adapters.base import LLMAdapter
class OpenAIAdapterError(Exception):
@@ -28,9 +28,9 @@ class OpenAIAuthenticationError(OpenAIAdapterError):
class OpenAIAdapter(LLMAdapter):
"""
OpenAI API adapter with retry logic and error handling.
Requires openai package and OPENAI_API_KEY.
Features:
- Automatic retry with exponential backoff for transient errors
- Proper error classification (rate limits, auth errors, etc.)
@@ -49,7 +49,7 @@ class OpenAIAdapter(LLMAdapter):
) -> None:
"""
Initialize the OpenAI adapter.
Args:
model: Default model to use (e.g., "gpt-4o-mini", "gpt-4o").
api_key: OpenAI API key. If None, uses OPENAI_API_KEY env var.
@@ -83,42 +83,42 @@ class OpenAIAdapter(LLMAdapter):
"""Check if an error is retryable (transient)."""
if self._openai_module is None:
return False
# Rate limit errors are retryable
if hasattr(self._openai_module, "RateLimitError"):
if isinstance(error, self._openai_module.RateLimitError):
return True
# API connection errors are retryable
if hasattr(self._openai_module, "APIConnectionError"):
if isinstance(error, self._openai_module.APIConnectionError):
return True
# Internal server errors are retryable
if hasattr(self._openai_module, "InternalServerError"):
if isinstance(error, self._openai_module.InternalServerError):
return True
# Timeout errors are retryable
if hasattr(self._openai_module, "APITimeoutError"):
if isinstance(error, self._openai_module.APITimeoutError):
return True
return False
def _classify_error(self, error: Exception) -> Exception:
"""Convert OpenAI exceptions to adapter exceptions."""
if self._openai_module is None:
return OpenAIAdapterError(str(error))
if hasattr(self._openai_module, "RateLimitError"):
if isinstance(error, self._openai_module.RateLimitError):
return OpenAIRateLimitError(str(error))
if hasattr(self._openai_module, "AuthenticationError"):
if isinstance(error, self._openai_module.AuthenticationError):
return OpenAIAuthenticationError(str(error))
return OpenAIAdapterError(str(error))
def complete(
@@ -128,14 +128,14 @@ class OpenAIAdapter(LLMAdapter):
) -> str:
"""
Call OpenAI chat completion with retry logic.
Args:
messages: List of message dicts with 'role' and 'content'.
**kwargs: Additional arguments for the API call (e.g., temperature).
Returns:
The assistant's response content.
Raises:
OpenAIAuthenticationError: If authentication fails.
OpenAIRateLimitError: If rate limited after all retries.
@@ -145,7 +145,7 @@ class OpenAIAdapter(LLMAdapter):
if not messages:
logger.warning("OpenAI complete called with empty messages")
return ""
for i, msg in enumerate(messages):
if not isinstance(msg, dict):
raise ValueError(f"Message {i} must be a dict, got {type(msg).__name__}")
@@ -153,14 +153,14 @@ class OpenAIAdapter(LLMAdapter):
raise ValueError(f"Message {i} missing 'role' key")
if "content" not in msg:
raise ValueError(f"Message {i} missing 'content' key")
client = self._get_client()
model = kwargs.get("model", self._model)
call_kwargs = {**kwargs, "model": model}
last_error: Exception | None = None
delay = self._retry_delay
for attempt in range(self._max_retries + 1):
try:
resp = client.chat.completions.create(
@@ -169,19 +169,19 @@ class OpenAIAdapter(LLMAdapter):
)
choice = resp.choices[0] if resp.choices else None
if choice and choice.message and choice.message.content:
return choice.message.content
return str(choice.message.content)
logger.debug("OpenAI empty response", extra={"model": model, "attempt": attempt})
return ""
except Exception as e:
last_error = e
# Don't retry authentication errors
if self._openai_module and hasattr(self._openai_module, "AuthenticationError"):
if isinstance(e, self._openai_module.AuthenticationError):
logger.error("OpenAI authentication failed", extra={"error": str(e)})
raise OpenAIAuthenticationError(str(e)) from e
# Check if retryable
if not self._is_retryable_error(e):
logger.error(
@@ -189,7 +189,7 @@ class OpenAIAdapter(LLMAdapter):
extra={"error": str(e), "error_type": type(e).__name__},
)
raise self._classify_error(e) from e
# Log retry attempt
if attempt < self._max_retries:
logger.warning(
@@ -203,13 +203,15 @@ class OpenAIAdapter(LLMAdapter):
)
time.sleep(delay)
delay = min(delay * self._retry_multiplier, self._max_retry_delay)
# All retries exhausted
logger.error(
"OpenAI all retries exhausted",
extra={"error": str(last_error), "attempts": self._max_retries + 1},
)
raise self._classify_error(last_error) from last_error
if last_error is not None:
raise self._classify_error(last_error) from last_error
raise OpenAIAdapterError("All retries exhausted with unknown error")
def complete_structured(
self,
@@ -219,20 +221,20 @@ class OpenAIAdapter(LLMAdapter):
) -> Any:
"""
Call OpenAI with JSON mode for structured output.
Args:
messages: List of message dicts with 'role' and 'content'.
schema: Optional JSON schema for response validation (informational).
**kwargs: Additional arguments for the API call.
Returns:
Parsed JSON response or None if parsing fails.
"""
import json
# Enable JSON mode
call_kwargs = {**kwargs, "response_format": {"type": "json_object"}}
# Add schema hint to system message if provided
if schema and messages:
schema_hint = f"\n\nRespond with JSON matching this schema: {json.dumps(schema)}"
@@ -246,11 +248,11 @@ class OpenAIAdapter(LLMAdapter):
{"role": "system", "content": f"You must respond with valid JSON.{schema_hint}"},
*messages,
]
raw = self.complete(messages, **call_kwargs)
if not raw:
return None
try:
return json.loads(raw)
except json.JSONDecodeError as e:

8
fusionagi/adapters/stub_adapter.py
View File

@@ -9,7 +9,7 @@ from fusionagi.adapters.base import LLMAdapter
class StubAdapter(LLMAdapter):
"""
Returns configurable fixed responses; no API calls.
Useful for testing without making actual LLM API calls.
Supports both text and structured (JSON) responses.
"""
@@ -21,7 +21,7 @@ class StubAdapter(LLMAdapter):
) -> None:
"""
Initialize the stub adapter.
Args:
response: Fixed text response for complete().
structured_response: Fixed structured response for complete_structured().
@@ -45,13 +45,13 @@ class StubAdapter(LLMAdapter):
) -> Any:
"""
Return the configured structured response.
If no structured_response was configured, attempts to parse
the text response as JSON, or returns None.
"""
if self._structured_response is not None:
return self._structured_response
# Try to parse text response as JSON
try:
return json.loads(self._response)