mirror of
https://github.com/arc53/DocsGPT.git
synced 2025-11-29 08:33:20 +00:00
fix: minor ui fix + added req changes
This commit is contained in:
Siddhant Rai
@@ -74,7 +74,7 @@ def run_async_chain(chain, question, chat_history):
|
||||
|
||||
def get_data_from_api_key(api_key):
|
||||
data = api_key_collection.find_one({"key": api_key})
|
||||
|
||||
|
||||
# # Raise custom exception if the API key is not found
|
||||
if data is None:
|
||||
raise Exception("Invalid API Key, please generate new key", 401)
|
||||
@@ -129,10 +129,10 @@ def save_conversation(conversation_id, question, response, source_log_docs, llm)
|
||||
"content": "Summarise following conversation in no more than 3 "
|
||||
"words, respond ONLY with the summary, use the same "
|
||||
"language as the system \n\nUser: "
|
||||
+question
|
||||
+"\n\n"
|
||||
+"AI: "
|
||||
+response,
|
||||
+ question
|
||||
+ "\n\n"
|
||||
+ "AI: "
|
||||
+ response,
|
||||
},
|
||||
{
|
||||
"role": "user",
|
||||
@@ -172,7 +172,9 @@ def get_prompt(prompt_id):
|
||||
return prompt
|
||||
|
||||
|
||||
def complete_stream(question, retriever, conversation_id, user_api_key):
|
||||
def complete_stream(
|
||||
question, retriever, conversation_id, user_api_key, isNoneDoc=False
|
||||
):
|
||||
|
||||
try:
|
||||
response_full = ""
|
||||
@@ -186,126 +188,136 @@ def complete_stream(question, retriever, conversation_id, user_api_key):
|
||||
elif "source" in line:
|
||||
source_log_docs.append(line["source"])
|
||||
|
||||
if isNoneDoc:
|
||||
for doc in source_log_docs:
|
||||
doc["source"] = "None"
|
||||
|
||||
llm = LLMCreator.create_llm(
|
||||
settings.LLM_NAME, api_key=settings.API_KEY, user_api_key=user_api_key
|
||||
)
|
||||
if(user_api_key is None):
|
||||
)
|
||||
if user_api_key is None:
|
||||
conversation_id = save_conversation(
|
||||
conversation_id, question, response_full, source_log_docs, llm
|
||||
)
|
||||
# send data.type = "end" to indicate that the stream has ended as json
|
||||
data = json.dumps({"type": "id", "id": str(conversation_id)})
|
||||
yield f"data: {data}\n\n"
|
||||
|
||||
|
||||
data = json.dumps({"type": "end"})
|
||||
yield f"data: {data}\n\n"
|
||||
except Exception as e:
|
||||
print("\033[91merr", str(e), file=sys.stderr)
|
||||
data = json.dumps({"type": "error","error":"Please try again later. We apologize for any inconvenience.",
|
||||
"error_exception": str(e)})
|
||||
data = json.dumps(
|
||||
{
|
||||
"type": "error",
|
||||
"error": "Please try again later. We apologize for any inconvenience.",
|
||||
"error_exception": str(e),
|
||||
}
|
||||
)
|
||||
yield f"data: {data}\n\n"
|
||||
return
|
||||
return
|
||||
|
||||
|
||||
@answer.route("/stream", methods=["POST"])
|
||||
def stream():
|
||||
try:
|
||||
data = request.get_json()
|
||||
# get parameter from url question
|
||||
question = data["question"]
|
||||
if "history" not in data:
|
||||
history = []
|
||||
else:
|
||||
history = data["history"]
|
||||
history = json.loads(history)
|
||||
if "conversation_id" not in data:
|
||||
conversation_id = None
|
||||
else:
|
||||
conversation_id = data["conversation_id"]
|
||||
if "prompt_id" in data:
|
||||
prompt_id = data["prompt_id"]
|
||||
else:
|
||||
prompt_id = "default"
|
||||
if "selectedDocs" in data and data["selectedDocs"] is None:
|
||||
chunks = 0
|
||||
elif "chunks" in data:
|
||||
chunks = int(data["chunks"])
|
||||
else:
|
||||
chunks = 2
|
||||
if "token_limit" in data:
|
||||
token_limit = data["token_limit"]
|
||||
else:
|
||||
token_limit = settings.DEFAULT_MAX_HISTORY
|
||||
try:
|
||||
data = request.get_json()
|
||||
question = data["question"]
|
||||
if "history" not in data:
|
||||
history = []
|
||||
else:
|
||||
history = data["history"]
|
||||
history = json.loads(history)
|
||||
if "conversation_id" not in data:
|
||||
conversation_id = None
|
||||
else:
|
||||
conversation_id = data["conversation_id"]
|
||||
if "prompt_id" in data:
|
||||
prompt_id = data["prompt_id"]
|
||||
else:
|
||||
prompt_id = "default"
|
||||
if "selectedDocs" in data and data["selectedDocs"] is None:
|
||||
chunks = 0
|
||||
elif "chunks" in data:
|
||||
chunks = int(data["chunks"])
|
||||
else:
|
||||
chunks = 2
|
||||
if "token_limit" in data:
|
||||
token_limit = data["token_limit"]
|
||||
else:
|
||||
token_limit = settings.DEFAULT_MAX_HISTORY
|
||||
|
||||
# check if active_docs or api_key is set
|
||||
# check if active_docs or api_key is set
|
||||
|
||||
if "api_key" in data:
|
||||
data_key = get_data_from_api_key(data["api_key"])
|
||||
chunks = int(data_key["chunks"])
|
||||
prompt_id = data_key["prompt_id"]
|
||||
source = {"active_docs": data_key["source"]}
|
||||
user_api_key = data["api_key"]
|
||||
elif "active_docs" in data:
|
||||
source = {"active_docs": data["active_docs"]}
|
||||
user_api_key = None
|
||||
else:
|
||||
source = {}
|
||||
user_api_key = None
|
||||
if "api_key" in data:
|
||||
data_key = get_data_from_api_key(data["api_key"])
|
||||
chunks = int(data_key["chunks"])
|
||||
prompt_id = data_key["prompt_id"]
|
||||
source = {"active_docs": data_key["source"]}
|
||||
user_api_key = data["api_key"]
|
||||
elif "active_docs" in data:
|
||||
source = {"active_docs": data["active_docs"]}
|
||||
user_api_key = None
|
||||
else:
|
||||
source = {}
|
||||
user_api_key = None
|
||||
|
||||
if (
|
||||
source["active_docs"].split("/")[0] == "default"
|
||||
or source["active_docs"].split("/")[0] == "local"
|
||||
):
|
||||
retriever_name = "classic"
|
||||
else:
|
||||
retriever_name = source["active_docs"]
|
||||
if source["active_docs"].split("/")[0] in ["default", "local"]:
|
||||
retriever_name = "classic"
|
||||
else:
|
||||
retriever_name = source["active_docs"]
|
||||
|
||||
prompt = get_prompt(prompt_id)
|
||||
prompt = get_prompt(prompt_id)
|
||||
|
||||
retriever = RetrieverCreator.create_retriever(
|
||||
retriever_name,
|
||||
question=question,
|
||||
source=source,
|
||||
chat_history=history,
|
||||
prompt=prompt,
|
||||
chunks=chunks,
|
||||
token_limit=token_limit,
|
||||
gpt_model=gpt_model,
|
||||
user_api_key=user_api_key,
|
||||
)
|
||||
|
||||
return Response(
|
||||
complete_stream(
|
||||
retriever = RetrieverCreator.create_retriever(
|
||||
retriever_name,
|
||||
question=question,
|
||||
retriever=retriever,
|
||||
conversation_id=conversation_id,
|
||||
source=source,
|
||||
chat_history=history,
|
||||
prompt=prompt,
|
||||
chunks=chunks,
|
||||
token_limit=token_limit,
|
||||
gpt_model=gpt_model,
|
||||
user_api_key=user_api_key,
|
||||
),
|
||||
mimetype="text/event-stream",
|
||||
)
|
||||
|
||||
except ValueError:
|
||||
message = "Malformed request body"
|
||||
print("\033[91merr", str(message), file=sys.stderr)
