@@ -1,5 +1,5 @@
-import base64
 import itertools
+import base64
 import logging
 import subprocess
 import time
@@ -23,6 +23,7 @@ from langchain.memory import ConversationTokenBufferMemory
 from langchain_community.tools.google_serper import GoogleSerperResults
 from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, SystemMessage
 from langchain_core.prompts.prompt import PromptTemplate
+from langchain_core.runnables import RunnableWithMessageHistory
 from langchain_openai.chat_models import ChatOpenAI
 from langchain_text_splitters import RecursiveCharacterTextSplitter
 from PIL import Image
@@ -183,26 +184,26 @@ class Chatgpt(SimpleService):
         ):
             self.llm.tiktoken_model_name = 'gpt-4'
         chat_history = self.get_chat_history()
-        conversation = ConversationChain(
-            llm=self.llm,
-            memory=chat_history,
-            prompt=PromptTemplate(
-                input_variables=['history', 'input'],
-                template='Human: История диалога:{history}. Human: {input} AI:',
-            ),
+        conversation = RunnableWithMessageHistory(
+            runnable=self.llm,
+            get_session_history= lambda _: self.get_chat_history().chat_memory
         )
         llm_input = HumanMessage(content=input_content)
         if file and not image:
             input_tokens = self.count_text_tokens(
                 [*chat_history.buffer_as_messages, llm_input, *chunks]
             )
+        elif image:
+            input_tokens = self.count_text_tokens(
+                [llm_input]
+            )
         else:
             input_tokens = self.count_text_tokens(
                 [*chat_history.buffer_as_messages, llm_input]
             )
         self.assert_enough_balance(input_tokens, image_size, model=self.llm.model_name)
         if image:
-            response = conversation.llm.invoke([llm_input])
+            response = self.llm.invoke([llm_input])
             chat_history.chat_memory.add_ai_message(response)
         elif file:
             human_messages = []
@@ -217,8 +218,10 @@ class Chatgpt(SimpleService):
                 ]
                 human_message = HumanMessage(content=prompt)
                 human_messages.append(human_message)
-                invoked = conversation.invoke([human_message])
-                response = AIMessage(content=invoked['response'])
+                response = conversation.invoke(
+                    {'input': human_message.content[0]['text']},
+                    config={"configurable": {"session_id": "default"}}
+                )
                 chunk_responses.append(response.content)
             combined_summary = ' '.join(chunk_responses)
             user_prompt = input_message.content if input_message.content.split() else 'Суммируй текст'
@@ -228,7 +231,10 @@ class Chatgpt(SimpleService):
             )
             input = HumanMessage(content=question_content)
             input_tokens = self.count_text_tokens(human_messages + [input])
-            response = conversation.llm.invoke([input])
+            response = conversation.invoke(
+                {'input': human_message.content[0]['text']},
+                config={"configurable": {"session_id": "default"}}
+            )
         elif info.get('use_web', False):
             prompt_schema = hub.pull('hwchase17/structured-chat-agent')
             tools = [GoogleSerperResults()]
@@ -296,8 +302,10 @@ class Chatgpt(SimpleService):
                     raise Exception('GPT not answer correctly, please retry later')
         else:
             # Somehow this chain doesn't support Vision, even though ChatOpenAI (above) does.
-            invoked = conversation.invoke([llm_input])
-            response = AIMessage(content=invoked['response'])
+            response = conversation.invoke(
+                {'input': llm_input.content[0]['text']},
+                config={"configurable": {"session_id": "default"}}
+            )
             chat_history.chat_memory.add_ai_message(response)
         process_time = timedelta(seconds=time.time() - start_time)
 
@@ -425,7 +433,7 @@ class Chatgpt(SimpleService):
         )
 
     def count_text_tokens(self, messages: list[BaseMessage]) -> int:
-        encoding = tiktoken.get_encoding('cl100k_base')
+        encoding = tiktoken.get_encoding('o200k_base')
         total_tokens = 0
         for message in messages:
             total_tokens += len(
@@ -64,10 +64,7 @@ class Epicphotogasm(SimpleService):
                     content_object=self.store,
                     elapsed_time=t,
                     content=input_prompt,
-                    file=File(
-                        BytesIO(requests.get(link).content),
-                        link.split('/')[-1],
-                    ),
+                    file=File(BytesIO(requests.get(link).content), '.png'),
                 )
             )
         if self.store:
@@ -18,6 +18,7 @@ from ml_model.models import (
     ModelVersion,
 )
 from ml_model.services.base import SimpleService
+from ml_model.tasks import replicate_run
 
 
 class Flux(SimpleService):
@@ -148,69 +149,28 @@ class Flux(SimpleService):
         ),
     }
 
-    def __init__(self, store: BaseStore) -> None:
-        super().__init__(store)
-        self.bfl_urls = {
+    _CALLBACK_BASE = 'black-forest-labs/'
+
+    def _call_bfl_api(self, payload: dict) -> list:
+        bfl_headers = {
+            'Content-Type': 'application/json',
+            'X-Key': settings.FLUX_API_KEY,
+        }
+        bfl_urls = {
             'generate': 'https://api.bfl.ml/v1/',
             'get': 'https://api.bfl.ml/v1/get_result?id=',
         }
-        self.replicate_urls = {
-            'generate': 'https://api.replicate.com/v1/models/black-forest-labs/',
-            'get': 'https://api.replicate.com/v1/predictions/',
-        }
-
-    def _get_results(
-            self, url: str, generation_id: str, headers: dict, statuses: tuple
-    ) -> dict:
-        result = requests.get(url=f'{url}{generation_id}', headers=headers)
-        while result.json()['status'] not in statuses:
-            result = requests.get(url=f'{url}{generation_id}', headers=headers)
-        return result.json()
-
-    def _call_api(self, payload: dict) -> list:
-        if payload['version'] == self.versions[0].slug:
-            bfl_headers = {
-                'Content-Type': 'application/json',
-                'X-Key': settings.FLUX_API_KEY,
-            }
-            response = requests.post(
-                url=f'{self.bfl_urls['generate']}{payload['version']}',
-                headers=bfl_headers,
-                json=payload,
-            )
-            if response.status_code != 200:
-                raise Exception(response.json())
-
-            return [
-                self._get_results(
-                    self.bfl_urls['get'],
-                    response.json().get('id'),
-                    bfl_headers,
-                    ('Ready', 'Error'),
-                )['result']['sample']
-            ]
-        else:
-            replicate_headers = {
-                'Authorization': f'Bearer {settings.REPLICATE_API_KEY}',
-                'Prefer': 'wait',
-            }
-            data = {'input': payload}
-            response = requests.post(
-                url=f'{self.replicate_urls['generate']}{payload['version']}/predictions',
-                headers=replicate_headers,
-                json=data,
-            )
-            if response.status_code != 201:
-                raise Exception(response.json())
-
-            result = self._get_results(
-                self.replicate_urls['get'],
-                response.json().get('id'),
-                replicate_headers,
-                ('succeeded', 'failed', 'canceled'),
-            )['output']
-
-            return result if isinstance(result, list) else [result]
+        response = requests.post(
+            url=f'{bfl_urls['generate']}{payload['version']}',
+            headers=bfl_headers,
+            json=payload,
+        )
+        if response.status_code != 200:
+            raise Exception(response.json())
+        result = requests.get(url=f'{bfl_urls['get']}{response.json().get('id')}', headers=bfl_headers)
+        while result.json()['status'] not in ('Ready', 'Error'):
+            result = requests.get(url=f'{bfl_urls['get']}{response.json().get('id')}', headers=bfl_headers)
+        return result.json()['result']['sample']
 
     def calculate_price(self, input_message: Message) -> Decimal:
         version_slug = input_message.info.get('version', 'flux-pro-1.1')
@@ -218,7 +178,10 @@ class Flux(SimpleService):
         if not payment_rule.pk:
             payment_rule.model = self.neuron_model
             payment_rule.save()
-        return payment_rule.rate * input_message.info.get('num_outputs', 1)
+        if version_slug in (self.versions[1].slug,):
+            return payment_rule.rate * input_message.info.get('num_outputs', 1)
+        else:
+            return payment_rule.rate
 
     def save_results(
             self,
@@ -259,7 +222,11 @@ class Flux(SimpleService):
             )
             input_message.file.close()
             callback_data.update({'image': image})
-        images = self._call_api(payload=callback_data)
+        if callback_data['version'] == 'flux-pro-1.1':
+            images = [self._call_bfl_api(payload=callback_data)]
+        else:
+            runner = replicate_run(f'{self._CALLBACK_BASE}{callback_data['version']}', callback_data)
+            images = runner if isinstance(runner, list) else [runner]
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(input_message.content_object.model, input_message)
         msgs = self.save_results(input_message.content, images, process_time, save)
@@ -73,10 +73,7 @@ class Kandinsky(SimpleService):
                     content_object=self.store,
                     elapsed_time=t,
                     content=input_prompt,
-                    file=File(
-                        BytesIO(requests.get(link).content),
-                        link.split('/')[-1],
-                    ),
+                    file=File(BytesIO(requests.get(link).content), '.png'),
                 )
             )
         if self.store:
@@ -89,10 +86,19 @@ class Kandinsky(SimpleService):
         activation_prompt = f'{translated_prompt}'
         negative_prompt = input_message.info.pop('negative_prompt', '')
         callback_data = dict(
-            prompt=f"Do not include any nudity, sexual content, or suggestive themes. "
-                   "Avoid any graphic violence, explicit scenes, or offensive symbols. "
-                   f"Generate a safe version of this: {activation_prompt}",
-            negative_prompt=negative_prompt,
+            prompt=activation_prompt,
+            negative_prompt=(
+                "any form of nudity, sexual content, explicit or suggestive themes, "
+                "graphic violence, disturbing imagery, offensive symbols, hate speech, abusive language, "
+                "discriminatory content, illegal activities, or any form of inappropriate or harmful material. "
+                "This includes, but is not limited to, full or partial nudity, suggestive body imagery, sexual innuendos, "
+                "pornographic content, sexual acts, and anything that could be perceived as sexual or inappropriate. "
+                "Also, avoid any form of graphic violence, torture, gore, blood, or injury depiction. "
+                "Do not include offensive symbols, hate speech, racial or ethnic slurs, or any material promoting hatred or discrimination. "
+                "Any content promoting illegal activities, substance abuse, self-harm, or violence is strictly prohibited. "
+                "Furthermore, avoid any content that is offensive, harmful, inappropriate for minors, or unsuitable for a general audience. "
+                f"Additionally, {negative_prompt} should be strictly avoided in any generated material."
+            ),
             **input_message.info,
         )
         result = replicate_run(self._CALLBACK, callback_data)
@@ -64,10 +64,7 @@ class Musicgen(SimpleService):
             Message(
                 content_object=self.store,
                 elapsed_time=t,
-                file=File(
-                    BytesIO(requests.get(r).content),
-                    r.split('/')[-1],
-                ),
+                file=File(BytesIO(requests.get(r).content), '.wav'),
             )
         ]
         if save:
@@ -66,10 +66,7 @@ class Openjourney(SimpleService):
                     content_object=self.store,
                     elapsed_time=t,
                     content=input_prompt,
-                    file=File(
-                        BytesIO(requests.get(link).content),
-                        link.split('/')[-1],
-                    ),
+                    file=File(BytesIO(requests.get(link).content), '.png'),
                 )
             )
         if save:
@@ -15,6 +15,7 @@ from ml_model.models import (
     ModelVersion,
 )
 from ml_model.services.base import SimpleService
+from ml_model.tasks import replicate_run
 
 
 class Recraft(SimpleService):
@@ -97,11 +98,6 @@ class Recraft(SimpleService):
         versions[1].slug: Decimal('44'),
     }
 
-    def __init__(self, store: BaseStore) -> None:
-        super().__init__(store)
-        self.generate_url = 'https://api.replicate.com/v1/models/recraft-ai/'
-        self.get_url = 'https://api.replicate.com/v1/predictions/'
-
     def _get_size(self, width: int, height: int) -> str:
         available_sizes = (
             (1024, 1024), (1365, 1024), (1024, 1365), (1536, 1024), (1024, 1536),
@@ -114,26 +110,6 @@ class Recraft(SimpleService):
             size = min(available_sizes, key=lambda size: abs(height - size[1]))
         return f'{size[0]}x{size[1]}'
 
-    def _call_api(self, payload: dict) -> list:
-        headers = {
-            'Authorization': f'Bearer {settings.REPLICATE_API_KEY}',
-            'Content-Type': 'application/json',
-            'Prefer': 'wait',
-        }
-        data = {'input': payload}
-        response = requests.post(
-            url=f'{self.generate_url}{payload.get('version', 'recraft-v3')}/predictions',
-            headers=headers,
-            json=data,
-        )
-        if response.status_code != 201:
-            raise Exception(response.json())
-
-        result = requests.get(url=f'{self.get_url}{response.json().get('id')}', headers=headers)
-        while result.json()['status'] not in ('succeeded', 'failed', 'canceled'):
-            result = requests.get(url=f'{self.get_url}{response.json().get('id')}', headers=headers)
-        return result.json()['output']
-
     def calculate_price(self, input_message: Message) -> Decimal:
         return self.payment_rules[input_message.info.get('version', 'recraft-v3')]
 
@@ -187,6 +163,7 @@ class Recraft(SimpleService):
         start_time = time.time()
         extension = '.svg' if input_message.info.get('version', 'recraft-v3') == self.versions[1].slug else '.png'
         size = self._get_size(input_message.info.pop('width', 1024), input_message.info.pop('height', 1024))
+        callback_url = f'recraft-ai/{input_message.info.get('version', 'recraft-v3')}'
         callback_data = dict(
             {
                 'prompt': (
@@ -198,7 +175,7 @@ class Recraft(SimpleService):
                 **input_message.info
             }
         )
-        image = self._call_api(payload=callback_data)
+        image = replicate_run(callback_url, callback_data)
         process_time = timedelta(seconds=(time.time() - start_time))
         self.handle_invoice(input_message.content_object.model, input_message)
         message = self.save_results(input_message.content, image, extension, process_time, save)
@@ -5,7 +5,6 @@ from ml_model.models import (
     ModelInput,
     ModelParameter,
     ModelSettings,
-    ModelStat,
     ModelVersion,
     NeuronModel,
 )
@@ -39,12 +38,6 @@ class ModelInputSerializer(serializers.ModelSerializer):
         exclude = ('id', 'model')
 
 
-class ModelStatSerializer(serializers.ModelSerializer):
-    class Meta:
-        model = ModelStat
-        exclude = ('id', 'created_at', 'model')
-
-
 class NeuronModelSerializer(serializers.ModelSerializer):
     settings = ModelSettingsSerializer()
     parameters = ModelParameterSerializer(many=True)
@@ -107,7 +107,7 @@ def transcript_audio(payload: dict[str, Any]):
 def replicate_run(callback_url: str, payload: dict[str, Any]):
     replicate_client = replicate.Client(settings.REPLICATE_API_KEY)
     return replicate_client.run(
-        model_version=callback_url,
+        ref=callback_url,
         input=payload,
     )
 
@@ -1,42 +1,25 @@
 .DEFAULT_GOAL=start
 
-# default startup
 start:
 	cp --update=none .env.dist .env
 	docker compose -f docker-compose.debug.yml --project-name air up
 .PHONY=start
 
-# fully rebuild with deps
 rebuild:
 	cp --update=none .env.dist .env
 	docker compose -f docker-compose.debug.yml --project-name air up --build
 .PHONY=rebuild
 
