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langchain:0.0.353
platform:windows10
python:3.10
I am a beginner in Langchain. I am a I want to use ConversationTokenBufferMemory to manually save the context, but an error occurred. My code is as follows
`import os
from lc.api_key import OPENAI_API_KEY
os.environ['OPENAI_API_KEY'] = OPENAI_API... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15560 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15560/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15560/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15560/events | https://github.com/langchain-ai/langchain/issues/15560 | 2,066,364,259 | I_kwDOIPDwls57Kjdj | 15,560 | Issue: How to use "n" completions with LCEL | {
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... | open | false | null | [] | null | 1 | 2024-01-04T21:31:34 | 2024-01-04T21:40:55 | null | NONE | null | ### Issue you'd like to raise.
I'm using Langchain 0.0.354 and ChatOpenAI. I want to use parameter "n" in OpenAI API to return "n" completions. However, ChatOpenAI always returns a single output. Ultimately, I would like to build my chain using LCEL as follows: `chain = prompt | ChatOpenAI (n=10) | MyCustomParser`. Ca... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15559 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15559/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15559/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15559/events | https://github.com/langchain-ai/langchain/pull/15559 | 2,066,302,740 | PR_kwDOIPDwls5jQf71 | 15,559 | core[patch]: Further restrict recursive URL loader | {
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"url... | closed | false | null | [] | null | 1 | 2024-01-04T20:37:59 | 2024-01-04T21:33:58 | 2024-01-04T21:33:57 | COLLABORATOR | null | Code from this PR:
https://github.com/langchain-ai/langchain/compare/HEAD...m0kr4n3:security/fix_ssrf
Added unit tests
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https://api.github.com/repos/langchain-ai/langchain/issues/15557 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15557/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15557/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15557/events | https://github.com/langchain-ai/langchain/pull/15557 | 2,066,274,624 | PR_kwDOIPDwls5jQZvJ | 15,557 | infra: try show last update time | {
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... | open | false | null | [] | null | 1 | 2024-01-04T19:48:30 | 2024-01-04T19:55:22 | null | NONE | null | ### Issue you'd like to raise.
I am trying to run the below:
> import requests
> import json
> from langchain.agents import AgentType, initialize_agent, load_tools
> from langchain_community.llms import OpenAI
> from langchain.chat_models import ChatOpenAI
>
>
> llm = ChatOpenAI(temperature=0,model= 'gpt-3... | {
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"node_... | closed | false | null | [] | null | 2 | 2024-01-04T19:46:04 | 2024-01-15T19:42:34 | 2024-01-15T19:42:34 | CONTRIBUTOR | null | - **Description:** Adds documentation for the `FirestoreChatMessageHistory` integration and lists integration in Google's documentation
- **Issue:** NA
- **Dependencies:** No
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"id": 56... | open | false | null | [] | null | 1 | 2024-01-04T19:08:46 | 2024-01-04T19:14:44 | null | NONE | null | ### Issue you'd like to raise.
```
from langchain.vectorstores.pgvector import PGVector
db = PGVector.from_documents(
documents= docs,
embedding = embeddings,
collection_name= "blog_posts",
distance_strategy = DistanceStrategy.COSINE,
connection_string=CONNECTION_STRING
)
```
This code ... | {
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Error stack
```
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
File <command-3066972537097411>, line 1
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I have a large Agent with lots of memory/observations but initializing takes to much time. Is there a way to save the memory and load it again? Whats the best way to achieve this? Ideally I would like to reuse the vector store for memory and then for each new user save/load the memory/co... | {
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I try to load pdf in from langchain.document_loaders import PyPDFDirectoryLoader
got error this WARNING:pypdf._reader:incorrect startxref pointer(3)
from langchain.document_loaders import PyPDFDirectoryLoader
from langchain_community.document_loaders import PyPDFLoader
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"url... | closed | false | null | [] | null | 1 | 2024-01-04T14:34:25 | 2024-01-15T19:43:13 | 2024-01-15T19:43:13 | CONTRIBUTOR | null | fix tongyi completion json parse error and prompt's params error
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python==3.10
langchain==0.0.326
langdetect==1.0.9
langsmith==0.0.54
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / P... | {
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... | closed | false | null | [] | null | 2 | 2024-01-04T12:31:33 | 2024-01-15T19:44:57 | 2024-01-15T19:44:57 | CONTRIBUTOR | null | - **Description:** Fix to IBM [watsonx.ai](https://www.ibm.com/products/watsonx-ai) LLM provider (stop (`stop_sequences`) param on watsonxLLM)
- **Dependencies:** [ibm-watsonx-ai](https://pypi.org/project/ibm-watsonx-ai/),
- **Tag maintainer:** : @hwchase17 , @eyurtsev , @baskaryan
Please make sure your PR ... | {
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google-cloud-bigquery = "^3.14.1"
google-api-core = "^2.15.0"
google-cloud-core = "^2.4.1"
grpcio = "^1.60.0"
grpcio-tools = "^1.60.0"
langchain-google-genai = "^0.0.5"
langchain-core = "^0.1.5"
google-cloud-aiplatform = "^1.38.1"
langchain-community = "^0.0.8"
### Who can help?
when test the... | {
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- **Issue:** #15536.
- **Dependencies:** `asyncio`, `time`.
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When using asynchronous loading the `RecursiveUrlLoader`, it would be nice to be able to set a limit for the number of parallel HTTP requests when scraping a website.
Right now, when using async loading it is very likely to get errors like the following:
```
04-01-24 12:02:53 [WARNING] recurs... | {
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TLDR:
In commit [7eec8f2](https://github.com/langchain-ai/langchain/commit/7eec8f24876fd624573c09ff82270362031e6a5f#) the function [tracing_enabled](https://github.com/langchain-ai/langchain/commit/7eec8f24876fd624573c09ff82270362031e6a5f#diff-aa3d4ef71b404ec... | {
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- Issue: #15531
- Dependencies: Argilla
- Also corrected some dead links. | {
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<!-- Thank you for contributing to LangChain!
Please title your PR "<package>: <description>", where <package> is whichever of langchain, community, core, experimental, etc. is being modified... | {
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... | open | false | null | [] | null | 1 | 2024-01-04T09:53:47 | 2024-01-04T10:07:41 | null | CONTRIBUTOR | null | ### System Info
Python version: 3.9.7
Langchain version: 0.0.352
Argilla version: 1.20.0
### Who can help?
@agola11
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / P... | {
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langchain 0.0.351
langchain-community 0.0.4
python 3.9
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Tem... | {
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- **Issue:** The input variable in the notebook example should be `api_key` instead of `zhipu_api_key`.
- **Depende... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15528 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15528/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15528/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15528/events | https://github.com/langchain-ai/langchain/issues/15528 | 2,065,203,802 | I_kwDOIPDwls57GIJa | 15,528 | Issue: document_variable_name context was not found in llm_chain input_variables: | {
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"node_... | open | false | null | [] | null | 3 | 2024-01-04T08:18:07 | 2024-01-05T07:30:47 | null | NONE | null | ### Issue you'd like to raise.
below is my code where I am implementing Memory with Prompt Template
def generate_custom_prompt(query=None,name=None,not_uuid=None,chroma_db_path=None):
check = query.lower()
embedding = OpenAIEmbeddings()
vectordb = Chroma(persist_directory=chroma_db_path, embedding_... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15527 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15527/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15527/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15527/events | https://github.com/langchain-ai/langchain/issues/15527 | 2,065,199,886 | I_kwDOIPDwls57GHMO | 15,527 | Issue: <How can I extract vector data from pgvector for use as a reference in the next conversation to enable long-term memory functionality for my chatbot?> | {
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"id":... | open | false | null | [] | null | 4 | 2024-01-04T08:14:43 | 2024-01-04T08:44:42 | null | NONE | null | ### Issue you'd like to raise.
