Commit Graph

7969 Commits

Author SHA1 Message Date
Lance Martin
72ae744588
RAPTOR (#18467)
Cookbook for RAPTOR paper
2024-03-04 13:16:33 -08:00
aditya thomas
7803b973c7
docs: update documentation of stackexchange component (#18486)
**Description:** Update documentation of the StackExchange component
**Issue:** None
**Dependencies:** None
2024-03-04 10:45:29 -08:00
aditya thomas
5c387a173f
docs: update to docstrings of ChatAnthropic class (#18493)
**Description:** Update docstrings of ChatAnthropic class
**Issue:** Change to ChatAnthropic from ChatAnthropicMessages
**Dependencies:** None
**Lint and test**:  `make format`, `make lint` and `make test` passed
2024-03-04 10:44:54 -08:00
Martin Kolb
63702a2044
docs: Improved notebook for vector store "HANA Cloud" (#18496)
- **Description:**
This PR fixes some issues in the Jupyter notebook for the VectorStore
"SAP HANA Cloud Vector Engine":
    * Slight textual adaptations
    * Fix of wrong column name VEC_META (was: VEC_METADATA)

  - **Issue:** N/A
  - **Dependencies:** no new dependecies added
  - **Twitter handle:** @sapopensource

path to notebook:
`docs/docs/integrations/vectorstores/hanavector.ipynb`
2024-03-04 10:44:16 -08:00
standby24x7
8461700738
docs: Update function "run" to "invoke" (#18499)
Currently llm_checker.ipynb uses a function "run".
Update to "invoke" to avoid following warning.

LangChainDeprecationWarning: The function `run` was deprecated in
LangChain 0.1.0
and will be removed in 0.2.0. Use invoke instead.

Signed-off-by: Masanari Iida <standby24x7@gmail.com>
2024-03-04 10:42:53 -08:00
standby24x7
6c9177681d
docs: Update function "run" to "invoke" in llm_math.ipynb (#18505)
This patch updates function "run" to "invoke".
Without this patch you see following warning.

LangChainDeprecationWarning: The function `run` was deprecated in
LangChain 0.1.0 and will be removed in 0.2.0. Use invoke instead.

Signed-off-by: Masanari Iida <standby24x7@gmail.com>
2024-03-04 10:42:36 -08:00
Bagatur
1c1a3a7415
docs: quickstart models (#18511) 2024-03-04 08:33:19 -08:00
aditya thomas
a727eec6ed
docs: add groq to list of providers (#18503)
**Description:** Add Groq to the list of providers
**Issue:** None
**Dependencies:** None
2024-03-04 08:20:40 -08:00
Erick Friis
24f9c700f2
anthropic[minor]: claude 3 (#18508) 2024-03-04 15:03:51 +00:00
William De Vena
172499404a
Docs: Updated callbacks/index.mdx adding example on invoke method (#18403)
## PR title
Docs: Updated callbacks/index.mdx adding example on runnable methods

## PR message
- **Description:** Updated callbacks/index.mdx adding an example on how
to pass callbacks to the runnable methods (invoke, batch, ...)
- **Issue:** #16379
- **Dependencies:** None
2024-03-04 09:11:48 -05:00
Jacob Lee
de2d9447c6
👥 Update LangChain people data (#18473)
👥 Update LangChain people data

Co-authored-by: github-actions <github-actions@github.com>
2024-03-03 19:58:58 -08:00
William FH
1cdb813196
Improve notebook wording (#18472) 2024-03-03 18:31:15 -08:00
William FH
1eec67e8fe
Evaluate on Version (#18471) 2024-03-03 17:47:35 -08:00
William FH
55b69d5ad1
Update Notebook Image (#18470) 2024-03-03 17:22:59 -08:00
Harrison Chase
73d653324f
[Evals] Session-level feedback (#18463)
Co-authored-by: William Fu-Hinthorn <13333726+hinthornw@users.noreply.github.com>
2024-03-03 17:18:29 -08:00
Scott Nath
b051bba1a9
community: Add you.com tool, add async to retriever, add async testing, add You tool doc (#18032)
- **Description:** finishes adding the you.com functionality including:
    - add async functions to utility and retriever
    - add the You.com Tool
    - add async testing for utility, retriever, and tool
    - add a tool integration notebook page
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** @scottnath
2024-03-03 14:30:05 -08:00
mackong
b89d9fc177
langchain[patch]: add tools renderer for various non-openai agents (#18307)
- **Description:** add tools_renderer for various non-openai agents,
make tools can be render in different ways for your LLM.
  - **Issue:** N/A
  - **Dependencies:** N/A