-# only create migrations
-migrations:
-	docker exec -ti migrator sh -c 'python manage.py makemigrations'
-
-# only migrate existing migrations
-migrate:
-	docker exec -ti migrator sh -c 'python manage.py migrate'
-
-# makemigrations && migrate
-fmigrate:
-	docker exec -ti migrator sh -c 'python manage.py makemigrations && python manage.py migrate'
-
-# remove containers and orphans
 stop:
 	cp --update=none .env.dist .env
 	docker compose -f docker-compose.debug.yml --project-name air down --remove-orphans
 .PHONY=stop
 
-# cleanup with volumes
 cleanup:
 	cp --update=none .env.dist .env
 	docker compose -f docker-compose.debug.yml --project-name air down --remove-orphans -v
 .PHONY=cleanup
 
-# cleanup volumes, images, project
 full-cleanup:
 	cp --update=none .env.dist .env
 	docker compose -f docker-compose.debug.yml --project-name air down --remove-orphans -v --rmi local
@@ -1813,20 +1813,24 @@ test = ["cffi (>=1.17.1)", "coverage (>=5.0)", "dnspython (>=1.16.0,<2.0)", "idn
 
 [[package]]
 name = "google-ai-generativelanguage"
-version = "0.4.0"
+version = "0.6.15"
 description = "Google Ai Generativelanguage API client library"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
-    {file = "google-ai-generativelanguage-0.4.0.tar.gz", hash = "sha256:c8199066c08f74c4e91290778329bb9f357ba1ea5d6f82de2bc0d10552bf4f8c"},
-    {file = "google_ai_generativelanguage-0.4.0-py3-none-any.whl", hash = "sha256:e4c425376c1ee26c78acbc49a24f735f90ebfa81bf1a06495fae509a2433232c"},
+    {file = "google_ai_generativelanguage-0.6.15-py3-none-any.whl", hash = "sha256:5a03ef86377aa184ffef3662ca28f19eeee158733e45d7947982eb953c6ebb6c"},
+    {file = "google_ai_generativelanguage-0.6.15.tar.gz", hash = "sha256:8f6d9dc4c12b065fe2d0289026171acea5183ebf2d0b11cefe12f3821e159ec3"},
 ]
 
 [package.dependencies]
-google-api-core = {version = ">=1.34.0,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
-proto-plus = ">=1.22.3,<2.0.0dev"
-protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
+google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
+google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0dev"
+proto-plus = [
+    {version = ">=1.22.3,<2.0.0dev", markers = "python_version < \"3.13\""},
+    {version = ">=1.25.0,<2.0.0dev", markers = "python_version >= \"3.13\""},
+]
+protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0dev"
 
 [[package]]
 name = "google-api-core"
@@ -1858,6 +1862,25 @@ grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status
 grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
+[[package]]
+name = "google-api-python-client"
+version = "2.161.0"
+description = "Google API Client Library for Python"
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "google_api_python_client-2.161.0-py2.py3-none-any.whl", hash = "sha256:9476a5a4f200bae368140453df40f9cda36be53fa7d0e9a9aac4cdb859a26448"},
+    {file = "google_api_python_client-2.161.0.tar.gz", hash = "sha256:324c0cce73e9ea0a0d2afd5937e01b7c2d6a4d7e2579cdb6c384f9699d6c9f37"},
+]
+
+[package.dependencies]
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0.dev0"
+google-auth = ">=1.32.0,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0.dev0"
+google-auth-httplib2 = ">=0.2.0,<1.0.0"
+httplib2 = ">=0.19.0,<1.dev0"
+uritemplate = ">=3.0.1,<5"
+
 [[package]]
 name = "google-auth"
 version = "2.37.0"
@@ -1883,22 +1906,40 @@ pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
 requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
+[[package]]
+name = "google-auth-httplib2"
+version = "0.2.0"
+description = "Google Authentication Library: httplib2 transport"
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
+    {file = "google-auth-httplib2-0.2.0.tar.gz", hash = "sha256:38aa7badf48f974f1eb9861794e9c0cb2a0511a4ec0679b1f886d108f5640e05"},
+    {file = "google_auth_httplib2-0.2.0-py2.py3-none-any.whl", hash = "sha256:b65a0a2123300dd71281a7bf6e64d65a0759287df52729bdd1ae2e47dc311a3d"},
+]
+
+[package.dependencies]
+google-auth = "*"
+httplib2 = ">=0.19.0"
+
 [[package]]
 name = "google-generativeai"
-version = "0.3.2"
+version = "0.8.4"
 description = "Google Generative AI High level API client library and tools."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "google_generativeai-0.3.2-py3-none-any.whl", hash = "sha256:8761147e6e167141932dc14a7b7af08f2310dd56668a78d206c19bb8bd85bcd7"},
+    {file = "google_generativeai-0.8.4-py3-none-any.whl", hash = "sha256:e987b33ea6decde1e69191ddcaec6ef974458864d243de7191db50c21a7c5b82"},
 ]
 
 [package.dependencies]
-google-ai-generativelanguage = "0.4.0"
+google-ai-generativelanguage = "0.6.15"
 google-api-core = "*"
-google-auth = "*"
+google-api-python-client = "*"
+google-auth = ">=2.15.0"
 protobuf = "*"
+pydantic = "*"
 tqdm = "*"
 typing-extensions = "*"
 