from langchain.chains import LLMChain
from langchain.prompts import (
ChatPromptTemplate,
HumanMessagePromptTemplate,
MessagesPlaceholder,
SystemMessagePromptTemplate,
)
import psycopg2
import os
from langchain.chat_models import ChatOpenAI
from langchain.memory... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15526 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15526/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15526/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15526/events | https://github.com/langchain-ai/langchain/issues/15526 | 2,065,192,495 | I_kwDOIPDwls57GFYv | 15,526 | ImportError: cannot import name 'tracing_enabled' from 'langchain_core.tracers.context' (/usr/local/lib/python3.11/site-packages/langchain_core/tracers/context.py | {
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... | closed | false | null | [] | null | 5 | 2024-01-04T08:08:19 | 2024-01-04T19:50:14 | 2024-01-04T19:45:32 | NONE | null | ### System Info
0.0.352 and 0.0.353
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Docume... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15525 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15525/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15525/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15525/events | https://github.com/langchain-ai/langchain/issues/15525 | 2,065,169,209 | I_kwDOIPDwls57F_s5 | 15,525 | Issue: <"How can I extract vector data from pgvector for use as a reference in the next conversation to enable long-term memory functionality for my chatbot?> | {
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"id":... | open | false | null | [] | null | 1 | 2024-01-04T07:51:08 | 2024-01-04T08:03:30 | null | NONE | null | ### Issue you'd like to raise.
from langchain.chains import LLMChain
from langchain.prompts import (
ChatPromptTemplate,
HumanMessagePromptTemplate,
MessagesPlaceholder,
SystemMessagePromptTemplate,
)
import psycopg2
import os
from langchain.chat_models import ChatOpenAI
from langchain.memo... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15524 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15524/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15524/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15524/events | https://github.com/langchain-ai/langchain/issues/15524 | 2,065,163,019 | I_kwDOIPDwls57F-ML | 15,524 | AsyncChromiumloader gives attribute error : COBOL | {
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... | open | false | null | [] | null | 1 | 2024-01-04T07:46:03 | 2024-01-04T07:59:06 | null | NONE | null | ### System Info
python 3.9.13
langchain==0.0.316
langchain-community==0.0.1
langchain-core==0.0.13
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [X] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts /... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15523 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15523/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15523/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15523/events | https://github.com/langchain-ai/langchain/issues/15523 | 2,065,149,238 | I_kwDOIPDwls57F602 | 15,523 | RuntimeError when calling asyncio.run() from a running event loop | {
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... | open | false | null | [] | null | 4 | 2024-01-04T07:35:01 | 2024-01-04T15:35:37 | null | NONE | null | https://github.com/langchain-ai/langchain/blob/7a93356cbc5d89cc0f7dd746d8f1bb52666fd0f1/libs/community/langchain_community/document_loaders/chromium.py#L78C40-L78C44
Hello,
I encountered a RuntimeError when running the code that uses the AsyncChromiumLoader class. The error message is asyncio.run() cannot be call... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15522 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15522/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15522/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15522/events | https://github.com/langchain-ai/langchain/issues/15522 | 2,065,084,378 | I_kwDOIPDwls57Fq_a | 15,522 | The current support for Milvus in Langchain seems insufficient in my opinion. Can it be strengthened? | {
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{
"id": 56... | open | false | null | [] | null | 1 | 2024-01-04T06:29:52 | 2024-01-04T06:41:59 | null | NONE | null | ### Issue you'd like to raise.
The current support for Milvus in Langchain seems insufficient in my opinion. Can it be strengthened?
### Suggestion:
The current support for Milvus in Langchain seems insufficient in my opinion. Can it be strengthened? | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15521 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15521/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15521/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15521/events | https://github.com/langchain-ai/langchain/issues/15521 | 2,065,015,603 | I_kwDOIPDwls57FaMz | 15,521 | Issue: Unable to use custom parser to parse the (intermediate) LLM chain output | {
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"node_id... | open | false | null | [] | null | 1 | 2024-01-04T05:18:04 | 2024-01-04T06:51:03 | null | NONE | null | ### Issue you'd like to raise.
I have been trying to use mixtral-7B as LLM agent with langchain. Agent has been provided a PythonREPL tool for any kind of code execution.