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
2024-03-03 14:25:12 -08:00
Harrison Chase
7ce2f32c64
improve query analysis docs (#18426) 2024-03-03 14:24:33 -08:00
William De Vena
a63cee04ac
nvidia-trt[patch]: Invoke callback prior to yielding token (#18446)
## PR title
nvidia-trt[patch]: Invoke callback prior to yielding

## PR message
- Description: Invoke on_llm_new_token callback prior to yielding token
in
_stream method.
- Issue: https://github.com/langchain-ai/langchain/issues/16913
- Dependencies: None
2024-03-03 14:15:11 -08:00
William De Vena
275877980e
community[patch]: Invoke callback prior to yielding token (#18447)
## PR title
community[patch]: Invoke callback prior to yielding token

## PR message
Description: Invoke callback prior to yielding token in _stream method
in llms/vertexai.
Issue: https://github.com/langchain-ai/langchain/issues/16913
Dependencies: None
2024-03-03 14:14:40 -08:00
William De Vena
67375e96e0
community[patch]: Invoke callback prior to yielding token (#18448)
## PR title
community[patch]: Invoke callback prior to yielding token

## PR message
- Description: Invoke callback prior to yielding token in _stream method
in llms/tongyi.
- Issue: https://github.com/langchain-ai/langchain/issues/16913
- Dependencies: None
2024-03-03 14:14:22 -08:00
William De Vena
2087cbae64
community[patch]: Invoke callback prior to yielding token (#18449)
## PR title
community[patch]: Invoke callback prior to yielding token

## PR message
- Description: Invoke callback prior to yielding token in _stream method
in chat_models/perplexity.
- Issue: https://github.com/langchain-ai/langchain/issues/16913
- Dependencies: None
2024-03-03 14:14:00 -08:00
William De Vena
eb04d0d3e2
community[patch]: Invoke callback prior to yielding token (#18452)
## PR title
community[patch]: Invoke callback prior to yielding token

## PR message
- Description: Invoke callback prior to yielding token in _stream and
_astream methods in llms/anthropic.
- Issue: https://github.com/langchain-ai/langchain/issues/16913
- Dependencies: None
2024-03-03 14:13:41 -08:00
William De Vena
371bec79bc
community[patch]: Invoke callback prior to yielding token (#18454)
## PR title
community[patch]: Invoke callback prior to yielding token

## PR message
- Description: Invoke callback prior to yielding token in _stream and
_astream methods in llms/baidu_qianfan_endpoint.
- Issue: https://github.com/langchain-ai/langchain/issues/16913
- Dependencies: None
2024-03-03 14:13:22 -08:00
Aayush Kataria
7c2f3f6f95
community[minor]: Adding Azure Cosmos Mongo vCore Vector DB Cache (#16856)
Description:

This pull request introduces several enhancements for Azure Cosmos
Vector DB, primarily focused on improving caching and search
capabilities using Azure Cosmos MongoDB vCore Vector DB. Here's a
summary of the changes:

- **AzureCosmosDBSemanticCache**: Added a new cache implementation
called AzureCosmosDBSemanticCache, which utilizes Azure Cosmos MongoDB
vCore Vector DB for efficient caching of semantic data. Added
comprehensive test cases for AzureCosmosDBSemanticCache to ensure its
correctness and robustness. These tests cover various scenarios and edge
cases to validate the cache's behavior.
- **HNSW Vector Search**: Added HNSW vector search functionality in the
CosmosDB Vector Search module. This enhancement enables more efficient
and accurate vector searches by utilizing the HNSW (Hierarchical
Navigable Small World) algorithm. Added corresponding test cases to
validate the HNSW vector search functionality in both
AzureCosmosDBSemanticCache and AzureCosmosDBVectorSearch. These tests
ensure the correctness and performance of the HNSW search algorithm.
- **LLM Caching Notebook** - The notebook now includes a comprehensive
example showcasing the usage of the AzureCosmosDBSemanticCache. This
example highlights how the cache can be employed to efficiently store
and retrieve semantic data. Additionally, the example provides default
values for all parameters used within the AzureCosmosDBSemanticCache,
ensuring clarity and ease of understanding for users who are new to the
cache implementation.
 
 @hwchase17,@baskaryan, @eyurtsev,
2024-03-03 14:04:15 -08:00
Bagatur
db47b5deee
docs: anthropic quickstart (#18440) 2024-03-03 13:59:28 -08:00
Bagatur
74f3908182
docs: anthropic qa quickstart (#18459) 2024-03-03 13:33:24 -08:00
Harrison Chase
bc768a12ed
more query analysis docs (#18358) 2024-03-02 08:44:22 -08:00
Erick Friis
f96dd57501
langchain[patch]: release 0.1.10 (#18410) 2024-03-02 01:48:57 +00:00
Erick Friis
1fd1ac8e95
community[patch]: release 0.0.25 (#18408) 2024-03-02 00:56:04 +00:00
aditya thomas
44b33fcc76
infra: update to pathspec for 'git grep' in lint check (#18178)
**Description:** Update to the pathspec for 'git grep' in lint check in
the Makefile
**Issue:** The pathspec {docs/docs,templates,cookbook} is not handled
correctly leading to the error during 'make lint' -
"fatal: ambiguous argument '{docs/docs,templates,cookbook}': unknown
revision or path not in the working tree."
See changes made in https://github.com/langchain-ai/langchain/pull/18058

Co-authored-by: Erick Friis <erick@langchain.dev>
2024-03-01 22:03:45 +00:00
standby24x7
57c733e560
docs: Fix spelling typos in apache_kafka notebook (#17998)
This patch fixes some spelling typos in
apache_kafka_message_handling.ipynb

Signed-off-by: Masanari Iida <standby24x7@gmail.com>
2024-03-01 13:58:04 -08:00
Erick Friis
9fda6ac7e6
docs: stop copying source (#18404) 2024-03-01 13:57:53 -08:00
Sourav Pradhan
50abeb7ed9
community[patch]: fix Chroma add_images (#17964)
###  Description

Fixed a small bug in chroma.py add_images(), previously whenever we are
not passing metadata the documents is containing the base64 of the uris
passed, but when we are passing the metadata the documents is containing
normal string uris which should not be the case.

### Issue

In add_images() method when we are calling upsert() we have to use
"b64_texts" instead of normal string "uris".

### Twitter handle

https://twitter.com/whitepegasus01
2024-03-01 21:55:58 +00:00
Sanjaypranav V M
d722525c70
templates: remove gemini_function_agent unused file (#18112)
- [X] Gemini Agent Executor imported `agent.py` has Gemini agent
executor which was not utilised in current template of gemini function
agent 🧑‍💻 instead openai_function_agent has been used


@sbusso  @jarib  please someone review it

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
2024-03-01 21:55:20 +00:00
Kate Silverstein
b7c71e2e07
community[minor]: llamafile embeddings support (#17976)
* **Description:** adds `LlamafileEmbeddings` class implementation for
generating embeddings using
[llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models.
Includes related unit tests and notebook showing example usage.
* **Issue:** N/A
* **Dependencies:** N/A
2024-03-01 13:49:18 -08:00
Massimiliano Pronesti
c3c987dd70
docs: update Azure OpenAI to v1 and langchain API to 0.1 (#18005)
**Description:** Updated Azure OpenAI docs to OpenAI API v1 and LLM
invocation to langchain 0.1
2024-03-01 13:47:00 -08:00
Mateusz Szewczyk
9298a0b941
langchain_ibm[patch] update docstring, dependencies, tests (#18386)
- **Description:** Update docstring, dependencies, tests, README
- **Dependencies:**
[ibm-watsonx-ai](https://pypi.org/project/ibm-watsonx-ai/),
  - **Tag maintainer:** : 

Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally -> 
Please make sure integration_tests passing locally -> 

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
2024-03-01 21:01:53 +00:00
Jib
c2b1abe91b
mongodb[patch]: Set delete_many only if count_documents is not 0 (#18402)
- [x] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** Remove the assert statement on the `count_documents`
in setup_class. It should just delete if there are documents present
    - **Issue:** the issue # Crashes on class setup
    - **Dependencies:** None
    - **Twitter handle:** @mongodb


- [x] **Add tests and docs**: If you're adding a new integration, please
include
  1. N/A


- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/

Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.

If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.

Co-authored-by: Jib <jib@byblack.us>
2024-03-01 13:01:28 -08:00
Kate Silverstein
c9153a3fd4
docs: add llamafile info to 'Local LLMs' guides (#18049)
- **Description:** add information about
[llamafile](https://github.com/Mozilla-Ocho/llamafile) (setup, example
usage) to ['Run LLMs
locally'](https://python.langchain.com/docs/guides/local_llms) and
['Using local models for Q&A with
RAG'](https://python.langchain.com/docs/use_cases/question_answering/local_retrieval_qa)
guides.
- **Issue:** N/A
- **Dependencies:** N/A
2024-03-01 12:44:31 -08:00
Tomaz Bratanic
f6bfb969ba
community[patch]: Add an option for indexed generic label when import neo4j graph documents (#18122)
Current implementation doesn't have an indexed property that would
optimize the import. I have added a `baseEntityLabel` parameter that
allows you to add a secondary node label, which has an indexed id
`property`. By default, the behaviour is identical to previous version.

Since multi-labeled nodes are terrible for text2cypher, I removed the
secondary label from schema representation object and string, which is
used in text2cypher.
2024-03-01 12:33:52 -08:00
aditya thomas
e6e60e2492
docs: ChatOpenAI update module import path and calling method (#18169)
**Description:**
(a) Update to the module import path to reflect the splitting up of
langchain into separate packages
(b) Update to the documentation to include the new calling method
(invoke)
2024-03-01 12:32:20 -08:00
Arun Sathiya
4adac20d7b
community[patch]: Make cohere_api_key a SecretStr (#12188)
This PR makes `cohere_api_key` in `llms/cohere` a SecretStr, so that the
API Key is not leaked when `Cohere.cohere_api_key` is represented as a
string.

---------

Signed-off-by: Arun <arun@arun.blog>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
2024-03-01 20:27:53 +00:00
Ryan Meinzer
d883fd4a37
docs: Correct WebBaseLoader URL: docs: python.langchain.com/docs/get_started/quickstartQuickstart (#17981)
**Description:** 
The URL of the data to index, specified to `WebBaseLoader` to import is
incorrect, causing the `langsmith_search` retriever to return a `404:
NOT_FOUND`.
Incorrect URL: https://docs.smith.langchain.com/overview
Correct URL: https://docs.smith.langchain.com

**Issue:** 
This commit corrects the URL and prevents the LangServe Playground from
returning an error from its inability to use the retriever when
inquiring, "how can langsmith help with testing?".

**Dependencies:** 
None.

**Twitter Handle:** 
@ryanmeinzer
2024-03-01 12:21:53 -08:00
Petteri Johansson
6c1989d292
community[minor], langchain[minor], docs: Gremlin Graph Store and QA Chain (#17683)
- **Description:** 
New feature: Gremlin graph-store and QA chain (including docs).
Compatible with Azure CosmosDB.
  - **Dependencies:** 
  no changes
2024-03-01 12:21:14 -08:00
Ather Fawaz
a5ccf5d33c
community[minor]: Add support for Perplexity chat model(#17024)
- **Description:** This PR adds support for [Perplexity AI
APIs](https://blog.perplexity.ai/blog/introducing-pplx-api).
  - **Issues:** None
  - **Dependencies:** None
  - **Twitter handle:** [@atherfawaz](https://twitter.com/AtherFawaz)

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
2024-03-01 12:19:23 -08:00
Rodrigo Nogueira
3438d2cbcc
community[minor]: add maritalk chat (#17675)
**Description:** Adds the MariTalk chat that is based on a LLM specially
trained for Portuguese.

