feat: add message tamplate

main.py

@@ -85,32 +85,13 @@ api_app = FastAPI(title="api app")
 app.mount("/api", api_app, name="api")
 app.mount("/", StaticFiles(directory="static",html = True), name="static")
 
-@api_app.post('/predict')
-async def predict(data: Predict):
-    user_prompt = data.prompt
-    if user_prompt:
-        # print(f'User Prompt: {user_prompt}')
-        # Get the answer from the chain
-        res = QA(user_prompt)
-        answer, docs = res["result"], res["source_documents"]
-
-        prompt_response_dict = {
-            "Prompt": user_prompt,
-            "Answer": answer,
-        }
-
-        prompt_response_dict["Sources"] = []
-        for document in docs:
-            prompt_response_dict["Sources"].append(
-                (os.path.basename(str(document.metadata["source"])), str(document.page_content))
-            )
-
-        return {"response": prompt_response_dict}
-    else:
-        raise HTTPException(status_code=400, detail="Prompt Incorrect")
 
 @api_app.get("/run_ingest")
 def run_ingest_route():
+    global DB
+    global RETRIEVER
+    global QA
+
     try:
         if os.path.exists(PERSIST_DIRECTORY):
             try:
@@ -121,6 +102,7 @@ def run_ingest_route():
             raise HTTPException(status_code=500, detail="The directory does not exist")
 
         run_langest_commands = ["python", "ingest.py"]
+
         if DEVICE_TYPE == "cpu":
             run_langest_commands.append("--device_type")
             run_langest_commands.append(DEVICE_TYPE)
@@ -136,6 +118,7 @@ def run_ingest_route():
             embedding_function=EMBEDDINGS,
             client_settings=CHROMA_SETTINGS,
         )
+
         RETRIEVER = DB.as_retriever()
         prompt, memory = get_prompt_template(promptTemplate_type="llama", history=False)
 
@@ -145,15 +128,53 @@ def run_ingest_route():
             retriever=RETRIEVER,
             return_source_documents=SHOW_SOURCES,
             chain_type_kwargs={
-                "prompt": prompt,
+                "prompt": QA_CHAIN_PROMPT,
             },
         )
 
         response = "Script executed successfully: {}".format(result.stdout.decode("utf-8"))
+
         return {"response": response}
     except Exception as e:
         raise HTTPException(status_code=500, detail=f"Error occurred: {str(e)}")
 
+@api_app.get("/api/delete_source", methods=["GET"])
+def delete_source_route():
+    folder_name = "SOURCE_DOCUMENTS"
+
+    if os.path.exists(folder_name):
+        shutil.rmtree(folder_name)
+
+    os.makedirs(folder_name)
+
+    return jsonify({"message": f"Folder '{folder_name}' successfully deleted and recreated."})
+
+
+@api_app.post('/predict')
+async def predict(data: Predict):
+    global QA
+    user_prompt = data.prompt
+    if user_prompt:
+        # print(f'User Prompt: {user_prompt}')
+        # Get the answer from the chain
+        res = QA(user_prompt)
+        answer, docs = res["result"], res["source_documents"]
+
+        prompt_response_dict = {
+            "Prompt": user_prompt,
+            "Answer": answer,
+        }
+
+        prompt_response_dict["Sources"] = []
+        for document in docs:
+            prompt_response_dict["Sources"].append(
+                (os.path.basename(str(document.metadata["source"])), str(document.page_content))
+            )
+
+        return {"response": prompt_response_dict}
+    else:
+        raise HTTPException(status_code=400, detail="Prompt Incorrect")
+
 @api_app.post("/save_document/")
 async def create_upload_file(file: Union[UploadFile, None] = None):
     try: