Okwu mmalite
Njikọ aka nke Artificial Intelligence (AI), DevOps, na injinịa ngwanrọ ewepụtala usoro ọhụrụ na mmepe ngwanrọ na nnyefe. A na-eji ngwa ọrụ AI na usoro ihe arụ ọrụ na-emezigharị akụkụ dị iche iche nke usoro ndụ mmepe ngwanrọ, gụnyere nyocha ihe merenụ na nnyefe ngwanrọ. N'isiokwu a, anyị ga-enyocha iji DSPy na LangChain maka nhazi nke DevOps kwadoro AI, na-elekwasị anya na nnyefe ngwanrọ na-akpaghị aka na nchọpụta ihe merenụ.
ndabere
DevOps bụ usoro mmepe ngwanrọ nke na-emesi mmekorita na nkwurịta okwu n'etiti mmepe na otu ọrụ iji melite ọsọ, ịdịmma na ntụkwasị obi nke nnyefe ngwanrọ. A na-eji ngwá ọrụ AI na-arụ ọrụ na usoro iji megharịa akụkụ dị iche iche nke DevOps, gụnyere nchọpụta ihe merenụ na nnyefe ngwanrọ.
DSPy bụ ọba akwụkwọ Eke Ọgba nke na-enye ụzọ dị mfe ma dị irè iji jikọta ngwa ọrụ AI na-arụ ọrụ na usoro na pipeline DevOps. LangChain bụ ọba akwụkwọ Eke Ọgba nke na-enye ụzọ dị mfe ma dị irè iji jikọta ngwa ọrụ AI kwadoro na usoro na pipeline mmepe software.
Nbufe ngwanrọ akpaaka na DSPy na LangChain
Nbufe ngwanrọ akpaghị aka bụ akụkụ dị oke mkpa nke DevOps nke gụnyere imezi nrụpụta, nwale, na ibunye ngwa ngwanrọ. Enwere ike iji DSPy na LangChain mee ka nnyefe ngwanrọ rụọ ọrụ site na ijikọ ngwa ọrụ AI na-arụ ọrụ na usoro na pipeline DevOps.
Nke a bụ ọmụmaatụ otu esi eji DSPy na LangChain rụọ ọrụ nnyefe ngwanrọ: "Python mbubata dspy si langchain mbubata LLM
Mepụta pipeline DSPy
ọkpọkọ = dspy.Pipeline ( aha = "ngwa-ngwa-ebufe", nzọụkwụ=[ dspy.Step("wuo", "build-software"), dspy.Step("ule", "ule-software"), dspy.Step("deploy", "deploy-software") ] )
Mepụta LangChain LLM
LM = LLM ( model_name = "koodu-davinci-002", max_length=1024 )
Kọwaa ọrụ iji megharịa nnyefe ngwanrọ
def automate_software_delivery(): # Nweta hash nke etinyere ugbu a eme_hash = dspy.get_commit_hash()
# Nweta ngalaba dị ugbu a
alaka = dspy.get_alaka ()
# Wulite ngwanro
build_output = dspy.build_software(commit_hash, alaka ụlọ ọrụ)
# Nwalee ngwanrọ ahụ
test_output = dspy.test_software(build_output)
# Mepụta ngwa ngwa
deploy_output = dspy.deploy_software(test_output)
# Weghachite nsonaazụ mbugharị
laghachi deploy_output
Gbaa ọrụ akpaaka
deployment_output = automate_software_delivery()
Bipụta mmepụta ntinye
ebipụta(nkwalite_mmepụta) `` Ihe ngọngọ koodu a na-egosiputa otu esi eji DSPy na LangChain mee ka nnyefe ngwanrọ rụọ ọrụ site na ijikọ ngwa ọrụ AI kwadoro na usoro na pipeline DevOps.
Nyocha ihe mere na DSPy na LangChain
Nnyocha ihe mberede bụ akụkụ dị oke egwu nke DevOps nke gụnyere nyocha na idozi ihe omume na-eme n'oge nnyefe software. Enwere ike iji DSPy na LangChain rụọ ọrụ nyocha ihe merenụ site na ijikọ ngwaọrụ ndị AI kwadoro na usoro ya na pipeline DevOps.
