Merge pull request #164 from NimbleBoxAI/yash/multiapi-bugfix

[chore] automate generation of components list

.github/workflows/static.yml

@@ -46,6 +46,8 @@ jobs:
           python -m pip install sphinx-rtd-theme==1.2.2
           cd server
           python3 -m pip install .
+          cd ..
+          python3 scripts/list_builtins.py ./api_docs/templates/components-list.rst ./api_docs/examples/components-list.rst
 
       - name: Build docs
         run: |

api_docs/cf_server/chainfury_server.api.rst

@@ -13,6 +13,5 @@ Submodules
    :maxdepth: 4
 
    chainfury_server.api.chains
-   chainfury_server.api.fury
    chainfury_server.api.prompts
    chainfury_server.api.user

api_docs/examples/components-list.rst

@@ -0,0 +1,75 @@
+Components List
+===============
+
+.. this is a jinja template document, run scripts/list_builtins.py to generate components-list.rst
+
+There are several components that are shipped with the ``chainfury``. You can find how to access the underlying function
+via the `components page`_.
+
+.. code-block::python
+
+  # load the registries you can do these imports
+  from chainfury import programatic_actions_registry, ai_actions_registry
+
+Programatic Actions
+-------------------
+
+Programatic means that these are generally not an LLM call rather something more standard like calling an API,
+transforming the data, etc.
+
+
+* `serper-api` - Search the web with Serper. Copy: ``programatic_actions_registry.get("serper-api")``
+
+* `call_api_requests` - Call an API using the requests library. Copy: ``programatic_actions_registry.get("call_api_requests")``
+
+* `regex_search` - Perform a regex search on the text and get items in an array. Copy: ``programatic_actions_registry.get("regex_search")``
+
+* `regex_substitute` - Perform a regex substitution on the text and get the result. Copy: ``programatic_actions_registry.get("regex_substitute")``
+
+* `json_translator` - Extract a value from a JSON object using a list of keys. Copy: ``programatic_actions_registry.get("json_translator")``
+
+
+AI Action Components
+--------------------
+
+These actions generally take the input, create a custom prompt, call the Model and respond back with the result.
+
+
+* `hello-world` - Python function loaded from a file used as an AI action. Copy: ``ai_actions_registry.get("hello-world")``
+
+* `deep-rap-quote` - J-type action will write a deep poem in the style of a character. Copy: ``ai_actions_registry.get("deep-rap-quote")``
+
+
+Memory Components
+-----------------
+
+Memory components are used to store data, which can be a Vector DB or Redis, etc.
+
+
+* `qdrant-write` - Write to the Qdrant DB using the Qdrant client. Copy: ``memory_registry.get_write("qdrant-write")``
+
+* `qdrant-read` - Function to read from the Qdrant DB using the Qdrant client. Copy: ``memory_registry.get_read("qdrant-read")``
+
+
+Model Components
+----------------
+
+Model are the different GenAI models that can be used from the ``chainfury``.
+
+
+* `stability-text-to-image` - Generate a new image from a text prompt. Copy: ``model_registry.get("stability-text-to-image")``
+
+* `chatnbx` - Chat with the ChatNBX API with OpenAI compatability, see more at https://chat.nbox.ai/. Copy: ``model_registry.get("chatnbx")``
+
+* `nbx-deploy` - Call NimbleBox LLMOps deploy API. Copy: ``model_registry.get("nbx-deploy")``
+
+* `openai-completion` - Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position. Copy: ``model_registry.get("openai-completion")``
+
+* `openai-chat` - Given a list of messages describing a conversation, the model will return a response. Copy: ``model_registry.get("openai-chat")``
+
+* `openai-embedding` - Given a list of messages create embeddings for each message. Copy: ``model_registry.get("openai-embedding")``
+
+
+.. all the links are here
+
+.. _components page: https://qdrant.tech/documentation/tutorials/bulk-upload/#upload-directly-to-disk

api_docs/index.rst

@@ -48,7 +48,6 @@ Read the latest blog posts:
 
    examples/install
    examples/storing-private-data
-   examples/use-chainfury-privately
 