**Twitter handle:** @MaritacaAI
2024-03-01 12:18:23 -08:00
sarahberenji
08fa38d56d
community[patch]: the syntax error for Redis generated query (#17717)
To fix the reported error:
https://github.com/langchain-ai/langchain/discussions/17397
2024-03-01 12:18:10 -08:00
certified-dodo
43e3244573
community[patch]: Fix MongoDBAtlasVectorSearch max_marginal_relevance_search (#17971)
Description:
* `self._embedding_key` is accessed after deletion, breaking
`max_marginal_relevance_search` search
* Introduced in:
e135e5257c
* Updated but still persists in:
ce22e10c4b

Issue: https://github.com/langchain-ai/langchain/issues/17963

Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-03-01 12:17:42 -08:00
Nikita Titov
9f2ab37162
community[patch]: don't try to parse json in case of errored response (#18317)
Related issue: #13896.

In case Ollama is behind a proxy, proxy error responses cannot be
viewed. You aren't even able to check response code.

For example, if your Ollama has basic access authentication and it's not
passed, `JSONDecodeError` will overwrite the truth response error.

<details>
<summary><b>Log now:</b></summary>

```
{
	"name": "JSONDecodeError",
	"message": "Expecting value: line 1 column 1 (char 0)",
	"stack": "---------------------------------------------------------------------------
JSONDecodeError                           Traceback (most recent call last)
File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/requests/models.py:971, in Response.json(self, **kwargs)
    970 try:
--> 971     return complexjson.loads(self.text, **kwargs)
    972 except JSONDecodeError as e:
    973     # Catch JSON-related errors and raise as requests.JSONDecodeError
    974     # This aliases json.JSONDecodeError and simplejson.JSONDecodeError

File /opt/miniforge3/envs/.gpt/lib/python3.10/json/__init__.py:346, in loads(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)
    343 if (cls is None and object_hook is None and
    344         parse_int is None and parse_float is None and
    345         parse_constant is None and object_pairs_hook is None and not kw):
--> 346     return _default_decoder.decode(s)
    347 if cls is None:

File /opt/miniforge3/envs/.gpt/lib/python3.10/json/decoder.py:337, in JSONDecoder.decode(self, s, _w)
    333 \"\"\"Return the Python representation of ``s`` (a ``str`` instance
    334 containing a JSON document).
    335 
    336 \"\"\"
--> 337 obj, end = self.raw_decode(s, idx=_w(s, 0).end())
    338 end = _w(s, end).end()

File /opt/miniforge3/envs/.gpt/lib/python3.10/json/decoder.py:355, in JSONDecoder.raw_decode(self, s, idx)
    354 except StopIteration as err:
--> 355     raise JSONDecodeError(\"Expecting value\", s, err.value) from None
    356 return obj, end

JSONDecodeError: Expecting value: line 1 column 1 (char 0)

During handling of the above exception, another exception occurred:

JSONDecodeError                           Traceback (most recent call last)
Cell In[3], line 1
----> 1 print(translate_func().invoke('text'))

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/runnables/base.py:2053, in RunnableSequence.invoke(self, input, config)
   2051 try:
   2052     for i, step in enumerate(self.steps):
-> 2053         input = step.invoke(
   2054             input,
   2055             # mark each step as a child run
   2056             patch_config(
   2057                 config, callbacks=run_manager.get_child(f\"seq:step:{i+1}\")
   2058             ),
   2059         )
   2060 # finish the root run
   2061 except BaseException as e:

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:165, in BaseChatModel.invoke(self, input, config, stop, **kwargs)
    154 def invoke(
    155     self,
    156     input: LanguageModelInput,
   (...)
    160     **kwargs: Any,
    161 ) -> BaseMessage:
    162     config = ensure_config(config)
    163     return cast(
    164         ChatGeneration,
--> 165         self.generate_prompt(
    166             [self._convert_input(input)],
    167             stop=stop,
    168             callbacks=config.get(\"callbacks\"),
    169             tags=config.get(\"tags\"),
    170             metadata=config.get(\"metadata\"),
    171             run_name=config.get(\"run_name\"),
    172             **kwargs,
    173         ).generations[0][0],
    174     ).message

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:543, in BaseChatModel.generate_prompt(self, prompts, stop, callbacks, **kwargs)
    535 def generate_prompt(
    536     self,
    537     prompts: List[PromptValue],
   (...)
    540     **kwargs: Any,
    541 ) -> LLMResult:
    542     prompt_messages = [p.to_messages() for p in prompts]
--> 543     return self.generate(prompt_messages, stop=stop, callbacks=callbacks, **kwargs)

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:407, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, **kwargs)
    405         if run_managers:
    406             run_managers[i].on_llm_error(e, response=LLMResult(generations=[]))
--> 407         raise e
    408 flattened_outputs = [
    409     LLMResult(generations=[res.generations], llm_output=res.llm_output)
    410     for res in results
    411 ]
    412 llm_output = self._combine_llm_outputs([res.llm_output for res in results])

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:397, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, **kwargs)
    394 for i, m in enumerate(messages):
    395     try:
    396         results.append(
--> 397             self._generate_with_cache(
    398                 m,
    399                 stop=stop,
    400                 run_manager=run_managers[i] if run_managers else None,
    401                 **kwargs,
    402             )
    403         )
    404     except BaseException as e:
    405         if run_managers:

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:576, in BaseChatModel._generate_with_cache(self, messages, stop, run_manager, **kwargs)
    572     raise ValueError(
    573         \"Asked to cache, but no cache found at `langchain.cache`.\"
    574     )
    575 if new_arg_supported:
--> 576     return self._generate(
    577         messages, stop=stop, run_manager=run_manager, **kwargs
    578     )
    579 else:
    580     return self._generate(messages, stop=stop, **kwargs)

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_community/chat_models/ollama.py:250, in ChatOllama._generate(self, messages, stop, run_manager, **kwargs)
    226 def _generate(
    227     self,
    228     messages: List[BaseMessage],
   (...)
    231     **kwargs: Any,
    232 ) -> ChatResult:
    233     \"\"\"Call out to Ollama's generate endpoint.
    234 
    235     Args:
   (...)
    247             ])
    248     \"\"\"
--> 250     final_chunk = self._chat_stream_with_aggregation(
    251         messages,
    252         stop=stop,
    253         run_manager=run_manager,
    254         verbose=self.verbose,
    255         **kwargs,
    256     )
    257     chat_generation = ChatGeneration(
    258         message=AIMessage(content=final_chunk.text),
    259         generation_info=final_chunk.generation_info,
    260     )
    261     return ChatResult(generations=[chat_generation])

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_community/chat_models/ollama.py:183, in ChatOllama._chat_stream_with_aggregation(self, messages, stop, run_manager, verbose, **kwargs)
    174 def _chat_stream_with_aggregation(
    175     self,
    176     messages: List[BaseMessage],
   (...)
    180     **kwargs: Any,
    181 ) -> ChatGenerationChunk:
    182     final_chunk: Optional[ChatGenerationChunk] = None
--> 183     for stream_resp in self._create_chat_stream(messages, stop, **kwargs):
    184         if stream_resp:
    185             chunk = _chat_stream_response_to_chat_generation_chunk(stream_resp)

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_community/chat_models/ollama.py:156, in ChatOllama._create_chat_stream(self, messages, stop, **kwargs)
    147 def _create_chat_stream(
    148     self,
    149     messages: List[BaseMessage],
    150     stop: Optional[List[str]] = None,
    151     **kwargs: Any,
    152 ) -> Iterator[str]:
    153     payload = {
    154         \"messages\": self._convert_messages_to_ollama_messages(messages),
    155     }
--> 156     yield from self._create_stream(
    157         payload=payload, stop=stop, api_url=f\"{self.base_url}/api/chat/\", **kwargs
    158     )

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_community/llms/ollama.py:234, in _OllamaCommon._create_stream(self, api_url, payload, stop, **kwargs)
    228         raise OllamaEndpointNotFoundError(
    229             \"Ollama call failed with status code 404. \"
    230             \"Maybe your model is not found \"
    231             f\"and you should pull the model with `ollama pull {self.model}`.\"
    232         )
    233     else:
--> 234         optional_detail = response.json().get(\"error\")
    235         raise ValueError(
    236             f\"Ollama call failed with status code {response.status_code}.\"
    237             f\" Details: {optional_detail}\"
    238         )
    239 return response.iter_lines(decode_unicode=True)

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/requests/models.py:975, in Response.json(self, **kwargs)
    971     return complexjson.loads(self.text, **kwargs)
    972 except JSONDecodeError as e:
    973     # Catch JSON-related errors and raise as requests.JSONDecodeError
    974     # This aliases json.JSONDecodeError and simplejson.JSONDecodeError
--> 975     raise RequestsJSONDecodeError(e.msg, e.doc, e.pos)

JSONDecodeError: Expecting value: line 1 column 1 (char 0)"
}
```

