mirror of
https://github.com/hwchase17/langchain.git
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community[minor]: Add tools calls to ChatEdenAI
(#22320)
### Description Add tools implementation to `ChatEdenAI`: - `bind_tools()` - `with_structured_output()` ### Documentation Updated `docs/docs/integrations/chat/edenai.ipynb` ### Notes We don´t support stream with tools as of yet. If stream is called with tools we directly yield the whole message from `generate` (implemented the same way as Anthropic did).
This commit is contained in:
@@ -246,11 +246,220 @@
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"source": [
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"chain.invoke({\"product\": \"healthy snacks\"})"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Tools\n",
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"\n",
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"### bind_tools()\n",
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"\n",
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"With `ChatEdenAI.bind_tools`, we can easily pass in Pydantic classes, dict schemas, LangChain tools, or even functions as tools to the model."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain_core.pydantic_v1 import BaseModel, Field\n",
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"\n",
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"llm = ChatEdenAI(provider=\"openai\", temperature=0.2, max_tokens=500)\n",
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"\n",
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"\n",
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"class GetWeather(BaseModel):\n",
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" \"\"\"Get the current weather in a given location\"\"\"\n",
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"\n",
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" location: str = Field(..., description=\"The city and state, e.g. San Francisco, CA\")\n",
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"\n",
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"\n",
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"llm_with_tools = llm.bind_tools([GetWeather])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"AIMessage(content='', response_metadata={'openai': {'status': 'success', 'generated_text': None, 'message': [{'role': 'user', 'message': 'what is the weather like in San Francisco', 'tools': [{'name': 'GetWeather', 'description': 'Get the current weather in a given location', 'parameters': {'type': 'object', 'properties': {'location': {'description': 'The city and state, e.g. San Francisco, CA', 'type': 'string'}}, 'required': ['location']}}], 'tool_calls': None}, {'role': 'assistant', 'message': None, 'tools': None, 'tool_calls': [{'id': 'call_tRpAO7KbQwgTjlka70mCQJdo', 'name': 'GetWeather', 'arguments': '{\"location\":\"San Francisco\"}'}]}], 'cost': 0.000194}}, id='run-5c44c01a-d7bb-4df6-835e-bda596080399-0', tool_calls=[{'name': 'GetWeather', 'args': {'location': 'San Francisco'}, 'id': 'call_tRpAO7KbQwgTjlka70mCQJdo'}])"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"ai_msg = llm_with_tools.invoke(\n",
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" \"what is the weather like in San Francisco\",\n",
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")\n",
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"ai_msg"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[{'name': 'GetWeather',\n",
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" 'args': {'location': 'San Francisco'},\n",
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" 'id': 'call_tRpAO7KbQwgTjlka70mCQJdo'}]"
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]
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},
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"execution_count": 17,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"ai_msg.tool_calls"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### with_structured_output()\n",
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"\n",
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"The BaseChatModel.with_structured_output interface makes it easy to get structured output from chat models. You can use ChatEdenAI.with_structured_output, which uses tool-calling under the hood), to get the model to more reliably return an output in a specific format:\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"GetWeather(location='San Francisco')"
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]
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},
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"execution_count": 18,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"structured_llm = llm.with_structured_output(GetWeather)\n",
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"structured_llm.invoke(\n",
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" \"what is the weather like in San Francisco\",\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Passing Tool Results to model\n",
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"\n",
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"Here is a full example of how to use a tool. Pass the tool output to the model, and get the result back from the model"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'11 + 11 = 22'"
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]
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},
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"execution_count": 19,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from langchain_core.messages import HumanMessage, ToolMessage\n",
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"from langchain_core.tools import tool\n",
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"\n",
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"\n",
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"@tool\n",
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"def add(a: int, b: int) -> int:\n",
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" \"\"\"Adds a and b.\n",
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"\n",
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" Args:\n",
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" a: first int\n",
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" b: second int\n",
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" \"\"\"\n",
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" return a + b\n",
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"\n",
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"\n",
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"llm = ChatEdenAI(\n",
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" provider=\"openai\",\n",
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" max_tokens=1000,\n",
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" temperature=0.2,\n",
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")\n",
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"\n",
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"llm_with_tools = llm.bind_tools([add], tool_choice=\"required\")\n",
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"\n",
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"query = \"What is 11 + 11?\"\n",
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"\n",
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"messages = [HumanMessage(query)]\n",
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"ai_msg = llm_with_tools.invoke(messages)\n",
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"messages.append(ai_msg)\n",
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"\n",
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"tool_call = ai_msg.tool_calls[0]\n",
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"tool_output = add.invoke(tool_call[\"args\"])\n",
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"\n",
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"# This append the result from our tool to the model\n",
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"messages.append(ToolMessage(tool_output, tool_call_id=tool_call[\"id\"]))\n",
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"\n",
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"llm_with_tools.invoke(messages).content"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Streaming\n",
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"\n",
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"Eden AI does not currently support streaming tool calls. Attempting to stream will yield a single final message."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/home/eden/Projects/edenai-langchain/libs/community/langchain_community/chat_models/edenai.py:603: UserWarning: stream: Tool use is not yet supported in streaming mode.\n",
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" warnings.warn(\"stream: Tool use is not yet supported in streaming mode.\")\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"[AIMessageChunk(content='', id='run-fae32908-ec48-4ab2-ad96-bb0d0511754f', tool_calls=[{'name': 'add', 'args': {'a': 9, 'b': 9}, 'id': 'call_n0Tm7I9zERWa6UpxCAVCweLN'}], tool_call_chunks=[{'name': 'add', 'args': '{\"a\": 9, \"b\": 9}', 'id': 'call_n0Tm7I9zERWa6UpxCAVCweLN', 'index': 0}])]"
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]
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},
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"execution_count": 24,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"list(llm_with_tools.stream(\"What's 9 + 9\"))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "langchain-pr",
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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@@ -96,6 +96,12 @@ CHAT_MODEL_FEAT_TABLE = {
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"package": "langchain-community",
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"link": "/docs/integrations/chat/vllm/",
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},
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"ChatEdenAI": {
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"tool_calling": True,
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"structured_output": True,
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"package": "langchain-community",
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"link": "/docs/integrations/chat/edenai/",
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},
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}
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