 .. toctree::
    :maxdepth: 2
@@ -65,6 +64,7 @@ Read the latest blog posts:
    :caption: Integrations
 
    source/chainfury.components
+   examples/components-list
 
 .. toctree::
    :maxdepth: 2

api_docs/templates/components-list.rst

@@ -0,0 +1,54 @@
+Components List
+===============
+
+.. this is a jinja template document, run scripts/list_builtins.py to generate components-list.rst
+
+There are several components that are shipped with the ``chainfury``. You can find how to access the underlying function
+via the `components page`_.
+
+.. code-block::python
+
+  # load the registries you can do these imports
+  from chainfury import programatic_actions_registry, ai_actions_registry
+
+Programatic Actions
+-------------------
+
+Programatic means that these are generally not an LLM call rather something more standard like calling an API,
+transforming the data, etc.
+
+{% for component in pc %}
+* `{{ component.id }}` - {{ component.description }}
+{% endfor %}
+
+AI Action Components
+--------------------
+
+These actions generally take the input, create a custom prompt, call the Model and respond back with the result.
+
+{% for component in ac %}
+* `{{ component.id }}` - {{ component.description }}
+{% endfor %}
+
+Memory Components
+-----------------
+
+Memory components are used to store data, which can be a Vector DB or Redis, etc.
+
+{% for component in mc %}
+* `{{ component.id }}` - {{ component.description }}
+{% endfor %}
+
+Model Components
+----------------
+
+Model are the different GenAI models that can be used from the ``chainfury``.
+
+{% for component in moc %}
+* `{{ component.id }}` - {{ component.description }}
+{% endfor %}
+
+.. all the links are here
+
+.. _components page: https://qdrant.tech/documentation/tutorials/bulk-upload/#upload-directly-to-disk
+

chainfury/agent.py

@@ -695,7 +695,7 @@ def __call__(self, **data: Dict[str, Any]) -> Any:
 
 class MemoryRegistry:
     def __init__(self) -> None:
-        self._memories = {}
+        self._memories: Dict[str, Node] = {}
 
     def register_write(
         self,

chainfury/base.py

@@ -577,7 +577,7 @@ def __init__(
         collection_name: str,
         id: str,
         fn: object,
-        description,
+        description: str = "",
         usage: List[Union[str, int]] = [],
         tags=[],
     ):

chainfury/components/qdrant/__init__.py

@@ -143,6 +143,7 @@ def _insert():
     fn=qdrant_write,
     outputs={"status": 0},
     vector_key="embeddings",
+    description="Write to the Qdrant DB using the Qdrant client",
 )
 
 
@@ -251,6 +252,7 @@ def qdrant_read(
     fn=qdrant_read,
     outputs={"items": 0},
     vector_key="embeddings",
+    description="Function to read from the Qdrant DB using the Qdrant client",
 )
 
 

scripts/list_builtins.py

@@ -0,0 +1,58 @@
+from fire import Fire
+import jinja2 as j2
+from chainfury import programatic_actions_registry, ai_actions_registry, memory_registry, model_registry
+
+
+def main(src_file: str, trg_file: str, v: bool = False):
+    with open(src_file, "r") as f:
+        temp = j2.Template(f.read())
+
+    # create the components list
+    pc = []
+    for node_id, node in programatic_actions_registry.nodes.items():
+        pc.append(
+            {
+                "id": node.id,
+                "description": node.description.rstrip(".") + f'. Copy: ``programatic_actions_registry.get("{node.id}")``',
+            }
+        )
+
+    ac = []
+    for node_id, node in ai_actions_registry.nodes.items():
+        ac.append(
+            {
+                "id": node.id,
+                "description": node.description.rstrip(".") + f'. Copy: ``ai_actions_registry.get("{node.id}")``',
+            }
+        )
+
+    mc = []
+    for node_id, node in memory_registry._memories.items():
+        fn = "get_read" if node.id.endswith("-read") else "get_write"
+        mc.append(
+            {
+                "id": node.id,
+                "description": node.description.rstrip(".") + f'. Copy: ``memory_registry.{fn}("{node.id}")``',
+            }
+        )
+
+    moc = []
+    for model_id, model in model_registry.models.items():
+        moc.append(
+            {
+                "id": model_id,
+                "description": model.description.rstrip(".") + f'. Copy: ``model_registry.get("{model_id}")``',
+            }
+        )
+
+    op = temp.render(pc=pc, ac=ac, mc=mc, moc=moc)
+    if v:
+        print(op)
+        print("Writing to", trg_file)
+
+    with open(trg_file, "w") as f:
+        f.write(op)
+
+
+if __name__ == "__main__":
+    Fire(main)