While providing the output, it either runs into agent timeout error or else it provide wrong answer (but in correct format). By further analys... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15520 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15520/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15520/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15520/events | https://github.com/langchain-ai/langchain/issues/15520 | 2,065,004,679 | I_kwDOIPDwls57FXiH | 15,520 | text_splitter module not found in langchain version 0.0.353. | {
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... | open | false | null | [] | null | 1 | 2024-01-04T05:02:15 | 2024-01-04T05:10:56 | null | NONE | null | ### System Info
langchain version 0.0.353.
python : 3.9
### Who can help?
_No response_
### Information
- [ ] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
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https://api.github.com/repos/langchain-ai/langchain/issues/15519 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15519/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15519/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15519/events | https://github.com/langchain-ai/langchain/pull/15519 | 2,064,938,751 | PR_kwDOIPDwls5jL5dl | 15,519 | Feat: add CHM file loader | {
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"url... | closed | false | null | [] | null | 2 | 2024-01-04T03:35:03 | 2024-01-07T17:28:53 | 2024-01-07T17:28:53 | CONTRIBUTOR | null | fix https://github.com/langchain-ai/langchain/issues/15469 | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15518 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15518/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15518/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15518/events | https://github.com/langchain-ai/langchain/issues/15518 | 2,064,893,373 | I_kwDOIPDwls57E8W9 | 15,518 | Issue: LCEL output parser error | {
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... | open | false | null | [] | null | 6 | 2024-01-04T02:26:08 | 2024-01-08T15:39:41 | null | NONE | null | ### Issue you'd like to raise.
Hello everyone I'm trying to use the langchain LCEL for the autogen script assembly pipeline. The first point that I'm trying to implement is for AI to determine which roles are needed in the autogen group chat to solve the user's task. I'm trying to parse the neural network's response t... | {
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Problem Statement:
I am currently working on tracking token consumption for asynchronous chain calls in my application. I am utilizing the AsyncIteratorCallbackHandler and its aiter() method to stream tokens to my client. However, I am facing challenges in determining how to track the t... | {
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... | open | false | null | [] | null | 7 | 2024-01-04T01:13:21 | 2024-01-06T04:39:03 | null | NONE | null | ### System Info
langchain==0.0.354
text_generation==0.6.1
python:3.10-slim
### Who can help?
@agola11 @hwaking
### Information
- [ ] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [X] Prompts / Prompt Templates ... | {
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This creates interfaces in `core` for some `community` modules that previously did not have interfaces from core. Ideally, these interfaces help with new integrations, move interfaces to the core == make interfaces more stable.
The next step will be to add these interfaces to the ... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15514 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15514/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15514/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15514/events | https://github.com/langchain-ai/langchain/pull/15514 | 2,064,831,832 | PR_kwDOIPDwls5jLj8X | 15,514 | langchain: Introducing Google Semantic Retriever and Attributed Question and Answering (AQA) | {
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Introducing two new features from Google's Generative Language API.
* Bundled embeddings calculation and vector storage for enabling semantic retrieval.
* State-of-the-art fine-tuned model for answering questions grounded in passages.
**Dependencies:**
The Python package [google-ai-generat... | {
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There are likely more | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15512 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15512/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15512/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15512/events | https://github.com/langchain-ai/langchain/issues/15512 | 2,064,809,247 | I_kwDOIPDwls57En0f | 15,512 | Langchain-Community LLM TextGen has wrong API endpoint | {
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... | open | false | null | [] | null | 2 | 2024-01-04T00:12:34 | 2024-01-04T15:45:40 | null | NONE | null | ### System Info
Windows 10 & Ubuntu 22.04
langchain==0.0.354
langchain-community==0.0.8
langchain-core==0.1.5
Python 3.10.13
https://github.com/langchain-ai/langchain/blob/master/libs/community/langchain_community/llms/textgen.py
