- Remove dynamic model creation in the `args()` property. _Only infer
for the decorator (and add an argument to NOT infer if someone wishes to
only pass as a string)_
- Update the validation example to make it less likely to be
misinterpreted as a "safe" way to run a repl
There is one example of "Multi-argument tools" in the custom_tools.ipynb
from yesterday, but we could add more. The output parsing for the base
MRKL agent hasn't been adapted to handle structured args at this point
in time
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
- This PR essentially implements the chains outlined in the [LangChain
Wiki](https://python.langchain.com/en/latest/use_cases/agents/baby_agi.html),
some slight modifications and re-factoring was done to get it to work
with the standard `VectorStore` class and to have all the relevant
functions in the same class as BabyAGI so that the chain could run
effectively independently
- I think it is worth having these chains as a standalone on the
LangChain repo, as orchestration is becoming huge, and there are a lot
of other chains being built off of these as a base
- `make lint` and `make format` have been run locally and are succeeding
## Background
This PR fixes this error when there are special tokens when querying the
chain:
```
Encountered text corresponding to disallowed special token '<|endofprompt|>'.
If you want this text to be encoded as a special token, pass it to `allowed_special`, e.g. `allowed_special={'<|endofprompt|>', ...}`.
If you want this text to be encoded as normal text, disable the check for this token by passing `disallowed_special=(enc.special_tokens_set - {'<|endofprompt|>'})`.
To disable this check for all special tokens, pass `disallowed_special=()`.
```
Refer to the code snippet below, it breaks in the chain line.
```
chain = ConversationalRetrievalChain.from_llm(
ChatOpenAI(openai_api_key=OPENAI_API_KEY),
retriever=vectorstore.as_retriever(),
qa_prompt=prompt,
condense_question_prompt=condense_prompt,
)
answer = chain({"question": f"{question}"})
```
However `ChatOpenAI` class is not accepting `allowed_special` and
`disallowed_special` at the moment so they cannot be passed to the
`encode()` in `get_num_tokens` method to avoid the errors.
## Change
- Add `allowed_special` and `disallowed_special` attributes to
`BaseOpenAI` class.
- Pass in `allowed_special` and `disallowed_special` as arguments of
`encode()` in tiktoken.
---------
Co-authored-by: samcarmen <“carmen.samkahman@gmail.com”>
I made a couple of improvements to the Comet tracker:
* The Comet project name is configurable in various ways (code,
environment variable or file), having a default value in code meant that
users couldn't set the project name in an environment variable or in a
file.
* I added error catching when the `flush_tracker` is called in order to
avoid crashing the whole process. Instead we are gonna display a warning
or error log message (`extra={"show_traceback": True}` is an internal
convention to force the display of the traceback when using our own
logger).
I decided to add the error catching after seeing the following error in
the third example of the notebook:
```
COMET ERROR: Failed to export agent or LLM to Comet
Traceback (most recent call last):
File "/home/lothiraldan/project/cometml/langchain/langchain/callbacks/comet_ml_callback.py", line 484, in _log_model
langchain_asset.save(langchain_asset_path)
File "/home/lothiraldan/project/cometml/langchain/langchain/agents/agent.py", line 591, in save
raise ValueError(
ValueError: Saving not supported for agent executors. If you are trying to save the agent, please use the `.save_agent(...)`
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/lothiraldan/project/cometml/langchain/langchain/callbacks/comet_ml_callback.py", line 449, in flush_tracker
self._log_model(langchain_asset)
File "/home/lothiraldan/project/cometml/langchain/langchain/callbacks/comet_ml_callback.py", line 488, in _log_model
langchain_asset.save_agent(langchain_asset_path)
File "/home/lothiraldan/project/cometml/langchain/langchain/agents/agent.py", line 599, in save_agent
return self.agent.save(file_path)
File "/home/lothiraldan/project/cometml/langchain/langchain/agents/agent.py", line 145, in save
agent_dict = self.dict()
File "/home/lothiraldan/project/cometml/langchain/langchain/agents/agent.py", line 119, in dict
_dict = super().dict()
File "pydantic/main.py", line 449, in pydantic.main.BaseModel.dict
File "pydantic/main.py", line 868, in _iter
File "pydantic/main.py", line 743, in pydantic.main.BaseModel._get_value
File "/home/lothiraldan/project/cometml/langchain/langchain/schema.py", line 381, in dict
output_parser_dict["_type"] = self._type
File "/home/lothiraldan/project/cometml/langchain/langchain/schema.py", line 376, in _type
raise NotImplementedError
NotImplementedError
```
I still need to investigate and try to fix it, it looks related to
saving an agent to a file.
## Use `index_id` over `app_id`
We made a major update to index + retrieve based on Metal Indexes
(instead of apps). With this change, we accept an index instead of an
app in each of our respective core apis. [More details
here](https://docs.getmetal.io/api-reference/core/indexing).
## What is this PR for:
* This PR adds a commented line of code in the documentation that shows
how someone can use the Pinecone client with an already existing
Pinecone index
* The documentation currently only shows how to create a pinecone index
from langchain documents but not how to load one that already exists
Sometimes the LLM response (generated code) tends to miss the ending
ticks "```". Therefore causing the text parsing to fail due to not
enough values to unpack.
The 2 extra `_` don't add value and can cause errors. Suggest to simply
update the `_, action, _` to just `action` then with index.
Fixes issue #3057
This pull request addresses the need to share a single `chromadb.Client`
instance across multiple instances of the `Chroma` class. By
implementing a shared client, we can maintain consistency and reduce
resource usage when multiple instances of the `Chroma` classes are
created. This is especially relevant in a web app, where having multiple
`Chroma` instances with a `persist_directory` leads to these clients not
being synced.
This PR implements this option while keeping the rest of the
architecture unchanged.
**Changes:**
1. Add a client attribute to the `Chroma` class to store the shared
`chromadb.Client` instance.
2. Modify the `from_documents` method to accept an optional client
parameter.
3. Update the `from_documents` method to use the shared client if
provided or create a new client if not provided.
Let me know if anything needs to be modified - thanks again for your
work on this incredible repo
This PR extends upon @jzluo 's PR #2748 which addressed dialect-specific
issues with SQL prompts, and adds a prompt that uses backticks for
column names when querying BigQuery. See [GoogleSQL quoted
identifiers](https://cloud.google.com/bigquery/docs/reference/standard-sql/lexical#quoted_identifiers).
Additionally, the SQL agent currently uses a generic prompt. Not sure
how best to adopt the same optional dialect-specific prompts as above,
but will consider making an issue and PR for that too. See
[langchain/agents/agent_toolkits/sql/prompt.py](langchain/agents/agent_toolkits/sql/prompt.py).
`langchain.prompts.PromptTemplate` is unable to infer `input_variables`
from jinja2 template.
```python
# Using langchain v0.0.141
template_string = """\
Hello world
Your variable: {{ var }}
{# This will not get rendered #}
{% if verbose %}
Congrats! You just turned on verbose mode and got extra messages!
{% endif %}
"""
template = PromptTemplate.from_template(template_string, template_format="jinja2")
print(template.input_variables) # Output ['# This will not get rendered #', '% endif %', '% if verbose %']
```
---------
Co-authored-by: engkheng <ongengkheng929@example.com>
- Updated `langchain/docs/modules/models/llms/integrations/` notebooks:
added links to the original sites, the install information, etc.
- Added the `nlpcloud` notebook.
- Removed "Example" from Titles of some notebooks, so all notebook
titles are consistent.
### https://github.com/hwchase17/langchain/issues/2997
Replaced `conversation.memory.store` to
`conversation.memory.entity_store.store`
As conversation.memory.store doesn't exist and re-ran the whole file.
