fixes error with loading plugins in package

optillm/__init__.py

@@ -2,7 +2,7 @@
 import os
 
 # Version information
-__version__ = "0.1.14"
+__version__ = "0.1.15"
 
 # Get the path to the root optillm.py
 spec = util.spec_from_file_location(

optillm/plugins/deepthink_plugin.py

@@ -5,10 +5,11 @@
 for enhanced reasoning in large language models.
 """
 
+import os
+import sys
+import importlib.util
 import logging
 from typing import Tuple, Dict, Any
-from optillm.plugins.deepthink.self_discover import SelfDiscover
-from optillm.plugins.deepthink.uncertainty_cot import UncertaintyRoutedCoT
 
 # Plugin identifier for optillm
 SLUG = "deepthink"
@@ -40,18 +41,38 @@ def run(
     """
     logger.info("Starting Deep Think reasoning process")
 
-    # Extract configuration parameters
-    config = _parse_config(request_config or {})
+    # Get the directory where this plugin is located
+    plugin_dir = os.path.dirname(os.path.abspath(__file__))
+    deepthink_dir = os.path.join(plugin_dir, 'deepthink')
+
+    # Add the deepthink directory to the Python path temporarily
+    if deepthink_dir not in sys.path:
+        sys.path.insert(0, deepthink_dir)
 
     try:
+        # Load the modules dynamically
+        self_discover_file = os.path.join(deepthink_dir, 'self_discover.py')
+        uncertainty_cot_file = os.path.join(deepthink_dir, 'uncertainty_cot.py')
+
+        spec1 = importlib.util.spec_from_file_location("self_discover", self_discover_file)
+        self_discover_module = importlib.util.module_from_spec(spec1)
+        spec1.loader.exec_module(self_discover_module)
+
+        spec2 = importlib.util.spec_from_file_location("uncertainty_cot", uncertainty_cot_file)
+        uncertainty_cot_module = importlib.util.module_from_spec(spec2)
+        spec2.loader.exec_module(uncertainty_cot_module)
+
+        # Extract configuration parameters
+        config = _parse_config(request_config or {})
+
         # Initialize components
-        self_discover = SelfDiscover(
+        self_discover = self_discover_module.SelfDiscover(
             client=client,
             model=model,
             max_tokens=config["max_tokens"]
         )
 
-        uncertainty_cot = UncertaintyRoutedCoT(
+        uncertainty_cot = uncertainty_cot_module.UncertaintyRoutedCoT(
             client=client,
             model=model,
             max_tokens=config["max_tokens"]
@@ -108,31 +129,10 @@ def run(
 
         return final_response, total_tokens
 
-    except Exception as e:
-        logger.error(f"Error in Deep Think plugin: {str(e)}")
-        logger.debug(f"Exception traceback:", exc_info=True)
-
-        # Fallback to simple generation
-        try:
-            logger.info("Attempting fallback to simple generation")
-            response = client.chat.completions.create(
-                model=model,
-                messages=[
-                    {"role": "system", "content": system_prompt},
-                    {"role": "user", "content": initial_query}
-                ],
-                max_tokens=config["max_tokens"],
-                temperature=config["temperature"],
-                top_p=config["top_p"]
-            )
-
-            logger.info("Fallback generation successful")
-            return response.choices[0].message.content.strip(), response.usage.completion_tokens
-
-        except Exception as fallback_error:
-            logger.error(f"Fallback generation also failed: {str(fallback_error)}")
-            logger.debug(f"Fallback exception traceback:", exc_info=True)
-            return f"Error in Deep Think plugin: {str(e)}", 0
+    finally:
+        # Remove from path after use
+        if deepthink_dir in sys.path:
+            sys.path.remove(deepthink_dir)
 
 def _parse_config(request_config: Dict[str, Any]) -> Dict[str, Any]:
     """Parse and validate configuration parameters."""

optillm/plugins/longcepo.py

@@ -5,11 +5,31 @@
 If you have any questions or want to contribute, please reach out to us on [cerebras.ai/discord](https://cerebras.ai/discord).
 """
 
+import os
+import sys
+import importlib.util
 from typing import Tuple
-from optillm.plugins.longcepo.main import run_longcepo
-
 