### Who can help?
@agola11 @hwchase17
### Information
- [ ] The official ... | {
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I've been playing around with the multimodal notebooks introduced in the [docs here.](https://blog.langchain.dev/semi-structured-multi-modal-rag/). However, the number of retrieved documents for every query is always 4. Specifically, for [cookbook 3](https://github.com/langchain-ai/langc... | {
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Full traceback:
```
File "/src/app.py", line 9, in <module>
from langchain.chains import ConversationalRetrievalChain
File "/venv/lib/python3.11/site-packages/langchain/chains/__init__.py", line 20, in <module>
from langchain.chains.api.base import APIChain
File "/venv/lib/python3... | {
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Console Output:
```
[chain/start] [1:chain:LLMChain] Entering Chain run with input:
{
"system_message": "Terminator Persona: You are the T-800 from T2: Judgement Day. Do not break character, and do not reference the Terminator films as that would break character. If you break chara... | {
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"id":... | open | false | null | [] | null | 1 | 2024-01-03T21:53:13 | 2024-01-03T22:01:52 | null | NONE | null | ### Feature request
Able to `persist` between batch when the embedding is between built:
```python
db = Chroma.from_documents(
documents=documents, embedding=embeddings, persist_directory=persist_directory)
db.persist()
return db
```
would be nice to be :
```python
db = Chroma.from_docum... | {
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- [x] copy over integration tests
- [x] update docs with new instructions in #15513
- [x] add linear ticket to bump core -> community, community->langchain, and core->openai deps
- [ ] (optional): add `pip install langchain-openai` command to each notebook using it
- [x] Update docstrings to not need `open... | {
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... | open | false | null | [] | null | 1 | 2024-01-03T20:17:12 | 2024-01-03T20:19:31 | null | NONE | null | ### System Info
0.0.354
### Who can help?
@hwchase17 @agol
### Information
- [ ] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loader... | {
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```
/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_deprecation.py:131: FutureWarning: 'InferenceApi' (from 'huggingface_hub.inference_api') is deprecated and will be removed from version '1.0'. `InferenceApi` client is deprecated in favor of the more feature-comple... | {
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Hi there,
I am learning how to use Pinecone properly with LangChain and OpenAI Embedding. I built an application which can allow user upload PDFs and ask questions about the PDFs. In the application I used Pinecone as the vector database and store embeddings in Pinecone. However, I w... | {
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"id": 56... | open | false | null | [] | null | 3 | 2024-01-03T19:31:06 | 2024-01-05T15:01:59 | null | NONE | null | ### Feature request
Provide a method to create the HNSW for the PGVector vectorstore
### Motivation
There is a similar method implemented for PGEmbedding but the embedding extension will be deprecated
### Your contribution
https://github.com/pgvector/pgvector?tab=readme-ov-file#hnsw
https://github.com... | {
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... | open | false | null | [] | null | 9 | 2024-01-03T18:58:45 | 2024-01-04T17:41:35 | null | NONE | null | ### Issue you'd like to raise.
Hi all,
I am trying to create an app that can act upon a natural language prompt to interact with the Monday API and then successfully carry out the relevant action.
The code I currently have is as follows:
> MondayDocs = """
>
>
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``` bash
bash-4.2# pip freeze | grep langchain
langchain==0.0.353
langchain-community==0.0.8
langchain-core==0.1.5
bash-4.2# python --version
Python 3.10.13
bash-4.2# uname -a
Linux 5b9ca59024db 6.1.61-85.141.amzn2023.x86_64 #1 SMP PREEMPT_DYNAMIC Wed Nov 8 00:39:18 UTC 2023 x86_64 x86_64 ... | {
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- **Issue:** None,
- **Dependencies:** None,
- **Twitter handle:** @hhvedoveli
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I've scoured the internet trying to find an example that would use a custom model (Mistral) with ```HuggingFaceTextGenInference``` which uses ```LLMChain``` to return a **streaming** response via ```fastapi```.
Does anyone have a working example?
### Suggestion:
_No response_ | {
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**Platform:**
Linux Ubuntu 22.04.1
**Python:**
3.10.12
**Langchain:**
- langchain 0.0.353
- langchain-community 0.0.7
- langchain-core 0.1.5
- langsmith 0.0.77
### Who can help?
@hwchase17
### Information
- [ ] The official exam... | {
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Chatglm3 has added many new features compared to previous chatglm and chatglm2, which is particularly useful for users. So there will definitely be more user demands in using Langchain to build a knowledge base, and it's unclear how long it will take for the community to adapt.