@@ -2196,6 +2237,21 @@ http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
 trio = ["trio (>=0.22.0,<1.0)"]
 
+[[package]]
+name = "httplib2"
+version = "0.22.0"
+description = "A comprehensive HTTP client library."
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+groups = ["main"]
+files = [
+    {file = "httplib2-0.22.0-py3-none-any.whl", hash = "sha256:14ae0a53c1ba8f3d37e9e27cf37eabb0fb9980f435ba405d546948b009dd64dc"},
+    {file = "httplib2-0.22.0.tar.gz", hash = "sha256:d7a10bc5ef5ab08322488bde8c726eeee5c8618723fdb399597ec58f3d82df81"},
+]
+
+[package.dependencies]
+pyparsing = {version = ">=2.4.2,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.0.2 || >3.0.2,<3.0.3 || >3.0.3,<4", markers = "python_version > \"3.0\""}
+
 [[package]]
 name = "httptools"
 version = "0.6.4"
@@ -2575,148 +2631,144 @@ zookeeper = ["kazoo (>=2.8.0)"]
 
 [[package]]
 name = "langchain"
-version = "0.1.20"
+version = "0.3.19"
 description = "Building applications with LLMs through composability"
 optional = false
-python-versions = "<4.0,>=3.8.1"
+python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain-0.1.20-py3-none-any.whl", hash = "sha256:09991999fbd6c3421a12db3c7d1f52d55601fc41d9b2a3ef51aab2e0e9c38da9"},
-    {file = "langchain-0.1.20.tar.gz", hash = "sha256:f35c95eed8c8375e02dce95a34f2fd4856a4c98269d6dc34547a23dba5beab7e"},
+    {file = "langchain-0.3.19-py3-none-any.whl", hash = "sha256:1e16d97db9106640b7de4c69f8f5ed22eeda56b45b9241279e83f111640eff16"},
+    {file = "langchain-0.3.19.tar.gz", hash = "sha256:b96f8a445f01d15d522129ffe77cc89c8468dbd65830d153a676de8f6b899e7b"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
-dataclasses-json = ">=0.5.7,<0.7"
-langchain-community = ">=0.0.38,<0.1"
-langchain-core = ">=0.1.52,<0.2.0"
-langchain-text-splitters = ">=0.0.1,<0.1"
-langsmith = ">=0.1.17,<0.2.0"
-numpy = ">=1,<2"
-pydantic = ">=1,<3"
+langchain-core = ">=0.3.35,<1.0.0"
+langchain-text-splitters = ">=0.3.6,<1.0.0"
+langsmith = ">=0.1.17,<0.4"
+numpy = {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""}
+pydantic = ">=2.7.4,<3.0.0"
 PyYAML = ">=5.3"
 requests = ">=2,<3"
 SQLAlchemy = ">=1.4,<3"
-tenacity = ">=8.1.0,<9.0.0"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 
 [package.extras]
-azure = ["azure-ai-formrecognizer (>=3.2.1,<4.0.0)", "azure-ai-textanalytics (>=5.3.0,<6.0.0)", "azure-cognitiveservices-speech (>=1.28.0,<2.0.0)", "azure-core (>=1.26.4,<2.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "azure-search-documents (==11.4.0b8)", "openai (<2)"]
-clarifai = ["clarifai (>=9.1.0)"]
-cli = ["typer (>=0.9.0,<0.10.0)"]
-cohere = ["cohere (>=4,<6)"]
-docarray = ["docarray[hnswlib] (>=0.32.0,<0.33.0)"]
-embeddings = ["sentence-transformers (>=2,<3)"]
-extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.0,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cohere (>=4,<6)", "couchbase (>=4.1.9,<5.0.0)", "dashvector (>=1.0.1,<2.0.0)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "langchain-openai (>=0.0.2,<0.1)", "lxml (>=4.9.3,<6.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "rdflib (==7.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "upstash-redis (>=0.15.0,<0.16.0)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
-javascript = ["esprima (>=4.0.1,<5.0.0)"]
-llms = ["clarifai (>=9.1.0)", "cohere (>=4,<6)", "huggingface_hub (>=0,<1)", "manifest-ml (>=0.0.1,<0.0.2)", "nlpcloud (>=1,<2)", "openai (<2)", "openlm (>=0.0.5,<0.0.6)", "torch (>=1,<3)", "transformers (>=4,<5)"]
-openai = ["openai (<2)", "tiktoken (>=0.3.2,<0.6.0)"]
-qdrant = ["qdrant-client (>=1.3.1,<2.0.0)"]
-text-helpers = ["chardet (>=5.1.0,<6.0.0)"]
+anthropic = ["langchain-anthropic"]
+aws = ["langchain-aws"]
+cohere = ["langchain-cohere"]
+community = ["langchain-community"]
+deepseek = ["langchain-deepseek"]
+fireworks = ["langchain-fireworks"]
+google-genai = ["langchain-google-genai"]
+google-vertexai = ["langchain-google-vertexai"]
+groq = ["langchain-groq"]
+huggingface = ["langchain-huggingface"]
+mistralai = ["langchain-mistralai"]
+ollama = ["langchain-ollama"]
+openai = ["langchain-openai"]
+together = ["langchain-together"]
+xai = ["langchain-xai"]
 
