Upload folder using huggingface_hub

.github/workflows/ci.yml

@@ -1,14 +1,14 @@
 name: Deploy Documentation
 on:
   push:
-    branches:
-      - master
-      - main
+    tags:
+      - '*'
 permissions:
   contents: write
 jobs:
   deploy:
     runs-on: ubuntu-latest
+    if: startsWith(github.ref, 'refs/tags/') && github.event.base_ref == 'refs/heads/master'
     steps:
       - uses: actions/checkout@v4
       - name: Configure Git Credentials
@@ -26,4 +26,4 @@ jobs:
           restore-keys: |
             mkdocs-material-
       - run: pip install mkdocs-material mkdocstrings mkdocstrings-python mkdocs-include-markdown-plugin
-      - run: mkdocs gh-deploy --force
+      - run: mkdocs gh-deploy --force

.github/workflows/update_space.yml

@@ -2,13 +2,13 @@ name: Deploy to HuggingFace
 
 on:
   push:
-    branches:
-      - main
-      - master
+    tags:
+      - '*'
 
 jobs:
   build:
     runs-on: ubuntu-latest
+    if: startsWith(github.ref, 'refs/tags/') && github.event.base_ref == 'refs/heads/master'
 
     steps:
       - name: Checkout

README.md

@@ -3,11 +3,14 @@ title: opensymbiose
 app_file: src/opensymbiose/gradio/app.py
 sdk: gradio
 sdk_version: 5.31.0
+python_version: 3.13
 ---
 # OpenSymbiose: Open Source Biotechnology AI Agent
 
 OpenSymbiose is an open-source biotechnology / biology research AI agent designed to support researcher.
 
+[DOCUMENTATION](https://lambda-science.github.io/OpenSymbiose/) - [DEMO ON HUGGINGFACE](https://huggingface.co/spaces/corentinm7/opensymbiose) - [CODE REPO](https://github.com/lambda-science/OpenSymbiose)
+
 Creator and Maintainer: [**Corentin Meyer**, PhD](https://cmeyer.fr/) - <[email protected]>
 
 ## Installation

src/opensymbiose/gradio/app.py

@@ -9,14 +9,19 @@ from mistralai import Mistral, ToolReferenceChunk
 import opensymbiose.config
 from opensymbiose.agents.create_agents import get_agents
 
+logging.basicConfig(
+    level=logging.WARNING,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+    handlers=[logging.StreamHandler()]
+)
 logger = logging.getLogger(__name__)
 client = Mistral(api_key=opensymbiose.config.MISTRAL_API_KEY)
 model = "mistral-medium-latest"
 
-
-def get_mistral_answer(message: str, history):
+def get_mistral_answer(message: str, history = None):
     # Start global execution timer
     global_start_time = time.time()
+    logger.info(f"Processing message: {message}")
 
     # Dictionary to track tool execution times
     tool_timers = {}
@@ -32,14 +37,17 @@ def get_mistral_answer(message: str, history):
     yield messages
     full_response = ""
     for chunk in stream_response:
-        print(chunk)
+        logger.info(f"Chunk: {chunk}")
         if chunk.event == "message.output.delta":
             if isinstance(chunk.data.content, str):
                 full_response += chunk.data.content
             if isinstance(chunk.data.content, ToolReferenceChunk):
                 full_response += f"([{chunk.data.content.title}]({chunk.data.content.url})) "
             # Update the last message with the current full response
-            messages[-1] = asdict(ChatMessage(role="assistant", content=full_response))
+            if messages and messages[-1].get("role") == "assistant" and not messages[-1].get("metadata"):
+                messages[-1] = asdict(ChatMessage(role="assistant", content=full_response))
+            else:
+                messages.append(asdict(ChatMessage(role="assistant", content=full_response)))
             yield messages
         elif chunk.event == "tool.execution.started":
             # Start timer for this tool
@@ -101,10 +109,12 @@ def get_mistral_answer(message: str, history):
                                                metadata={"title": f"✅ Conversation response complete.",
                                                          "log": f"Tokens: Prompt: {chunk.data.usage.prompt_tokens}, Completion: {chunk.data.usage.completion_tokens}, Total: {chunk.data.usage.total_tokens} Connectors: {chunk.data.usage.connector_tokens}",
                                                          "duration": round(global_duration, 2)})))
+            logger.info(f"Conversation response complete. Duration: {round(global_duration, 2)}s, Total tokens: {chunk.data.usage.total_tokens}")
             yield messages
         elif chunk.event == "conversation.response.error":
             # Add a new message for conversation response error
             error_message = f"Error: {chunk.data.message} (Code: {chunk.data.code})"
+            logger.error(f"Conversation response error: {error_message}")
             messages.append(asdict(ChatMessage(role="assistant", content="",
                                                metadata={"title": f"❌ {error_message}"})))
             yield messages
@@ -127,4 +137,6 @@ with gr.Blocks() as demo:
     )
 
 if __name__ == "__main__":
+    logger.setLevel(logging.INFO)
+    logging.getLogger().setLevel(logging.INFO)
     demo.launch()