Merge branch 'arc53:main' into main

application/api/answer/routes.py

@@ -28,12 +28,15 @@ vectors_collection = db["vectors"]
 prompts_collection = db["prompts"]
 answer = Blueprint('answer', __name__)
 
-if settings.LLM_NAME == "gpt4":
-    gpt_model = 'gpt-4'
+gpt_model = ""
+# to have some kind of default behaviour
+if settings.LLM_NAME == "openai":
+    gpt_model = 'gpt-3.5-turbo'
 elif settings.LLM_NAME == "anthropic":
     gpt_model = 'claude-2'
-else:
-    gpt_model = 'gpt-3.5-turbo'
+
+if settings.MODEL_NAME:  # in case there is particular model name configured
+    gpt_model = settings.MODEL_NAME
 
 # load the prompts
 current_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
@@ -95,7 +98,7 @@ def is_azure_configured():
     return settings.OPENAI_API_BASE and settings.OPENAI_API_VERSION and settings.AZURE_DEPLOYMENT_NAME
 
 
-def complete_stream(question, docsearch, chat_history, api_key, prompt_id, conversation_id):
+def complete_stream(question, docsearch, chat_history, api_key, prompt_id, conversation_id, chunks=2):
     llm = LLMCreator.create_llm(settings.LLM_NAME, api_key=api_key)
 
     if prompt_id == 'default':
@@ -106,8 +109,11 @@ def complete_stream(question, docsearch, chat_history, api_key, prompt_id, conve
         prompt = chat_combine_strict
     else:
         prompt = prompts_collection.find_one({"_id": ObjectId(prompt_id)})["content"]
-
-    docs = docsearch.search(question, k=2)
+        
+    if chunks == 0:
+        docs = []
+    else:
+        docs = docsearch.search(question, k=chunks)
     if settings.LLM_NAME == "llama.cpp":
         docs = [docs[0]]
     # join all page_content together with a newline
@@ -190,6 +196,10 @@ def stream():
         prompt_id = data["prompt_id"]
     else:
         prompt_id = 'default'
+    if 'chunks' in data:
+        chunks = int(data["chunks"])
+    else:
+        chunks = 2
 
     # check if active_docs is set
 
@@ -211,7 +221,8 @@ def stream():
         complete_stream(question, docsearch,
                         chat_history=history, api_key=api_key,
                         prompt_id=prompt_id,
-                        conversation_id=conversation_id), mimetype="text/event-stream"
+                        conversation_id=conversation_id,
+                        chunks=chunks), mimetype="text/event-stream"
     )
 
 
@@ -237,6 +248,10 @@ def api_answer():
         prompt_id = data["prompt_id"]
     else:
         prompt_id = 'default'
+    if 'chunks' in data:
+        chunks = int(data["chunks"])
+    else:
+        chunks = 2
 
     if prompt_id == 'default':
         prompt = chat_combine_template
@@ -260,7 +275,10 @@ def api_answer():
 
 
 
-        docs = docsearch.search(question, k=2)
+        if chunks == 0:
+            docs = []
+        else:
+            docs = docsearch.search(question, k=chunks)
         # join all page_content together with a newline
         docs_together = "\n".join([doc.page_content for doc in docs])
         p_chat_combine = prompt.replace("{summaries}", docs_together)
@@ -359,9 +377,15 @@ def api_search():
         vectorstore = get_vectorstore({"active_docs": data["active_docs"]})
     else:
         vectorstore = ""
+    if 'chunks' in data:
+        chunks = int(data["chunks"])
+    else:
+        chunks = 2
     docsearch = VectorCreator.create_vectorstore(settings.VECTOR_STORE, vectorstore, embeddings_key)
-
-    docs = docsearch.search(question, k=2)
+    if chunks == 0:
+        docs = []
+    else:
+        docs = docsearch.search(question, k=chunks)
 
     source_log_docs = []
     for doc in docs:

application/core/settings.py

@@ -9,6 +9,7 @@ current_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__
 
 class Settings(BaseSettings):
     LLM_NAME: str = "docsgpt"
+    MODEL_NAME: Optional[str] = None # when LLM_NAME is openai, MODEL_NAME can be e.g. gpt-4-turbo-preview or gpt-3.5-turbo
     EMBEDDINGS_NAME: str = "huggingface_sentence-transformers/all-mpnet-base-v2"
     CELERY_BROKER_URL: str = "redis://localhost:6379/0"
     CELERY_RESULT_BACKEND: str = "redis://localhost:6379/1"