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fix: enriched result vector not passed to storage when using weaviate #342

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fix: enriched result vector not passed to storage when using weaviate #342

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8 changes: 5 additions & 3 deletions babyagi.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,9 @@

client = chromadb.Client(Settings(anonymized_telemetry=False))

# Use Weaviate instead of ChromaDB
WEAVIATE_USE_EMBEDDED = os.getenv("WEAVIATE_USE_EMBEDDED", "False").lower() == "true"

# Engine configuration

# Model: GPT, LLAMA, HUMAN, etc.
Expand Down Expand Up @@ -250,7 +253,6 @@ def query(self, query: str, top_results_num: int) -> List[dict]:
# Initialize results storage
def try_weaviate():
WEAVIATE_URL = os.getenv("WEAVIATE_URL", "")
WEAVIATE_USE_EMBEDDED = os.getenv("WEAVIATE_USE_EMBEDDED", "False").lower() == "true"
if (WEAVIATE_URL or WEAVIATE_USE_EMBEDDED) and can_import("extensions.weaviate_storage"):
WEAVIATE_API_KEY = os.getenv("WEAVIATE_API_KEY", "")
from extensions.weaviate_storage import WeaviateResultsStorage
Expand Down Expand Up @@ -573,11 +575,11 @@ def main():
}
# extract the actual result from the dictionary
# since we don't do enrichment currently
# vector = enriched_result["data"]
vector = enriched_result["data"] if WEAVIATE_USE_EMBEDDED else None

result_id = f"result_{task['task_id']}"

results_storage.add(task, result, result_id)
results_storage.add(task, result, result_id, vector=vector)

# Step 3: Create new tasks and re-prioritize task list
# only the main instance in cooperative mode does that
Expand Down