 SLUG = "longcepo"
 
 def run(system_prompt: str, initial_query: str, client, model: str) -> Tuple[str, int]:
-    return run_longcepo(system_prompt, initial_query, client, model)
+    # Get the directory where this plugin is located
+    plugin_dir = os.path.dirname(os.path.abspath(__file__))
+    longcepo_dir = os.path.join(plugin_dir, 'longcepo')
+    main_file = os.path.join(longcepo_dir, 'main.py')
+
+    # Load the main module dynamically
+    spec = importlib.util.spec_from_file_location("longcepo_main", main_file)
+    longcepo_main = importlib.util.module_from_spec(spec)
+
+    # Add the longcepo directory to the Python path temporarily
+    if longcepo_dir not in sys.path:
+        sys.path.insert(0, longcepo_dir)
+
+    try:
+        spec.loader.exec_module(longcepo_main)
+        return longcepo_main.run_longcepo(system_prompt, initial_query, client, model)
+    finally:
+        # Remove from path after use
+        if longcepo_dir in sys.path:
+            sys.path.remove(longcepo_dir)

optillm/plugins/longcepo/chunking.py

@@ -3,7 +3,7 @@
 import re
 from typing import List
 
-from optillm.plugins.longcepo.utils import logger
+from .utils import logger
 
 
 def get_prompt_length(prompt: str, tokenizer, no_special_tokens=False, **kwargs) -> int:

optillm/plugins/longcepo/main.py

@@ -2,8 +2,9 @@
 from typing import Tuple
 from functools import partial
 
-from optillm.plugins.longcepo.mapreduce import mapreduce
-from optillm.plugins.longcepo.utils import (
+# Use relative imports that work within the dynamically loaded module
+from .mapreduce import mapreduce
+from .utils import (
     get_prompt_response,
     logger,
     longcepo_init,

optillm/plugins/longcepo/mapreduce.py

@@ -1,15 +1,15 @@
 from functools import partial
 from typing import Tuple, List
 
-from optillm.plugins.longcepo.utils import (
+from .utils import (
     CBLog,
     LongCepoConfig,
     get_prompt_response,
     concurrent_map,
     logger,
     loop_until_match,
 )
-from optillm.plugins.longcepo.chunking import (
+from .chunking import (
     chunk_context,
     get_prompt_length,
 )

optillm/plugins/longcepo/utils.py

@@ -3,7 +3,7 @@
 from concurrent.futures import ThreadPoolExecutor, as_completed
 
 from transformers import AutoTokenizer, PreTrainedTokenizerBase
-from optillm.plugins.longcepo.config import LongCepoConfig
+from .config import LongCepoConfig
 
 logger = logging.getLogger(__name__)
 

optillm/plugins/spl.py

@@ -13,8 +13,10 @@
 LLM incrementally better at solving problems by learning from its experiences.
 """
 
+import os
+import sys
+import importlib.util
 from typing import Tuple
-from optillm.plugins.spl.main import run_spl
 
 # Plugin identifier
 SLUG = "spl"
@@ -34,4 +36,23 @@ def run(system_prompt: str, initial_query: str, client, model: str, request_conf
     Returns:
         Tuple[str, int]: The LLM response and token count
     """
-    return run_spl(system_prompt, initial_query, client, model, request_config)
+    # Get the directory where this plugin is located
+    plugin_dir = os.path.dirname(os.path.abspath(__file__))
+    spl_dir = os.path.join(plugin_dir, 'spl')
+    main_file = os.path.join(spl_dir, 'main.py')
+
+    # Load the main module dynamically
+    spec = importlib.util.spec_from_file_location("spl_main", main_file)
+    spl_main = importlib.util.module_from_spec(spec)
+
+    # Add the spl directory to the Python path temporarily
+    if spl_dir not in sys.path:
+        sys.path.insert(0, spl_dir)
+
+    try:
+        spec.loader.exec_module(spl_main)
+        return spl_main.run_spl(system_prompt, initial_query, client, model, request_config)
+    finally:
+        # Remove from path after use
+        if spl_dir in sys.path:
+            sys.path.remove(spl_dir)

optillm/plugins/spl/main.py

@@ -6,22 +6,22 @@
 import logging
 from typing import Tuple, Dict, List, Optional, Any
 
-from optillm.plugins.spl.strategy import Strategy, StrategyDatabase
-from optillm.plugins.spl.generation import (
+from .strategy import Strategy, StrategyDatabase
+from .generation import (
     classify_problem,
     generate_strategy,
     should_create_new_strategy
 )
-from optillm.plugins.spl.evaluation import (
+from .evaluation import (
     select_relevant_strategies,
     evaluate_strategy_effectiveness,
     refine_strategy
 )
-from optillm.plugins.spl.utils import (
+from .utils import (
     extract_thinking,
     augment_system_prompt
 )
-from optillm.plugins.spl.config import (
+from .config import (
     DEFAULT_MAX_TOKENS,
     MAINTENANCE_INTERVAL,
     STRATEGY_MERGING_THRESHOLD,

setup.py

@@ -3,7 +3,7 @@
 
 setup(
     name="optillm",
-    version="0.1.14",
+    version="0.1.15",
     packages=find_packages(include=['optillm', 'optillm.*']),  # This ensures all subpackages are included
     py_modules=['optillm'],
     package_data={