Merge pull request #810 from macrocosm-os/release/v3.0.5

Bump project version to 3.0.5

Author: bkb2135

apex/services/deep_research/deep_research_base.py

@@ -6,5 +6,5 @@
 class DeepResearchBase(LLMBase):
     async def invoke(
         self, messages: list[dict[str, str]], body: dict[str, Any] | None = None
-    ) -> tuple[str, list[dict[str, str]]]:
+    ) -> tuple[str, list[dict[str, str]], list[dict[str, Any]]]:
         raise NotImplementedError

apex/services/deep_research/deep_research_langchain.py

@@ -14,7 +14,7 @@ def __init__(self, base_url: str, model: str, key: str):
 
     async def invoke(
         self, messages: list[dict[str, str]], body: dict[str, Any] | None = None
-    ) -> tuple[str, list[dict[str, str]]]:
+    ) -> tuple[str, list[dict[str, str]], list[dict[str, Any]]]:
         headers = {
             "Authorization": "Bearer " + self._key,
             "Content-Type": "application/json",
@@ -35,7 +35,8 @@ async def invoke(
 
                 data = await response.json()
                 content = data.get("choices", [{}])[0].get("message", {}).get("content", "")
-                return str(content), []
+                # This base LLM does not build multi-step chains; return empty reasoning_traces
+                return str(content), [], []
 
     def __str__(self) -> str:
         return f"{self.__class__.__name__}({self._base_url}, {self._model})"

apex/services/llm/llm.py

@@ -4,5 +4,5 @@
 class LLMBase:
     async def invoke(
         self, messages: list[dict[str, str]], body: dict[str, Any] | None = None
-    ) -> tuple[str, list[dict[str, str]]]:
+    ) -> tuple[str, list[dict[str, str]], list[dict[str, Any]]]:
         raise NotImplementedError

apex/services/llm/llm_base.py

@@ -19,10 +19,14 @@
 async def generate_query(llm: LLMBase, websearch: WebSearchBase) -> str:
     random_words = " ".join(random.sample(get_english_words(), 3))
     # Perform a lightweight search and pick a single result as context.
-    search_results = await websearch.search(random_words, max_results=5)
-    search_website = random.choice(search_results)
-    search_content = search_website.content
+    try:
+        search_results = await websearch.search(random_words, max_results=5)
+        search_website = random.choice(search_results)
+        search_content = search_website.content
+    except Exception as exc:
+        logger.debug(f"Error during web search: {exc}")
+        search_content = ""
     query = QUERY_PROMPT_TEMPLATE.format(context=search_content)
-    query_response, _ = await llm.invoke([{"role": "user", "content": query}])
+    query_response, _, _ = await llm.invoke([{"role": "user", "content": query}])
     logger.debug(f"Generated query.\nPrompt: '{query}'\nResponse: '{query_response}'")
     return query_response

apex/validator/generate_query.py

@@ -1,9 +1,13 @@
+from typing import Any
+
 from loguru import logger
 
 from apex.services.deep_research.deep_research_base import DeepResearchBase
 
 
-async def generate_reference(llm: DeepResearchBase, query: str) -> tuple[str, list[dict[str, str]]]:
+async def generate_reference(
+    llm: DeepResearchBase, query: str
+) -> tuple[str, list[dict[str, str]], list[dict[str, Any]]]:
     """Generate a reference response for the given prompt.
 
     Args:
@@ -22,13 +26,9 @@ async def generate_reference(llm: DeepResearchBase, query: str) -> tuple[str, li
     }
     user_message: dict[str, str] = {
         "role": "user",
-        "content": (
-            f"Research Question: {query}\n\n"
-            "Please think through the answer carefully, annotate each step with citations like [1], [2], etc., "
-            'and conclude with a "References:" list mapping each [n] to its source URL or title.'
-        ),
+        "content": query,
     }
 
-    response, tool_history = await llm.invoke([system_message, user_message])
+    response, tool_history, reasoning_traces = await llm.invoke([system_message, user_message])
     logger.debug(f"Generated reference.\nPrompt: '{user_message}'\nResponse: '{response}'")
-    return response, tool_history
+    return response, tool_history, reasoning_traces

apex/validator/generate_reference.py

@@ -46,13 +46,15 @@ async def log(
         reference: str | None = None,
         discriminator_results: MinerDiscriminatorResults | None = None,
         tool_history: list[dict[str, str]] | None = None,
+        reasoning_traces: list[dict[str, Any]] | None = None,
     ) -> None:
         """Log an event to wandb."""
         if self.run:
             if discriminator_results:
                 processed_event = self.process_event(discriminator_results.model_dump())
                 processed_event["reference"] = reference
                 processed_event["tool_history"] = tool_history
+                processed_event["reasoning_trace"] = reasoning_traces
                 self.run.log(processed_event)
 
     def process_event(self, event: Mapping[str, Any]) -> dict[str, Any]:

apex/validator/logger_wandb.py

@@ -84,12 +84,15 @@ async def run_single(self, task: QueryTask) -> str:
 
         reference = None
         tool_history: list[dict[str, str]] = []
+        reasoning_traces: list[dict[str, Any]] = []
         if random.random() < self.reference_rate:
             try:
                 generator_results = None
                 ground_truth = 0
                 logger.debug(f"Generating task reference for query: {query[:20]}..")
-                reference, tool_history = await generate_reference(llm=self.deep_research, query=query)
+                reference, tool_history, reasoning_traces = await generate_reference(
+                    llm=self.deep_research, query=query
+                )
             except BaseException as exc:
                 logger.exception(f"Failed to generate reference: {exc}")
 
@@ -100,7 +103,9 @@ async def run_single(self, task: QueryTask) -> str:
             if random.random() < self.redundancy_rate:
                 try:
                     logger.debug(f"Generating redundant task reference for query: {query[:20]}..")
-                    reference, tool_history = await generate_reference(llm=self.deep_research, query=query)
+                    reference, tool_history, reasoning_traces = await generate_reference(
+                        llm=self.deep_research, query=query
+                    )
                 except BaseException as exc:
                     logger.warning(f"Failed to generate redundant reference: {exc}")
 
@@ -111,7 +116,10 @@ async def run_single(self, task: QueryTask) -> str:
 
         if self.logger_wandb:
             await self.logger_wandb.log(
-                reference=reference, discriminator_results=discriminator_results, tool_history=tool_history
+                reference=reference,
+                discriminator_results=discriminator_results,
+                tool_history=tool_history,
+                reasoning_traces=reasoning_traces,
             )
 
         if self._debug:

apex/validator/pipeline.py

@@ -1,6 +1,6 @@
 [project]
 name = "apex"
-version = "3.0.4"
+version = "3.0.5"
 description = "Bittensor Subnet 1: Apex"
 readme = "README.md"
 requires-python = "~=3.11"
@@ -36,6 +36,7 @@ dependencies = [
     "pytest-mock>=3.14.1",
     "wandb>=0.21.1",
     "ruff>=0.12.5",
+    "langchain-experimental>=0.3.4",
 ]