 [[package]]
 name = "langchain-community"
-version = "0.0.38"
+version = "0.3.18"
 description = "Community contributed LangChain integrations."
 optional = false
-python-versions = "<4.0,>=3.8.1"
+python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain_community-0.0.38-py3-none-any.whl", hash = "sha256:ecb48660a70a08c90229be46b0cc5f6bc9f38f2833ee44c57dfab9bf3a2c121a"},
-    {file = "langchain_community-0.0.38.tar.gz", hash = "sha256:127fc4b75bc67b62fe827c66c02e715a730fef8fe69bd2023d466bab06b5810d"},
+    {file = "langchain_community-0.3.18-py3-none-any.whl", hash = "sha256:0d4a70144a1750045c4f726f9a43379ed2484178f76e4b8295bcef3a7fdf41d5"},
+    {file = "langchain_community-0.3.18.tar.gz", hash = "sha256:fa2889a8f0b2d22b5c306fd1b070c0970e1f11b604bf55fad2f4a1d0bf68a077"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
 dataclasses-json = ">=0.5.7,<0.7"
-langchain-core = ">=0.1.52,<0.2.0"
-langsmith = ">=0.1.0,<0.2.0"
-numpy = ">=1,<2"
+httpx-sse = ">=0.4.0,<1.0.0"
+langchain = ">=0.3.19,<1.0.0"
+langchain-core = ">=0.3.37,<1.0.0"
+langsmith = ">=0.1.125,<0.4"
+numpy = {version = ">=1.26.2,<3", markers = "python_version >= \"3.12\""}
+pydantic-settings = ">=2.4.0,<3.0.0"
 PyYAML = ">=5.3"
 requests = ">=2,<3"
 SQLAlchemy = ">=1.4,<3"
-tenacity = ">=8.1.0,<9.0.0"
-
-[package.extras]
-cli = ["typer (>=0.9.0,<0.10.0)"]
-extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "azure-ai-documentintelligence (>=1.0.0b1,<2.0.0)", "azure-identity (>=1.15.0,<2.0.0)", "azure-search-documents (==11.4.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.6,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cloudpickle (>=2.0.0)", "cohere (>=4,<5)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "elasticsearch (>=8.12.0,<9.0.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "friendli-client (>=1.2.4,<2.0.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "gradientai (>=1.4.0,<2.0.0)", "hdbcli (>=2.19.21,<3.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "httpx (>=0.24.1,<0.25.0)", "httpx-sse (>=0.4.0,<0.5.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "lxml (>=4.9.3,<6.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "nvidia-riva-client (>=2.14.0,<3.0.0)", "oci (>=2.119.1,<3.0.0)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "oracle-ads (>=2.9.1,<3.0.0)", "oracledb (>=2.2.0,<3.0.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "premai (>=0.3.25,<0.4.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pyjwt (>=2.8.0,<3.0.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "rdflib (==7.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "tidb-vector (>=0.0.3,<1.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "tree-sitter (>=0.20.2,<0.21.0)", "tree-sitter-languages (>=1.8.0,<2.0.0)", "upstash-redis (>=0.15.0,<0.16.0)", "vdms (>=0.0.20,<0.0.21)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
 
 [[package]]
 name = "langchain-core"
-version = "0.1.53"
+version = "0.3.37"
 description = "Building applications with LLMs through composability"
 optional = false
-python-versions = "<4.0,>=3.8.1"
+python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain_core-0.1.53-py3-none-any.whl", hash = "sha256:02a88a21e3bd294441b5b741625fa4b53b1c684fd58ba6e5d9028e53cbe8542f"},
-    {file = "langchain_core-0.1.53.tar.gz", hash = "sha256:df3773a553b5335eb645827b99a61a7018cea4b11dc45efa2613fde156441cec"},
+    {file = "langchain_core-0.3.37-py3-none-any.whl", hash = "sha256:8202fd6506ce139a3a1b1c4c3006216b1c7fffa40bdd1779f7d2c67f75eb5f79"},
+    {file = "langchain_core-0.3.37.tar.gz", hash = "sha256:cda8786e616caa2f68f7cc9e811b9b50e3b63fb2094333318b348e5961a7ea01"},
 ]
 
 [package.dependencies]
 jsonpatch = ">=1.33,<2.0"
-langsmith = ">=0.1.0,<0.2.0"
-packaging = ">=23.2,<24.0"
-pydantic = ">=1,<3"
+langsmith = ">=0.1.125,<0.4"
+packaging = ">=23.2,<25"
+pydantic = [
+    {version = ">=2.5.2,<3.0.0", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
+]
 PyYAML = ">=5.3"
-tenacity = ">=8.1.0,<9.0.0"
-
-[package.extras]
-extended-testing = ["jinja2 (>=3,<4)"]
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0"
+typing-extensions = ">=4.7"
 
