Merge branch 'dev/proxy-server' into develop

bolna/ingestion_server/datachecks/__init__.py

@@ -46,4 +46,4 @@ class RAGTask(BaseModel):
     _status:str = RAGTaskStatus.WAIT
     _message:str = ""
     _index:str = ""
-    _nodes:list = []
+    _nodes:list = []

bolna/ingestion_server/main.py

@@ -1,10 +1,13 @@
-from fastapi import FastAPI, UploadFile
+import time
+import json
+import dotenv
+
+from fastapi import FastAPI, File, UploadFile, Form
+from typing import Dict, Any, Optional, Union
+
 from bolna.ingestion_server.datachecks import RAGConfig
 from bolna.ingestion_server import RAGFactory
 import uvicorn
-import time
-from typing import Dict
-import dotenv
 
 dotenv.load_dotenv()
 DB: Dict[str, RAGConfig] = {}
@@ -22,10 +25,8 @@ def heartbeat() -> float:
 @app.post("/create-rag")
 def create_rag(request: RAGConfig) -> Dict[str, str]:
     """Create a RAG configuration and return its ID.
-
     Args:
         request (RAGConfig): The RAG configuration to create.
-
     Returns:
         Dict[str, str]: A dictionary containing the created RAG ID.
     """
@@ -37,11 +38,9 @@ def create_rag(request: RAGConfig) -> Dict[str, str]:
 @app.post("/rag-upload-file/{rag_id}")
 async def rag_upload_file(file: UploadFile, rag_id: str) -> Dict[str, str]:
     """Upload a file for a specific RAG ID.
-
     Args:
         file (UploadFile): The file to upload.
         rag_id (str): The ID of the RAG to associate with the file.
-
     Returns:
         Dict[str, str]: A dictionary containing the upload status and index.
     """
@@ -50,21 +49,64 @@ async def rag_upload_file(file: UploadFile, rag_id: str) -> Dict[str, str]:
         return {"index": task._index, "status": task._status, "message": "DONE"}
     except Exception as e:
         return {"index": None, "status": "ERROR", "message": f"{e}"}
+
+@app.post("/make-rag")
+async def make_rag(
+    file: UploadFile = File(...),
+    config: str = Form(...)
+) -> Dict[str, Any]:
+    """
+    Create a RAG configuration, return its ID, and ingest the uploaded file.
+    
+    Args:
+        file (UploadFile): The file to upload and ingest.
+        config (str): The RAG configuration as a JSON string.
     
+    Returns:
+        Dict[str, Any]: A dictionary containing the created RAG ID, upload status, and index.
+    """
+    try:
+        # Parse the JSON string into a RAGConfig object
+        rag_config = RAGConfig.parse_raw(config)
+
+        # Create RAG configuration
+        rag_id = rag_factory.make_rag(rag_config)
+
+        # Ingest the file
+        task = await rag_factory.file_ingest(rag_name=rag_id, file=file)
+
+        return {
+            "rag_id": rag_id,
+            "index": task._index,
+            "status": task._status,
+            "message": "RAG created and file ingested successfully"
+        }
+    except json.JSONDecodeError:
+        return {
+            "rag_id": None,
+            "index": None,
+            "status": "ERROR",
+            "message": "Invalid JSON in config parameter"
+        }
+    except Exception as e:
+        return {
+            "rag_id": None,
+            "index": None,
+            "status": "ERROR",
+            "message": f"Error creating RAG or ingesting file: {str(e)}"
+        }
 
 @app.get("/rag-retrive/{rag_id}/{index}")
 async def rag_retrive(query: str, rag_id: str, index: str) -> list:
     """Retrieve documents based on a query for a specific RAG ID and index.
-
     Args:
         query (str): The query string to search for.
         rag_id (str): The ID of the RAG to search in.
         index (str): The index to search in.
-
     Returns:
         list: A list of documents matching the query.
     """
-    docs = await rag_factory.retrive_query(rag_name=rag_id, index=index, query=query)
+    docs = await rag_factory.retrieve_query(rag_name=rag_id, index=index, query=query)
     send_filter = [{"text": node.text, "score": node.score} for node in docs]
     return send_filter
 

bolna/models.py

@@ -171,6 +171,7 @@ class LLM(BaseModel):
     presence_penalty: Optional[float] = 0.0
     provider: Optional[str] = "openai"
     base_url: Optional[str] = None
+    extra_config: Optional[ExtraConfig] = None
 
 
 class SIMPLE_LLM_AGENT(LLM):

local_setup/ngrok-config.yml

@@ -11,7 +11,7 @@ tunnels:
   bolna-app:
     addr: bolna-app:5001
     proto: http
-  ingestion-app:
-    addr: ingestion-app:8000
-    proto: http
+  # ingestion-app:
+  #   addr: ingestion-app:8000
+  #   proto: http