</details>


<details>

<summary><b>Log after a fix:</b></summary>

```
{
	"name": "ValueError",
	"message": "Ollama call failed with status code 401. Details: <html>\r
<head><title>401 Authorization Required</title></head>\r
<body>\r
<center><h1>401 Authorization Required</h1></center>\r
<hr><center>nginx/1.18.0 (Ubuntu)</center>\r
</body>\r
</html>\r
",
	"stack": "---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[2], line 1
----> 1 print(translate_func().invoke('text'))

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/runnables/base.py:2053, in RunnableSequence.invoke(self, input, config)
   2051 try:
   2052     for i, step in enumerate(self.steps):
-> 2053         input = step.invoke(
   2054             input,
   2055             # mark each step as a child run
   2056             patch_config(
   2057                 config, callbacks=run_manager.get_child(f\"seq:step:{i+1}\")
   2058             ),
   2059         )
   2060 # finish the root run
   2061 except BaseException as e:

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:165, in BaseChatModel.invoke(self, input, config, stop, **kwargs)
    154 def invoke(
    155     self,
    156     input: LanguageModelInput,
   (...)
    160     **kwargs: Any,
    161 ) -> BaseMessage:
    162     config = ensure_config(config)
    163     return cast(
    164         ChatGeneration,
--> 165         self.generate_prompt(
    166             [self._convert_input(input)],
    167             stop=stop,
    168             callbacks=config.get(\"callbacks\"),
    169             tags=config.get(\"tags\"),
    170             metadata=config.get(\"metadata\"),
    171             run_name=config.get(\"run_name\"),
    172             **kwargs,
    173         ).generations[0][0],
    174     ).message

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:543, in BaseChatModel.generate_prompt(self, prompts, stop, callbacks, **kwargs)
    535 def generate_prompt(
    536     self,
    537     prompts: List[PromptValue],
   (...)
    540     **kwargs: Any,
    541 ) -> LLMResult:
    542     prompt_messages = [p.to_messages() for p in prompts]
--> 543     return self.generate(prompt_messages, stop=stop, callbacks=callbacks, **kwargs)

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:407, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, **kwargs)
    405         if run_managers:
    406             run_managers[i].on_llm_error(e, response=LLMResult(generations=[]))
--> 407         raise e
    408 flattened_outputs = [
    409     LLMResult(generations=[res.generations], llm_output=res.llm_output)
    410     for res in results
    411 ]
    412 llm_output = self._combine_llm_outputs([res.llm_output for res in results])

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:397, in BaseChatModel.generate(self, messages, stop, callbacks, tags, metadata, run_name, **kwargs)
    394 for i, m in enumerate(messages):
    395     try:
    396         results.append(
--> 397             self._generate_with_cache(
    398                 m,
    399                 stop=stop,
    400                 run_manager=run_managers[i] if run_managers else None,
    401                 **kwargs,
    402             )
    403         )
    404     except BaseException as e:
    405         if run_managers:

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_core/language_models/chat_models.py:576, in BaseChatModel._generate_with_cache(self, messages, stop, run_manager, **kwargs)
    572     raise ValueError(
    573         \"Asked to cache, but no cache found at `langchain.cache`.\"