Nke a bụ ọmụmaatụ otu esi eji DSPy na LangChain arụ ọrụ nyocha ihe merenụ: "Python mbubata dspy si langchain mbubata LLM
Mepụta pipeline DSPy
ọkpọkọ = dspy.Pipeline ( aha = "omume-nyocha", nzọụkwụ=[ dspy.Step("nyocha", "nyocha-ihe mere"), dspy.Step("dozie", "ihe kpatara nsogbu") ] )
Mepụta LangChain LLM
LM = LLM ( model_name = "koodu-davinci-002", max_length=1024 )
Kọwaa ọrụ iji megharịa nchọpụta ihe merenụ
def automate_incident_investigation(): # Nweta ihe mere ugbu a merenụ = dspy.get_incident()
# Nyochaa ihe merenụ
analysis_output = dspy.analyze_incident(omume)
# Kpebie ihe merenụ
resolution_output = dspy.resolve_incident(analysis_output)
# Weghachite nsonaazụ mkpebi
weghachi mkpebi_mmepụta
Gbaa ọrụ akpaaka
resolution_output = automate_incident_investigation()
Bipụta mmepụta mkpebi
ebipụta(mpụta_mpụta) `` Ihe ngọngọ koodu a na-egosi otu esi eji DSPy na LangChain megharịa nchọpụta ihe merenụ site na ijikọ ngwa ọrụ AI kwadoro na usoro na pipeline DevOps.
Top 5-10 Iwu/Snippets kacha eji
Nke a bụ iwu/snippets 5-10 kacha eji eme ihe maka DSPy na LangChain:
dspy.Pipeline(): Na-emepụta pipeline DSPy ọhụrụ.- `dspy.Step()': Na-agbakwụnye nzọụkwụ ọhụrụ na pipeline DSPy.
- `langchain.LLM()': Na-emepụta LangChain LLM ọhụrụ.
- `dspy.get_commit_hash()': Na-enweta hash ugbu a.
dspy.get_branch(): Na-enweta alaka dị ugbu a.dspy.build_software(): Na-ewuli ngwanro.dspy.test_software(): Na-anwale ngwanro.dspy.deploy_software(): Na-ebunye ngwanro.- `dspy.analyze_incident()': Nyochaa ihe merenụ.
dspy.resolve_incident(): dozie ihe merenụ.
Nlere anya
Nke a bụ nleba anya nke usoro ọrụ DSPy na LangChain na-eji Chart.js: Json { "ụdị": "ogwe", "data": { "labels": ["Nnyefe ngwanrọ akpaaka", "Nnyocha ihe mberede"], "datasets": [ { "label": "DSPy", "data": [10, 5], "backgroundColor": ["#4CAF50", "#FF9800"] }, { "label": "LangChain", "data": [5, 10], "backgroundColor": ["#2196F3", "#9C27B0"] } ] }, "Nhọrọ": { " aha": { "ngosi": eziokwu, "ederede": "DSPy na LangChain Workflow" }, "akụkọ ifo": { "ngosi": eziokwu } } } `` Ọhụụ a gosipụtara iji DSPy na LangChain maka nnyefe ngwanrọ na akpaghị aka na nyocha ihe merenụ.
Mmechi
DSPy na LangChain na-enye ụzọ dị ike ma dị irè iji jikọta ngwaọrụ ndị AI kwadoro na usoro na pipeline DevOps. Site na iji DSPy na LangChain, òtù dị iche iche nwere ike megharịa nnyefe ngwanrọ na nyocha ihe merenụ, na-emezi ọsọ ọsọ, ịdịmma na ntụkwasị obi nke nnyefe ngwanrọ. Ihe mgbochi koodu na nleba anya enyere na edemede a gosipụtara iji DSPy na LangChain maka nnyefe ngwanrọ na akpaghị aka na nyocha ihe merenụ.
Ọrụ Ọdịnihu
Ọrụ n'ọdịnihu gụnyere:
- Ijikọ DSPy na LangChain na ngwaọrụ ndị ọzọ na-akwado AI.
- Ịmepụta atụmatụ ọhụrụ na arụmọrụ maka DSPy na LangChain.
- Imelite arụmọrụ na scalability nke DSPy na LangChain.
Ntụaka
- Akwụkwọ DSPy: https://dspy.readthedocs.io/
- Akwụkwọ LangChain: https://langchain.readthedocs.io/
- Akwụkwọ Chart.js: https://www.chartjs.org/docs/latest/