|
||||
return Response(
|
||||
error_stream_generate(message),
|
||||
status=400,
|
||||
mimetype="text/event-stream",
|
||||
)
|
||||
except Exception as e:
|
||||
)
|
||||
|
||||
return Response(
|
||||
complete_stream(
|
||||
question=question,
|
||||
retriever=retriever,
|
||||
conversation_id=conversation_id,
|
||||
user_api_key=user_api_key,
|
||||
isNoneDoc=data.get("isNoneDoc"),
|
||||
),
|
||||
mimetype="text/event-stream",
|
||||
)
|
||||
|
||||
except ValueError:
|
||||
message = "Malformed request body"
|
||||
print("\033[91merr", str(message), file=sys.stderr)
|
||||
return Response(
|
||||
error_stream_generate(message),
|
||||
status=400,
|
||||
mimetype="text/event-stream",
|
||||
)
|
||||
except Exception as e:
|
||||
print("\033[91merr", str(e), file=sys.stderr)
|
||||
message = e.args[0]
|
||||
status_code = 400
|
||||
# # Custom exceptions with two arguments, index 1 as status code
|
||||
if(len(e.args) >= 2):
|
||||
if len(e.args) >= 2:
|
||||
status_code = e.args[1]
|
||||
return Response(
|
||||
error_stream_generate(message),
|
||||
status=status_code,
|
||||
mimetype="text/event-stream",
|
||||
)
|
||||
error_stream_generate(message),
|
||||
status=status_code,
|
||||
mimetype="text/event-stream",
|
||||
)
|
||||
|
||||
|
||||
def error_stream_generate(err_response):
|
||||
data = json.dumps({"type": "error", "error":err_response})
|
||||
yield f"data: {data}\n\n"
|
||||
data = json.dumps({"type": "error", "error": err_response})
|
||||
yield f"data: {data}\n\n"
|
||||
|
||||
|
||||
@answer.route("/api/answer", methods=["POST"])
|
||||
def api_answer():
|
||||
@@ -346,10 +358,7 @@ def api_answer():
|
||||
source = data
|
||||
user_api_key = None
|
||||
|
||||
if (
|
||||
source["active_docs"].split("/")[0] == "default"
|
||||
or source["active_docs"].split("/")[0] == "local"
|
||||
):
|
||||
if source["active_docs"].split("/")[0] in ["default", "local"]:
|
||||
retriever_name = "classic"
|
||||
else:
|
||||
retriever_name = source["active_docs"]
|
||||
@@ -375,6 +384,10 @@ def api_answer():
|
||||
elif "answer" in line:
|
||||
response_full += line["answer"]
|
||||
|
||||
if data.get("isNoneDoc"):
|
||||
for doc in source_log_docs:
|
||||
doc["source"] = "None"
|
||||
|
||||
llm = LLMCreator.create_llm(
|
||||
settings.LLM_NAME, api_key=settings.API_KEY, user_api_key=user_api_key
|
||||
)
|
||||
@@ -395,7 +408,6 @@ def api_answer():
|
||||
@answer.route("/api/search", methods=["POST"])
|
||||
def api_search():
|
||||
data = request.get_json()
|
||||
# get parameter from url question
|
||||
question = data["question"]
|
||||
if "chunks" in data:
|
||||
chunks = int(data["chunks"])
|
||||
@@ -413,10 +425,7 @@ def api_search():
|
||||
source = {}
|
||||
user_api_key = None
|
||||
|
||||
if (
|
||||
source["active_docs"].split("/")[0] == "default"
|
||||
or source["active_docs"].split("/")[0] == "local"
|
||||
):
|
||||
if source["active_docs"].split("/")[0] in ["default", "local"]:
|
||||
retriever_name = "classic"
|
||||
else:
|
||||
retriever_name = source["active_docs"]
|
||||
@@ -437,4 +446,9 @@ def api_search():
|
||||
user_api_key=user_api_key,
|
||||
)
|
||||
docs = retriever.search()
|
||||
|
||||
if data.get("isNoneDoc"):
|
||||
for doc in docs:
|
||||
doc["source"] = "None"
|
||||
|
||||
return docs
|
||||
|
||||
Reference in New Issue
Block a user