 [[package]]
 name = "langchain-google-genai"
-version = "0.0.9"
+version = "2.0.9"
 description = "An integration package connecting Google's genai package and LangChain"
 optional = false
-python-versions = ">=3.9,<4.0"
+python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain_google_genai-0.0.9-py3-none-any.whl", hash = "sha256:82c0ca9540132a59b09fc38ff249a2dd06f8a587ed37c291a4fe7678d5566d15"},
-    {file = "langchain_google_genai-0.0.9.tar.gz", hash = "sha256:466a228032bb06b0c1def822e57cbf2dfe9e4d1cc91dffa473a3025eb760f0ef"},
+    {file = "langchain_google_genai-2.0.9-py3-none-any.whl", hash = "sha256:48d8c78c42048d54f40dff333db9d359746644e0feb0e08b5eabdf34ad7149ca"},
+    {file = "langchain_google_genai-2.0.9.tar.gz", hash = "sha256:65205089da1f72688a0ed6e7c6914af308b6514ab8038fd8126ecb20f1df234c"},
 ]
 
 [package.dependencies]
-google-generativeai = ">=0.3.1,<0.4.0"
-langchain-core = ">=0.1,<0.2"
-
-[package.extras]
-images = ["pillow (>=10.1.0,<11.0.0)"]
+filetype = ">=1.2.0,<2.0.0"
+google-generativeai = ">=0.8.0,<0.9.0"
+langchain-core = ">=0.3.27,<0.4.0"
+pydantic = ">=2,<3"
 
 [[package]]
 name = "langchain-openai"
-version = "0.0.2.post1"
+version = "0.3.6"
 description = "An integration package connecting OpenAI and LangChain"
 optional = false
-python-versions = ">=3.8.1,<4.0"
+python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain_openai-0.0.2.post1-py3-none-any.whl", hash = "sha256:ba468b94c23da9d8ccefe5d5a3c1c65b4b9702292523e53acc689a9110022e26"},
-    {file = "langchain_openai-0.0.2.post1.tar.gz", hash = "sha256:f8e78db4a663feeac71d9f036b9422406c199ea3ef4c97d99ff392c93530e073"},
+    {file = "langchain_openai-0.3.6-py3-none-any.whl", hash = "sha256:05f0869f6cc963e2ec9e2e54ea1038d9c2af784c67f0e217040dfc918b31649a"},
+    {file = "langchain_openai-0.3.6.tar.gz", hash = "sha256:7daf92e1cd98865ab5213ec5bec2cbd6c28f011e250714978b3a99c7e4fc88ce"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.1.7,<0.2"
-numpy = ">=1,<2"
-openai = ">=1.6.1,<2.0.0"
-tiktoken = ">=0.5.2,<0.6.0"
+langchain-core = ">=0.3.35,<1.0.0"
+openai = ">=1.58.1,<2.0.0"
+tiktoken = ">=0.7,<1"
 
 [[package]]
 name = "langchain-text-splitters"
-version = "0.0.2"
+version = "0.3.6"
 description = "LangChain text splitting utilities"
 optional = false
-python-versions = "<4.0,>=3.8.1"
+python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
-    {file = "langchain_text_splitters-0.0.2-py3-none-any.whl", hash = "sha256:13887f32705862c1e1454213cb7834a63aae57c26fcd80346703a1d09c46168d"},
-    {file = "langchain_text_splitters-0.0.2.tar.gz", hash = "sha256:ac8927dc0ba08eba702f6961c9ed7df7cead8de19a9f7101ab2b5ea34201b3c1"},
+    {file = "langchain_text_splitters-0.3.6-py3-none-any.whl", hash = "sha256:e5d7b850f6c14259ea930be4a964a65fa95d9df7e1dbdd8bad8416db72292f4e"},
+    {file = "langchain_text_splitters-0.3.6.tar.gz", hash = "sha256:c537972f4b7c07451df431353a538019ad9dadff7a1073ea363946cea97e1bee"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.1.28,<0.3"
-
-[package.extras]
-extended-testing = ["beautifulsoup4 (>=4.12.3,<5.0.0)", "lxml (>=4.9.3,<6.0)"]
+langchain-core = ">=0.3.34,<1.0.0"
 
 [[package]]
 name = "langchainhub"
@@ -4032,6 +4084,27 @@ files = [
 [package.dependencies]
 typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
+[[package]]
+name = "pydantic-settings"
+version = "2.7.1"
+description = "Settings management using Pydantic"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "pydantic_settings-2.7.1-py3-none-any.whl", hash = "sha256:590be9e6e24d06db33a4262829edef682500ef008565a969c73d39d5f8bfb3fd"},
+    {file = "pydantic_settings-2.7.1.tar.gz", hash = "sha256:10c9caad35e64bfb3c2fbf70a078c0e25cc92499782e5200747f942a065dec93"},
+]
+
+[package.dependencies]
+pydantic = ">=2.7.0"
+python-dotenv = ">=0.21.0"
+
+[package.extras]
+azure-key-vault = ["azure-identity (>=1.16.0)", "azure-keyvault-secrets (>=4.8.0)"]
+toml = ["tomli (>=2.0.1)"]
+yaml = ["pyyaml (>=6.0.1)"]
+
 [[package]]
 name = "pyjwt"
 version = "2.10.1"
@@ -4082,6 +4155,21 @@ files = [
     {file = "pypandoc-1.15.tar.gz", hash = "sha256:ea25beebe712ae41d63f7410c08741a3cab0e420f6703f95bc9b3a749192ce13"},
 ]
 