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https://api.github.com/repos/langchain-ai/langchain/issues/15477 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15477/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15477/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15477/events | https://github.com/langchain-ai/langchain/issues/15477 | 2,064,133,232 | I_kwDOIPDwls57CCxw | 15,477 | Add TTL support for DynamoDBChatMessageHistory | {
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... | open | false | null | [] | null | 1 | 2024-01-03T14:29:38 | 2024-01-03T14:32:03 | null | NONE | null | ### Feature request
DynamoDBChatMessageHistory class is missing a TTL feature that would allow for history to automatically expire and be deleted by AWS DynamoDB service.
### Motivation
While implementing a chat history using DynamoDBChatMessageHistory, I encoutered a growing history session table. Since AWS DynamoD... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15476 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15476/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15476/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15476/events | https://github.com/langchain-ai/langchain/issues/15476 | 2,064,094,863 | I_kwDOIPDwls57B5aP | 15,476 | Issue: Large database schema too big for context window using SQLDatabaseChain | {
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How do I use SQLDatabaseChain with a big db schema?
I'm using:
`db = SQLDatabase.from_uri(f"postgresql://localhost:5432/test")
db_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)
`
And all models complain about context window. A smaller database schema works with some mo... | {
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Dear all,
Happy new year!
Due to work legacy stuff, I am still forced to use this library. I am wondering if there is a way to pass multiple prompt template (system, human and ai) instead of just one
Hopefully my man Dosubot can help!
Thanks you so much
Cheers,... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15474 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15474/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15474/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15474/events | https://github.com/langchain-ai/langchain/issues/15474 | 2,063,844,827 | I_kwDOIPDwls57A8Xb | 15,474 | Issue: Issue while implementing RAG with Gemini LLM | {
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... | open | false | null | [] | null | 4 | 2024-01-03T11:35:01 | 2024-01-17T12:01:00 | null | NONE | null | ### Issue you'd like to raise.
`document_variable_name="\n\n---\n\n".join([doc.page_content for doc in result["source_documents"]])
model = ChatGoogleGenerativeAI(model="gemini-pro",google_api_key=GOOGLE_API_KEY,temperature=0.2,convert_system_message_to_human=True)
template = f"""Use the following pieces of contex... | {
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... | open | false | null | [] | null | 1 | 2024-01-03T11:31:43 | 2024-01-15T19:49:38 | null | CONTRIBUTOR | null | fix https://github.com/langchain-ai/langchain/issues/15472 | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15472 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15472/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15472/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15472/events | https://github.com/langchain-ai/langchain/issues/15472 | 2,063,787,050 | I_kwDOIPDwls57AuQq | 15,472 | S3FileLoader doesn't provide the way of passing extra (unstructured_kwargs) parameters | {
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... | open | false | null | [] | null | 1 | 2024-01-03T11:04:15 | 2024-01-03T11:06:38 | null | NONE | null | ### System Info
python 3.11
langchain==0.0.350
### Who can help?
@eyurtsev
### Information
- [ ] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [X... | {
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... | open | false | null | [] | null | 3 | 2024-01-03T10:45:00 | 2024-01-03T10:56:46 | null | NONE | null | ### Feature request
Hello
The best practice is using comments inside the class/function,
however, comments/TODOs have been placed before in many cases,
Splitting it from the class/function hides some free text that can help understand the purpose and intention of class/function and may cause misinterpreted co... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15470 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15470/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15470/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15470/events | https://github.com/langchain-ai/langchain/pull/15470 | 2,063,659,208 | PR_kwDOIPDwls5jHj-H | 15,470 | Docs: fix excel document loader typo | {
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... | closed | false | null | [] | null | 2 | 2024-01-03T09:57:30 | 2024-01-07T17:28:54 | 2024-01-07T17:28:54 | NONE | null | ### Feature request
Add document loader for CHM (Microsoft Compiled HTML Help) documents, possibly using pychm.
### Motivation
A lot of Windows applications provide documentation in the form of CHM files. Being able to directly load those into the language model, would greatly simplify the workflow of ingesting docu... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15468 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15468/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15468/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15468/events | https://github.com/langchain-ai/langchain/pull/15468 | 2,063,638,165 | PR_kwDOIPDwls5jHfNi | 15,468 | Patch: improve openai.ChatCompletion getter | {
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The following is the code I ran, referring to the official documentation. It looks like prompt_template is not effective and there is no explicit call of prompt_template in the code. How should I customize a prompt for initialize_agent.
