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Merge pull request #1500 from ManishMadan2882/main

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Limiting Conversational history
This commit is contained in:
Alex
2024-12-19 18:23:44 +00:00
committed by GitHub
parent 8e7d5340d7 132326136a
commit 5a882fe37f
7 changed files with 46 additions and 34 deletions
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7
application/api/answer/routes.py
View File

@@ -18,7 +18,7 @@ from application.error import bad_request
from application.extensions import api
from application.llm.llm_creator import LLMCreator
from application.retriever.retriever_creator import RetrieverCreator
from application.utils import check_required_fields
from application.utils import check_required_fields, limit_chat_history
logger = logging.getLogger(__name__)
@@ -324,8 +324,7 @@ class Stream(Resource):
try:
question = data["question"]
history = str(data.get("history", []))
history = str(json.loads(history))
history = limit_chat_history(json.loads(data.get("history", [])), gpt_model=gpt_model)
conversation_id = data.get("conversation_id")
prompt_id = data.get("prompt_id", "default")
@@ -456,7 +455,7 @@ class Answer(Resource):
try:
question = data["question"]
history = data.get("history", [])
history = limit_chat_history(json.loads(data.get("history", [])), gpt_model=gpt_model)
conversation_id = data.get("conversation_id")
prompt_id = data.get("prompt_id", "default")
chunks = int(data.get("chunks", 2))

2
application/core/settings.py
View File

@@ -16,7 +16,7 @@ class Settings(BaseSettings):
MONGO_URI: str = "mongodb://localhost:27017/docsgpt"
MODEL_PATH: str = os.path.join(current_dir, "models/docsgpt-7b-f16.gguf")
DEFAULT_MAX_HISTORY: int = 150
MODEL_TOKEN_LIMITS: dict = {"gpt-3.5-turbo": 4096, "claude-2": 1e5}
MODEL_TOKEN_LIMITS: dict = {"gpt-4o-mini": 128000, "gpt-3.5-turbo": 4096, "claude-2": 1e5}
UPLOAD_FOLDER: str = "inputs"
PARSE_PDF_AS_IMAGE: bool = False
VECTOR_STORE: str = "faiss" # "faiss" or "elasticsearch" or "qdrant" or "milvus" or "lancedb"

8
application/retriever/brave_search.py
View File

@@ -2,7 +2,6 @@ import json
from application.retriever.base import BaseRetriever
from application.core.settings import settings
from application.llm.llm_creator import LLMCreator
from application.utils import num_tokens_from_string
from langchain_community.tools import BraveSearch
@@ -73,15 +72,8 @@ class BraveRetSearch(BaseRetriever):
yield {"source": doc}
if len(self.chat_history) > 1:
tokens_current_history = 0
# count tokens in history
for i in self.chat_history:
if "prompt" in i and "response" in i:
tokens_batch = num_tokens_from_string(i["prompt"]) + num_tokens_from_string(
i["response"]
)
if tokens_current_history + tokens_batch < self.token_limit:
tokens_current_history += tokens_batch
messages_combine.append(
{"role": "user", "content": i["prompt"]}
)

12
application/retriever/classic_rag.py
View File

@@ -3,7 +3,6 @@ from application.core.settings import settings
from application.vectorstore.vector_creator import VectorCreator
from application.llm.llm_creator import LLMCreator
from application.utils import num_tokens_from_string
class ClassicRAG(BaseRetriever):
@@ -73,15 +72,8 @@ class ClassicRAG(BaseRetriever):
yield {"source": doc}
if len(self.chat_history) > 1:
tokens_current_history = 0
# count tokens in history
for i in self.chat_history:
if "prompt" in i and "response" in i:
tokens_batch = num_tokens_from_string(i["prompt"]) + num_tokens_from_string(
i["response"]
)
if tokens_current_history + tokens_batch < self.token_limit:
tokens_current_history += tokens_batch
if "prompt" in i and "response" in i:
messages_combine.append(
{"role": "user", "content": i["prompt"]}
)
@@ -89,7 +81,7 @@ class ClassicRAG(BaseRetriever):
{"role": "system", "content": i["response"]}
)
messages_combine.append({"role": "user", "content": self.question})
llm = LLMCreator.create_llm(
settings.LLM_NAME, api_key=settings.API_KEY, user_api_key=self.user_api_key
)

12
application/retriever/duckduck_search.py
View File

@@ -1,7 +1,6 @@
from application.retriever.base import BaseRetriever
from application.core.settings import settings
from application.llm.llm_creator import LLMCreator
from application.utils import num_tokens_from_string
from langchain_community.tools import DuckDuckGoSearchResults
from langchain_community.utilities import DuckDuckGoSearchAPIWrapper
@@ -89,16 +88,9 @@ class DuckDuckSearch(BaseRetriever):
for doc in docs:
yield {"source": doc}
if len(self.chat_history) > 1:
tokens_current_history = 0
# count tokens in history
if len(self.chat_history) > 1:
for i in self.chat_history:
if "prompt" in i and "response" in i:
tokens_batch = num_tokens_from_string(i["prompt"]) + num_tokens_from_string(
i["response"]
)
if tokens_current_history + tokens_batch < self.token_limit:
tokens_current_history += tokens_batch
if "prompt" in i and "response" in i:
messages_combine.append(
{"role": "user", "content": i["prompt"]}
)

37
application/utils.py
View File

@@ -46,3 +46,40 @@ def check_required_fields(data, required_fields):
def get_hash(data):
return hashlib.md5(data.encode()).hexdigest()
def limit_chat_history(history, max_token_limit=None, gpt_model="docsgpt"):
"""
Limits chat history based on token count.
Returns a list of messages that fit within the token limit.
"""
from application.core.settings import settings
max_token_limit = (
max_token_limit
if max_token_limit and
max_token_limit < settings.MODEL_TOKEN_LIMITS.get(
gpt_model, settings.DEFAULT_MAX_HISTORY
)
else settings.MODEL_TOKEN_LIMITS.get(
gpt_model, settings.DEFAULT_MAX_HISTORY
)
)
if not history:
return []
tokens_current_history = 0
trimmed_history = []
for message in reversed(history):
if "prompt" in message and "response" in message:
tokens_batch = num_tokens_from_string(message["prompt"]) + num_tokens_from_string(
message["response"]
)
if tokens_current_history + tokens_batch < max_token_limit:
tokens_current_history += tokens_batch
trimmed_history.insert(0, message)
else:
break
return trimmed_history

2
frontend/package-lock.json generated
View File

@@ -1649,7 +1649,7 @@
"version": "18.3.0",
"resolved": "https://registry.npmjs.org/@types/react-dom/-/react-dom-18.3.0.tgz",
"integrity": "sha512-EhwApuTmMBmXuFOikhQLIBUn6uFg81SwLMOAUgodJF14SOBOCMdU04gDoYi0WOJJHD144TL32z4yDqCW3dnkQg==",
"devOptional": true,
"dev": true,
"dependencies": {
"@types/react": "*"
}