    574     )
    575 if new_arg_supported:
--> 576     return self._generate(
    577         messages, stop=stop, run_manager=run_manager, **kwargs
    578     )
    579 else:
    580     return self._generate(messages, stop=stop, **kwargs)

File /opt/miniforge3/envs/.gpt/lib/python3.10/site-packages/langchain_community/chat_models/ollama.py:250, in ChatOllama._generate(self, messages, stop, run_manager, **kwargs)
    226 def _generate(
    227     self,
    228     messages: List[BaseMessage],
   (...)
    231     **kwargs: Any,
    232 ) -> ChatResult:
    233     \"\"\"Call out to Ollama's generate endpoint.
    234 
    235     Args:
   (...)
    247             ])
    248     \"\"\"
--> 250     final_chunk = self._chat_stream_with_aggregation(
    251         messages,
    252         stop=stop,
    253         run_manager=run_manager,
    254         verbose=self.verbose,
    255         **kwargs,
    256     )
    257     chat_generation = ChatGeneration(
    258         message=AIMessage(content=final_chunk.text),
    259         generation_info=final_chunk.generation_info,
    260     )
    261     return ChatResult(generations=[chat_generation])

File /storage/gpt-project/Repos/repo_nikita/gpt_lib/langchain/ollama.py:328, in ChatOllamaCustom._chat_stream_with_aggregation(self, messages, stop, run_manager, verbose, **kwargs)
    319 def _chat_stream_with_aggregation(
    320     self,
    321     messages: List[BaseMessage],
   (...)
    325     **kwargs: Any,
    326 ) -> ChatGenerationChunk:
    327     final_chunk: Optional[ChatGenerationChunk] = None
--> 328     for stream_resp in self._create_chat_stream(messages, stop, **kwargs):
    329         if stream_resp:
    330             chunk = _chat_stream_response_to_chat_generation_chunk(stream_resp)

File /storage/gpt-project/Repos/repo_nikita/gpt_lib/langchain/ollama.py:301, in ChatOllamaCustom._create_chat_stream(self, messages, stop, **kwargs)
    292 def _create_chat_stream(
    293     self,
    294     messages: List[BaseMessage],
    295     stop: Optional[List[str]] = None,
    296     **kwargs: Any,
    297 ) -> Iterator[str]:
    298     payload = {
    299         \"messages\": self._convert_messages_to_ollama_messages(messages),
    300     }
--> 301     yield from self._create_stream(
    302         payload=payload, stop=stop, api_url=f\"{self.base_url}/api/chat\", **kwargs
    303     )

File /storage/gpt-project/Repos/repo_nikita/gpt_lib/langchain/ollama.py:134, in _OllamaCommonCustom._create_stream(self, api_url, payload, stop, **kwargs)
    132     else:
    133         optional_detail = response.text
--> 134         raise ValueError(
    135             f\"Ollama call failed with status code {response.status_code}.\"
    136             f\" Details: {optional_detail}\"
    137         )
    138 return response.iter_lines(decode_unicode=True)

ValueError: Ollama call failed with status code 401. Details: <html>\r
<head><title>401 Authorization Required</title></head>\r
<body>\r
<center><h1>401 Authorization Required</h1></center>\r
<hr><center>nginx/1.18.0 (Ubuntu)</center>\r
</body>\r
</html>\r
"
}
```

</details>

The same is true for timeout errors or when you simply mistyped in
`base_url` arg and get response from some other service, for instance.

Real Ollama errors are still clearly readable:

```
ValueError: Ollama call failed with status code 400. Details: {"error":"invalid options: unknown_option"}
```

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-03-01 12:17:29 -08:00