+[[package]]
+name = "pyparsing"
+version = "3.2.1"
+description = "pyparsing module - Classes and methods to define and execute parsing grammars"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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+    {file = "pyparsing-3.2.1.tar.gz", hash = "sha256:61980854fd66de3a90028d679a954d5f2623e83144b5afe5ee86f43d762e5f0a"},
+]
+
+[package.extras]
+diagrams = ["jinja2", "railroad-diagrams"]
+
 [[package]]
 name = "pypdf2"
 version = "3.0.1"
@@ -4533,23 +4621,21 @@ files = [
 
 [[package]]
 name = "replicate"
-version = "0.10.0"
+version = "1.0.4"
 description = "Python client for Replicate"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "replicate-0.10.0-py3-none-any.whl", hash = "sha256:71464d62259b22a17f5383e83ebaf158cace69ba0153a9de21061283ac2c3a4b"},
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+    {file = "replicate-1.0.4-py3-none-any.whl", hash = "sha256:f568f6271ff715067901b6094c23c37373bbcfd7de0ff9b85e9c9ead567e09e7"},
+    {file = "replicate-1.0.4.tar.gz", hash = "sha256:f718601863ef1f419aa7dcdab1ea8770ba5489b571b86edf840cd506d68758ef"},
 ]
 
 [package.dependencies]
+httpx = ">=0.21.0,<1"
 packaging = "*"
-pydantic = ">1"
-requests = ">2"
-
-[package.extras]
-dev = ["black", "mypy", "pytest", "responses", "ruff"]
+pydantic = ">1.10.7"
+typing_extensions = ">=4.5.0"
 
 [[package]]
 name = "requests"
@@ -5121,48 +5207,43 @@ tests = ["pytest", "pytest-cov"]
 
 [[package]]
 name = "tiktoken"
-version = "0.5.2"
+version = "0.9.0"
 description = "tiktoken is a fast BPE tokeniser for use with OpenAI's models"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
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-    {file = "tiktoken-0.5.2.tar.gz", hash = "sha256:f54c581f134a8ea96ce2023ab221d4d4d81ab614efa0b2fbce926387deb56c80"},
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+    {file = "tiktoken-0.9.0-cp313-cp313-win_amd64.whl", hash = "sha256:5ea0edb6f83dc56d794723286215918c1cde03712cbbafa0348b33448faf5b95"},
+    {file = "tiktoken-0.9.0-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:c6386ca815e7d96ef5b4ac61e0048cd32ca5a92d5781255e13b31381d28667dc"},
+    {file = "tiktoken-0.9.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:75f6d5db5bc2c6274b674ceab1615c1778e6416b14705827d19b40e6355f03e0"},
+    {file = "tiktoken-0.9.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e15b16f61e6f4625a57a36496d28dd182a8a60ec20a534c5343ba3cafa156ac7"},
+    {file = "tiktoken-0.9.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ebcec91babf21297022882344c3f7d9eed855931466c3311b1ad6b64befb3df"},
+    {file = "tiktoken-0.9.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:e5fd49e7799579240f03913447c0cdfa1129625ebd5ac440787afc4345990427"},
+    {file = "tiktoken-0.9.0-cp39-cp39-win_amd64.whl", hash = "sha256:26242ca9dc8b58e875ff4ca078b9a94d2f0813e6a535dcd2205df5d49d927cc7"},
+    {file = "tiktoken-0.9.0.tar.gz", hash = "sha256:d02a5ca6a938e0490e1ff957bc48c8b078c88cb83977be1625b1fd8aac792c5d"},
 ]
 
 [package.dependencies]
@@ -5823,4 +5904,4 @@ testing = ["coverage[toml]", "zope.event", "zope.testing"]
 [metadata]
 lock-version = "2.1"
 python-versions = "^3.12"
-content-hash = "306f28fc88cf28fcdbfc71b0d0f690c06444689894f685834c3160cfe263e1c4"
+content-hash = "05b49eeacc304695f22cd6a2942fc3ea572e8b24b55b4698da75f97db81c35fa"
@@ -9,7 +9,6 @@ package-mode = false
 
 [tool.poetry.dependencies]
 python = "^3.12"
-replicate = "^0.10.0"
 deepl = "^1.15.0"
 django = "5.0.*"
 django-cors-headers = "^4.2.0"
@@ -32,10 +31,7 @@ openpyxl = "^3.1.2"
 pypdf2 = "^3.0.1"
 python-docx = "^1.1.0"
 mutagen = "^1.47.0"
-langchain = "^0.1.0"
-langchain-openai = "^0.0.2"
 pillow = "^10.2.0"
-langchain-google-genai = "^0.0.9"
 langserve = {extras = ["client"], version = "^0.0.46"}
 django-ordered-model = "^3.7.4"
 langchainhub = "^0.1.15"
@@ -57,10 +53,15 @@ httptools = "^0.6.4"
 uvloop = "^0.21.0"
 wsproto = "^1.2.0"
 channels-redis = "^4.2.1"
-tiktoken = "<0.6.0"
+langchain = "^0.3.19"
+langchain-openai = "^0.3.6"
+langchain-google-genai = "^2.0.9"
+tiktoken = "^0.9.0"
+langchain-community = "^0.3.17"
 docx2txt = "^0.8"
 pypandoc = "^1.15"
 faiss-cpu = "^1.10.0"
+replicate = "^1.0.4"
 ruff = "^0.9.9"