```python
prompt_template = """
Translate th... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15466 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15466/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15466/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15466/events | https://github.com/langchain-ai/langchain/issues/15466 | 2,063,615,767 | I_kwDOIPDwls57AEcX | 15,466 | Issue:While implementing Gemini, getting error while using prompt template | {
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... | open | false | null | [] | null | 2 | 2024-01-03T09:36:43 | 2024-01-03T10:32:51 | null | NONE | null | ### Issue you'd like to raise.
below is my code
`context_text="\n\n---\n\n".join([doc.page_content for doc in result["source_documents"]])
print(context_text,"======================")
question = "Describe the Multi-head attention layer in detail?"
embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-0... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15465 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15465/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15465/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15465/events | https://github.com/langchain-ai/langchain/issues/15465 | 2,063,613,427 | I_kwDOIPDwls57AD3z | 15,465 | "Multiple top-level packages discovered in a flat-layout" when installing from source | {
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Mint 20.3
Python 3.11
Conda 23.9
Pip 23.3.2
Setuptools 69.0.3
### Who can help?
_No response_
### Information
- [X] The official example notebooks/scripts
- [ ] My own modified scripts
### Related Components
- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prom... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15464 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15464/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15464/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15464/events | https://github.com/langchain-ai/langchain/pull/15464 | 2,063,590,614 | PR_kwDOIPDwls5jHUcg | 15,464 | Refactor: use SecretStr for zapier tool | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15462 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15462/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15462/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15462/events | https://github.com/langchain-ai/langchain/pull/15462 | 2,063,531,700 | PR_kwDOIPDwls5jHHOe | 15,462 | [Improvement] File_Tools added | {
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"node_id... | closed | false | null | [] | null | 1 | 2024-01-03T08:53:00 | 2024-01-10T18:12:08 | 2024-01-10T18:12:04 | NONE | null | now you can provice selected_tools like below.
```
from langchain_community.agent_toolkits.file_management.toolkit import File_Tools, FileManagementToolkit
toolkit = FileManagementToolkit(root_dir=clone_path,selected_tools=[File_Tools.write_file,File_Tools.list_dir])
tools = toolkit.get_tools()
```
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https://api.github.com/repos/langchain-ai/langchain/issues/15461 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15461/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15461/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15461/events | https://github.com/langchain-ai/langchain/pull/15461 | 2,063,528,202 | PR_kwDOIPDwls5jHGcL | 15,461 | Community: Support different Pinecone initializations depending on the version | {
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**Issue**: N/A
**Dependencies**: N/A
**Twitter handle**: N/A
Tested by installing different versions of the Pinecone client and trying to create an index (both regular and serverless for the new ... | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15460 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15460/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15460/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15460/events | https://github.com/langchain-ai/langchain/pull/15460 | 2,063,502,025 | PR_kwDOIPDwls5jHAlj | 15,460 | Feat: add url support for UnstructuredHTMLLoader | {
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... | open | false | null | [] | null | 1 | 2024-01-03T08:35:10 | 2024-01-15T19:54:24 | null | CONTRIBUTOR | null | usage:
```python
from langchain.document_loaders import UnstructuredHTMLLoader
source_url = "https://www.sec.gov/ix?doc=/Archives/edgar/data/40987/000004098720000010/gpc-12312019x10k.htm"
loader = UnstructuredHTMLLoader(source_url)
documents = loader.load()
print(documents)
``` | {
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https://api.github.com/repos/langchain-ai/langchain/issues/15459 | https://api.github.com/repos/langchain-ai/langchain | https://api.github.com/repos/langchain-ai/langchain/issues/15459/labels{/name} | https://api.github.com/repos/langchain-ai/langchain/issues/15459/comments | https://api.github.com/repos/langchain-ai/langchain/issues/15459/events | https://github.com/langchain-ai/langchain/pull/15459 | 2,063,473,381 | PR_kwDOIPDwls5jG6MJ | 15,459 | Fixed streaming support using callback handler for Google genai | {
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- **Issue:** #14709 #15006
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